oxidative stress tolerance as a component of the tissue

Oxidative stress tolerance as a component

of the tissue tolerance mechanism in

wheat and barley

by

Haiyang Wang

School of Land and Food

MSc Huazhong Agricultural University China

BSc Henan Agricultural University China

Submitted in fulfilment of the requirement for the Degree of Doctor of

Philosophy

University of Tasmania

August 2018

Preliminaries

i

Declarations and statements

Declaration of originality

This thesis contains no material which has been accepted for a degree or diploma

by the University or any other institution except by way of background information

and duly acknowledged in the thesis and to the best of my knowledge and belief

no material previously published or written by another person except where due

acknowledgement is made in the text of the thesis nor does the thesis contain any

material that infringes copyright

Authority of access

This thesis is not to be made available for loan or copying for two years following

the date this statement was signed Following that time the thesis may be made

available for loan and limited copying and communication in accordance with the

Copyright Act 1968

Statement regarding published work contained in thesis

The publishers of the papers comprising Chapters 3 to 6 hold the copyright for that

content and access to the material should be sought from the respective journals

The remaining non-published content of the thesis may be made available for loan

and limited copying and communication in accordance with the Copyright Act

1968

Haiyang Wang


August 2018

Preliminaries

ii

Statement of co-authorship

The following people and institutions contributed to the publication of work

undertaken as part of this thesis

Candidate Haiyang Wang University of Tasmania

Author 1 Sergey Shabala University of Tasmania

Author 2 Lana Shabala University of Tasmania

Author 3 Meixue Zhou University of Tasmania

Author details and their roles

Paper 1 Hydrogen peroxide-induced root Ca2+ and K+ fluxes correlate with

salt tolerance in cereals towards the cell-based phenotyping

Published in International Journal of Molecular Sciences (2015) 19 702 Located

in chapter 3

Candidate contributed to 80 to the planning execution and preparation of the

work for the paper Author 1 author 2 and author 3 contributed to the conception

and design of the research project and drafted significant parts of the paper

Paper 2 Developing a high-throughput phenotyping method for oxidative

stress tolerance in cereal roots

Submitted to Plant Methods Located in chapter 6




We the undersigned agree with the above stated ldquoproportion of work undertakenrdquo

for each of the above published (or submitted) peer-reviewed manuscripts

contributing to this thesis

Preliminaries

iii

Signed

Sergey Shabala Holger Meinke

Supervisor Director

Tasmanian Institute of Agriculture Tasmanian Institute of Agriculture

University of Tasmania University of Tasmania

Date 31072018 ____________________

Preliminaries

iv

List of publications

Journal publications

Wang H Shabala L Zhou M Shabala S (2018) Hydrogen peroxide-induced root

Ca2+ and K+ fluxes correlate with salt tolerance in cereals towards the cell-based

phenotyping International Journal of Molecular Sciences 19 702

Wang H Shabala L Zhou M Shabala S Developing a high-throughput

phenotyping method for oxidative stress tolerance in cereal roots Plant Methods

(submitted 12042018)

Manuscripts in preparation

Wang H Shabala L Zhou M Shabala S H2O2-induced ion fluxes as physiological

markers for salinity stress tolerance breeding in cereals and QTL identification

regarding this trait

Conference papers

Wang H Shabala L Zhou M Shabala S (Oral presentation) ldquoRevealing the causal

relationship between salinity and oxidative stress tolerance in wheat and barleyrdquo

The XIX International Botanical Congress July 2017 Shenzhen China

Wang H Shabala L Zhou M Shabala S (Poster presentation) ldquoHigh-throughput

assays for oxidative stress tolerance in cerealsrdquo The XIX International Botanical

Congress July 2017 Shenzhen China

Wang H Shabala L Zhou M Shabala S (Poster presentation) ldquoRevealing the

causal relationship between salinity and oxidative stress tolerance in wheat and

barleyrdquo Australian Barley Technical Symposium September 2017 Hobart

Tasmania

Wang H Shabala L Zhou L Shabala S (Poster presentation) ldquoDeveloping a

high-throughput phenotyping method for oxidative stress tolerance in cereal

rootsrdquo 10th International Symposium on Root Research July 2018 Jerusalem

Israel

Preliminaries

v

Acknowledgements

Four years ago I was enrolled as a PhD candidate in University of Tasmania

Here at this special moment with completion of my PhD study I would like to

express my sincere thanks to UTAS and Grain Research and Development

Corporation (GRDC) for their great financial support during my candidature

At the same time I am very glad and lucky to be a member in Sergey Shabalarsquos

Plant Physiology lab with the dedicated supervision by Prof Sergey Shabala Prof

Meixue Zhou and Dr Lana Shabala As my primary supervisor Prof Sergey

Shabala showed his omnipotence in solving any problems I met during my PhD

study He also enlightened me with his wide knowledge and professionalism in

papers writing My co-supervisor Prof Meixue Zhou and Dr Lana Shabala also

helped me a lot both of them were very kind-hearted in guiding my study on all

aspects during the past years I am really appreciated for the great help and

instructions from AProf Zhonghua Chen with the genetic analysis work Many

thanks to all of them

I also would like to thank sincerely all my current (Juan Liu Ping Yun Dr

Tracey Cuin Ali Kiani-Pouya Amarah Batool Babar Shahzad Fatemeh Rasouli

Joseph Hartley Hassan Dhshan Justin Direen Mohsin Tanveer Muhammad Gill

Dr Nadia Bazihizina Tetsuya Ishikawa Widad Al-Shawi and Hasanuzzaman

Hasan) and former (Dr Nana Su Dr Qi Wu Dr Yuan Huang Dr Min Yu Dr

Xuewen Li Dr Yun Fan Dr Xin Huang Dr Min Zhu Dr Honghong Wu Dr

Yanling Ma Dr Feifei Wang Dr Xuechen Zhang Dr Maheswari Jayakumar Dr

Jayakumar Bose Dr William Percey Dr Edgar Bonales Shivam Sidana Zhinous

Falakboland and Dr Getnet Adam) lab colleagues for their help I will always

remember them all

Great thanks to my family (mother father sister) Thanks for their

unconditional support and love to me and great concern for my living and studying

during my stay in Australia

Finally special thanks to my beloved idol Mr Kai Wang who appeared in

October 2015 and fulfilled my spiritual life He also gave me a good example of

insisting on his originality and having the right attitude towards his acting career I

will always learn from him and try to be a professional in my research area in the

near future

Preliminaries

vi

Table of Contents

Declarations and statements i

Declaration of originality i

Authority of access i

Statement regarding published work contained in thesis i

Statement of co-authorship ii

List of publications iv

Acknowledgements v

List of illustrations and tables xi

List of abbreviation xiv

Abstract xvii

Chapter 1 Literature review 1

11 Salinity as an issue 1

12 Factors contributing to salinity stress tolerance 1

121 Osmotic adjustment 1

122 Root Na+ uptake and efflux 2

123 Vacuolar Na+ sequestration 3

124 Control of xylem Na+ loading 4

125 Na+ retrieval from the shoot 5

126 K+ retention 5

127 Reactive oxygen species (ROS) detoxification 6

13 Oxidative component of salinity stress 6

131 Major types of ROS 6

132 ROS friends and foes 6

133 ROS production in plants under saline conditions 7

134 Mechanisms for ROS detoxification 10

14 ROS control over plant ionic homeostasis salinity stress

context 11

Preliminaries

vii

141 ROS impact on membrane integrity and cellular structures 11

142 ROS control over plant ionic homeostasis 12

143 ROS signalling under stress conditions 16

15 Linking salinity and oxidative stress tolerance 17

151 Genetic variability in oxidative stress tolerance 18

152 Tissue specificity of ROS signalling and tolerance 19

16 Aims and objectives of this study 20

161 Aim of the project 20

162 Outline of chapters 22

Chapter 2 General materials and methods 24

21 Plant materials 24

22 Growth conditions 24

221 Hydroponic system 24

222 Paper rolls 24

23 Microelectrode Ion Flux Estimation (MIFE) 24

231 Ion-selective microelectrodes preparation 24

232 Ion flux measurements 25

Chapter 3 Hydrogen peroxide-induced root Ca2+ and K+

fluxes correlate with salt tolerance in cereals towards the

cell-based phenotyping 26

31 Introduction 26

32 Materials and methods 28

321 Plant materials and growth conditions 28

322 K+ and Ca2+ fluxes measurements 29

323 Experimental protocols for microelectrode ion flux estimation (MIFE)

measurements 29

324 Quantifying plant damage index 30

325 Statistical analysis 30

33 Results 30

331 H2O2-induced ion fluxes are dose-dependent 30

332 Genotypic variation in H2O2-induced Ca2+ and K+ fluxes in barley 33

333 Genotypic variation in H2O2-induced Ca2+ and K+ fluxes in wheat 35

Preliminaries

viii

334 Genotypic variation of hydroxyl radical-induced Ca2+ and K+ fluxes in

barley 37

34 Discussion 39

341 The magnitude of the hydroxyl radical-induced K+ and Ca2+ fluxes does

not correlate with salinity stress tolerance in barley 40

342 H2O2-induced K+ and Ca2+ fluxes in cereals correlate with their overall

salinity stress tolerance but only in mature zone 41

343 Reactive oxygen species (ROS)-induced K+ efflux is accompanied by

an increased Ca2+ uptake 43

344 Implications for breeders 44

Chapter 4 Validating using MIFE technique-measured

H2O2-induced ion fluxes as physiological markers for

salinity stress tolerance breeding in wheat and barley 45

41 Introduction 45


421 Plant materials and growth conditions and Ca2+ and K+ flux

measurements 46

422 Pharmacological experiments 46


43 Results 47

431 H2O2-induced ions kinetics in mature root zone of cereals 47

432 H2O2-induced K+ efflux and Ca2+ uptake from the mature root zone

correlates with the overall salinity tolerance in barley 47


correlates with the overall salinity stress tolerance in bread wheat 49


correlates with the overall salinity stress tolerance in durum wheat 51

435 Barley tends to leak less K+ and acquire less Ca2+ than wheat in mature

root zone upon oxidative stress 52

436 H2O2-induced ion flux in root mature zone can be prevented by TEA+

Gd3+ and DPI in both barley and wheat 53

44 Discussion 54

441 H2O2-induced ions fluxes from root mature zone as a novel

physiological trait to explore mechanisms of salinity stress tolerance 54

442 Barley tends to retain more K+ and acquire less Ca2+ into cytosol in root

mature zone than wheat when subjected to oxidative stress 56

Preliminaries

ix

443 Different identity of ions transport systems in root mature zone upon

oxidative stress between barley and wheat 57

Chapter 5 QTLs for ROS-induced ions fluxes associated

with salinity stress tolerance in barley 59

51 Introduction 59


521 Plant material growth conditions and Ca2+ and K+ flux measurements

60

522 QTL analysis 61

523 Genomic analysis of potential genes for salinity tolerance 61

53 Results 62

531 Peak K+ and Ca2+ fluxes of the DH lines under H2O2 treatment 62

532 QTLs for H2O2-induced peak K+ flux and peak Ca2+ flux 63

533 QTL for KF when using CaF as a covariate 64

534 Potential genes for H2O2-induced K+ and Ca2+ flux on 2H 5H and 7H

65

54 Discussion 66

541 QTL on 2H and 7H for oxidative stress control both K+ and Ca2+ flux 66

542 Potential genes contribute to oxidative stress tolerance 68

Chapter 6 Developing a high-throughput phenotyping

method for oxidative stress tolerance in cereal roots 71

61 Introduction 71



622 Viability assay 74

623 Root growth assay 75


63 Results 76

631 H2O2 causes loss of the cell viability in a dose-dependent manner 76

632 Genetic variability of root cell viability in response to 10 mM H2O2 77

633 Methodological experiments for cereal screening in root growth upon

oxidative stress 80

Preliminaries

x

634 H2O2ndashinduced changes of root length correlate with the overall salinity

tolerance 81

64 Discussion 82

641 H2O2 causes a loss of the cell viability and decline of growth in barley

roots 82

642 Salt tolerant barley roots possess higher root viability in elongation

zone after long-term ROS exposure 83

643 Evaluating root growth assay screening for oxidative stress tolerance 84

Chapter 7 General discussion and future prospects 86

71 General discussion 86

72 Future prospects 89

References 93

Preliminaries

xi

List of illustrations and tables

Figure 11 ROS production pattern in plantshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip9

Figure 12 Model of ROS detoxification by Asc-GSH cyclehelliphelliphelliphelliphelliphelliphellip10

Figure 13 Model of ROS detoxification by GPX cyclehelliphelliphelliphelliphelliphelliphelliphelliphellip11

Figure 14 ROS-activated Ca2+-permeable NSCCs in mediating root

elongationhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip16

Figure 31 Descriptions of cereal root ion fluxes in response to H2O2 and bullOH in a

single experimenthelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip31

Figure 32 Net K+ fluxes measured from barley variety TX9425 in both root

elongation and mature zone with respective H2O2 concentrations and their

dose-dependencyhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip32

Figure 33 Net Ca2+ fluxes measured from barley variety TX9425 in both root



Figure 34 Kinetics of K+ fluxes from three representative barley varieties in

response to 10 mM H2O2 treatment from both root elongation and mature

zone and their correlation between H2O2-induced K+ fluxes and overall

salinity stress tolerancehelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip34

Figure 35 Kinetics of Ca2+ fluxes from three representative barley varieties in


zone and their correlation between H2O2-induced Ca2+ fluxes and overall

salinity stress tolerancehelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip35

Figure 36 Kinetics of K+ fluxes from three representative wheat varieties in




Figure 37 Kinetics of Ca2+ fluxes from three representative wheat varieties in


Preliminaries

xii




response to 031 bullOH treatment from both root elongation and mature zone

and their correlation between bullOH-induced K+ fluxes and overall salinity

stress tolerancehelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip38



and their correlation between bullOH-induced Ca2+ fluxes and overall salinity

stress tolerancehelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip39

Figure 41 Descriptions of net K+ and Ca2+ flux from cereals root mature zone in

response to 10 mM H2O2 in a representative experiment helliphelliphelliphelliphellip47

Figure 42 Genetic variability of oxidative stress tolerance in barleyhelliphelliphelliphellip49

Figure 43 Genetic variability of oxidative stress tolerance in bread wheathelliphellip51

Figure 44 Genetic variability of oxidative stress tolerance in durum wheathellip52

Figure 45 General comparison of H2O2-induced net K+ and Ca2+ fluxes

initialpeak K+ flux and Ca2+ flux values net mean K+ efflux and Ca2+ uptake

values from mature root zone in barley bread wheat and durum

wheathelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip53

Figure 46 Effect of DPI Gd3+ and TEA+ pre-treatment on H2O2-induced net mean

K+ and Ca2+ fluxes from the mature root zone of barley and

wheat helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip54

Figure 51 Frequency distribution for peak K+ flux and peak Ca2+ flux of DH lines

derived from a cross of CM72 and Gairdner exposed to 10 mM H2O2

treatmenthelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip62

Figure 52 QTLs associated with H2O2-induced peak K+ flux and H2O2-induced

peak Ca2+ fluxhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip64

Figure 53 Chart view of QTLs for H2O2-induced peak K+ and Ca2+ flux in the DH

line helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip65

Preliminaries

xiii

Figure 61 Viability staining and fluorescence image acquisitionhelliphelliphelliphelliphellip75

Figure 62 Viability staining of Naso Nijo roots exposed to 0 03 1 3 10 mM

H2O2 for 1 day and 3 dayshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip76

Figure 63 Red fluorescence intensity measured from roots of Naso Nijo upon

exposure to various H2O2 concentrations for either one day or three

days helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip77

Figure 64 Viability staining of root elongation and mature zones of four barley

varieties exposed to 10 mM H2O2 for 3 dayshelliphelliphelliphelliphelliphelliphelliphelliphelliphellip78

Figure 65 Quantitative red fluorescence intensity from root elongation and mature

zone of five barley varieties exposed to 10 mM H2O2 for 3 dhelliphelliphelliphellip79

Figure 66 Genetic variability in the relative root length in 11 barley varieties

treated with 1 mM H2O2 for 3 d and their correlation with the overall salinity

tolerancehelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip81

Table 31 List of barley and wheat varieties used in this studyhelliphelliphelliphelliphelliphelliphellip29

Table 41 List of barley varieties used in this studyhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip48

Table 42 List of wheat varieties used in this studyhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip50

Table 51 H2O2-induced peak K+ and Ca2+ flux from parental and DH lineshellip62

Table 52 QTLs for H2O2-induced peak K+ and Ca2+ flux in the DH line of CM72

and Gairdner QTL for H2O2-induced peak K+ flux when using H2O2-induced

peak Ca2+ flux as a covariatehelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip63

Table 53 Candidate genes for H2O2-induced K+ and Ca2+ fluxhelliphelliphelliphelliphellip66

Table 61 Barley varieties used in the studyhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip73

Preliminaries

xiv

List of abbreviation

3Chl Triplet state chlorophyll

1O2 Singlet oxygen

ABA Abscisic acid

AO Antioxidant

APX Ascorbate peroxidase

Asc Ascorbate

BR Brassinosteroid

BSM Basic salt medium

CaLB Calcium-dependent lipid-binding

Cas CRISPR-associated

CAT Catalase

CML Calmodulin like

CNGC Cyclic nucleotide-gated channels

CRISPR Clustered regularly interspaced short palindromic repeats

crRNA CRISPR RNA

CS Compatible solutes

CuA CopperAscorbate

Cys Cysteine

DArT Diversity Array Technology

DH Double haploid

DHAR Dehydroascorbate reductase

DMSP Dimethylsulphoniopropionate

DPI Diphenylene iodonium

DSB Double-stranded break

ER Endoplasmic reticulum

ET Ethylene

ETC Electron transport chain

FAO Food and Agriculture Organization

FDA Fluorescein diacetate

FV Fast vacuolar channel

GA Gibberellin

Gd3+ Gadolinium chloride

GORK Guard cell outward rectifying K+ channel

GPX Glutathione peroxidase

Preliminaries

xv

GR Glutathione reductase

gRNA Guide RNA

GSH Glutathione (reduced form)

GSSG Glutathione (oxidized form)

H2 Hydrogen gas

H2O2 Hydrogen peroxide

HKT High-affinity K+ Transporter

HOObull Perhydroxy radical

IL Introgression line

IM Interval mapping

indel Insertiondeletion

JA Jasmonate

LEA Late-embryogenesis-abundant

LCK1 Low affinity cation transporter

LOD Logarithm of the odds

LOOH Lipid hydroperoxides

MAS Marker assisted selection

MDA Malondialdehyde

MDAR Monodehydroascorbate reductase

MIFE Microelectrode Ion Flux Estimation

MQM Multiple QTL model

Nax1 NA+ EXCLUSION 1


NHX Na+H+ exchanger

NO Nitric oxide

NSCCs Non-Selective Cation Channels

O2- Superoxide radicals

bullOH Hydroxyl radicals

PCD Programmed Cell Death

PI Propidium iodide

PIP21 Plasma membrane intrinsic protein 21

PM Plasma membrane

POX Peroxidase

PP2C Protein phosphatase 2C family protein

PSI Photosystem I

Preliminaries

xvi

PSII Photosystem II

PUFAs Polyunsaturated fatty acids

QCaF QTLs for H2O2-induced peak Ca2+ flux

QKF QTLs for H2O2-induced peak K+ flux

QTL Quantitative Trait Locus

RBOH Respiratory burst oxidase homologue

RObull Alkoxy radicals

ROS Reactive Oxygen Species

RRL Relative root length

RT-PCR Real-time polymerase chain reaction

SA Salicylic acid

SE Standard error

SKOR Stellar K+ outward rectifier

SL Strigolactone

SODs Superoxide dismutases

SOS Salt Overly Sensitive

SSR Simple Sequence Repeat

SV Slow vacuolar channel

TALENs Transcription activator-like effector nucleases

TEA+ Tetraethylammonium chloride

TFs Transcription factors

tracrRNA Trans-activating crRNA

UQ Ubiquinone

V-ATPase Vacuolar H+-ATPase

VK Vacuolar K+-selective channels

V-PPase Vacuolar H+-PPase

W-W Waterndashwater

ZNFs Zinc finger nucleases

Abstract

xvii

Abstract

Soil salinity is a global issue and a major factor limiting crop production

worldwide One side effect of salinity stress is an overproduction and accumulation

of reactive oxygen species (ROS) causing oxidative stress and leading to severe

cellular damage to plants While the major focus of the salinity-oriented breeding

programs in the last decades was on traits conferring Na+ exclusion or osmotic

adjustment breeding for oxidative stress tolerance has been largely overlooked

ROS are known to activate several different types of ion channels affecting

intracellular ionic homeostasis and thus plantrsquos ability to adapt to adverse

environmental conditions However the molecular identity of many ROS-activated

ion channels remains unexplored and to the best of our knowledge no associated

QTLs have been reported in the literature

This work aimed to fill the above knowledge gaps by evaluating a causal link

between oxidative and salinity stress tolerance The following specific objectives

were addressed

To develop MIFE protocols as a tool for salinity tolerance screening in

cereals

To validate the role of specific ROS in salinity stress tolerance by applying

developed MIFE protocols to a broad range of cereal varieties and establish a causal

relationship between oxidative and salinity stress tolerance in cereals

To map QTLs controlling oxidative stress tolerance in barley

To develop a simple and reliable high-throughput phenotyping method

based on above traits

Working along these lines a range of electrophysiological pharmacological

and imaging experiments were conducted using a broad range of barley and wheat

varieties and barley double haploid (DH) lines

In order to develop the applicable MIFE protocols the causal relationship

between salinity and oxidative stress tolerance in two cereal crops - barley and

wheat - was investigated by measuring the magnitude of ROS-induced net K+ and

Ca2+ fluxes from various root tissues and correlating them with overall whole-plant

responses to salinity No correlation was found between root responses to hydroxyl

radicals and the salinity tolerance However a significant positive correlation was

found for the magnitude of H2O2-induced K+ efflux and Ca2+ uptake in barley and

Abstract

xviii

the overall salinity stress tolerance but only for mature zone and not the root apex

The same trends were found for wheat These results indicate high tissue specificity

of root ion fluxes response to ROS and suggest that measuring the magnitude of

H2O2-induced net K+ and Ca2+ fluxes from mature root zone may be used as a tool

for cell-based phenotyping in breeding programs aimed to improve salinity stress

tolerance in cereals

In the next chapter 44 barley and 40 wheat (20 bread wheat and 20 durum

wheat) cultivars contrasting in their salinity tolerance were screened to validate the

above correlation between H2O2-induced ions fluxes and the overall salinity stress

tolerance A strong and negative correlation was reported for all the three cereal

groups indicating the applicability of using the MIFE technique as a reliable

screening tool in cereal breeding programs Pharmacological experiments were

then conducted to explore the molecular identity of H2O2 sensitive Ca2+ and K+

channels in both barley and wheat We showed that both non-selective cation and

K+-selective channels are involved in ROS-induced Ca2+ and K+ flux in barley and

wheat At the same time the ROS generation enzyme NADPH oxidative was also

playing vital role in controlling this process The findings may assist breeders in

identifying possible targets for plant genetic engineering for salinity stress

tolerance

Once the causal association between oxidative and salinity stress has been

established we have mapped QTLs associated with H2O2-induced Ca2+ and K+

fluxes as a proxy for salinity stress tolerance using over 100 DH lines from a cross

between CM72 (salt tolerant) and Gairdner (salt sensitive) Three major QTLs on

2H (QKFCG2H) 5H (QKFCG5H) and 7H (QKFCG7H) were identified to be

responsible for H2O2-induced K+ fluxes while two major QTLs on 2H

(QCaFCG2H) and 7H (QCaFCG7H) were for H2O2-induced Ca2+ fluxes QTL

analysis for H2O2-induced K+ flux by using H2O2-induced Ca2+ flux as covariate

showed that the two QTLs for K+ flux located at 2H and 7H were also controlling

Ca2+ flux while another QTL mapped at 5H was only involved in K+ flux

According to this finding the nearest sequence markers (bpb-8484 on 2H bpb-

5506 on 5H and bpb-3145 on 7H) were selected to identify candidate genes for

salinity tolerance and annotated genes between 6445 and 8095 cM on 2H 4299

and 4838 cM on 5H 11983 and 14086 cM on 7H were deemed to be potential

genes

Abstract

xix

The above findings open previously unexplored prospects of improving

salinity tolerance by pyramiding the new trait - H2O2-induced Ca2+ and K+ fluxes -

alongside with other (traditional) mechanisms However as the MIFE method has

relatively low throughput capacity finding a suitable proxy will benefit plant

breeders Two high-throughput phenotyping methods - viability assay and root

growth assay - were then tested and assessed In viability staining experiments a

dose-dependent H2O2-triggered loss of root cell viability was observed with salt

sensitive varieties showing significantly more root cell damage In the root growth

assays relative root length (RRL) was measured in plants under different H2O2

concentrations The biggest difference in RRL between contrasting varieties was

observed for 1 mM H2O2 treatment Under these conditions a significant negative

correlation in the reduction in RRL and the overall salinity tolerance was reported

among 11 barley varieties Although both assays showed similar results with that

of MIFE method the root growth assay was way simpler that do not need any

specific skills and training and less time-consuming than MIFE (1 d vs 6 months)

thus can be used as an effective high-throughput phenotyping method

In conclusion this project established a causal link between oxidative and

salinity stress tolerance in both barley and wheat and provided new insights into

fundamental mechanisms conferring salinity stress tolerance in cereals The high

throughput screening protocols were developed and validated and it was H2O2-

induced Ca2+ uptake and K+ efflux from the mature root zone correlated with the

overall salinity stress tolerance with salt-tolerant barley and wheat varieties

possessed greater K+ retention and lesser Ca2+ uptake ability when challenged with

H2O2 The QTL mapping targeting this trait in barley showed three major QTLs for

oxidative stress tolerance conferring salinity stress tolerance The future work

should be focused on pyramiding these QTLs and creating robust salt tolerant

genotypes

Chapter 1 Literature review

1


11 Salinity as an issue

Soil salinity or salinization termed as a soil with high level of soluble salts

occurs all over the world (Rengasamy 2006) It affects approximate 15 (45 out of

230 million hectares) of the worldrsquos agricultural land especially in arid and semi-

arid regions (Munns and Tester 2008) At the same time the consequences of the

global climate change such as rising of seawater level and intrusion of sea salt into

coastal area as well as human activities such as excessive irrigation and land

exploitation are making salinity issue even worse (Horie et al 2012 Ismail and

Horie 2017) The direct impact of soil salinity is that it disturbs cellular metabolism

and plant growth reduces crop production and leads to considerable economic

losses (Schleiff 2008 Shabala et al 2014 Gorji et al 2015) It is estimated that

salinity-caused economic penalties from global agricultural production excesses

US$27 billion per annual this value is ascending on a daily basis (Shabala et al

2015) Furthermore increasing agricultural food production is required to feed the

expanding world population which is unlikely to be simply acquired from the

existing arable land (Shabala 2013) This prompts a need to utilise the salt affected

lands to increase yields To achieve this new traits conferring salinity tolerance

should be discovered and QTLs related to salt tolerance traits should be pyramided

to create salt tolerant crop germplasm

12 Factors contributing to salinity stress tolerance

Salinity tolerance is a complex and multi-genic trait which is attributed to a

range of biological mechanisms The main components are osmotic adjustment

Na+ exclusion from uptake vacuolar Na+ sequestration control of xylem Na+

loading Na+ retrieval from the shoot K+ retention and ROS detoxification (Munns

and Tester 2008 Shabala et al 2010 Wu et al 2015)

121 Osmotic adjustment

Osmotic adjustment also termed as osmoregulation occurs during the process

of cellular dehydration and plays key role in plants adaptive response to minify the

adverse impact of stress induced by excessive external salts especially during the


2

first phase of salinity stress (Hare et al 1998 Mager et al 2000 Serraj and Sinclair

2002 Shabala and Shabala 2011) It can be achieved by (i) controlling ions fluxes

across membranes from different cellular compartments (ii) accumulating

inorganic ions (eg K+ Na+ and Cl-) (iii) synthesizing a diverse range of organic

osmotica (collectively known as ldquocompatible solutesrdquo) to counteract the osmotic

pressure from external medium (Garcia et al 1997 Serraj and Sinclair 2002

Shabala and Shabala 2011)

Compatible solutes (CS) are low-molecular-weight organic compounds with

high solubility and non-toxic even if they accumulate to high concentration

(Yancey 2005) The ability of plants to accumulate CS has long been taken as a

selection criterion in traditional crop (most of which are glycophytes) breeding

programs to increase osmotic stress tolerance (Ludlow and Muchow 1990 Zhang

et al 1999) Generally these osmoprotectants are identified as (1) amino acids (eg

proline glycine arginine and alanine) (2) non-protein amino acids (eg pipecolic

acid γ-aminobutyric acid ornithine and citrulline) (3) amides (eg glutamine and

asparagine) (4) soluble proteins (eg late-embryogenesis-abundant (LEA) protein)

(5) sugars (eg sucrose glucose trehalose raffinose fructose and fructans) (6)

polyols (or ldquosugar alcoholsrdquo as another name eg mannitol inositol pinitol

sorbitol and glycerol) (7) tertiary sulphonium compounds (eg

dimethylsulphoniopropionate (DMSP)) and (8) quaternary ammonium compounds

(eg glycine betaine β-alanine betaine proline betaine pipecolate betaine

hydroxyproline betaine and choline-O-sulphate) (Slama et al 2015 Parvaiz and

Satyawati 2008)

122 Root Na+ uptake and efflux

There are several major pathways mediating Na+ uptake across plasma

membrane (PM) (i) Non-selective cation channels (NSCCs) (Tyerman and Skerrett

1998 Amtmann and Sanders 1998 White 1999 Demidchik et al 2002) (ii) High

affinity K+ transporter (HKT1) (Laurie et al 2002 Garciadeblas et al 2003) (iii)

Low affinity cation transporter (LCK1) (Schachtman et al 1997 Amtmann et al

2001) which therefore facilitate Na+ uptake However only a small fraction of

absorbed Na+ is accumulated in root tissues indicating that a major bulk of the Na+

is extruded from cytosol to the rhizosphere (Munns 2002) However unlike animals

which require Na+ to maintain normal cell metabolism most plant especially


3

glycophytes do not take Na+ as an essential molecule (Blumwald 2000) Thus

plants lack specialised Na+-pumps to extrude Na+ from root when exposed to

salinity stress (Garciadeblas et al 2001) It is believed that Na+ exclusion from

plant roots is mediated by the PM Na+H+ exchangers encoded by SOS1 gene (Zhu

2003 Ji et al 2013) This process is energised by the PM proton pump establishing

an H+ electrochemical potential gradient across the PM as driving force for Na+

exclusion (Palmgren and Nissen 2011) Salt tolerant wheat (Cuin et al 2011) and

the halophyte Thellungiella (Oh et al 2010) were observed with higher SOS1

andor SOS1-like Na+H+ exchanger activity Moreover overexpression of SOS1

or its homologues have been shown to result in enhanced salt tolerance in

Arabidopsis (Shi et al 2003 Yang et al 2009) and tobacco (Yue et al 2012)

123 Vacuolar Na+ sequestration

Plants are also capable of handling excessive cytosolic Na+ by moving it into

vacuole across the tonoplast to maintain cytosol sodium content at non-toxic levels

upon salinity stress (Blumwald et al 2000 Shabala and Shabala 2011) This

process is called ldquoNa+ sequestrationrdquo and is mediated by the tonoplast-localized

Na+H+ antiporters (Blumwald et al 2000) and energised by vacuolar H+-ATPase

(V-ATPase) and H+-PPase (V-PPase) (Zhang and Blumwald 2001 Fukuda et al

2004a) Na+H+ exchanger (NHX) genes are known to operate Na+ sequestration

and express in both roots and leaves Arabidopsis Na+H+ antiporter gene AtNHX1

was the first NHX homolog identified in plants (Rodriacuteguez-Rosales et al 2009)

and another five isoforms of AtNHX gene were then identified and characterised

(Yokoi et al 2002 Aharon et al 2003 Bassil et al 2011a Bassil et al 2011b

Qiu 2012 Barragan et al 2012) Overexpression of NHX1 in Arabidopsis (Apse

et al 1999) rice (Fukuda et al 2004b) maize (Yin et al 2004) wheat (Xue et al

2004) tomato (Zhang and Blumwald 2001) canola (Zhang et al 2001) and

tobacco (Lu et al 2014) result in enhanced salt tolerance in transformed plants

indicating the importance of Na+ transporting into vacuole in conferring plants

salinity stress tolerance (Ismail and Horie 2017) Besides the tonoplast NSCCs -

SV (slow vacuolar channel) and FV (fast vacuolar channel) - have been shown to

control Na+ leak back to the cytoplasm (Bonales-Alatorre et al 2013) which

further make Na+ sequestration more efficient


4

124 Control of xylem Na+ loading

Plant roots are responsible for absorption of nutrients and inorganic ions The

latter are generally loaded into xylem vessels from where they are transported to

shoot via the transpiration stream of the plant (Wegner and Raschke 1994 Munns

and Tester 2008) This makes toxic ion such as Na+ accumulate in shoot easily

under salinity stress Higher concentration of Na+ in mesophyll cells is always

harmful as it compromises plantrsquos leaf photochemistry and thus whole plant

performance One of the strategies to reduce Na+ accumulation in shoot is control

of xylem Na+ loading which can be achieved by either minimizing Na+ entry into

the xylem from the root or maximizing the retrieval of Na+ from the xylem before

it reaches sensitive tissues in the shoot (Tester and Davenport 2003 Katschnig et

al 2015)

The high-affinity K+ transporter (HKT) proteins (especially HKT1 subfamily)

which mainly express in the xylem parenchyma cells show their Na+-selective

transporting activity and play major role in Na+ unloading from xylem in several

plant species such as Arabidopsis rice and wheat (Munns and Tester 2008)

AtHKT11 (Sunarpi et al 2005 Davenport et al 2007 Moslashller et al 2009) and

OsHKT15 (Ren et al 2005) were reported to function in these processes

Moreover OsHKT14 (expressed in both rice leaf sheaths and stems Cotsaftis et

al 2012) and OsHKT11 (strongly expressed in the vicinity of the xylem in rice

leaves Wang et al 2015) were also suggested contributing to Na+ unloading from

the xylem of these tissues In durum wheat TmHKT14 and TmHKT15 were

identified as causal genes of NA+ EXCLUSION 1 ( Nax1 Huang et al 2006) and

NA+ EXCLUSION 2 (Nax2 Byrt et al 2007) respectively Both function by

removing Na+ from roots and the lower parts of leaves making Na+ concentration

low in leaf blade (James et al 2011) Recently introgression of TmHKT15-A into

a salt-sensitive durum wheat cultivar substantially decreased Na+ concentration in

leaves of transformed plants making their grain yield in saline soils increased by

up to 25 (Munns et al 2012) indicating the applicability of targeting this trait

for salinity stress tolerance breeding


5

125 Na+ retrieval from the shoot

Another strategy to prevent shoot Na+ over-accumulation is removal of Na+

from this tissue which was believed to be mediated by HKT1 in the recirculation

of Na+ back to the root by the phloem (Maathuis et al 2014) AtHKT11

(Berthomieu et al 2003) and OsHKT11 (Wang et al 2015) were suggested to

contribute to this process Moreover studies in salinity tolerant wild tomato

(Alfocea et al 2000) and the halophyte reed plants (Matsushita and Matoh 1991)

have revealed that they exhibited higher extent of Na+ recirculation than their

domestic tomato counterparts and the salt-sensitive rice plants respectively

Nevertheless it seems this notion does not hold in all the cases By using an hkt11

mutant Davenport et al (2007) demonstrated that AtHKT11 was not involved in

this process in the phloem which requires further investigation regarding this trait

126 K+ retention

The reason for Na+ being toxic molecule in plants lies in its inhibition of

enzymatic activity especially for those require K+ for functioning (Maathuis and

Amtmann 1999) Since over 70 metabolic enzymes are activated by K+ (Dreyer and

Uozumi 2011 Anschuumltz et al 2014) it is likely that it is the cytosolic K+Na+ ratio

but not the absolute quantity of Na+ that determines plantrsquos ability to survive in

saline soils (Shabala and Cuin 2008) Therefore except for cytosolic Na+ exclusion

efficient cytosolic K+ retention may be another essential factor in the maintenance

of higher K+Na+ ratio to sustain cell metabolism under salinity stress Indeed a

strong positive correlation between K+ retention ability in root tissue and the overall

salinity stress tolerance has been reported in a wide range of plant species including

barley (Chen et al 2005 2007ac) wheat (Cuin et al 2008 2009) lucerne

(Smethurst et al 2008 Guo et al2016) Arabidopsis (Sun et al 2015) pepper

(Bojorquez-Quintal et al 2016) cotton (Wang et al 2016b) and cucumber

(Redwan et al 2016) Likewise a recent study in barley also emphasized the

importance of K+ retention in leaf mesophyll to confer plants salinity stress

tolerance (Wu et al 2015) K+ leakage through PM of both root and shoot tissues

is known to be mediated by two channels namely GORKs (guard cell outward-

rectifying K+ channels) and NSCCs (Shabala and Pottosin 2014) which play major


6

role in cytosolic K+ homeostasis maintenance However until now no salt tolerant

germplasm regarding this trait has been established

127 Reactive oxygen species (ROS) detoxification

The loading of toxic Na+ into plant cytosol not only interferes with various

physiological processes but also leads to the overproduction and accumulation of

reactive oxygen species (ROS) which cause oxidative stress and have major

damage effect to macromolecules (Vellosillo et al 2010 Karuppanapandian et al

2011) A large amount of antioxidant components (enzymes and low molecular

weight compounds) can be found in plants which constitute their defence system

to detoxify excessive ROS and protect cells from oxidative damage Therefore it

seems plausible that plants with higher antioxidant activity (in other words lower

ROS level) may be much more salt tolerant This is the case in many halophytes

and a range of glycophytes with higher salinity tolerance (reviewed in Bose et al

2014b) However ROS are also indispensable signalling molecules involved in a

broad range of physiological processes (Mittler 2017) detoxification of ROS may

interfere with these processes and cause pleiotropic effects (Bose et al 2014b)

making the link between antioxidant activity and salinity stress tolerance

complicated This can be reflected in a range of reports which failed to reveal or

showed negative correlation between the above traits (Bose et al 2014b)

13 Oxidative component of salinity stress

131 Major types of ROS

Reactive oxygen species (ROS) are inevitable by-products of various

metabolic pathways occurring in chloroplast mitochondria and peroxisomes (del

Riacuteo et al 2006 Navrot et al 2007) The major types of ROS are composed of

superoxide radicals (O2-) hydroxyl radical (bullOH) perhydroxy radical (HOObull)

alkoxy radicals (RObull) hydrogen peroxide (H2O2) and singlet oxygen (1O2) (Mittler

2002 Gill and Tuteja 2010)

132 ROS friends and foes

ROS have long been considered as unwelcome by-products of aerobic

metabolism (Mittler 2002 Miller et al 2008) While numerous reports have


7

demonstrated that ROS are acting as signalling molecules to control a range of

physiological processes such as deference responses and cell death (Bethke and

Jones 2001 Mittler 2002) gravitropism (Joo et al 2001) stomatal closure (Pei et

al 2000 Yan et al 2007) cell expansion and polar growth (Coelho et al 2002

Foreman et al 2003) hormone signalling (Mori and Schroeder 2004 Foyer and

Noctor 2009) and leaf development (Yue et al 2000 Rodrıguez et al 2002 Lu

et al 2014)

Under optimal growth conditions ROS production in plants is programmed

and beneficial for plants at both physiological (Foreman et al 2003) and genetical

(Mittler et al 2004) levels However when exposed to stress conditions (eg

drought salinity extreme temperature heavy metals pathogens etc) ROS are

dramatically overproduced and accumulated which ultimately results in oxidative

stress (Apel and Hirt 2004) As highly reactive and toxic substances detrimental

effects of excessive ROS produced during adverse environmental conditions are a

result of their ability to cause lipid peroxidation DNA damage protein

denaturation carbohydrate oxidation pigment breakdown and the impairment of

enzymatic activity (Ozgur et al 2013 Choudhury et al 2017)

133 ROS production in plants under saline conditions

Major sources of ROS in plants

ROS are formed as a result of a multistep reduction of oxygen (O2) in aerobic

metabolism pathway in living organisms (Asada 2006 Saed-Moucheshi et al 2014

Nita and Grzybowski 2016) In plants subcellular compartments such as

chloroplasts mitochondria and peroxisomes are the main sources that contribute

to ROS production (Mittler et al 2004 Asada 2006) O2- forms at the first step of

oxygen reduction and then quickly catalysed to H2O2 by superoxide dismutases

(SODs) (Ozgur et al 2013 Bose et al 2014b) In the presence of transition metals

such as Fe2+ and Cu+ H2O2 can be converted to highly toxic bullOH (Rodrigo-Moreno

et al 2013b) bullOH has a really short half-life (less than 1 μs) while H2O2 is the

most stable ROS with half-life in minutes (Pitzschke et al 2006 Bose et al 2014b)

Apart from the cellular compartments mentioned above ROS can also be produced

in the apoplastic spaces These sources include plasma membrane (PM) NADPH

oxidases cell-wall-bound peroxidases amine oxidases pH-dependent oxalate


8

peroxidases and germin-like oxidases (Bolwell and Wojtaszek 1997 Mittler 2002

Hu et al 2003 Walters 2003)

Changes in ROS production under saline conditions

In green tissue of plant cells ROS are mainly generated from chloroplasts and

peroxisomes especially under light condition (Navrot et al 2007) In non-green

tissue or dark condition mitochondria are the major source for ROS production

(Foyer and Noctor 2003 Rhoads et al 2006) Normally ROS homeostasis is able

to keep ROS in a lower non-toxic level (Mittler 2002 Miller et al 2008) However

elevated cytosolic ROS level is deleterious which can be observed when plants are

exposed to saline conditions (Hernandez et al 2001 Tanou et al 2009)

PSI (photosystem I) and PSII (photosystem II) reaction centres in thylakoids

are major sites involved in chloroplastic ROS production (Pfannschmidt 2003

Asada 2006 Gill and Tuteja 2010) Under normal circumstances the

photosynthetic product oxygen accepts electrons passing through the

photosystems and form superoxide radicals by Mehler reaction at the antenna

pigments in PSI (Asada 1993 Polle 1996 Asada 2006) After being reduced to

NADPH the electron flow then enters the Calvin cycle and fixes CO2 (Gill and

Tuteja 2010) Under saline conditions both osmotically-induced stomatal closure

and accumulation of high levels of cytosolic Na+ impair photosynthesis apparatus

and reduce plantrsquos capacity to assimilate CO2 in conjunction with fully utilise light

absorbed by photosynthetic pigments (Biswal et al 2011 Ozgur et al 2013) As

a result the excessive light captured allow overwhelming electrons passing through

electron transport chain (ETC) and lead to enhanced generation of superoxide

radicals (Asada 2006 Ozgur et al 2013) In mitochondria ETC the ROS

generation sites complexes I and complexes III overreduce ubiquinone (UQ) pool

upon salt stress and pass electron to O2 lead to increased production of O2minus (Noctor

2006) which readily catalysed into H2O2 by SODs (Raha and Robinson 2000

Moslashller 2001 Quan et al 2008) Peroxisomes are single membrane-bound

organelles which can generate H2O2 effectively during photorespiration by the

oxidation of glycolate to glyoxylate via glycolate oxidase reaction (Foyer and

Noctor 2009 Bauwe et al 2010) Salinity stress-induced stomatal closure reduces

CO2 content in leaf mesophyll cells leading to enhanced photorespiration and

increased glycolate accumulation and therefore elevated H2O2 production in these


9

organelles (Hernandez et al 2001 Karpinski et al 2003) Salinity-induced

apoplastic ROS generation is generally regulated by the plasma membrane NADPH

oxidases which is activated by elevated cytosolic free Ca2+ following NaCl-

induced activation of depolarization-activated Ca2+ channels (DACC) (Chen et al

2007a Demidchik and Maathuis 2007) This PM NADPH oxidase-mediated ROS

production plays a vital role in the regulation of acclimation to salinity stress

(Kurusu et al 2015) ROS production pattern is detailed in Figure11

Figure 11 ROS production pattern in plants From Bose et al (2014) J Exp Bot

65 1242-1257

Genetic variability in ROS production

Plantsrsquo ability to produce ROS under unfavourable environment varies which

may indicate their variability in salt stress tolerance Comparative analysis of two

rice genotypes contrasting in their salinity stress tolerance revealed higher level of

H2O2 in the salt sensitive cultivar in response to either short-term (Vaidyanathan et

al 2003) or long-term (Mishra et al 2013) salt stimuli A comparative study


10

between a cultivated tomato Solanum lycopersicum L and its salt tolerant

counterparts ndash wild tomato S pennellii - have demonstrated that the latter had less

oxidative damage by increasing the activities of related antioxidants indicating less

ROS were produced under salinity stress (Shalata et al 2001) Similar scenario

was also found between salt-sensitive Plantago media and salt-tolerant P

maritima (Hediye Sekmen et al 2007) The ROS production pattern between

Cakile maritime (halophyte) and Arabidopsis thaliana (glycophyte) also varies

with the latter had continuous increasing of H2O2 concentration during the 72 h

NaCl treatment while H2O2 level of the former declined after 4 h onset of salt

application (Ellouzi et al 2011)

134 Mechanisms for ROS detoxification

Two major types of antioxidants - enzymatic or non-enzymatic - constitute the

major defence mechanism that protect plant cells against oxidative damage by

quenching excessive ROS without converting themselves to deleterious radicals

(Scandalios 1993 Mittler et al 2004 Bose et al 2014b)

Enzymatic mechanisms

The enzymatic components of the antioxidative defence system comprise of

antioxidant enzymes such as superoxide dismutase (SOD) catalase (CAT)

ascorbate peroxidase (APX) peroxidase (POX) glutathione peroxidase (GPX)

monodehydroascorbate reductase (MDAR) dehydroascorbate reductase (DHAR)

and glutathione reductase (GR) (Saed-Moucheshi et al 2014) They are involved

in the process of converting O2- to H2O2 by SOD andor H2O2 to H2O by CAT

ascorbatendashglutathione cycle (Asc-GSH Figure 12) and glutathione peroxidase

cycle (GPX Figure 13) (Apel and Hirt 2004 Asada 2006)

Figure 12 Model of ROS detoxification by Asc-GSH cycle From Apel and Hirt

(2004) Annu Rev Plant Biol 55 373-399


11

Figure 13 Model of ROS detoxification by GPX cycle From Apel and Hirt


Non-enzymatic mechanisms

Non-enzymic components of the antioxidative defense system comprise

of Asc GSH α-tocopherol carotenoids and phenolic compounds (Apel and Hirt

2004 Ahmad et al 2010 Das and Roychoudhury 2014) They are able to scavenge

the highly toxic ROS such as 1O2 and bullOH protect numerous cellular components

from oxidative damage and influence plant growth and development as well (de

Pinto and De Gara 2004)

14 ROS control over plant ionic homeostasis salinity

stress context

141 ROS impact on membrane integrity and cellular structures

The detrimental effects of excess ROS produced under salinity stress are a


denaturation carbohydrate oxidation pigment breakdown and an impairment of


Lipid peroxidation occurs when ROS level reaches above the threshold

During this process ROS attack carbon-carbon double bond(s) and the ester linkage

between glycerol and the fatty acid making polyunsaturated fatty acids (PUFAs)

more prone to be attacked Oxidation of lipids is particularly dangerous once

initiated it will propagate free radicals through the ldquochain reactionsrdquo until

termination products are produced (Anjum et al 2015) during which a single bullOH

can result in peroxidation of many PUFAs in irreversible manner (Sharma et al

2012) The main products of lipid peroxidation are lipid hydroperoxides

(LOOH) Among the many different aldehydes terminal products

malondialdehyde (MDA) 4-hydroxy-2-nonenal 4-hydroxy-2-hexenal and acrolein

are taken as markers of oxidative stress (Del Rio et al 2005 Farmer and Mueller


12

2013) The excessively produced ROS especially bullOH can attack the sugar and

base moieties of DNA results in deoxyribose oxidation strand breakage

nucleotides removal DNA-protein crosslinks and nucleotide bases modifications

which may lead to malfunctioned or inactivated encoded proteins (Sharma et al

2012) They also attack and modify proteins directly through nitrosylation

carbonylation disulphide bond formation and glutathionylation (Yamauchi et al

2008) Indirectly the terminal products of lipid peroxidation MDA and 4-

hydroxynonenal are capable of reacting and oxidizing a range of amino acids such

as cysteine and methionine (Davies 2016) The role of carbohydrate oxidation in

stress signalling are obscure and much less studied However this process may be

harmful to plants as well as bullOH can react with xyloglucan and pectin breaking

them down and causing cell wall loosening (Fry et al 2002)

142 ROS control over plant ionic homeostasis

Salinity-induced plasma membrane depolarization (Jayakannan et al 2013)

and generation of ROS (Cuin and Shabala 2008) are the major reasons to cause

cytosolic ion imbalance ROS are capable of activating non-selective cation

channels (NSCCs) and guard cell outward-rectifying K+ channels (GORKs)

inducing ionic conductance and transmembrane fluxes of important ions such as K+

and Ca2+ (Demidchik et al 2003 20072010) Nowadays plant regulatory

networks such as stress perception action of signalling molecules and stimulation

of elongation growth have included ROS-activated channels as key components

The interest in these systems are mainly in linking ions transmembrane fluxes (such

as Ca2+ K+) to the production of ROS Both phenomena are ubiquitous and crucial

for plants as they together control a wide range of physiological and

pathophysiological reactions (Demidchik 2018)

Non-selective cation channels

Plant ROS-activated NSCCs were initially discovered in the charophyte

Nitella flexilis by Demidchik et al (1996 1997ab 2001) who showed that

exposure of intact cells to redox-active transition metals Cu+ and Fe2+ lead to the

production of hydroxyl radicals (bullOH) which induced instantaneous voltage-

independent and non-selective cationic conductance that allow passage of different

cations This idea was then examined in higher plants (Demidchik et al 2003


13

Foreman et al 2003 Inoue et al 2005) with the bullOH generating mixture-activated

cation-selective channels in permeability series of K+ (100) asymp NH4+ (091) asymp Na+

(071) asymp Cs+ (067) gt Ba2+ (032) asymp Ca2+ (024) in Arabidopsis root epidermal cells

The ROS activation of Ca2+-permeable NSCCs in a range of physiological

pathways will be discussed in detail below

K+ permeable channels

ROS are known to activate a certain class of K+ permeable NSCC channels

(Demidchik et al 2003 Shabala and Pottosin 2014) and GORK channels

(Demidchik et al 2010) resulting in massive K+ leak from cytosol and a rapid

decline of the cytosolic K+ pool (Shabala et al 2006) Since maintaining

intracellular K+ homeostasis is essential for turgor maintenance cytosolic pH

homeostasis maintenance enzyme activation protein synthesis stabilization

charge balance and membrane potential formation (Shabala 2003 Dreyer and

Uozumi 2011) the ROS-induced depletion of cytosolic K+ pool compromise these

functions Also it can activate caspase-like proteases and trigger programmed cell

death (PCD) (Shabala 2009) ROS-activated K+ leakage was first detected in the

green alga Chlorella vulgaris treated with copper ions (McBrien and Hassall 1965)

The idea was later extended to root tissue of higher plants Agrostis tenuis

(Wainwright and Woolhouse 1977) and Silene cucubalus (De Vos et al 1989) and

leaf tissue of Avena sativa (Luna et al 1994)

In Arabidopsis studies have shown that exogenous bullOH application to mature

roots can activate cation currents (Demidchik et al 2003) However H2O2-

activated cation currents can only be found when it was added to the cytosolic side

of the PM (Demidchik et al 2007) indicating the existence of a transition metal-

binding site in the cation channel mediating ROS-activated K+ efflux (Rodrigo-

Moreno et al 2013a) Using Metal Detector ver 20 software (Universities of

Florence and Trento Florence Italy) Demidchik et al(2014) identified the putative

CuFe binding sites in CNGC19 and CNGC20 with Cys 102 107 and 110 of

CNGC19 and Cys 133 138 and 141 of CNCG20 coordinating CuFe and

assembling them into the metal-binding sites in a probability close to 100 Given

that bullOH is extremely short-lived and unable to act at a distance gt 1 nm from the

generation site these identified sites may be crucial for the activation of bullOH


14

Guard cells are able to accumulate K+ for stomatal opening (Humble and

Raschke 1971) or release K+ for stomatal closing (MacRobbie 1981) The latter

was then observed with high GORK gene expression levels in Arabidopsis as

suggested by quantitative RT-PCR analyses (Ache et al 2000) and proved to be

mediated by GORK channels (Schroeder 2003 Hosy et al 2003) These

observations demonstrated that GORK channels play a key role in the control of

stomatal movements to allow plant to reduce transpirational water loss during stress

conditions

GORK channels are also highly expressed in root epidermis Using

electrophysiological means Demidchik et al (2003 2010) showed that exogenous

bullOH (generated by the mixture of Cu2+ and ascorbateH2O2) application to

Arabidopsis mature root results in massive K+ efflux which was inhibited in

Arabidopsis K+ channel knockout mutant Atgork1-1 indicating channels mediating

K+ efflux are encoded by the GORK GORK transcription was up-regulated upon

salt stress (Becker et al 2003) which may result from salt-induced ROS

production lead to an increased activity of this channel and massive K+ efflux (Tran

et al 2013) This efflux may operate as a ldquometabolic switchrdquo decreasing metabolic

activity under stress condition by releasing K+ and turn plant cells into a lsquohibernated

statersquo for stress acclimation (Shabala and Pottosin 2014)

SKOR (stellar K+ outward rectifier) channels found within the xylem

parenchyma of root tissue and mediated K+ loadingleaking from root stelar cells

into xylem (Gaymard et al 1998) can be activated by H2O2 through oxidation of

the Cys residue - Cys168 - within the S3 α-helix of the voltage sensor complex This

is very similar to the structure of GORK with its Cys residue exposed to the outside

when the GORK channel is in the open conformation Moreover substitution of

this cysteine moieties in SKOR channels abolished their sensitivity to H2O2

indicating that Cys168 is a critical target for H2O2 which may regulate ROS-

mediated control of the K+ channel in mineral nutrient partitioning in the plant

More recently Michard et al (2017) demonstrated that SKOR may also express in

pollen tube and showed its ROS sensitivity

Ca2+ permeable channels

ROS-induced Ca2+ influx from extracellular space to the cytosol was initially

found in the higher plants dayflower (Price 1990) and tobacco (Price et al 1994)


15

exogenously treated with H2O2 or paraquat (a ROS-generating chemical) The

similar observation was later reported by Demidchik et al (2003 2007) who treated

Arabidopsis mature root protoplast using bullOH-generating mixtures (Cu2+

H2O2ascorbate) or H2O2 and showed that ROS-induced Ca2+ uptake was mediated

by Ca2+-permeable NSCC with channel activation of bullOH is in a direct manner

from the extracellular spaces and H2O2 acts only at the cytosolic side of the mature

root epidermal PM The fact that H2O2 did induce inward Ca2+ currents in

protoplasts isolated from the Arabidopsis elongation root epidermis may indicate

that either Ca2+-permeable NSCCs have different structure andor regulatory

properties between root mature and elongation zones or cells in the latter zones

harbor a higher density of H2O2-permeable aquaporins in their PM allowing H2O2

diffuse into the cytosol (Demidchik and Maathuis 2007)

ROS-activated Ca2+-permeable NSCCs play a key role in mediating stomatal

closure in guard cells (Pei et al 2000) and elongationexpansion of plant cells

(Foreman et al 2003 Demidchik et al 2003 2007) Environmental stresses such

as drought and salt decrease water availability in plants leading to increased

production of ABA in guard cells (Cutler et al 2010 Kim et al 2010) ABA

however is able to stimulate NADPH oxidase-mediated production of H2O2

leading to the activation of Ca2+-permeable NSCCs in the guard cells PM for Ca2+

uptake and mediating stomatal closure (Pei et al 2000 Sah et al 2016) During

this process the PM localized NADPH oxidase can be activated by elevated Ca2+

with its subunit genes AtrbohD and AtrbohF responsible for the subsequent

production of H2O2 (Kwak et al 2003) Moreover the plasma membrane intrinsic

protein 21 (PIP21) aquaporin is likely mediating H2O2 enters into guard cell for

channel activation (Grondin et al 2015) In root tissues the growing root cells

from root hairs and root elongation zones show higher Ca2+-permeable NSCCs

activity than cells from mature zones (Demidchik and Maathuis 2007) This results

in enhanced Ca2+ influx into cytosol of elongating cells which stimulates

actinmyosin interaction to accelerate exocytosis polar vesicle embedment and

sustains cell expansion (Carol and Dolan 2006) In a study conducted by Foreman

et al (2003) the rhd2-1 mutants lacking NADPH oxidase was observed with far

less produced extracellular ROS exhibited stunted expansion in root elongation

zones and formed short root hairs indicating the importance of this process in

mediating cell elongation Similar to guard cell the PM NADPH oxidase in root


16

growing tissues is also responsible for the production of ROS required for the

activation of Ca2+-permeable NSCCs and can be stimulated by elevated cytosolic

Ca2+ (Figure 14) These processes form a self-amplifying lsquoROS- Ca2+ hubrdquo to

enhance and transduce Ca2+ and ROS signals (Demidchik and Shabala 2018) The

same ideas are also applicable for pollen tube growth (Malho et al 2006 McInnis

et al 2006 Potocky et al 2007) The H2O2-activated Ca2+ influx conductance has

been demonstrated in pollen tube protoplasts of pear (Wu et al 2010) and pollen

grain protoplasts of lily (Breygina et al 2016) mediating pollen tube growth and

pollen grain germination The cytosol-localized annexins were proposed to form

Ca2+-permeable channels based on the observation that exogenous application of

corn-derived purified annexin protein to Arabidopsis root epidermal protoplasts

results in elevation of cytosolic free Ca2+ in the latter (Laohavisit et al 2009 2012

Baucher et al 2012)

Figure 14 ROS-activated Ca2+-permeable NSCCs in mediating root elongation

From Demidchik and Maathuis (2007) New Phytol 175 387-404

143 ROS signalling under stress conditions

ROS have long been known as toxic by-products in aerobic metabolism

(Mittler et al 2017) However ROS produced in organelles or through PM


17

NADPH oxidase under stress conditions can act as beneficial signal transduction

molecules to activate acclimation and defence mechanisms in plants to counteract

stress-associated oxidative stress (Mittler et al 2004 Miller et al 2008) During

these processes ROS signals may either be limited within cells between different

organelles by (non-)enzymatic AO or auto-propagated to transfer rapidly between

cells for a long distance throughout the plant (Miller et al 2009) The latter signal

is mainly generated by H2O2 due to its long half-life (1 ms) thus can accumulate to

high concentrations (Cheeseman 2006 Moslashller et al 2007) or diffuse freely

through peroxiporin membrane channels to adjacent subcellular compartments and

cross neighbouring cells (Neill et al 2002) However plant cells contain different

cellular compartments with specific sets of stress proteins H2O2 generated in these

sites process identical properties which unable to distinguish the particular

stimulus to selectively regulate nuclear genes and trigger an appropriate

acclimation response (Moslashller and Sweetlove 2010 Mittler et al 2011) This may

attribute to the associated functioning of ROS signal with other signals such as

peptides hormones lipids cell wall fragments or the ROS signal itself carries a

decoded message to convey specificity (Mittler et al 2011)

Besides ROS signalling generated under salt stress condition can also trigger

acclimation responses in association with other well-established cellular signalling

components such as plant hormone (eg ABA - abscisic acid SA - salicylic acid

JA - jasmonate ET - ethylene BR - brassinosteroid GA - gibberellin and SL -

strigolactone) Ca2+ NO and H2 (Bari and Jones 2009 Jin et al 2013 Xu et al

2013 Nakashima and Yamaguchi-Shinozaki 2013 Xie 2014 Xia et al 2015

Mignolet-Spruyt et al 2016)

15 Linking salinity and oxidative stress tolerance

Salinity stress in plants reduces cell turgor and induces entry of large amount

of Na+ into cytosol Mechanisms such as osmotic adjustment and Na+ exclusion

were used by plants in maintaining cell turgor pressure and minimizing sodium

toxicity which has long been taken as the major components of salinity stress

tolerance However excessive ROS production always accompanies salinity stress

making oxidative stress tolerance the third component of salinity stress tolerance

Therefore revealing the mechanism of oxidative stress tolerance in plants and


18

linking it with salinity stress tolerance may open new avenue in breeding

germplasms with improved salinity stress tolerance

151 Genetic variability in oxidative stress tolerance

Plants exhibit various abilities to oxidative stress tolerance due to their genetic

variability in stress response It has been shown that the existence of genetic

variability in stress tolerance is due to the existence of differential expression of

stress‐responsive genes it is also an essential factor for the development of more

tolerant cultivars (Senthil‐Kumar et al 2003 Bita and Gerats 2013) Since

oxidative stress is one of the components of salinity stress the genetic variability

for tolerance to oxidative stress present in plants could be exploited to screen

germplasm and select cultivars that exhibit superior salinity stress tolerance This

promotes a need to establish a link between oxidative stress and salinity stress

tolerance

Plants biochemical markers such as antioxidants levelactivities (eg SOD

APX CAT ndash Maksimović et al 2013 total phenolic compounds flavonoids ndash

Dbira et al 2018) the extend of oxidative damage or lipid peroxidation (eg MDA

level Gόmez et al 1999 Hernandez et al 2001 Liu and Huang 2000 Suzuki and

Mittler 2006) and physiological markers such as chlorophyll content (Kasajima

2017) have been used for oxidative stress tolerance in lots of studies These markers

were also tested as a tool for salt tolerance screening in Kunth (Luna et al 2000)

the pasture grass Cenchrus ciliaris L (Castelli et al 2010) and barley (Maksimović

et al 2013) In this case targeting oxidative stress tolerance may help breeders

achieve salinity stress tolerance and genetic variation in oxidative stress tolerance

among a wide range of varieties is ideal for the identification of QTLs (quantitative

trait loci) which was often quantified by AO activity as a simple measure Indeed

enhanced AO (especially the enzymatic AO) activity has been frequently

mentioned as a major trait of oxidative stress tolerance in plants and a range of

publication have revealed positive correlation between AO activity and salinity

stress tolerance in major crop plants such as wheat (El-Bastawisy 2010 Bhutta

2011) rice (Vaidyanathan et al 2003) maize (Azooz et al 2009) tomato (Mittova

et al 2002) and canola (Ashraf and Ali 2008) However the above link is not as

straightforward as one may expect because ROS have dual role either as beneficial


19

second messengers or toxic by-products making them have pleiotropic effects in

plants (Bose et al 2014b) This may be the reason why no or negative correlation

between oxidative and salinity stress were revealed in a range of plant species such

as barley (Fan et al 2014) rice (Dionisio-Sese and Tobita 1998) radish (Noreen

and Ashraf 2009) and turnip (Noreen et al 2010) Moreover Frary et al (2010)

identified 125 AO QTLs associated with salinity stress tolerance in a tomato

introgression line indicating that the use of this trait is practically unfeasible This

prompts a need to find other physiological markers for oxidative stress tolerance

and link them with salinity stress tolerance in cereals Previous studies from our

laboratory reported that H2O2-induced K+ flux from root mature zone were

markedly different showed genetic variability between two barley varieties

contrasting in their salinity stress tolerance (Chen et al 2007a Maksimović et al

2013) with the salt tolerant variety leaking less K+ than its sensitive counterpart

indicating the possibility of using this trait as a novel physiological marker for

oxidative stress tolerance

152 Tissue specificity of ROS signalling and tolerance

The signalling role of ROS in regulating plant responses to abiotic and biotic

stress have been characterized mainly functioning in leaves andor roots (Maruta et

al 2012) Due to the cell type specificity in these tissues their ROS production

pathways vary with chloroplasts and peroxisomes the major generation site in

leaves and mitochondria being responsible for this process in roots (Foyer and

Noctor 2003 Rhoads et al 2006 Navrot et al 2007) Stress-induced ROS

generation in these organelles are capable of triggering a cascade of changes in the

nuclear transcriptome and influencing gene expression by modifying transcription

factors (Apel and Hirt 2004 Laloi et al 2004) However it is now believed that

the roles of ROS signalling are attributed to the differences of RBOHs (respiratory

burst oxidase homologues also known as NADPH oxidases) regulation in various

signal transduction pathways activated in assorted tissue and cell types under stress

conditions (Baxter et al 2014)

NADPH oxidases-derived ROS are known to activate a range of ion channels

to perform their signalling roles The most frequently mentioned example is H2O2-

induced stomatal closure in plant guard cells via the activation of Ca2+-permeable

NSCCs under stress conditions which has been detailed in the previous section


20

regarding Ca2+-permeable channel This indicates a link between ROS and Ca2+

signalling network as the flux kinetics of the latter ion (uptake into cytosol) is

known as the early signalling events in plants in response to salinity stress (Baxter

et al 2014) Similar mechanism can be found in growing tissues (ie root tips root

hairs pollen tubes) under normal growth condition where elevated cytosolic Ca2+

induced by ROS facilitates exocytosis to sustains cell expansion and elongation

(Demidchik and Maathuis 2007)

ROS activated K+ efflux from the cytosol is also of great significance In leaves

this phenomenon plays key role in mediating stress-associated stomatal closure

(MacRobbie 1981) In root tissues ROS-induced K+ efflux is several-fold higher

of magnitude in elongation root zone compared with the mature root zone

(Demidchik et al 2003 Adem et al 2014) which probably indicated that there

are major differences in ROS productiondetoxification pattern or ROS-sensitive

channelstransporters between the two root zones (Shabala et al 2016) Besides

ROS-induced K+ efflux from root epidermis was in a dose-dependent manner (Cuin

and Shabala 2007) and it was shown that salt-induced accumulation of ROS in

barley root was highly tissue specific and observed only in root elongation zone

indicating that the increased production of ROS in elongation zone may be able to

induce greater K+ loss (Shabala et al 2016) This phenomenon may be the reason

of elongation root zone with higher salt sensitivity However ROS-induced higher

K+ efflux in this tissue may be of some specific benefits As per Shabala and Potosin

(2014) the massive K+ leakage from the young active root apex results in a decline

of cytosolic K+ content which may enable cells transition from normal metabolism

to a ldquohibernated staterdquo during the first stage of salt stress onset This mechanism

may be essential for cells from this root zone to reallocate their ATP pool towards

stress defence responses (Shabala 2017)

16 Aims and objectives of this study

161 Aim of the project

As discussed in this chapter oxidative stress is one of the components of

salinity stress and the previous studies on the relationship between salinity and

oxidative stress were largely focused on the antioxidant system in conferring

salinity stress tolerance ignoring the fact that ROS are essential molecules for plant


21

development and play signalling role in plant biology Until now applying major

enzymatic AOs level as the biochemical markers of salinity stress tolerance have

been explored in cereals However the attempts to identify specific genes

controlling the above process have been not characterised Therefore our main aim

in this study was to establish a causal link between oxidative stress and salinity

stress tolerance in cereals by other means (such as MIFE microelectrode ion flux

estimation) develop a convenient inexpensive and quick method for crop

screening and pyramid major oxidative stress-related QTLs in association with

salinity stress tolerance

It has been commonly known that excessive ROS in plant tissues can be

destructive to key macro-molecules and cellular structures However ROS impact

on plant ionic homeostasis may occur well before such damage is observed

Electrophysiological methods have demonstrated that ROS are able to activate a

broad range of ion channels resulting in disequilibrium of the cytosolic ions pools

and leading to the occurrence of PCD The major ions involved in ROS activation

are K+ and Ca2+ as retention of the former and elevation of the latter ion in cytosol

under stress conditions has been widely reported in salinity stress studies Therefore

the ROS-induced K+ and Ca2+ fluxes ldquosignaturesrdquo may be used as prospective

physiological markers in breeding programs aimed at improving salinity stress

tolerance In order to validate this hypothesis and develop high throughput

phenotyping methods for oxidative stress tolerance in cereals this work employed

electrophysiological methods (specifically non-invasive microelectrode ion flux

estimation MIFE technique) to measure ROS-induced K+ and Ca2+ fluxes in a

range of barley and wheat varieties Our ultimate aim is to link kinetics of ion flux

responses with salinity stress tolerance and provide breeders with appropriate tools

and novel target traits to be used in genetic improvement of the salinity tolerance

in cereal crops

In the light of the above four main objectives of this project were as follows

1) To investigate a suitability of the non-invasive MIFE (microelectrodes

ion flux measurements) technique as a proxy for oxidative stress tolerance in

cereals


22

The main objective of this work was to establish a causal link between

oxidative stress and salinity stress tolerance and then determine the most suitable

parameter(s) to be used as a physiological marker in future studies

2) To validate developed MIFE protocols and reveal the identity of ions

transport system in cereals mediating ROS-induced ion fluxes

In this part a large number of contrasting barley bread wheat and durum

wheat accessions were used Their ROS-induced Ca2+ and K+ fluxes from specific

root zones were acquired and correlated with their overall salinity stress tolerance

The pharmacological experiments were conducted using different channel blockers

andor specific enzymatic inhibitors to investigate the role of specific transport

systems as downstream targets of salt-induced ROS signalling

3) To map QTLs for ROS-induced ions fluxes associated with salinity stress

tolerance in barley

The main objective of this part was to identify major QTLs controlling ROS-

induced K+ and Ca2+ fluxes with the premise of revealing a causal correlation

between oxidative stress and salinity stress tolerance in barley Data for QTL

analysis were acquired from a double haploid barley population (eg derived from

CM72 and Gairdner) using the developed MIFE protocols

4) To develop a simple and reliable high-throughput phenotyping method to

replace the complicated MIFE technique for screening

Several simple alternative high-throughput assays were developed and

assessed for their suitability in screening germplasm for oxidative stress tolerance

as a proxy for the skill-demanding electrophysiological MIFE methods

162 Outline of chapters


Chapter 2 General materials and methods

Chapter 3 Hydrogen peroxide-induced root Ca2+ and K+ fluxes correlate with


Chapter 4 Validating using MIFE technique-measured H2O2-induced ion

fluxes as physiological markers for salinity stress tolerance breeding in wheat and

barley


23

Chapter 5 QTLs for ROS-induced ions fluxes associated with salinity stress

tolerance in barley

Chapter 6 Developing a high-throughput phenotyping method for oxidative


Chapter 7 General discussion and future prospects


24


21 Plant materials

All the cereal genotypes used in this research were acquired from the

Australian Winter Cereal Collection and reproduced in our laboratory These

include a range of barley bread wheat and durum wheat varieties and a double

haploid (DH) population originated from the cross of two barley varieties CM72

and Gairdner

22 Growth conditions

221 Hydroponic system

Seeds were surface sterilized with ten-fold diluted commercial bleach for 10

min and then rinsed thoroughly with tap water Sterilized seeds were grown in basic

salt medium (BSM 01 mM CaCl2 and 05 mM KCl pH 56) in aerated hydroponic

system in darkness at 24 plusmn 1 for 4 days Seedlings with root length between 60

and 80 mm were used in all the electrophysiological experiments in this study

222 Paper rolls


min and then rinsed thoroughly with tap water Sterilized seeds were germinated in

Petri dishes on wet filter paper for 1 d Uniformly germinated seeds were then

chosen placed in paper rolls (Pandolfi et al 2010) and grown in a basic salt

medium (BSM 01 mM CaCl2 and 05 mM KCl pH 56) in darkness at 24 plusmn 1

for another 3 d

23 Microelectrode Ion Flux Estimation (MIFE)

231 Ion-selective microelectrodes preparation

Net ion fluxes were measured with ion-selective microelectrodes non-

invasively using MIFE technique (University of Tasmania Hobart Australia)

(Newman 2001) Blank microelectrodes were pulled out from borosilicate glass

capillaries (GC150-10 15 mm OD x 086 mm ID x 100 mm L Harvard Apparatus


25

UK) using a vertical puller then dried at 225 overnight in an oven and then

silanized with chlorotributylsilane (282707-25G Sigma-Aldrich Sydney NSW

Australia) Silanized electrode tips were flattened to a diameter of 2 - 3 microm and

backfilled with respective backfilling solutions (200 mM KCl for K+ and 500 mM

CaCl2 for Ca2+) Electrode tips were then front-filled with respective commercial

ionophore cocktails (Cat 99311 for K+ and 99310 for Ca2+ Sigma-Aldrich) Filled

microelectrodes were mounted in the electrode holders of the MIFE set-up and

calibrated in a set of respective calibration solutions (250 500 1000 microM KCl for

calibrating K+ electrode and 100 200 400 microM CaCl2 for calibrating Ca2+ electrode)

before and after measurements Electrodes with a slope of more than 50 mV per

decade for K+ and more than 25 mV per decade for Ca2+ and correlation

coefficients of more than 09990 have been used

232 Ion flux measurements

Net fluxes of Ca2+ and K+ were measured from mature (2 - 3 cm from root

apex) and elongation (1 - 2 mm from root apex) root zones To do this plant roots

were immobilized in a measuring chamber containing 30 ml of BSM solution and

left for 40 min adaptation prior to the measurement The calibrated electrodes were

co-focused and positioned 40ndash50 microm away from the measuring site on the root

before starting the experiment After commencing a computer-controlled stepper

motor (hydraulic micromanipulator) moved microelectrodes 100 microm away from the

site and back in a 12 s square-wave manner to measure electrochemical gradient

potential between two positions The CHART software was used to acquire data

(Shabala et al 1997 Newman 2001) and ion fluxes were then calculated using the

MIFEFLUX program (Newman 2001)

Chapter 3 ROS-induced ions fluxes in root of several cereal varieties

26

Chapter 3 Hydrogen peroxide-induced root Ca2+

and K+ fluxes correlate with salt tolerance in

cereals towards the cell-based phenotyping

31 Introduction

Salinity stress is one of the major environmental constraints limiting crop

production worldwide that results in massive economic penalties especially in arid

and semi-arid regions (Schleiff 2008 Shabala et al 2014 Gorji et al 2015)

Because of this plant breeding for salt tolerance is considered to be a major avenue

to improve crop production in salt affected regions (Genc et al 2016) According

to the classical view two major components - osmotic stress and specific ion

toxicity - limit plant growth in saline soils (Deinlein et al 2014) Unsurprisingly

in the past decades many attempts have been made to target these two components

in plant breeding programs The major efforts were focused on either improving

plant capacity to exclude Na+ from uptake by targeting SOS1 (Martinez-Atienza et

al 2007 Xu et al 2008 Feki et al 2011) and HKT1 (Munns et al 2012 Byrt et

al 2014 Suzuki et al 2016) genes or increasing de novo synthesis of organic

osmolytes for osmotic adjustment (Sakamoto et al 1998 Sakamoto and Murata

2000 Wani et al 2013) However none of these approaches has resulted in truly

tolerant crops in the farmersrsquo fields and even the best performing genotypes created

showed a 50 of yield loss when grown under saline conditions (Munns et al

2012)

One of the reasons for the above detrimental effects of salinity on plant growth

is the overproduction and accumulation of reactive oxygen species (ROS) under

saline condition (Miller et al 2010 Bose et al 2014) The increasing level of ROS

in green tissues under saline condition results from the impairment of the

photosynthetic apparatus and a limited capability for CO2 assimilation in a

conjunction with plantrsquos inability to fully utilize light captured by photosynthetic

pigments (Biswal et al 2011 Ozgur et al 2013) However the leaf is not the only

site of ROS generation as they can also be produced in root tissues under saline

condition (Luna et al 2000 Mittler 2002 Miller et al 2008 2010 Turkan and

Demiral 2009) In Arabidopsis roots increasing hydroxyl radicals (OH)


27

(Demidchik et al 2010) and H2O2 (Xie et al 2011) levels were observed under

salt stress Accumulation of NaCl-induced H2O2 was also observed in rice (Khan

and Panda 2008) and pea roots (Bose et al 2014c)

When ROS are accumulated in excessive quantities in plant tissues significant

damage to key macromolecules and cellular structures occurs (Vellosillo et al

2010 Karuppanapandian et al 2011) However the disturbance to cell metabolism

(and associated growth penalties) may occur well before this damage is observed

ROS generation in root tissues occurs rapidly in response to salt stimuli and leads

to the activation of a broad range of ion channels including Na+-permeable non-

selective cation channels (NSCCs) and outward rectifying efflux K+ channels

(GORK) This results in a disequilibrium of the cytosolic ions pools and a

perturbation of cell metabolic processes When the cytosolic K+Na+ ratio is shifted

down beyond some critical threshold the cell can undergo a programmed cell death

(PCD) (Demidchik et al 2014 Shabala and Pottosin 2014) Taken together these

findings have prompted an idea of improving salinity stress tolerance via enhancing

plant antioxidant activity (Kim et al 2005 Hasanuzzaman et al 2012) However

despite numerous attempts (Dionisio-Sese and Tobita 1998 Sairam et al 2005

Gill and Tuteja 2010) the practical outcomes of this approach are rather modest

(Allen 1995 Rizhsky et al 2002)

One of the reasons for the above failure to improve plant stress tolerance via

constitutive expression of enzymatic antioxidants is the fact that ROS also play an

important signaling role in plant adaptive and developmental responses (Mittler

2017) Therefore scavenging ROS by constitutive expression of enzymatic

antioxidants (AOs) may interfere with these processes and cause pleiotropic effects

As a result the reported association between activity of AO enzymes and salinity

stress tolerance is often controversial (Maksimović et al 2013) and the entire

concept ldquothe higher the AO activity the betterrdquo does not hold in many cases

(Mandhania et al 2006 Noreen and Ashraf 2009a Seckin et al 2009)

ROS are known to activate Ca2+ and K+-permeable plasma membrane channels

in root epidermis (Demidchik et al 2003) resulting in elevated Ca2+ and depleted

K+ pool in the cytosol with a consequent disturbance to intracellular ion homeostasis

A pivotal importance of K+ retention under salinity stress is well known and has been

widely reported to correlate positively with the overall salinity tolerance in roots of

both barley and wheat as well as many other species (reviewed by Shabala 2017)


28

Elevation in the cytosolic free Ca2+ is also observed in response to a broad range of

abiotic and biotic stimuli and has long been considered an essential component of

cell stress signaling mechanism (Chen et al 2010 Bose et al 2011 Wang et al

2013) In the light of the above and given the dual role of ROS and their involvement

in multiple signaling transduction pathways (Mittler 2017) should salt tolerant

species and genotypes be more or less sensitive to ROS Is this sensitivity the same

for all tissues or does it show some specificity Can the magnitude of the ROS-

induced ion fluxes across the plasma membrane be used as a physiological marker in

breeding programs to improve plant salinity stress tolerance To the best of our

knowledge none of the previous studies has examined ROS-sensitivity of ion

transporters in the context of tissue-specificity or explored a causal link between two

types of ROS applied and stress-induced changes in plant ionic homeostasis in the

context of salinity stress tolerance This gap in our knowledge was addressed in this

work by employing the non-invasive microelectrode ion flux estimation (MIFE)

technique and investigating the correlation between oxidative stress-induced ion

responses and plantrsquos overall salinity stress tolerance

32 Materials and methods

321 Plant materials and growth conditions

Eight barley (seven Hordeum vulgare L and one H vulgare ssp Spontaneum)

and six wheat (bread wheat Triticum aestivum) varieties contrasting in salinity

tolerance were used in this study The list of cultivars is shown in Table 31

Seedlings for experiment were grown in hydroponic system (see section 221 for

details)


29

Table 31 List of barley and wheat varieties used in this study Scores represent

quantified damage degree of cereals under salinity stress reported as damage

index score from 0 to 10

Barley Wheat

Tolerant Sensitive Tolerant Sensitive

Varieties Score Varieties Score Varieties Score Varieties Score

SYR01 025 Gairdner 400 Titmouse S 183 Seville20 383

TX9425 100 ZUG403 575 Cranbrook 250 Iran118 417

CM72 125 Naso Nijo 750 Westonia 300 340 550

ZUG293 175 Unicorn 950

0 - highest overall salinity tolerance 10 - lowest level of salt tolerance Data collected from

our previous study from Wu et al 2014 2015

322 K+ and Ca2+ fluxes measurements

All details for ion-selective microelectrodes preparation and ion flux

measurements protocols are available in the section 23

323 Experimental protocols for microelectrode ion flux estimation

(MIFE) measurements

Two types of ROS were tested - hydrogen peroxide (H2O2) and hydroxyl

radicals (OH) A final working concentration of H2O2 in BSM was achieved by

adding H2O2 stock to the measuring chamber As the half-life of H2O2 in the

absence of transition metals is of an order of magnitude of several (up to 10) hours

(Yazici and Deveci 2010) and the entire duration of our experiments did not exceed

30 min one can assume that bath H2O2 concentration remained stable during

measurements A mixture of coppersodium ascorbate (CuA 0310 mM) was

used to generate OH (Demidchik et al 2003) The measuring solution containing

05 mM KCl and 01 mM CaCl2 was buffered with 4mM MESTris to achieve pH

56 Net Ca2+ and K+ fluxes were measured from mature and elongation zones of a

root for 4 to 5 min to ensure the stability of initial ion fluxes Then a stressor (either

H2O2 or OH) was added to the bath and Ca2+ and K+ fluxes were acquired for

another 20 min The first 30 ndash 60 s after adding the treatment solution (H2O2 or


30

CuA mixture) were discarded during data analyses in agreement with the MIFE

theory that requires non-stirred conditions (Newman 2001)

324 Quantifying plant damage index

The extent of plant salinity tolerance was quantified by allocating so-called

ldquodamage index scorerdquo to each plant The use of such damage index is a widely

accepted practice by plant breeders (Zhu et al 2015 Wu et al 2014 2015) This

index is based on evaluation of the extent of leaf chlorosis and plant survival rate

and relies on the visual assessment of plant performance after about 30 days of

exposure to high salinity The score ranges between 0 (no stress symptoms) and 10

(completely dead plant) and it was shown before that the damage index score

correlated strongly with the grain yield under stress conditions (Zhu et al 2015)

325 Statistical analysis

Statistical significance of mean values was determined by the standard

Studentrsquos t -test at p lt 005 level

33 Results

331 H2O2-induced ion fluxes are dose-dependent

Two parameters were identified and analyzed from transient response curves

(Figure 31) The first one was peak value defined as the maximum flux value

measured after the treatment and the second was the end value defined as a

baseline flux 20 min after the treatment application


31

Figure 31 Descriptions (see inserts in each panel) of cereal root ion fluxes in

response to H2O2 and hydroxyl radicals (OH) in a single experiment (AB) Ion

flux kinetics in root elongation zone (A) and mature zone (B) in response to

H2O2 (CD) Ion flux kinetics in root elongation zone (C) and mature zone (D)

in response to OH Two distinctive flux points were identified in kinetics of

responses peak value-identified as a maximum flux value measured after a

treatment end value-identified 20 min after the treatment application An arrow

in each panel represents when oxidative stress was imposed

Two barley varieties (TX9425 salinity tolerant Naso Nijo salinity sensitive)

were used for optimizing the dosage of H2O2 treatment Accordingly TX9425 and

Naso Nijo roots were treated with 01 03 10 30 and 10 mM H2O2 and ion fluxes

data were acquired from both root mature and elongation zones for 15 min after

application of H2O2 We found that except for 01 mM all the H2O2 concentrations

triggered significant ion flux responses in both root zones (Figures 32A 32B and

33A 33B) In the elongation root zone an initial K+ efflux (negative flux values

Figure 32A) and Ca2+ uptake (positive flux values Figure 33A) were observed

Application of H2O2 to the root led to a more intensive K+ efflux and a reduced Ca2+

influx (the latter turned to efflux when concentration of H2O2 was ge 1 mM) (Figures

32A and 33A) In the mature root zone the initial K+ uptake (Figure 32B) and Ca2+

efflux (Figure 33B) were observed Application of H2O2 to the bath led to a dramatic

K+ efflux and Ca2+ uptake (Figures 32B and 33B) Ca2+ flux has returned to pre-

stress level after reaching a peak (Figures 33A 33B) Fluxes of K+ however


32

remained negative after reaching the respective peak (Figure 32A 32B) The time

required to reach a peak increased with an increase in H2O2 concentration (Figures

32A 32B and 33A 33B)

The peak values for both Ca2+ and K+ fluxes showed a clear dose-dependency

for H2O2 concentrations used (Figures 32C 32D and 33C 33D) The biggest

significant difference (p ˂ 005) in ion flux responses of contrasting varieties was

observed at 10 mM H2O2 for both K+ (Figure 32C 32D) and Ca2+ fluxes (Figure

33C 33D) Accordingly 10 mM H2O2 was chosen as the most suitable

concentration for further experiments

Figure 32 (AB) Net K+ fluxes measured from barley variety TX9425 root

elongation zone (A) - about 1 mm from the root tip and mature zone (B) - about

30mm from the root tip with respective H2O2 concentrations (CD) Dose-

dependency of H2O2-induced K+ fluxes from root elongation zone (C) and

mature zone (D) Error bars are means plusmn SE (n = 6 minus 8) Asterisks indicate

statistically significant differences between two varieties ( p lt 005 Studentrsquos

t-test) Responses from Naso Nijo were qualitatively similar to those shown for

TX9425


33

Figure 33 (AB) Net Ca2+ fluxes measured from barley variety TX9425 root

elongation zone (A) and mature zone (B) with respective H2O2 concentrations

(CD) Dose-dependency of H2O2-induced Ca2+ fluxes from root elongation zone

(C) and mature zone (D) Error bars are means plusmn SE (n = 6 minus 8) Asterisks

indicate statistically significant differences between two varieties ( p lt 005

Studentrsquos t-test) Responses from Naso Nijo were qualitatively similar to those

shown for TX9425

332 Genotypic variation in H2O2-induced Ca2+ and K+ fluxes in

barley

Once the optimal H2O2 concentration was chosen eight barley varieties

contrasting in their salt tolerance (see Table 31) were tested for their ability to

maintain K+ and Ca2+ homeostasis under 10 mM H2O2 treatment (Figures 34 and

35) The kinetics of K+ flux responses were qualitatively similar and the

magnitudes were dramatically different between mature and elongation zones as

well as between the varieties tested (Figure 34A 34B) Highest and smallest peak

and end fluxes of K+ were observed in Naso Nijo and CM72 respectively in the

elongation root zone (Figure 34C 34D) The same trend was found in the mature

root zone for K+ peak fluxes with a small difference in K+ end fluxes where the

highest flux was observed in another cultivar Unicorn (Figure 34E 34F) Ca2+

peak flux responses varied among cultivars (Figure 35A 35B) with the highest


34

and smallest Ca2+ fluxes observed in SYR01 and Gairdner in elongation zone

(Figure 35C) and Naso Nijo and ZUG403 in mature zone (Figure 35D)

We then used a quantitative scoring system (Wu et al 2015) to correlate the

magnitude of measured flux responses with the salinity tolerance of each genotype

The overall salinity tolerance of barley was quantified as a damage index score

ranging between 0 and 10 with 0 representing most tolerant and 10 representing

most sensitive variety (Table 31) Peak and end flux values of K+ and Ca2+ were

then plotted against respective tolerance scores A significant (p lt 005) positive

correlation was found between H2O2-induced K+ efflux (Figure 34I 34J) the Ca2+

uptake (Figure 35F) and the salinity damage index score in the mature root zone

At the same time no correlation was found in the elongation zone for either K+

(Figure 34G 34H) or Ca2+ flux (Figure 35E)


response to 10 mM H2O2 treatment from both root elongation zone (A) and

mature zone (B) Error bars are means plusmn SE (n = 6 minus 8) (CDGH) Peak (C)

and end (D) K+ fluxes of eight barley varieties in response to 10 mM H2O2 and

their correlation with damage index (GH respectively) in root elongation zone

(EFIJ) Peak (E) and end (F) K+ fluxes of eight barley varieties in response to

10 mM H2O2 and their correlation with damage index (IJ respectively) in root

mature zone


35



mature zone (B) Error bars are means plusmn SE (n = 6minus8) (CE) Peak Ca2+ fluxes

(C) of eight barley varieties in response to 10 mM H2O2 and their correlation

with damage index (E) in root elongation zone (DF) Peak Ca2+ fluxes (D) of

eight barley varieties in response to 10 mM H2O2 and their correlation with

damage index (F) in root mature zone


wheat

Six wheat varieties contrasting in their salt tolerance were used to check

whether the above trends observed in barley are also applicable to wheat species

Transient K+ and Ca2+ flux responses to 10 mM H2O2 in wheat were qualitatively

identical to those measured from barley roots in both zones (Figures 36A 36B

and 37A 37B) When peak and end flux values were plotted against the salinity

damage index (Table 31 Wu et al 2014) a strong positive correlation was found

between H2O2-induced K+ (Figure 36E 36F) and Ca2+ (Figure 37D) fluxes and

the overall salinity tolerance (Table 31) in wheat root mature zone (p lt 001 for


36

Figure 36I 36J p lt 005 for Figure 37F) Similar to barley no correlation was

found between salt damage index (Table 31) and the magnitude of ion flux

responses (Figures 36C 36D and 37C) in the root elongation zone of wheat

(Figures 36G 36H and 37E)



mature zone (B) Error bars are means plusmn SE (n = 6minus8) (CDGH) Peak (C) and

end (D) K+ fluxes of six wheat varieties in response to 10 mM H2O2 and their

correlation with damage index (GH respectively) in root elongation zone

(EFIJ) Peak (E) and end (F) K+ fluxes of six wheat varieties in response to 10

mM H2O2 and their correlation with damage index (IJ respectively) in root

mature zone


37




(C) of six wheat varieties in response to 10 mM H2O2 and their correlation with

damage index (E) in root elongation zone (DF) Peak Ca2+ fluxes (D) of six

wheat varieties in response to 10 mM H2O2 and their correlation with damage

index (F) in root mature zone

Taken together the above results suggest that the H2O2-induced fluxes of Ca2+

and K+ in mature root zone correlate well with the damage index but no such

correlation exists in the elongation zone

334 Genotypic variation of hydroxyl radical-induced Ca2+ and

K+ fluxes in barley

Using eight barley varieties listed in Table 31 we then repeated the above

experiments using a hydroxyl radical the most aggressive ROS species of which

can be produced during Fenton reaction between transition metal and ascorbate

(Halliwell and Gutteridge 2015) Hydroxyl radicals (OH) were generated by


38

applying 0310 mM Cu2+ascorbate mixture (Demidchik et al 2003) This

treatment caused a dramatic K+ efflux (6ndash8 fold greater than the treatment with

H2O2 data not shown) with fluxes reaching their peak efflux magnitude after 3 to

4 min of stress application in elongation zone and 7 to 13 min in the mature zone

(Figure 38A 38B) The mean peak values ranged from minus3686 plusmn 600 to minus8018 plusmn

536 nmol mminus2middotsminus1 and from minus7669 plusmn 27 to minus11930 plusmn 619 nmolmiddotmminus2middotsminus1 respectively

for the two zones (data not shown)


response to 031 OH treatment from both root elongation zone (A) and mature

zone (B) Error bars are means plusmn SE (n = 6minus8) (CDGH) Peak (C) and end (D)

K+ fluxes of eight barley varieties in response to OH and their correlation with

damage index (GH respectively) in root elongation zone (EFIJ) Peak (E)

and end (F) K+ fluxes of eight barley varieties in response to OH and their

correlation with damage index (IJ respectively) in root mature zone

Contrary to H2O2 treatment a dramatic and instantaneous net Ca2+ efflux was

observed in both zones immediately after application of OH-generation mixture to

the bath (Figure 39A 39B) This Ca2+ efflux was short lived and net Ca2+ influx

was measured after about 2 min from elongation and after 8 min from mature root

zones respectively (Figure 39A 39B) No significant correlation between overall

salinity tolerance (damage index see Table 31) and either Ca2+ or K+ fluxes in


39

response to OH treatment was found in either zone (Figures 38G - 38J and 39E

39F)


response to 031 mM Cu2+ascorbate (OH) treatment from both root

elongation zone (A) and mature zone (B) Error bars are means plusmn SE (n = 6minus8)

(CE) Peak Ca2+ fluxes (C) of eight barley varieties in response to OH and their

correlation with damage index (E) in root elongation zone (DF) Peak Ca2+

fluxes (D) of eight barley varieties in response OH and their correlation with


34 Discussion

ROS are the ldquodual edge swordsrdquo that are essential for plant growth and

signaling when they are maintained at the non-toxic level but that can be

detrimental to plant cells when ROS production exceeds a certain threshold (Mittler

2017) This is particularly true for the role of ROS in plant responses to salinity

Salt-stress induced ROS production is considered to be an essential step in

triggering a cascade of adaptive responses including early stomatal closure (Pei et

al 2000) control of xylem Na+ loading (Jiang et al 2012 Zhu et al 2017) and


40

sodium compartmentalization (de la Garma et al 2015) At the same time

excessive ROS accumulation may have negative impact on intracellular ionic

homeostasis under saline conditions Of specific importance is ROS-induced

cytosolic K+ loss that stimulates protease and endonuclease activity promoting

program cell death (Demidchik et al 2010 2014 Shabala and Pottosin 2014

Hanin et al 2016) Here in this study we show that ROS regulation of ion fluxes

is highly plant tissue-specific and differs between various ROS species

341 The magnitude of the hydroxyl radical-induced K+ and Ca2+

fluxes does not correlate with salinity stress tolerance in barley

Hydroxyl radicals (OH) are considered to be very short-lived (half-life of 1

ns) and highly aggressive agents that are a prime cause of oxidative damage to

proteins and nucleic acids as well as lipid peroxidation during oxidative stress

(Demidchik 2014) At physiologically relevant concentrations they have the

greatest potency to induce activation of Ca2+ and K+ channels leading to massive

fluxes of these ions across cellular membranes (Demidchik et al 2003 2010) with

detrimental effects on cell metabolism This is clearly demonstrated by our data

showing that OH-induced K+ efflux was an order of magnitude stronger compared

with that induced by H2O2 for the appropriate variety and a root zone (eg Figures

34 and 38) Due to their short life they can diffuse over very short distances (lt 1

nm) (Sies 1993) and thus are less suitable for the role of the signaling molecules

Importantly OH cannot be scavenged by traditional enzymatic antioxidants and

the control of OH level in cells is achieved via an elaborate network of non-

enzymatic antioxidants (eg polyols tocopherols polyamines ascorbate

glutathione proline glycine betaine polyphenols carotenoids reviewed by Bose

et al 2014b) It was shown that exogenous application of some of these non-

enzymatic antioxidants prevented OH-induced K+ efflux from plant cells (Cuin

and Shabala 2007) and resulted in improved salinity stress tolerance (Ashraf and

Foolad 2007 Chen and Murata 2008 Pandolfi et al 2010) Thus an ability of

keeping OH levels under control appears to be essential for plant survival under

salt stress conditions and all barley genotypes studied in our work appeared to

possess this ability (although most likely by different means)


41

A recent study from our laboratory (Shabala et al 2016) has shown that higher

sensitivity of the root apex to salinity stress (as compared to mature root zone) was

partially explained by the higher population of OH-inducible K+-permeable efflux

channels in this tissue At the same time root apical cells responses to salinity stress

by a massive increase in the level of allantoin a substance with a known ability to

mitigate oxidative damage symptoms (Watanabe et al 2014) and alleviate OH-

induced K+ efflux from root cells (Shabala et al 2016) This suggests an existence

of a feedback mechanism that compensates hypersensitivity of some specific tissue

and protects it against the detrimental action of OH From our data reported here

we speculate that the same mechanism may exist amongst diverse barley

germplasm (eg those salt sensitive varieties but with less OH-induced K+ efflux)

Thus from the practical point of view the lack of significant correlation between

OH-induced ion fluxes and salinity stress tolerance (Figures 38 and 39) makes

this trait not suitable for salinity breeding programs

342 H2O2-induced K+ and Ca2+ fluxes in cereals correlate with

their overall salinity stress tolerance but only in mature zone

Earlier observations showed that salt sensitive barley varieties (with higher

damage index) have higher K+ efflux in response to H2O2 compared to salt tolerant

varieties (Chen et al 2007a Maksimović et al 2013) In this study we extrapolated

these initial observations made on a few selected varieties to a larger number of

genotypes We have also shown that (1) the same trend is also applicable to wheat

species (2) larger K+ efflux is mirrored by the higher Ca2+ uptake in H2O2-treated

roots and (3) the correlation between salinity tolerance and H2O2-induced ion flux

responses exist only in mature but not elongation root zone

Over the last decade an ability of various plant tissues to retain potassium

under stress conditions has evolved as a novel and essential mechanism of salinity

stress tolerance in plants (reviewed by Shabala and Pottosin 2014 and Shabala et

al 2014 2016) Reported initially for barley roots (Chen et al 2005 2007ac) a

positive correlation between the overall salinity stress tolerance and the ability of a

root tissue to retain K+ was later expanded to many other species (reviewed by

Shabala 2017) and also extrapolated to explain the inter-specific variability in

salinity stress tolerance (Sun et al 2009 Lu et al 2012 Chakraborty et al 2016)


42

In roots this NaCl-induced K+ efflux is mediated predominantly by outward-

rectifying K+ channels GORK that are activated by both membrane depolarization

(Very et al 2014) and ROS (Demidchik et al 2010) as shown in direct patch-

clamp experiments Thus the reduced H2O2 sensitivity of roots of tolerant wheat

and barley genotypes may be potentially explained by either smaller population of

ROS-sensitive GORK channels or by higher endogenous level of enzymatic

antioxidants in the mature root zone It is not clear at this stage if H2O2 is less prone

to induce K+ efflux (eg root cells are less sensitive to this ROS) in salt tolerant

plants or the ldquoeffectiverdquo H2O2 concentration in root cells is lower in salt-tolerant

plants due to a higher scavenging or detoxificating capacity However given the

fact that the activity of major antioxidant enzymes has been shown to be higher in

salt sensitive barley cultivars in both control and H2O2 treated roots (Maksimović

et al 2013) the latter hypothesis is less likely to be valid

The molecular identity of ROS-sensitive transporters should be revealed in the

future pharmacological and (forward) genetic experiments Previously we have

shown that H2O2-induced Ca2+ and K+ fluxes were significantly attenuated in

Arabidopsis Atann1 mutants and enhanced in overexpressing lines (Richards et al

2014) making annexin a likely candidate to this role Further H2O2-induced Ca2+

uptake in Arabidopsis roots was strongly suppressed by application of 30 microM Gd3+

a known blocker of non-selective cation channels (Demidchik et al 2007 ) and

roots pre-treatment with either cAMP or cGMP significantly reduced H2O2-induced

K+-leakage and Ca2+-influx (Ordontildeez et al 2014) implicating the involvement of

cyclic nucleotide-gated channels (one type of NSCC) (Demidchik and Maathuis

2007)

The lack of the above correlation between H2O2-induced K+ efflux and salinity

tolerance in the elongation root zone is very interesting and requires some further

discussion In recent years a ldquometabolic switchrdquo concept has emerged (Demidchik

2014 Shabala 2017) which implies that K+ efflux from metabolically active cells

may be a part of the mechanism inhibiting energy-consuming anabolic reactions

and saving energy for adaptation and reparation needs This mechanism is

implemented via transient decrease in cytosolic K+ concentration and accompanied

reduction in the activity of a large number of K+-dependent enzymes allowing a

redistribution of ATP pool towards defense responses (Shabala 2017) Thus high

K+ efflux from the elongation zone in salt-tolerant varieties may be an important


43

part of this adaptive strategy This suggestion is also consistent with the observation

that plants often respond to salinity stress by the increase in the GORK transcript

level (Adem et al 2014 Chakraborty et al 2016)

It should be also commented that salt tolerant varieties used in this study

usually have lower grain yield under control condition (Chen et al 2007c Cuin et

al 2009) showing a classical trade-off between tolerance and productivity (Weis

et al 2000) most likely as a result of allocation of a larger metabolic pool towards

constitutive defense traits such as maintenance of more negative membrane

potential in plant roots (Shabala et al 2016) or more reliance on the synthesis of

organic osmolytes for osmotic adjustment

343 Reactive oxygen species (ROS)-induced K+ efflux is

accompanied by an increased Ca2+ uptake

Elevation in the cytosolic free calcium is crucial for plant growth

development and adaptation Calcium influx into plant cells may be mediated by a

broad range of Ca2+-permeable channels Of specific interest are ROS-activated

Ca2+-permeable channels that form so-called ldquoROS-Ca2+ hubrdquo (Demidchik and

Shabala 2018) This mechanism implies that Ca2+-activated NADPH oxidases work

in concert with ROS-activated Ca2+-permeable cation channels to generate and

amplify stress-induced Ca2+ and ROS signals (Demidchik et al 2003 2007

Demidchik and Maathuis 2007 Shabala et al 2015) This self-amplification

mechanism may be essential for early stress signaling events as proposed by

Shabala et al 2015 and may operate in the root apex where the salt stress sensing

most likely takes place (Wu et al 2015) In the mature zone however continues

influx of Ca2+ may cause excessive apoplastic O2 production where it is rapidly

reduced to H2O2 By interacting with transition metals (Cu+ and Fe2+) in the cell

wall the hydroxyl radicals are formed (Demidchik 2014) activating K+ efflux

channels This may explain the observed correlation between the magnitude of

H2O2-induced Ca2+ influx and K+ efflux measured in this tissue (Figures 34I 34J

35F 36I 36J and 37F) This notion is further supported by the previous reports

that in Arabidopsis mature root cell protoplasts hydroxyl radicals were proved to

activate and mediate inward Ca2+ and outward K+ currents (Demidchik et al 2003

2007) while exogenous H2O2 failed to activate inward Ca2+ currents (Demidchik


44

et al 2003) The conductance resumed when H2O2 was applied to intact mature

roots (Demidchik et al 2007) This indicated that channel activation by H2O2 may

be indirect and mediated by its interaction with cell wall transition (Fry 1998

Halliwell and Gutteridge 2015)

344 Implications for breeders

Despite great efforts made in plant breeding for salt tolerance in the past

decades only limited success was achieved (Gregorio et al 2002 Munns et al

2006 Shahbaz and Ashraf 2013) It becomes increasingly evident that the range of

the targeted traits needs to be extended shifting a focus from those related to Na+

exclusion from uptake (Shi et al 2003 Byrt et al 2007 James et al 2011 Suzuki

et al 2016) to those dealing with tissue tolerance The latter traits have become the

center of attention of many researchers in the last years (Roy et al 2014 Munns et

al 2016) However to the best of our knowledge none of the previous works

provided an unequivocal causal link between salinity-stress tolerance and ROS

activation of root ion transporters mediating ionic homeostasis in plant cells We

took our first footstep to fill this gap in our knowledge by the current study

Taken together our results indicate high tissue specificity of root ion flux

response to ROS and suggest that measuring the magnitude of H2O2-induced net

K+ and Ca2+ fluxes from mature root zone may potentially be used as a tool for

cell-based phenotyping in breeding programs aimed to improve salinity stress

tolerance in cereals The next step in this process will be a full-scale validation of

the proposed method and finding QTLs associated with ROS-induced ion fluxes in

plant roots

Chapter 4 H2O2-induced ions fluxes in root of various cereal varieties

45

Chapter 4 Validating using MIFE technique-

measured H2O2-induced ion fluxes as physiological

markers for salinity stress tolerance breeding in

wheat and barley

41 Introduction

Wheat and barley are known as important staple food worldwide (Baik and

Ullrich 2008 Shewry 2009) According to FAO

(httpwwwfaoorgworldfoodsituationcsdben) data the world annual wheat and

barley production in 2017 is forecasted at 755 and 148 million tonnes respectively

making them the second and fourth most-produced cereals However the

production rates are increasing rather slow and hardly sufficient to meet the demand

of feeding the estimated 93 billion populations by 2050 (Tester and Langridge

2010) To the large extent this mismatch between potential supply and demand is

determined by the impact of agricultural food production from abiotic stresses

among which soil salinity is one of such factors

The salinity stress tolerance mechanisms of cereals in the context of oxidative

stress tolerance specifically ROS-induced ion fluxes has been investigated and

correlated with the former in our previous study (Chapter 3) By using the MIFE

technique we measured transient ion fluxes from the root epidermis of several

contrasting barley and wheat varieties in response to different types of ROS Being

confined to mature root zone and H2O2 treatment we reported a strong correlation

between H2O2-induced K+ efflux and Ca2+ uptake and their overall salinity stress

tolerance in this root zone with salinity tolerant varieties leaking less K+ and

acquiring less Ca2+ under this stress condition While these finding opened a new

and previously unexplored opportunity to use these novel traits (H2O2-induced K+

and Ca2+ fluxes) as potential physiological markers in breeding programs the

number of genotypes screened was not large enough to convince breeders in the

robustness of this new approach This calls for the validation of the above approach

using a broader range of genotypes In order to validate the applicability of the

above developed MIFE protocol for breeding and examine how robust the above


46

correlation is we extend our work to 44 barley 20 bread wheat and 20 durum wheat

genotypes contrasting in their salinity stress tolerance

Another aim of this study is to reveal the physiological andor molecular

identity of the downstream targets mediating above ion flux responses to ROS

Pharmacological experiments were further conducted using different channel

blockers andor specific enzymatic inhibitors to address this issue and explore the

molecular identity of H2O2-responsive ion transport systems in cereal roots



measurements

Forty-four barley (43 Hordeum vulgare L 1 H vulgare ssp Spontaneum

SYR01) twenty bread wheat (Triticum aestivum) and twenty durum wheat

(Triticum turgidum spp durum) varieties were employed in this study Seedlings

were grown hydroponically as described in the section 221 All details for ion-

selective microelectrodes preparation and ion flux measurements protocols are

available in the section 23 Based on our findings in chapter 3 ions fluxes were

measured from the mature root zone in response to 10 mM H2O2

422 Pharmacological experiments

Mechanisms mediating H2O2-induced Ca2+ and K+ fluxes in root mature zone

in cereals were investigated by the introduction of pharmacological experiments

using one barley (Naso Nijo) and wheat (durum wheat Citr 7805) variety Prior to

the application of H2O2 stress for MIFE measurements roots pre-treated for 1 h

with one of the following chemicals 20 mM tetraethylammonium chloride (TEA+

a known blocker of K+-selective plasma membrane channels) 01 mM gadolinium

chloride (Gd3+ a known blocker of NSCCs) or 20 microM diphenylene iodonium (DPI

a known inhibitor of NADPH oxidase) All chemicals were from Sigma-Aldrich


Statistical significance of mean plusmn SE values was determined by the standard

Studentrsquos t -test at P lt 005 level


47

43 Results

431 H2O2-induced ions kinetics in mature root zone of cereals

Consistent with our previous study in chapter 3 net K+ uptake was measured

in the mature root zone of cereals in resting state (Figure 41A) along with slight

efflux for Ca2+ (Figure 41B) Acute (10 mM) H2O2 treatment caused an immediate

and massive K+ efflux (Figure 41A) and Ca2+ uptake (Figure 41B) with a

gradually recovery of Ca2+ after 20 min of H2O2 application (Figure 41B) The K+

flux never recovered in full and remained negative (Figure 41A)

Figure 41 Descriptions (see inserts in each panel) of net K+ (A) and Ca2+ (B)

flux from cereals root mature zone in response to 10 mM H2O2 in a

representative experiment Two distinctive flux points were marked on the

curves a peak value ndash identified as maximum flux value measured after

treatment and an end value ndash values measured 20 min after the H2O2 treatment

application The arrow in each panel represents the moment when H2O2 was

applied Figures derived from chapter 3

432 H2O2-induced K+ efflux and Ca2+ uptake from the mature root

zone correlates with the overall salinity tolerance in barley

After imposition of 10 mM H2O2 K+ flux changed from net uptake to efflux

The smallest peak and end net flux (leaking less K+) was found in salt-tolerant

CM72 cultivar (-377 + 48 nmol m-2 s-1 and -269 + 39 nmol m-2 s-1 respectively)

The highest peak and end K+ efflux was observed in varieties Naso Nijo (-185 + 35

nmol m-2 s-1) and Dash (-113 + 11 nmol m-2 s-1) (Figures 42A and 42C) At the

same time this treatment resulted in various degree of Ca2+ influx among all the

forty-four barley varieties with the mean peak Ca2+ flux ranging from 155 plusmn 25


48

nmol m-2 s-1 in SYR01 (salinity tolerant) to 652 plusmn 43 nmol m-2 s-1 in Naso Nijo

(salinity sensitive) (Figure 42E) A linear correlation between the overall salinity

stress tolerance (quantified as the salt damage index see Wu et al 2015 and Table

41 for details) and the H2O2-induced ions fluxes were plotted Pronounced and

negative correlations (at P ˂ 0001 level) were found in H2O2-induced of K+ efflux

(Figures 42B and 42D) and Ca2+ uptake (Figure 42F) In our previous study on

chapter 3 conducted on eight contrasting barley genotypes we showed the same

significant correlation between oxidative stress and salinity stress tolerance Here

we validated the finding and provided a positive conclusion about the casual

relationship between salinity stress and oxidative stress tolerance in barley H2O2-

induced Ca2+ uptake and K+ deprivation in barley root mature zone correlates with

their overall salinity tolerance

Table 41 List of barley varieties used in this study Scores represent quantified

extent of damage imposed by salinity to barley plants on a 0 to 10 scale (0 ndash

highest overall salinity tolerance no visual stress symptoms 10 ndash lowest level

of salt tolerance dead plants) Data collected from our previous study by Wu et

al 2015

Damage Index Score of Barley

SYR01 025 RGZLL 200 AC Burman 267 Yan89110 450

TX9425 100 Xiaojiang 200 Clipper 275 Yiwu Erleng 500

CM72 125 YU6472 200 93-3143 C60 300 YPSLDM 500

Honen 150 Barque73 225 Lixi143 300 ZUG403 575

YWHKSL 150 CXHKSL 225 Schooner 300 Dash 600

YYXT 150 Mundah 225 YSM3 300 Macquarie 700

Flagship 175 Dayton 250 Franklin 325 Naso Nijo 750

Gebeina 175 Skiff 250 Hu93-045 325 Haruna Nijo 775

Numar 175 Yan90260 250 Aizao3 350 YF374 800

ZUG293 175 Yerong 250 Gairdner 400 Kinu Nijo 850

DYSYH 200 Zhepi2 250 Sahara 400 Unicorn 950


49

Figure 42 Genetic variability of oxidative stress tolerance in barley Peak K+

flux (A) end K+ flux value (C) and peak Ca2+ flux (E) of forty-four barley

varieties in response to 10 mM H2O2 and their correlation with the damage index

(B D and F respectively) Fluxes were measured from the root mature zone of

4-d-old seedlings Means plusmn SE (n = 6-8 individual plants) Each point (in B D

and F) represents a single variety


zone correlates with the overall salinity stress tolerance in bread

wheat

H2O2-induced ions fluxes in bread wheat were similar with those in barley By

comparing K+ and Ca2+ fluxes of the twenty bread wheat varieties we found salt

tolerant cultivar Titmouse S and sensitive Iran 118 exhibited smallest and biggest

K+ and Ca2+ peak fluxes respectively (Figures 43A and 43E) Similar

observations were found for K+ end flux values for contrasting Berkut and Seville

20 varieties respectively (Figure 43C) A significant (P ˂ 005) correlation

between salinity damage index (Wu et al 2014 Table 42) and H2O2-induced Ca2+

and K+ fluxes were found for bread wheat (Figures 43B 43D and 43F) which

was consistent with our previous results conducted on six contrasting bread wheat

genotypes


50

Table 42 List of wheat varieties used in this study Scores represent quantified



of salt tolerance dead plants) Data collected based on our previous study by Wu

et al 2014

Damage Index Score of Bread Wheat Damage Index Score of Durum Wheat

Berkut 183 Gladius 350 Alex 400 Timilia 633

Titmouse S 183 Kukri 350 Zulu 533 Jori 650

Cranbrook 250 Seville20 383 AUS12746 583 Hyperno 650

Excalibur 250 Halberd 383 Covelle 583 Tamaroi 650

Drysdale 283 Iraq43 417 Jandaroi 600 Odin 683

Persia6 317 Iraq50 417 Kalka 600 AUS19762 733

H7747 317 Iran118 417 Tehuacan60 617 Caparoi 750

Opata 317 Krichauff 450 AUS16469 633 C250 783

India38 333 Sokoll 500 Biskiri ac2 633 Towner 783

Persia21 333 Janz 517 Purple Grain 633 Citr7805 817


51

Figure 43 Genetic variability of oxidative stress tolerance in bread wheat Peak

K+ flux (A) end K+ flux value (C) and peak Ca2+ flux (E) of twenty bread wheat


(B D and F respectively) Fluxes were measured from the mature root zone of




zone correlates with the overall salinity stress tolerance in durum

wheat

Similar to barley and bread wheat H2O2-induced K+ efflux and Ca2+ influx

also correlated with their overall salinity tolerance (Figure 44)


52

Figure 44 Genetic variability of oxidative stress tolerance in durum wheat Peak

K+ flux (A) end K+ flux value (C) and peak Ca2+ flux (E) of twenty durum

wheat varieties in response to 10 mM H2O2 and their correlation with the damage

index (B D and F respectively) Fluxes were measured from the mature root

zone of 4-d-old seedlings Means plusmn SE (n = 6-8 individual plants) Each point

(in B D and F) represents a single variety

435 Barley tends to leak less K+ and acquire less Ca2+ than wheat

in mature root zone upon oxidative stress

A general comparison of K+ and Ca2+ fluxes in response to H2O2 among barley

bread wheat and durum wheat is given in Figure 45 Net flux was calculated as

mean value in each species group (eg 44 barley 20 bread wheat and 20 durum

wheat respectively Figures 45A and 45B) At resting state both bread wheat and

durum wheat showed stronger K+ uptake ability than barley (180 plusmn 12 and 225 plusmn

18 vs 130 plusmn 7 nmol m-2 middot s-1 respectively P ˂ 001 Figure 45C) but no significant

difference was found in their Ca2+ kinetics (Figure 45D) After being treated with

10 mM H2O2 the peak K+ flux did not exhibit obvious significance among the three

species (Figure 45C) while Ca2+ loading from wheat was twice as high as the

loading in barley (52 vs 26 nmol m-2 middot s-1 respectively P ˂ 0001 Figure 45D)

The net mean leakage of K+ and acquisition of Ca2+ showed clear difference among


53

these species with K+ loss and Ca2+ acquisition from barley mature root zone

generally less than bread wheat and durum wheat (Figures 45E and 45F) The

overall trend in H2O2-induced K+ efflux and Ca2+ uptake followed the pattern

durum wheat gt bread wheat gt barley reflecting differences in salinity stress

tolerance between species (Munns and Tester 2008)

Figure 45 General comparison of H2O2-induced net K+ (A) and Ca2+ (B) fluxes

initialpeak K+ flux (C) and Ca2+ flux (D) values net mean K+ efflux (E) and

Ca2+ (F) uptake values from mature root zone in barley bread wheat and durum

wheat Mean plusmn SE (n = 44 20 and 20 genotypes respectively)

436 H2O2-induced ion flux in root mature zone can be prevented

by TEA+ Gd3+ and DPI in both barley and wheat

Pharmacological experiments using two K+-permeable channel blockers (Gd3+

blocks NSCCs TEA+ blocks K+-selective plasma membrane channels) and one

plasma membrane (PM) NADPH oxidase inhibitor (DPI) were conducted to

identify the likely candidate ion transporting systems mediating the above

responses in barley and wheat H2O2-induced K+ efflux and Ca2+ uptake in the

mature root zone was significantly inhibited by Gd3+ TEA+ and DPI (Figure 46)

Both Gd3+ and TEA+ caused a similar (around 60) block to H2O2-induced K+


54

efflux in both species the blocking effect in DPI pre-treated roots was 66 and

49 respectively (Figures 46A and 46B) At the same time the NSCCs blocker

Gd3+ results in more than 90 inhibition of H2O2-induced Ca2+ uptake in both

barley and wheat the K+ channel blocker TEA+ also affected the acquisition of Ca2+

to higher extent (88 and 71 inhibition respectively Figures 46C and 46D)

The inactivation of PM NADPH oxidase caused significant inhibition (up to 96)

of Ca2+ uptake in barley while 51 inhibition was observed in wheat samples

(Figures 46C and 46D)

Figure 46 Effect of DPI (20 microm) Gd3+ (01 mM) and TEA+ (20 mM) pre-

treatment (1 h) on H2O2-induced net mean K+ and Ca2+ fluxes from the mature

root zone of barley (A and C respectively) and wheat (B and D respectively)

Mean plusmn SE (n = 5 ndash 6 plants)

44 Discussion


physiological trait to explore mechanisms of salinity stress

tolerance

H2O2 is known for its signalling role and has been implicated in a broad range

of physiological processes in plants (Choudhury et al 2017 Mittler 2017) such as


55

plant growth development and differentiation (Schmidt and Schippers 2015)

pathogen defense and programmed cell death (Dangl and Jones 2001 Gechev and

Hille 2005 Torres et al 2006) stress sensing signalling and acclimation (Slesak

et al 2007 Baxter et al 2014 Dietz et al 2016) hormone biosynthesis and

signalling (Bartoli et al 2013) root gravitropism (Joo et al 2001) and stomatal

closure (Pei et al 2000) This role is largely explained by the fact that H2O2 has a

long half-life (minutes) and thus can diffuse some distance from the production site

(Pitzschke et al 2006) However excessive production and accumulation of ROS

can be toxic leading to oxidative stress Salinity is one of the abiotic factors causing

such oxidative damage (Hernandez et al 2000) Therefore numerous efforts aimed

at increasing major antioxidants (AO) activity had been taken in breeding for

oxidative stress tolerance associated with salinity tolerance while the outcome

appears unsatisfactory because of the failure in either revealing a correlation

between AO activity and salinity tolerance in a range of species (Dionisio-Sese and

Tobita 1998 Noreen and Ashraf 2009b Noreen et al 2010 Fan et al 2014) or

pyramiding major AO QTLs (Frary et al 2010) Here in this work by using the

seminal MIFE technique we established a causal link between the oxidative and

salinity stress tolerance We showed that H2O2-induced K+ efflux and Ca2+ uptake

in the mature root zone in cereals correlates with their overall salinity tolerance

(Figures 42 43 and 44) with salinity tolerant varieties leak less K+ and acquire

less Ca2+ and vice versa The reported findings here provide additional evidence

about the importance of K+ retention in plant salinity stress tolerance and new

(previously unexplored) thoughts in the ldquoCa2+ signaturerdquo (known as the elevation

in the cytosolic free Ca2+ at the bases of the PM Ca2+-permeable channels

activation during this process (Richards et al 2014) The K+ efflux and the

accompanying Ca2+ uptake upon H2O2 may indicate a similar mechanism

controlling these processes

The existence of a causal association between oxidative and salinity stress

tolerance allows H2O2-induced K+ and Ca2+ fluxes being used as physiological

markers in breeding programs The next step would be creation of the double

haploid population to be used for QTL mapping of the above traits This can be

achieved using varieties with weaker (eg CM72 for barley Titmouse S for bread

wheat AUS 12748 for durum wheat) and stronger (eg Naso Nijo for barley Iran

118 for bread wheat C250 for durum wheat) K+ efflux and Ca2+ flux responses to


56

H2O2 treatment as potential parental lines to construct DH lines The above traits

which are completely new and previously unexplored may be then used to create

salt tolerant genotypes alongside with other mechanisms through the ldquopyramidingrdquo

approach (Flowers and Yeo 1995 Tester and Langridge 2010 Shabala 2013)

442 Barley tends to retain more K+ and acquire less Ca2+ into

cytosol in root mature zone than wheat when subjected to oxidative

stress

All the barley and wheat varieties screened in this study varied largely in their

initial root K+ uptake status (data not shown) and H2O2-induced K+ and Ca2+ flux

(Figures 42 43 and 44 left panels) while their general tendency is comparable

(Figures 45A and 45B) Barley is considered to be the most salt tolerant cereal

followed by the moderate tolerant bread wheat and sensitive durum wheat (Munns

and Tester 2008) In this study the highest K+ uptake ability in root mature zone at

resting state was observed in the salt sensitive durum wheat (Figure 45C) followed

by bread wheat and barley which is consistent with previous reports that leaf K+

content (mmolmiddotg-1 DW) was found highest in durum wheat (146) compared with

bread wheat and barley (126 and 112 respectively) (Wu et al 2014 2015)

According to the concept of ldquometabolic hypothesisrdquo put forward by Demidchik

(2014) K+ a known activator of more than 70 metabolic enzymes (Dreyer and

Uozumi 2011 Anschuumltz et al 2014) and with high concentration in cytosol may

activate the activity of metabolic enzymes and draw the major bulk of available

energy towards the metabolic processes driven by these conditions When plants

encountered stress stimuli a large pool of ATP will be redirected to defence

reactions and energy balance between metabolism and defence determines plantrsquos

stress tolerance (Shabala 2017) Therefore in this study the salt sensitive durum

wheat may utilise the majority bulk of K+ pool for cell metabolism thus the amount

of available energy is limited to fight with salt stress Taken together these findings

further revealed that either higher initial K+ content (Wu et al 2014) or higher

initial K+ uptake value has no obvious beneficial effect to the overall salinity


Unlike the case of steady K+ under control conditions K+ retention ability

under stress conditions has been intensively reported and widely accepted as an


57

essential mechanism of salinity stress tolerance in a range of species (Shabala 2017)

In this study we also revealed a higher K+ retention ability in response to oxidative

stress in the salt tolerant barley variety compared with salt sensitive wheat variety

(Figure 45E) which was accompanied with the same trend in their Ca2+ restriction

ability upon H2O2 exposure (Figure 45F) This may be attributed to the existence

of more ROS sensitive K+ and Ca2+ channels in the latter species While Ca2+

kinetics between the two wheat clusters seems to be another situation Although

H2O2-induced Ca2+ uptake in bread was as higher as that of durum wheat (Figures

45B 45D and 45F) the former cluster was not equally salt sensitive as the latter

(damage index score 355 vs 638 respectively Plt0001 Wu et al 2014) The

physiological rationale behind this observation may be that bread wheat possesses

other (additional) mechanisms to deal with salinity such as a higher K+ retention

(Figure 45E) or Na+ exclusion abilities (Shah et al 1987 Tester and Davenport

2003 Sunarpi et al 2005 Cuin et al 2008 2011 Horie et al 2009) to

compensate for the damage effect of higher Ca2+ in cytosol

443 Different identity of ions transport systems in root mature

zone upon oxidative stress between barley and wheat

Earlier studies reported that ROS is able to activate GORK channel

(Demidchik et al 2010) and NSCCs (Demidchik et al 2003 Shabala and Pottosin

2014) in the root epidermis mediating K+ efflux and Ca2+ influx respectively The

specific oxidant that directly activates these channels is known as bullOH which can

be converted by interaction between H2O2 and cell wall transition metals (Shabala

and Pottosin 2014) We believe that the similar ions transport system is also

applicable to cereals in response to H2O2 At the same time the so-called ldquoROS-

Ca2+ hubrdquo mechanism (Demidchik and Shabala 2018) with the involvement of PM

NADPH oxidase should not be neglected However whether the underlying

mechanisms between barley and wheat are different or not remains elusive As

expected Gd3+ (the NSCCs blocker) and TEA+ (the K+-selective channel blocker)

inhibited H2O2-induced K+ efflux from both cereals (Figures 46A and 46B) The

fact that the extent of inhibition of both blockers was equal in both cereals may be

indicative of an equivalent importance of both NSCC and GORK involved in this

process At the same time Gd3+ caused gt 90 inhibition of Ca2+ uptake in both


58

barley and wheat roots (Figures 46C and 46D) This suggests that H2O2-induced

Ca2+ uptake from the root mature zone of cereals is predominantly mediated by

ROS-activated Ca2+-permeable NSCCs (Demidchik and Maathuis 2007) These

findings suggested that barley and wheat are likely showing similar identities in

ROS sensitive channels

In the case of 1 h pre-treatment with DPI an inhibitor of NADPH oxidase H2O2-

induced Ca2+ uptake was suppressed in both barley and wheat (Figures 46C and

46D) This is fully consistent with the idea that PM NADPH oxidase acts as the

major ROS generating source which lead to enhanced H2O2 production in

apoplastic area under stress conditions (Demidchik and Maathuis 2007) The

apoplastic H2O2 therefore activates Ca2+-permeable NSCC and leads to elevated

cytosolic Ca2+ content which in turn activates PM NADPH oxidase to form a so

called self-amplifying ldquoROS-Ca2+ hubrdquo thus enhancing and transducing Ca2+ and

redox signals (Demidchik and Shabala 2018) Given the fact that K+-permeable

channels (such as GORK and NSCCs) are also activated by ROS the inhibition of

H2O2-induced Ca2+ uptake may lead to major alterations in intracellular ionic

homeostasis which reflected and supported by the observation that DPI pre-

treatment lead to reduced H2O2-induced K+ efflux (Figures 46A and 46B)

However the observation that DPI pre-treatment results in much higher inhibition

effect of H2O2-induced Ca2+ uptake in barley (as high as the Gd3+ pre-treatment

for direct inhibition Figure 46C) compared with wheat (96 vs 51 Figures

46C and 46D) in this study may be indicative of the existence of other Ca2+-

independent Ca2+-permeable channels in the latter cereal The Ca2+-permeable

CNGCs (cyclic nucleotide-gated channels one type of NSCC) therefore may

possibly be involved in this process in wheat mature root cells (Gobert et al

2006 Ordontildeez et al 2014)

Chapter 5 QTLs identification in DH barley population

59

Chapter 5 QTLs for ROS-induced ions fluxes

associated with salinity stress tolerance in barley

51 Introduction

Soil salinity is one of the most major environmental constraints reducing crop

yield and threatening global food security (Munns and Tester 2008 Shahbaz and

Ashraf 2013 Butcher et al 2016) Given the fact that salt-free land is dwindling

and world population is exploding creating salt tolerant crops becomes an

imperative (Shabala 2013 Gupta and Huang 2014)

Salinity stress is complex trait that affects plant growth by imposing osmotic

ionic and oxidative stresses on plant tissues (Adem et al 2014) In this term the

tolerance to each of above components is conferred by numerous contributing

mechanisms and traits Because of this using genetic modification means to

improve crop salt tolerance is not as straightforward as one may expect It has a

widespread consensus that altering the activity of merely one or two genes is

unlikely to make a pronounced change to whole plant performance against salinity

stress Instead the ldquopyramiding approachrdquo was brought forward (Flowers 2004

Yamaguchi and Blumwald 2005 Munns and Tester 2008 Tester and Langridge

2010 Shabala 2013) which can be achieved by the use of marker assisted selection

(MAS) MAS is an indirect selection process of a specific trait based on the

marker(s) linked to the trait instead of selecting and phenotyping the trait itself

(Ribaut and Hoisington 1998 Collard and Mackill 2008) which has been

extensively explored and proposed for plant breeding However not much progress

was achieved in breeding programs based on DNA markers for improving

quantitative whole-plant phenotyping traits (Ben-Ari and Lavi 2012) Taking

salinity stress tolerance as an example although considerable efforts has been made

by prompting Na+ exclusion and organic osmolytes production of plants in

responses to this stress breeding of salt-tolerant germplasm remains unsatisfying

which propel researchers to take oxidative stress (one of the components of salinity

stress tolerance) into consideration

One of the most frequently mentioned traits of oxidative stress tolerance is an

enhanced antioxidants (AOs) activity in plants While a positive correlation


60

between salinity stress tolerance and the level of enzymatic antioxidants has been

reported from a wide range of plant species such as wheat (Bhutta 2011 El-

Bastawisy 2010) rice (Vaidyanathan et al 2003) tomato (Mittova et al 2002)

canola (Ashraf and Ali 2008) and maize (Azooz et al 2009) equally large number

of papers failed to do so (barley - Fan et al 2014 rice - Dionisio-Sese and Tobita

1998 radish - Noreen and Ashraf 2009 turnip - Noreen et al 2010) Also by

evaluating a tomato introgression line (IL) population of S lycopersicum M82

and S pennellii LA716 Frary (Frary et al 2010) identified 125 AO QTLs

(quantitative trait loci) associated with salinity stress tolerance Obviously the

number is too big to make QTL mapping of this trait practically feasible (Bose et

al 2014b)

Previously in Chapter 3 and 4 we have revealed a causal relationship between

oxidative stress and salinity stress tolerance in barley and wheat and explored the

oxidative stress-related trait H2O2-induced Ca2+ and K+ fluxes as potential

selection criteria for crop salinity stress tolerance Here in this chapter we have

applied developed MIFE protocols to a double haploid (DH) population of barley

to identify QTLs associated with ROS-induced root ion fluxes (and overall salinity

tolerance) Three major QTLs regarding to oxidative stress-induced ions fluxes in

barley were identified on 2H 5H and 7H respectively This finding suggested the

potential of using oxidative stress-induced ions fluxes as a powerful trait to select

salt tolerant germplasm which also provide new thoughts in QTL mapping for

salinity stress tolerance based on different physiological traits


521 Plant material growth conditions and Ca2+ and K+ flux

measurements

A total of 101 double haploid (DH) lines from a cross between CM72 (salt

tolerant) and Gairdner (salt sensitive) were used in this study Seedlings were

grown hydroponically as described in the section 221 All details for ion-selective

microelectrodes preparation and ion flux measurements protocols are available in

the section 23 Based on our previous findings ions fluxes were measured from

the mature root zone in response to 10 mM H2O2


61

522 QTL analysis

Two physiological markers namely H2O2-induced peak K+ and Ca2+ fluxes

were used for QTL analysis The genetic linkage map was constructed using 886

markers including 18 Simple Sequence Repeat (SSR) and 868 Diversity Array

Technology (DArT) markers The software package MapQTL 60 (Ooijen 2009)

was used to detect QTL QTL analysis was first conducted by interval mapping

(IM) For this the closest marker at each putative QTL identified using interval

mapping was selected as a cofactor and the selected markers were used as genetic

background controls in the approximate multiple QTL model (MQM) A logarithm

of the odds (LOD) threshold values ge 30 was applied to declare the presence of a

QTL at 95 significance level To determine the effects of another trait on the

QTLs for salinity tolerance the QTLs for salinity tolerance were re-analysed using

another trait as a covariate Two LOD support intervals around each QTL were

established by taking the two positions left and right of the peak that had LOD

values of two less than the maximum (Ooijen 2009) after performing restricted

MQM mapping The percentage of variance explained by each QTL (R2) was

obtained using restricted MQM mapping implemented with MapQTL60

523 Genomic analysis of potential genes for salinity tolerance

The sequences of markers bpb-8484 (on 2H) bpb-5506 (on 5H) and bpb-3145

(on 7H) associated with different QTL for oxidative stress tolerance were used to

identify candidate genes for salinity tolerance The sequences of these markers were

downloaded from the website httpwwwdiversityarrayscom followed by a blast

search on the website httpwebblastipkgaterslebendebarley to identify the

corresponding morex_contig of these markers The morex_contig_48280

morex_contig_136756 and morex_contig_190772 were found to be homologous

with bpb-8484 (Identities = 684703 97) bpb-5506 (Identities = 726736 98)

and bpb-3145 (Identities = 247261 94) respectively The genome position of

these contigs were located at 7691 cM on 2H 4413 cM on 5H and 12468 cM on

7H Barley genomic data and gene annotations were downloaded from

httpwebblastipk-gaterslebendebarley_ibscdownloads Annotated high

confidence genes between 6445 and 8095 cM on 2H 4299 and 4838 cM on 5H


62

11983 and 14086 cM on 7H were deemed to be potential genes for salinity

tolerance

53 Results

531 Peak K+ and Ca2+ fluxes of the DH lines under H2O2 treatment

As shown in Table 51 two parental lines showed significant difference in

H2O2-induced peak K+ and Ca2+ flux with the salt tolerant cultivar CM72 leaking

less K+ (less negative) and acquiring less Ca2+ (less positive) than the salt sensitive

cultivar Gairdner DH lines from the cross between CM72 and Gairdner also

showed significantly different Ca2+ (from 15 to 60 nmolmiddotm-2middots-1) and K+ (from -43

to -190 nmolmiddotm-2middots-1) fluxes in response to 10 mM H2O2 Figure 51 shows the

frequency distribution of peak K+ flux and peak Ca2+ flux upon H2O2 treatment in

101 DH lines

Table 51 H2O2-induced peak K+ and Ca2+ flux from parental and DH lines

Cultivars Peak K+ flux (nmolmiddotm-2middots-1) Peak Ca2+ flux (nmolmiddotm-2middots-1)

CM72 -47 plusmn 33 264 plusmn 35

Gairdner -122 plusmn 134 404 plusmn12

DH lines average -97 plusmn 174 335 plusmn 39

DH lines range -43 to -190 15 to 60

Data are Mean plusmn SE (n = 6)

Figure 51 Frequency distribution for Peak K+ flux (A) and Peak Ca2+ flux (B)

of DH lines derived from a cross of CM72 and Gairdner exposed to 10 mM H2O2

treatment


63

532 QTLs for H2O2-induced peak K+ flux and peak Ca2+ flux

Three QTLs for H2O2-induced peak K+ flux were identified on chromosomes

2H 5H and 7H which were designated as QKFCG2H QKFCG5H and

QKFCG7H respectively (Table 52 Figure 52) The nearest marker for

QKFCG2H is bPb-4482 which explained 92 of phenotypic variation The bPb-

5506 is the nearest marker for QKFCG5H and explained 103 of phenotypic

variation The third one QKFCG7H accounts for 117 of phenotypic variation

with bPb-0773 being the closest marker

Two QTLs for H2O2-induced Peak Ca2+ flux were identified on chromosomes

2H (QCaFCG2H) and 7H (QCaFCG7H) (Table 52 Figure 52) with the nearest

marker is bPb-0827 and bPb-8823 respectively The former explained 113 of

phenotypic variation while the latter explained 148



peak Ca2+ flux as a covariate

Traits QTL

Linkage

group

Nearest

marker

Position

(cM) LOD

R2

() Covariate

KF

QKFCG2H 2H bPb-4482 126 312 92

QKFCG5H 5H bPb-5506 507 348 103 NA

QKFCG7H 7H bPb-0773 166 391 117

CaF QCaFCG2H 2H bPb-0827 1128 369 113

NA QCaFCG7H 7H bPb-8823 156 425 148

KF

QKFCG2H 2H

NS NS

CaF QKFCG5H 5H bPb-0616 47 514 145

QKFCG7H 7H

NS NS

KFCaF H2O2-induced peak K+ Ca2+ flux NS not significant NA not applicable


64

Figure 52 QTLs associated with H2O2-induced peak K+ flux (in red) and H2O2-

induced peak Ca2+ flux (in blue) For better clarity only parts of the chromosome

regions next to the QTLs are shown

533 QTL for KF when using CaF as a covariate

As shown in Table 52 QTLs related to oxidative stress induced peak K+ flux

and Ca2+ flux were observed on 2H 5H and 7H By compare the physical position

of the linkage map QTLs on 2H for peak K+ and Ca2+ flux and on 7H were located

at similar positions indicating a possible relationship between these two traits

(Table 52 Figures 53A and 53B) To further confirm this a QTL analysis for KF

was conducted by using CaF as a covariate Of the three QTLs for H2O2-induced

peak K+ flux only QKFCG5H was not affected (LOD = 347 R2 = 101) when

CaF was used as a covariate The other two QTLs QKFCG2H and QKFCG7H

which located at similar positions to those for H2O2-induced peak Ca2+ flux

became insignificant (LOD ˂ 2) (Figure 53C)


65

Figure 53 Chart view of QTLs for H2O2-induced peak K+ (A) and Ca2+ (B) flux

in the DH line (C) Chart view of QTLs for H2O2-induced peak K+ flux when

using H2O2-induced peak Ca2+ flux as covariate Arrows (peaks of LOD value)

in panels indicate the position of associated markers

534 Potential genes for H2O2-induced K+ and Ca2+ flux on 2H 5H

and 7H

Three QTLs were identified for H2O2-induced K+ and Ca2+ flux with QTLs

from 2H and 7H being involved in both H2O2-induced K+ and Ca2+ fluxes and QTL

from 5H being associated with H2O2-induced K+ flux only By blast searching of

the three closely linked markers bpb-8484 on 2H bpb-5506 on 5H and bpb-3145

on 7H high confidence genes were extracted near these markers Among all

annotated genes a total of eight genes in these marker regions were chosen as the

candidate genes for these traits (Table 53) which can be used for in-depth study in

the near future


66

Table 53 Candidate genes for H2O2-induced K+ and Ca2+ flux

Chromosome Candidate genes

2H Calcium-dependent lipid-binding (CaLB domain) family

protein 1

Annexin 8 1

5H NAC transcription factor 2

AP2-like ethylene-responsive transcription factor 2

7H

Calcium-binding EF-hand family protein 1

Calmodulin like 37 (CML37) 1

Protein phosphatase 2C family protein (PP2C) 3

WRKY family transcription factor 2

1 Calcium-dependent proteins 2 transcription factors 3 other proteins

54 Discussion

541 QTL on 2H and 7H for oxidative stress control both K+ and

Ca2+ flux

Salinity stress is one of the major yield-limiting factors and plantrsquos tolerance

mechanisms to this stress is highly complex both physiologically and genetically

(Negratildeo et al 2017) Three major components are involved in salinity stress in

crops osmotic stress specific ion toxicity and oxidative stress Among them

improving plant ability to synthesize organic osmotica for osmotic adjustment and

exclude Na+ from uptake have been targeted to create salt tolerant crop germplasm

(Sakamoto and Murata 2000 Martinez-Atienza et al 2007 Munns et al 2012

Wani et al 2013 Byrt et al 2014) However these efforts have been met with a

rather limited success (Shabala et al 2016)

Until now no QTL associated with oxidative stress-induced control of plant

ion homeostasis have been reported yet for any crop species Here we identified

two QTLs on 2H and 7H controlling H2O2-induced K+ flux (QKFCG2H and


67

QKFCG7H respectively) and Ca2+ flux (QCaFCG2H and QCaFCG7H

respectively) and one QTL on 5H related to H2O2-induced K+ flux (QKFCG5H)

in the seedling stage from a DH population originated from the cross of two barley

cultivars CM72 and Gairdner Further analysis on the QTL for KF using CaF as a

covariate confirmed that same genes control KF and CaF on both 2H and 7H

(Figure 53C) QKFCG5H was less affected (Figure 53C) when CaF was used as

a covariate indicating the exclusive involvement of this QTL in H2O2-induced K+

efflux Therefore all these three major QTL (one on each 2H 5H and 7H) identified

in this work could be candidate loci for further oxidative stress tolerance study The

genetic evidence for oxidative stress tolerance revealed in this study may also be of

great importance for salinity stress tolerance Plantsrsquo K+ retention ability under

unfavorable conditions has been largely studied in a range of species in recent years

indicating the important role of this trait played in conferring salinity stress

tolerance (Shabala 2017) This can be reflected by the fact that K+ content in plant

cell is more than 100-fold than in the soil (Dreyer and Uozumi 2011) It is also

involved in various key physiological pathways including enzyme activation

membrane potential formation osmoregulation cytosolic pH homeostasis and

protein synthesis (Veacutery and Sentenac 2003 Gierth and Maumlser 2007 Dreyer and

Uozumi 2011 Wang et al 2013 Anschuumltz et al 2014 Cheacuterel et al 2013) making

the maintenance of high cytosolic K+ content highly required (Wu et al 2014) On

the other hand plants normally maintain a constant and low (sub-micromolar) level

of free calcium in cytosol to use it as a second messenger in many developmental

and signaling cascades Upon sensing salinity cytosolic free Ca2+ levels are rapidly

elevated (Bose et al 2011) prompting a cascade of downstream events One of

them is an activation of the NADPH oxidase This plasma membrane-based protein

is encoded by RBOH (respiratory burst oxidase homolog) genes and has two EF-

hand motifs in the hydrophilic N-terminal region and is synergistically activated by

Ca2+-binding to the EF-hand motifs along with phosphorylation (Marino et al

2012) Ca2+ binding then triggers a conformational change that results in the

activation of electron transfer originating from the interaction between the N-

terminal Ca2+-binding domain and the C-terminal superdomain (Baacutenfi et al 2004)

Plant plasma membranes also harbor various non-selective cation channels

(NSCCs) which are permeable to Ca2+ and may be activated by both membrane

depolarisation and ROS (Demidchik and Maathuis 2007) Together RBOH and


68

NSCC forms a positive feedback loop termed ldquoROS-Ca2+ hubrdquo (Demidchik and

Shabala 2018) that amplifies stress-induced Ca2+ and ROS transients While this

process is critical for plant adaptation the inability to terminate it may be

detrimental to the organism Thus lower ROS-induced Ca2+ uptake seems to give

plant a competitive advantage

By using the same DH population as in this study a QTL associated with leaf

temperature (one of the traits for drought tolerance) was reported at the similar

position with our QTLs for oxidative stress tolerance on 2H (Liu et al 2017)

Moreover meta-analysis of major QTL for abiotic stress tolerance in barley also

indicated a high density of QTL for drought salinity and waterlogging stress at this

location on 2H (Zhang et al 2017) The same publication also summarized a range

of major QTLs for salinity stress tolerance at the position of 5H as in this study

(Zhang et al 2017) Another study using TX9425Naso Nijo DH population

reported a QTL associated with waterlogging stress tolerance at the similar position

of 7H with this study (Xu et al 2012) While both drought and water logging stress

are able to induce transient Ca2+ uptake to cytosol (Bose et al 2011) and K+ efflux

to extracellular spaces (Wang et al 2016) then ROS produced due to drought

stress-induced stomatal closure and water logging stress-induced oxygen

deprivation may be one of the factors facilitate these processes Therefore as ROS

production under stress conditions is a common denominator (Shabala and Pottosin

2014) the QTLs for oxidative stress identified in this study which associated with

salinity stress tolerance may at least in part possess similar mechanisms with the

mentioned stresses above

542 Potential genes contribute to oxidative stress tolerance

ROS (especially bullOH) are known to activate a number of K+- and Ca2+-

permeable channels (Demidchik et al 2003 2007 2010 Demidchik and Maathuis

2007 Zepeda-Jazo et al 2011) prompting Ca2+ influx into and K+ efflux from

cytosol especially in cells from the mature root zone Therefore the identified

QTLs for H2O2-induced ions fluxes might be probably closely related to these ions

transporting systems or act as subunit of these channels In our previous chapter

(Chapter 4) we explored the molecular identity of ion transport system upon H2O2

treatment in root mature zone of both barley and wheat and revealed an

involvement of NSCCs GORK channels and PM NADPH oxidase in this process


69

The ROS-activated K+-permeable NSCCs and GORK channels mediated H2O2-

induced K+ efflux At the same time ROS-activated Ca2+-permeable NSCCs

mediated H2O2-induced Ca2+ uptake with the activation of PM NADPH oxidase

by elevated cytosolic Ca2+ It is not clear at this stage which specific genes

contribute to these processes Plants utilise transmembrane osmoreceptors to

perceive and transduce external oxidative stress signal inducing expression of

functional response genes associated with these ion channels or other processes

(Liu et al 2017) Therefore genes in these pathways have higher possibility to be

taken as candidate genes In this study the nearest markers of the QTL detected

were located around 7691 cM on 2H 4413 cM on 5H and 12468 cM on 7H

Several candidate genes in the vicinity of the reported markers appear to be present

associated with ions fluxes These include calcium-dependent proteins

transcription factors and other stress related proteins (Table 53)

Since H2O2-induced Ca2+ acquisition was spotted therefore proteins binding

Ca2+ or contributing to Ca2+ signalling can be deemed as candidates It is claimed

that many signals raise cytosolic Ca2+ concentration via Ca2+-binding proteins

among which three quarters contain Ca2+-binding EF-hand motif(s) (Day et al

2002) making calcium-binding EF-hand family protein as one of the potential

genes One example is PM-based NADPH oxidase mentioned above Other

candidates that possess Ca2+-binding property is calmodulin like proteins (CML

such as CML 37) and Ca2+-dependent lipid-binding (CaLB) domains The former

are putative Ca2+ sensors with 50 family and varying number of EF hands reported

in Arabidopsis (Vanderbeld and Snedden 2007 Zeng et al 2015) the latter also

known as C2 domains are a universal Ca2+-binding domains (Rizo and Sudhof

1998 de Silva et al 2011) Both were shown to be involved in plant response to

various abiotic stresses (Zhang et al 2013 Zeng et al 2015) Annexins are a group

of Ca2+-regulated phospholipid and membrane-binding proteins which have been

frequently mentioned to catalyse transmembrane Ca2+ fluxes (Clark and Roux 1995

Davies 2014) and contributes to plant cell adaptation to various stress conditions

(Laohavisit and Davies 2009 2011 Clark et al 2012) In Arabidopsis AtANN1 is

the most abundant annexin and a PM protein that regulates H2O2-induced Ca2+

signature by forming Ca2+-permeable channels in planar lipid bilayers (Lee et al

2004 Richards et al 2014) Its role in other species such as cotton (GhAnn1 -

Zhang et al 2015) potato (STANN1 - Szalonek et al 2015) rice (OsANN1 - Qiao


70

et al 2015) brassica (AnnBj1 - Jami et al 2008) and lotus (NnAnn1 - Chu et al

2012) was also reported While reports about Annexin 8 are rare a study by

overexpressing AnnAt8 in Arabidopsis and tobacco showed enhanced abiotic stress

tolerance in the transgenic lines (Yadav et al 2016) Therefore the identified

candidate gene Annexin 8 could be taken into consideration for the QTL found in

2H in this study

Transcription factors (TFs) are DNA-binding domains containing proteins that

initiate the process of converting DNA to RNA (Latchman 1997) which regulate

downstream activities including stress responsive genes expression (Agarwal and

Jha 2010) In Arabidopsis thaliana 1500 TFs were described to be involved in this

process (Riechmann et al 2000) According to our genomic analysis in this study

three transcription factors in the vicinity of nearest markers were observed

including NAC transcription factor and AP2-like ethylene-responsive transcription

factor on 5H and WRKY family transcription factor on 7H (Table 53) Indeed

previous studies about these transcription factors have been well-documented

(Nakashima et al 2012 Licausi et al 2013 Nuruzzaman et al 2013 Rinerson et

al 2015 Guo et al 2016 Jiang et al 2017) indicating their role in plant stress

responses

Protein phosphatases type 2C (PP2Cs) may also be potential target genes

They constitute one of the classes of protein serinethreonine phosphatases sub-

family which form a structurally and functionally unique class of enzymes

(Rodriguez 1998 Meskiene et al 2003) They are also known as evolutionary

conserved from prokaryotes to eukaryotes and playing vital role in stress signalling

pathways (Fuchs et al 2013) Recent studies have demonstrated that

overexpression of PP2C in rice (Singh et al 2015) and tobacco (Hu et al 2015)

resulted in enhanced salt tolerance in the related transgenic lines Its function in

barley deserves further verification

Chapter 6 High-throughput assay

71

Chapter 6 Developing a high-throughput

phenotyping method for oxidative stress tolerance

in cereal roots

61 Introduction

Both global climate change and unsustainable agricultural practices resulted

in significant soil salinization thus reducing crop yields (Horie et al 2012 Ismail

and Horie 2017) Until now more than 20 of the worldrsquos agricultural land (which

accounts for 6 of the worldrsquos total land) has been affected by excessive salts this

number is increasing daily ( Ismail and Horie 2017 Gupta and Huang 2014) Given

the fact that more food need to be acquired from the limited arable land to feed the

expanding world population in the next few decades (Brown and Funk 2008 Ruan

et al 2010 Millar and Roots 2012) generating crop germplasm which can grow

in high-salt-content soil is considering a major avenue to fully utilise salt-affected

land (Shabala 2013)

One of constraints imposed by salinity stress on plants is an excessive

production and accumulation of reactive oxygen species (ROS) causing oxidative

stress This results in a major perturbation to cellular ionic homeostasis (Demidchik

2015) and in extreme cases has severe damage to plant lipids DNA proteins

pigments and enzymes (Ozgur et al 2013 Choudhury et al 2017) Plants deal

with excessive ROS production by increased activity of antioxidants (AO)

However given the fact that AO profiles show strong time- and tissue- (and even

organelle-specific) dependence and in 50 cases do not correlate with salinity

stress tolerance (Bose et al 2014b) the use of AO activity as a biochemical marker

for salt tolerance is highly questionable (Tanveer and Shabala 2018)

In chapter 3 and 4 we have shown that roots of salt-tolerant barley and wheat

varieties possessed greater K+ retention and lower Ca2+ uptake when challenged

with H2O2 These ionic traits were measured by using the MIFE (microelectrode

ion flux estimation) technique We have then applied MIFE to DH (double haploid)

barley lines revealing a major QTL for the above flux traits in chapter 5 These

findings open exciting prospects for plant breeders to screen germplasm for

oxidative stress tolerance targeting root-based genes regulating ion homeostasis


72

and thus conferring salinity stress tolerance The bottleneck in application of this

technique in breeding programs is a currently low throughput capacity and

technical complications for the use of the MIFE method

The MIFE technique works as a non-invasive mean to monitor kinetics of ion

transport (uptake or release) across cellular membranes by using ion-selective

microelectrodes (Shabala et al 1997) This is based on the measurement of

electrochemical gradients near the root surface The microelectrodes are made on a

daily basis by the user by filling prefabricated pulled microcapillary with a sharp

tip (several microns diameter) with specific backfilling solution and appropriate

liquid ionophore specific to the measured ion Plant roots are mounted in a

horizontal position in a measuring chamber and electrodes are positioned in a

proximity of the root surface using hand-controlled micromanipulators Electrodes

are then moved in a slow square-wave 12 sec cycle measuring ion diffusion

profiles (Shabala et al 2006) Net ion fluxes are then calculated based on measured

voltage gradients between two positions close to the root surface and some

distance (eg 50 microm) away The method is skill-demanding and requires

appropriate training of the personnel The initial setup cost is relatively high

(between $60000 and $100000 depending on a configuration and availability of

axillary equipment) and the measurement of one specimen requires 20 to 25 min

Accounting for the additional time required for electrodes manufacturing and

calibration one operator can process between 15 and 20 specimens per business

day using developed MIFE protocols in chapter 3 As breeders are usually

interested in screening hundreds of genotypes the MIFE method in its current form

is hardly applicable for such a work

In this work we attempted to seek much simpler alternative phenotyping

methods that can be used to screen cereal plants for oxidative stress tolerance In

order to do so we developed and compared two high-throughput assays (a viability

assay and a root growth assay) for oxidative stress screening of a representative

cereal crop barley (Hordeum vulgare) The biological rationale behind these

approaches lies in a fact that ROS-induced cytosolic K+ depletion triggers

programmed cell death (Shabala 2007 Shabala 2009 Demidchik at al 2010) and

results in the loss of cell viability This effect is strongest in the root apex (Shabala

et al 2016) and is associated with an arrest of the root growth Reliability and


73

feasibility of these high-throughput assays for plant breeding for oxidative stress

tolerance are discussed in this paper



Eleven barley (ten Hordeum vulgare L and one H vulgare ssp Spontaneum)

varieties contrasting in salinity tolerance were used in this study All seeds were

obtained from the Australian Winter Cereal Collection The list of varieties is

shown in Table 61 Seedlings for experiment were grown in paper roll (see 222

for details)

Treatment with H2O2 was started at two different age points 1 d and 3 d and

lasted until plant seedlings reached 4 d of growth at which point assessments were

conducted so that in both cases 4-d old plants were assayed Concentrations of H2O2

ranged from 0 to 10 mM Fresh solutions were made on a daily basis to compensate

for a possible decrease of H2O2 activity

Table 61 Barley varieties used in the study The damage index scores represent

quantified damage degree of barley under salinity stress with scores from 0 to

10 indicating barley overall salinity tolerance from the best (0) to the worst (10)

(see Wu et al 2015 for details)

Varieties Damage Index Score

SYR01 025

TX9425 100

CM72 120

YYXT 145

Numar 170

ZUG293 170

Hu93-045 325

ZUG403 570

Naso Nijo 750

Kinu Nijo 6 845

Unicorn 945


74

622 Viability assay

Viability assessment of barley root cells was performed using a double staining

method that included fluorescein diacetate (FDA Cat No F7378 Sigma-Aldrich)

and propidium iodide (PI Cat No P4864 Sigma-Aldrich) (Koyama et al 1995)

Briefly control and H2O2-treated root segments (about 5 mm long) were isolated

from both a root tip and a root mature zone (20 to 30 mm from the root tip) stained

with freshly prepared 5 microgml FDA for 5 min followed by 3 microgml PI for 10 min

and washed thoroughly with distilled water Stained root segment was placed on a

microscope slide covered with a cover slip and assessed immediately using a

fluorescent microscope Staining and slide preparation were done in darkness A

fluorescent microscope (Leica MZ12 Leica Microsystems Wetzlar Germany)

with I3-wavelength filter (Leica Microsystems) and illuminated by an ultra-high-

pressure mercury lamp (Leica HBO Hg 100 W Leica Microsystems) was used to

examine stained root segments The excitation and emission wavelengths for FDA

and PI were 450 ndash 495 nm and 495 ndash 570 nm respectively Photographs were taken

by a digital camera (Leica DFC295 Leica Microsystems) Images were acquired

and processed by LAS V38 software (Leica Microsystems) The exposure features

of the camera were set to constant values (gain 10 x saturation 10 gamma 10) in

each experiment allowing direct comparison of various genotypes For untreated

roots the exposure time was 591 ms for H2O2-treated roots it was increased to 19

s The overview of the experimental protocol for viability assay by the FDA - PI

double staining method is shown in Figure 61 The ImageJ software was used to

quantify red fluorescence intensity that is indicative of the proportion of dead cells

Images of H2O2-treated roots were normalised using control (untreated) roots as a

background


75

Figure 61 Viability staining and fluorescence image acquisition (A) Isolated

root segments from control (C) and treatment (T) seedlings placed in a Petri dish

(35 mm diameter) separated with a cut yellow pipette tip for convenience

stained with FDA followed by PI (B) Stained and washed root segments

positioned on a glass slide and covered with a cover slip The prepared slide was

then placed on a fluorescent microscope mechanical stage (C) Sample area

observed under the fluorescent light (D) A typical root fluorescent image

acquired by the LAS V38 software from mature root zone of a control plant

623 Root growth assay

Root lengths of 4-d old barley seedlings were measured after 3 d of treatments

with various concentrations of H2O2 ranging between 0 and 10 mM (0 01 03 1


76

3 10 mM) The relative root lengths (RRL) were estimated as percentage of root

lengths to controls of the respective genotypes




63 Results

631 H2O2 causes loss of the cell viability in a dose-dependent

manner

Barley variety Naso Nijo was used to study dose-dependent effects of H2O2 on

cell viability The concentrations of H2O2 used were from 03 to 10 mM Both 1 d-

(Figure 62A) and 3 d- (Figure 62B) exposure to oxidative stress caused dose-

dependent loss of the root cell viability One-day H2O2 treatment was less severe

and was observed only at the highest H2O2 concentration used (Figure 62A) When

roots were treated with H2O2 for 3 days the red fluorescence signal can be readily

observed from H2O2 treatments above 3 mM (Figure 62B)

Figure 62 Viability staining of Naso Nijo roots (elongation and mature zones)

exposed to 0 03 1 3 10 mM H2O2 for 1 day (A) and 3 days (B) One (of five)

typical images is shown from each concentration and root zone Bar = 1 mm


77

Quantitative analyses of the red fluorescence intensity were implemented in

order to translate images into numerical values (Figure 63) Mild root damage was

observed upon 1 d H2O2 treatment and there was no significant difference between

elongation zone and mature zone for any concentration used (Figure 63A) Similar

findings (eg no difference between two zones) were observed in 3 d H2O2

treatment when the concentration was low (le 3 mM) (Figure 63B) Application of

10 mM H2O2 resulted in severe damage to root cells and clearly differentiated the

insensitivity difference between the two root zones with elongation zone showing

more severe root damage compared to the mature zone (Figure 63B significant at

P ˂ 005) Accordingly 10 mM H2O2 with 3 d treatment was chosen as the optimum

experimental treatment for viability staining assays on contrasting barley varieties

Figure 63 Red fluorescence intensity (in arbitrary units) measured from roots

of Naso Nijo upon exposure to various H2O2 concentrations for either one day

(A) or three days (B) Mean plusmn SE (n = 5 individual plants)

632 Genetic variability of root cell viability in response to 10 mM

H2O2

Five contrasting barley varieties (salt tolerant CM72 and YYXT salt sensitive

ZUG403 Naso Nijo and Unicorn) were employed to explore the extent of root

damage upon oxidative stress by the means of viability staining of both elongation

and mature root zones A visual assessment showed clear root damage upon 3 d-

exposure to 10 mM H2O2 in all barley varieties and both root zones and damage in

the elongation zone was more severe than in the mature zone (Figures 62B and

64)


78

Figure 64 Viability staining of root elongation (A) and mature (B) zones of four

barley varieties (CM72 YYXT ZUG403 Unicorn) exposed to 10 mM H2O2 for

3 days One (of five) typical images is shown for each zone Bar = 1 mm

The quantitative analyses of the fluorescence intensity revealed that salt

sensitive varieties showed stronger red fluorescence signal in the root elongation

zone than tolerant ones (Figure 65A) indicating much severe root damage of the

sensitive genotypes By pooling sensitive and tolerant varieties into separate

clusters a significant (P ˂ 001) difference between two contrasting groups was

observed (Figure 65B) In mature root zone however no significant difference

was observed amongst the root cell viability of five contrasting varieties studied

(Figure 65C)


79

Figure 65 Quantitative red fluorescence intensity from root elongation (A) and

mature zones (C) of five barley varieties exposed to 10 mM H2O2 for 3 d (B)

Average red fluorescence intensity measured from root elongation zone of salt

tolerant and salt sensitive barley groups Mean plusmn SE (n = 6) Asterisks indicate

statistically significant differences between salt tolerant and sensitive varieties

at P lt 001 (Studentrsquos t-test)

The results in this section were consistent with our findings in chapter 3 and 4

using MIFE technique which elucidated that not only oxidative stress-induced

transient ions fluxes but also long-term root damage correlates with the overall

salinity tolerance in barley

Based on these findings we can conclude that plant oxidative and salinity

stress tolerance can be quantified by the viability staining of roots treated with 10

mM H2O2 for 3 days that would include staining the root tips with FDA and PI and

then quantifying intensity of the red fluorescence signal (dead cells) from root

elongation zone This protocol is simpler and quicker than MIFE assessment and

requires only a few minutes of measurements per sample making this assay

compliant with the requirements for high throughput assays


80

633 Methodological experiments for cereal screening in root

growth upon oxidative stress

Being a high throughput in nature the above imaging assay still requires

sophisticated and costly equipment (eg high-quality fluorescence camera

microscope etc) and thus may be not easily applicable by all the breeders This

has prompted us to go along another avenue by testing root growth assays Two

contrasting barley varieties TX9425 (salt tolerant) and Naso Nijo (salt sensitive)

were used for standardizing concentration of ROS (H2O2) treatment in preliminary

experiments After 3 d of H2O2 treatment root length declined in both the varieties

for any given concentration tested (01 03 1 3 10 mM) and salt tolerant variety

TX9425 grew better (had higher relative root length RRL) than salt sensitive

variety Naso Nijo at each the treatment used (Figure 66A) The decreased RRL

showed the dose-dependency upon increasing H2O2 concentration with a strong

difference (P ˂ 0001) occurring from 1 to 10 mM H2O2 treatments between the

contrasting varieties (Figure 66A) The biggest difference in RRL between the

varieties was observed under 1 mM H2O2 treatment (Figure 66A) which was

chosen for screening assays


81

Figure 66 (A) Relative root length of TX9425 and Naso Nijo seedlings treated

with 0 01 03 1 3 10 mM H2O2 for 3 d Mean plusmn SE (n =14) Asterisks indicate

statistically significant differences between two varieties at P lt 0001 (Studentrsquos

t-test) (B) Genetic variability in the relative root length in 11 barley varieties

treated with 1 mM H2O2 for 3 d Mean plusmn SE (n =14) (C) Correlation between

H2O2ndashtreated relative root length and the overall salinity tolerance (damage

index see Table 61) of 11 barley varieties

634 H2O2ndashinduced changes of root length correlate with the

overall salinity tolerance

Eleven barley varieties were selected to test the relationship between the root

growth under oxidative stress and their overall salinity tolerance under 1 mM H2O2

treatment After 3 d exposure to 1 mM H2O2 the relative root length (RRL) of all

the barley varieties reduced rapidly ranging from the lowest 227 plusmn 03 (in the

variety Unicorn) to the highest 632 plusmn 2 (in SYR01) (Figure 66B) The RRL

values were then correlated with the ldquodamage index scoresrdquo (Table 61) a

quantitative measure of the extent of salt damage to plants provided by the visual

assessment on a 0 to 10 score (0 = no symptoms of damage 10 = completely dead


82

plants see section 324 for more details) A significant correlation (r2 = 094 P ˂

0001) between RRL and the overall salinity tolerance was observed (Figure 66C)

indicating a strong suitability of the RRL assay method as a proxy for

oxidativesalinity stress tolerance Given the ldquono cost no skillrdquo nature of this

method it can be easily taken on board by plant breeders for screening the

germplasm and mapping QTLs for oxidative stress tolerance (one of components

of the salt tolerance mechanism)

64 Discussion

641 H2O2 causes a loss of the cell viability and decline of growth

in barley roots

H2O2 is one of the major ROS produced in plant tissues under stress conditions

that leads to oxidative damage The effect of this stable oxidant on plant cell

viability and root growth was investigated in this study Both parameters decreased

in a dose- andor time-dependent manner upon H2O2 exposure (Figures 62 and

66A 66B) The physiological rationale behind these observations may lay in a

fact that exogenous application of H2O2 causes instantaneous [K+]cyt and [Ca2+]cyt

changes in different root zones

Stress-induced enhanced K+ leakage from root epidermis results in depletion

of cytosolic K+ pool (Shabala et al 2006) thus activating caspase-like proteases

and endonucleases and triggering PCD (Shabala 2009 Demidchik et al 2014)

leading to deleterious effect on plant viability (Shabala 2017) This is reflected in

our findings that roots lost their viability after being treated with H2O2 especially

upon higher dosage and long-term exposure (Figure 63) Furthermore K+ is

required for root cell expansion (Walker et al 1998) and plays a key role in

stimulating growth (Nieves-Cordones et al 2014 Demidchik 2014) Therefore

the loss of a large quantity of cytosolic K+ might be the primary reason for the

inhibition of the root elongation in our experiments (Figure 66A 66B) This is

consistent with root growth retardation observed in plants grown in low-K+ media

(Kellermeier et al 2013)

High concentration of cytosolic K+ is essential for optimizing plant growth

and development Also essential is maintenance of stable (and relatively low)


83

levels of cytosolic free Ca2+ (Hepler 2005 Wang et al 2013) Therefore H2O2-

induced cytosolic Ca2+ disequilibrium may be another contributing factor to the

observed loss of cell viability and reported decrease in the relative root length in

this study (Figures 64 and 66A 66B) In our previous chapters we showed that

plants responded to H2O2 by increased Ca2+ uptake in mature root epidermis This

is expected to result in [Ca2+]cyt elevation that may be deleterious to plants as it

causes protein and nucleic acids aggregation initiates phosphates precipitation and

affects the integrity of the lipid membranes (Case et al 2007) It may also make

cell walls less plastic through rigidification thus inhibiting cell growth (Hepler

2005) In root tips however increased Ca2+ loading is required for the stimulation

of actinmyosin interaction to accelerate exocytosis that sustains cell expansion and

elongation (Carol and Dolan 2006) The rhd2 Arabidopsis mutant lacking

functional NADPH oxidase exhibited stunted roots as plants were unable to

produce sufficient ROS to activate Ca2+-permeable NSCCs to enable Ca2+ loading

into the cytosol (Foreman et al 2003)

642 Salt tolerant barley roots possess higher root viability in

elongation zone after long-term ROS exposure

It was argued that the ROS-induced self-amplification mechanism between

Ca2+-activated NADPH oxidases and ROS-activated Ca2+-permeable cation

channels in the plasma membrane and transient K+ leakage from cytosol may be

both essential for the early stress signalling (Shabala et al 2015 Shabala 2017

Demidchik and Shabala 2018) As salt sensing mechansim is most likely located in

the root meristem (Wu et al 2015) this may explain why the correlation between

the overall salinity tolerance and H2O2-induced transient ions fluxes was not found

in this zone in short-term experiments (see Chapter 3 for detailed finding) Under

long-term H2O2 exposures however (as in this study) we observed less severe root

damage in the elongation zone in salt tolerant varieties (Figure 65A 65B) This

suggested a possible recovery of these genotypes from the ldquohibernated staterdquo

(transferred from normal metabolism by reducing cytosolic K+ and Ca2+ content for

salt stress acclimation) to stress defence mechanisms (Shabala and Pottosin 2014)

which may include a superior capability in maintaining more negative membrane

potential and increasing the production of metabolites in this zone (Shabala et al


84

2016) This is consistent with a notion of salt tolerant genotypes being capable of

maintaining more negative membrane potential values resulting from higher H+-

ATPases activity in many species (Chen et al 2007b Bose et al 2014a Lei et al

2014) and the fact that a QTL for the membrane potential in root epidermal cells

was colocated with a major QTL for the overall salinity stress tolerance (Gill et al

2017)

In the mature root zone the salt-sensitive varieties possessed a higher transient

K+ efflux in response to H2O2 yet no major difference in viability staining was

observed amongst the genotypes in this root zone after a long-term (3 d) H2O2

exposure (Figure 64B and 65C) This is counterintuitive and suggests an

involvement of some additional mechanisms One of these mechanisms may be a

replenishing of the cytosolic K+ pool on the expense of the vacuole As a major

ionic osmoticum in both the cytosolic and vacuolar pools potassium has a

significant role in maintaining cell turgor especially in the latter compartment

(Walker et al 1996) Increasing cytosolic Ca2+ was first shown to activate voltage-

independent vacuolar K+-selective (VK) channels in Vicia Faba guard cells (Ward

and Schroeder 1994) mediating K+ back leak into cytosol from the vacuole pool

This observation was later extended to cell types isolated from Arabidopsis shoot

and root tissues (Gobert et al 2007) as well as other species such as barley rice

and tobacco (Isayenkov et al 2010) Thus the higher Ca2+ influx in sensitive

varieties upon H2O2 treatment is expected to increase their cytosolic free Ca2+

concentration thus inducing a strong K+ leak from the vacuole to compensate for

the cytosolic K+ loss from ROS-activated GORK channel This process will be

attenuated in the salt tolerant varieties which have lower H2O2-induced Ca2+ uptake

As a result 3 days after the stress onset the amount of K+ in the cytosol in mature

root zone may be not different between contrasting varieties explaining the lack of

difference in viability staining

643 Evaluating root growth assay screening for oxidative stress

tolerance

A rapid and revolutionary progress in plant molecular breeding has been

witnessed since the development of molecular markers in the 1980s (Nadeem et al

2018) At the same time the progress in plant phenotyping has been much slower


85

and in most cases lack direct causal relationship with the traits targeted However

future breeding programmes are in a need of sensitive low cost and efficient high-

throughput phenotyping methods The novel approach developed in chapter 3

allowed us to use the MIFE technique for the cell-based phenotyping for root

sensitivity to ROS one of the key components of mechanism of salinity stress

tolerance Being extremely sensitive and allowing directly target operation of

specific transport proteins this method is highly sophisticated and is not expected

to be easily embraced by breeders In this study we provided an alternative

approach namely root growth assay which can be used as the high-throughput

phenotyping method to replace the sophisticated MIFE technique This screening

method has minimal space requirements (only a small growth room) and no

measuring equipment except a simple ruler Assuming one can acquire 5 length

measurements per minute and 15 biological replicates are sufficient for one

genotype the time needed for one genotype is just three minutes which means one

can finish the screening of 100 varieties in 5 h This is a blazing fast avenue

compared to most other methods This offers plant breeders a convenient assay to

screen germplasm for oxidative stress tolerance and identify root-based QTLs

regulating ion homeostasis and conferring salinity stress tolerance

Chapter 7 General conclusion and future prospects

86


71 General discussion

Soil salinity is a major global issue threatening cereal production worldwide

(Shrivastava and Kumar 2015) The majority of cereals are glycophytes and thus

perform poorly in saline soils (Hernandez et al 2000) Therefore developing salt

tolerant crops is important to ensure adequate food supply in the coming decades

to meet the demands of the increasing population Generally the major avenues

used to produce salt tolerant crops have been conventional breeding and modern

biotechnology (Flowers and Flowers 2005 Roy et al 2014) However due to

some obvious practical drawbacks (Miah et al 2013) the former has gradually

given way to the latter Marker assisted selection (MAS) and genetic engineering

are the two known modern biotechnologies (Roy et al 2014) MAS is an indirect

selection process of a specific trait based on the marker(s) linked to the trait instead

of selecting and phenotyping the trait itself (Ribaut and Hoisington 1998 Collard

and Mackill 2008) While genetic engineering can be achieved by either

introducing salt-tolerance genes or altering the expression levels of the existing salt

tolerance-associated genes to create transgenic plants (Yamaguchi and Blumwald

2005) Given the fact that the application of transgenic crop plants is rather

controversial and the MAS technique can facilitate the process of pyramiding traits

of interest to improve crop salt tolerance substantially (Yamaguchi and Blumwald

2005 Collard and Mackill 2008) the latter may be more acceptable in plant

breeding pipeline However exploring the detailed characteristics of QTLs needs

the combination of both biotechnologies

Oxidative stress tolerance is one of the components of salinity stress tolerance

This trait has been usually considered in the context of ROS detoxification

However being both toxic agents and essential signalling molecules ROS may

have pleiotropic effects in plants (Bose et al 2014b) making the attempts in

pyramiding major antioxidants-associated QTLs for salinity stress tolerance

unsuccessful Besides ROS are also able to activate a range of ion channels to cause

ion disequilibrium (Demidichik et al 2003 2007 2014 Demidchik and Maathuis

2007) Indeed several studies have revealed that both H2O2 and bullOH-induced ion


87

fluxes showed their distinct difference between several barley varieties contrasting

in their salt stress tolerance (Chen et al 2007a Maksimović et al 2013 Adem et

al 2014) and different cell type showed different sensitivity to ROS (Demidichik

et al 2003) Since wheat and barley are two major grain crops cultivated all over

the world with sufficient natural genetic variations for exploitation the attempts of

producing salt tolerant cereals using proper selection processes (such as MAS) with

proper ROS-related physiological markers (such as ROS on cell ionic relations)

would deserve a trial Funded by Grain Research amp Development Corporation and

aimed at understanding ROS sensitivity in a range of cereal (wheat and barley)

varieties in various cell types and validating the applicability of using ROS-induced

ion fluxes as a physiological marker in breeding programs to improve plant salinity

stress tolerance we established a causal association between ROS-induced ion

fluxes and plants overall salinity stress tolerance validated the applicability of the

above marker identified major QTLs associated with salinity stress tolerance in

barley and found an alternative high-throughput phenotyping method for oxidative


The major findings in this project were (i) the magnitude of H2O2-induced K+

and Ca2+ fluxes from root mature zone of both wheat and barley correlated with

their overall salinity stress tolerance (ii) H2O2-induced K+ and Ca2+ fluxes from

mature root zone of cereals can be used as a novel physiological trait of salinity

stress tolerance in plant breeding programs (iii) major QTLs for ROS-induced K+

and Ca2+ flux associated with salinity stress tolerance in barley were identified on

chromosome 2 5 and 7 (iv) root growth assay was suggested as an alternative

high-throughput phenotyping method for oxidative stress tolerance in cereal roots

H2O2 and bullOH are two frequently mentioned ROS in plants with the former

has a half-life in minutes and the latter less than 1 μs (Pitzschke et al 2006 Bose

et al 2014b) This determines the property of H2O2 to diffuse freely for long

distance making it suitable for the role of signalling molecule Therefore it is not

surprising that the correlation between cereals overall salinity stress tolerance and

ROS-induced K+ efflux and Ca2+ uptake were found under H2O2 treatment but not

bullOH At the same time we also found that H2O2-induced K+ and Ca2+ fluxes showed

some cell-type specificity with the above correlation only observed in root mature

zone The recently emerged ldquometabolic switchrdquo concept indicated that high K+

efflux from the elongation zone in salt-tolerant varieties can inactivate the K+-


88

dependent enzymes and redistribute ATP pool towards defence responses for stress

adaptation (Shabala 2007) which may explain the reason of the lack of the above

correlation in root elongation zone It should be also commented that different cell

types show diverse sensitivity to specific stimuli and are adapted for specific andor

various functions due to the different expression level of genes in that tissue so it

is important to pyramid trait in a specific cell type in breeding program

In order to validate the above correlations a range of barley bread wheat and

durum wheat varieties were screened using the developed protocol above We

showed that H2O2-induced K+ and Ca2+ fluxes in root mature zone correlated with

the overall salinity stress tolerance in barley bread wheat and durum wheat with

salt sensitive varieties leaking more K+ and acquiring more Ca2+ These findings

also indicate the applicability of using the MIFE technique as a reliable screening

tool and H2O2-induced K+ and Ca2+ fluxes as a new physiological marker in cereal

breeding programs Due to the fact that previous studies on oxidative stress mainly

focused on AO activity our newly developed oxidative stress-related trait in this

study may provide novel avenue in exploring the mechanism of salinity stress

Previous efforts in pyramiding AO QTLs associated with salinity stress

tolerance in tomato was unsuccessful because more than 100 major QTLs has been

identified (Frary et al 2010) making QTL mapping of this trait practically

unfeasible Besides no major QTL associated with oxidative stress-induced control

of plant ion homeostasis has been reported yet in any crop species Here in this

study by using the aforementioned physiological marker of salinity stress tolerance

and genetic linkage map with DNA markers we identified three QTLs associated

with H2O2-induced Ca2+ and K+ fluxes for salinity stress tolerance in barley based

on the correlation found between these two traits These QTLs were located on

chromosome 2 5 and 7 respectively with the QTLs on 2H and 7H controlling both

K+ flux and Ca2+ flux and the QTL on 5H only involved in K+ flux H2O2-induced

K+ efflux is known to be mediated by GROK and K+-permeable NSCC

(Demidichik et al 2003 2014) while H2O2-induced Ca2+ uptake is mediated by

Ca2+-permeable NSCCs (Demidichik et al 2007 Demidchik and Maathuis 2007)

Taken together these two types of NSCC may exhibit some similarity since the

same QTLs from 2H and 7H were observed to control both ion flux While the one

on 5H controlling K+ efflux may be related to GORK channel Given the fact that

this is the very first time the major oxidative stress-associated QTLs being


89

identified it warrants in-depth study in this direction Accordingly several

potential genes comprise of calcium-dependent proteins protein phosphatase and

stress-related transcription factors were chosen for further investigation


salinity tolerance by pyramiding H2O2-induced Ca2+ and K+ fluxes However the

bottleneck of many breeding programs for salinity stress tolerance is a lack of

accurate plant phenotyping method In this study although we have proved that

H2O2-induced Ca2+ and K+ fluxes measured by using MIFE technique is reliable

for screening for salinity stress tolerance this method is too complicated with rather

low throughput capacity This poses a need to find a simple phenotyping method

for large scale screening Field screening for grain yield for example might be the

most reliable indicator Besides Plant above-ground performance such as plant

height and width plant senescence chlorosis and necrosis etc (Gaudet and Paul

1998) also reflect the overall plant performance as plant growth is an integral

parameter (Hunt et al 2002) However given the fact that these methods are time-

space- and labour-consuming and it is also affected by many other uncontrollable

factors such as temperature nutrition water content and wind screening in the

field becomes extremely unreliable and difficult Biochemical tests (measurements

of AO activity) are simple and plausible for screening But this method does not

work all the time because the properties of AO profiles are highly dynamic and

change spatially and temporally making it not reliable for screening Here we have

tested and compared two high-throughput phenotyping methods ndash root viability

assay and root growth assay ndash under H2O2 stress condition We then observed the

similar results with that of MIFE method and deemed root growth assay as a proxy

due to the fact that it does not need any specific skills and training and has the

minimal space and simple tool (a ruler) requirements which can be easily handled

by anyone

72 Future prospects

The establishment of a causal relationship between oxidative stress and

salinity stress tolerance in cereals using MIFE technique the identification of novel

QTLs for salinity tolerance under oxidative stress condition in barley and the

finding of using root growth assay as a simple high-throughput phenotyping


90

method for oxidative stress tolerance screening are valuable to salt stress tolerance

studies in cereals These findings improved our understanding on effects of stress-

induced ROS accumulation on cell ionic relations in different cell types and

opened previously unexplored prospects for improving salinity tolerance The

further progress in the field may be achieved addressing the following issues

i) Investigating the causal relationship between oxidative stress and other

stress factors in crops using MIFE technique

ROS production is a common denominator of literally all biotic and abiotic

stress (Shabala and Pottosin 2014) However studies in ROS has been largely

emphasised on their detoxification by a range of antioxidants ignoring the fact that

basal level of ROS are also indispensable and playing signalling role in plant

biology Although the generated ROS signal upon different stresses to trigger

appropriate acclimation responses may show some specificity (Mittler et al 2011)

our success in revealing a causal link between oxidative and salinity stress tolerance

by applying ROS exogenously and measuring ROS-induced ions flux may worth a

decent trial in correlation with other stresses such as drought flooding heavy metal

toxicity or temperature extremes

ii) Verifying chosen candidate genes and picking out the most likely genes

for further functional analysis

Using a DH population derived from CM72 and Gairdner three major QTLs

have been identified in this study and eight potential genes were chosen including

four calcium-dependent proteins three transcription factors and PP2C protein

through our genetic analysis A differential expression analysis of the potential

genes can be conducted to pick out the most likely genes for further functional

analysis Typically gene function can be investigated by changing its expression

level (overexpression andor inactivation) in plants (Sitnicka et al 2010) In this

study the identified QTLs were controlling K+ efflux andor Ca2+ uptake upon the

onset of ROS therefore any inactivation of the genes may have a positive effect

(eg plants leaking less K+ andor acquire less Ca2+) Conventionally the basic

principle of gene knockout was to introduce a DNA fragment into the site of the

target gene by homological recombination to block its expression This DNA

fragment can be either a non-coding fragment or deletion cassette (Sitnicka et al

2010) However this technique is less efficient with high expenses In recent years


91

researcher have developed alternative gene-editing techniques to achieve the above

goal such as ZNFs (Zinc finger nucleases) (Petolino 2015) TALENs

(Transcription activator-like effector nucleases) (Joung and Sander 2015) and

CRISPR (clustered regularly interspaced short palindromic repeats)Cas

(CRISPR-associated) system (Ran et al 2013 Ledford 2015) among which

CRISPRCas system has become revolutionized and the most widespread technique

in a range of research fields due to its high-efficiency target design simplicity and

generation of multiplexed mutations (Paul and Qi 2016)

CRISPRCas9 is a frequently mentioned version of the CRISPRCas system

which contains the Cas9 protein and a short non-coding gRNA (guide RNA) that

is composed of two components a target-specific crRNA (CRISPR RNA) and a

tracrRNA (trans-activating crRNA) The target sequence can be specified by

crRNA via base pairing between them and cleaved by Cas9 protein to induce a

DSB (double-stranded break) DNA damage repair machinery then occurs upon

cleavage which would then result in error-prone indel (insertiondeletion)

mutations to achieve gene knockout purpose (Ran et al 2013) This genetic

engineering technique has been widely used for genome editing in plants such as

Arabidopsis barley wheat rice soybean Brassica oleracea tomato cotton

tobacco etc (Malzahn et al 2017) Therefore after picking out the most likely

genes in this study it would be a good choice to perform the subsequent gene

functional analysis study using CRISPRCas9 gene editing technique

Functions of candidate genes in this study can also be investigated by

overexpression This can be achieved by vector construction for gene

overexpression (Lloyd 2003) and a subsequent Agrobacterium-mediated

transformation of the constructed vector into plant cell (Karimi et al 2002)

iii) Pyramiding the new developed trait (H2O2-induced Ca2+ and K+ fluxes)

alongside with other mechanisms of salinity stress tolerance


range of biological mechanisms (Shabala et al 2010 Wu et al 2015) Therefore

it is highly unlikely that modification of one gene would result in great

improvements Oxidative stress can occur in any biotic and abiotic stress conditions

When plants are under salinity stress the knockout of gene(s) controlling ROS-

induced Ca2+ andor K+ fluxes may partly relief the adverse effect caused by the

associated oxidative stress and confer plants salinity stress tolerance At the same


92

time if pyramiding the above process with other traditional mechanisms of salinity

stress tolerance such as Na+ exclusion and osmotic adjustment it may provide

double or several fold cumulative effect in improving plants salinity stress tolerance

This may include a knockout of the candidate gene in this study alongside with an

overexpression of the SOS1 or HKT1 gene or introduction of the glycine betaine

biosynthesis gene such as codA betA and betB into plants

References

93

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Cuin TA Shabala S (2007) Compatible solutes reduce ROS-induced potassium

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Day IS Reddy VS Ali GS Reddy AS (2002) Analysis of EF-hand-containing

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Dietz KJ Mittler R Noctor G (2016) Recent progress in understanding the role of

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Flowers TJ Yeo AR (1995) Breeding for salinity resistance in crop plants where

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Fry SC (1998) Oxidative scission of plant cell wall polysaccharides by ascorbate-

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Garciadeblas B Benito B Rodriguez-Navarro A (2001) Plant cells express several

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Garciadeblas B Senn ME Banuelos MA Rodriguez-Navarro A (2003) Sodium

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Gaymard F Pilot G Lacombe B Bouchez D Bruneau D Boucherez J Michaux-

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Gierth M Maumlser P (2007) Potassium transporters in plants - involvement in K+

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Gill MB Zeng F Shabala L Zhang G Fan Y Shabala S Zhou M (2017) Cell-

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Gill SS Tuteja N (2010) Reactive oxygen species and antioxidant machinery in

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Gobert A Isayenkov S Voelker C Czempinski K Maathuis FJM (2007) The two-

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Gobert A Park G Amtmann A Sanders D Maathuis FJM (2006) Arabidopsis

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Gόmez JM Hernaacutendez JA Jimeacutenez A del Rίo LA Sevilla F (1999) Differential

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Gorji T Tanik A Sertel E (2015) Soil salinity prediction monitoring and mapping

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Gregorio GB Senadhira D Mendoza RD Manigbas NL Roxas JP Guerta CQ

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Grondin A Rodrigues O Verdoucq L Merlot S Leonhardt N Maurel C (2015)

Aquaporins contribute to ABA-triggered stomatal closure through OST1-

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Guo B Wei Y Xu R Lin S Luan H Lv C Zhang X Song X Xu R (2016)

Genome-wide analysis of APETALA2ethylene-responsive factor (AP2ERF)

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Gupta B Huang BR (2014) Mechanism of salinity tolerance in plants

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Halliwell B Gutteridge JMC (2015) In Free Radicals in Biology and Medicine 5th

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Hanin M Ebel C Ngom M Laplaze L Masmoudi K (2016) New insights on plant

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Hasanuzzaman M Hossain MA da Silva JAT Fujita M (2012) Plant response and

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Venkateswarlu B Shanker A Shanker C Maheswari M Eds

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Hare PD Cress WA Van Staden J (1998) Dissecting the roles of osmolyte

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Hediye Sekmen A Tuumlrkan İ Takio S (2007) Differential responses of antioxidative

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Hepler PK (2005) Calcium a central regulator of plant growth and development

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Hernandez JA Ferrer MA Jimeacutenez A Barcelo AR Sevilla F (2001) Antioxidant

systems and O2bull-H2O2 production in the apoplast of pea leaves Its relation

with salt-induced necrotic lesions in minor veins Plant Physiol 127 817ndash

831

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Huang S Spielmeyer W Lagudah ES James RA Platten JD Dennis ES Munns

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447-453

Hu W Yan Y Hou X He Y Wei Y Yang G He G Peng M (2015) TaPP2C1 a

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Hu X Bidney DL Yalpani N Duvick JP Crasta O Folkerts O Lu G (2003)

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Copper elicits an increase in cytosolic free calcium in cultured tobacco cells

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2939ndash2947

Jami SK Clark GB Turlapati SA Handley C Roux SJ Kirti PB (2008) Ectopic

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1019-1030

Jayakannan M Bose J Babourina O Rengel Z Shabala S (2013) Salicylic acid

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2268

Jiang CF Belfield EJ Mithani A Visscher A Ragoussis J Mott R Smith JAC

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Ji H Pardo JM Batelli G Van Oosten MJ Bressan RA Li X (2013) The Salt

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Kim SY Lim JH Park MR Kim YJ Park TI Se YW Choi KG Yun SJ (2005)

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Kwak JM Mori IC Pei ZM Leonhardt N Torres MA Dangl JL Bloom RE Bodde

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Laohavisit A Mortimer JC Demidchik V Coxon KM Stancombe MA

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Laohavisit A Shang Z Rubio L Cuin TA Veacutery AA Wang A Mortimer JC

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Laurie S Feeney KA Maathuis FJ Heard PJ Brown SJ Leigh RA (2002) A role

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Lloyd A (2003) Vector construction for gene overexpression as a tool to elucidate

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Luna C Seffino LG Arias C Taleisnik E (2000) Oxidative stress indicators as

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Lu W Guo C Li X Duan W Ma C Zhao M Gu J Du X Liu Z Xiao K (2014)

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Lu Y Li N Sun J Hou P Jing X Zhu H Deng S Han Y Huang X Ma X Zhao

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Malzahn A Lowder L Qi Y (2017) Plant genome editing with TALEN and

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Mandhania S Madan S Sawhney V (2006) Antioxidant defense mechanism under

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Marino D Dunand C Puppo A Pauly N (2012) A burst of plant NADPH oxidases

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Martinez-Atienza J Jiang X Garciadeblas B Mendoza I Zhu JK Pardo JM

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Maruta T Noshi M Tanouchi A Tamoi M Yabuta Y Yoshimura K Ishikawa T

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McInnis SM Desikan R Hancock JT Hiscock SJ (2006) Production of reactive

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Miller G Schlauch K Tam R Cortes D Torres MA Shulaev V Dangl JL Mittler

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Nadeem MA Nawaz MA Shahid MQ Doğan Y Comertpay G Yıldız M

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Nieves-Cordones M Aleman F Martinez V Rubio F (2014) K+ uptake in plant

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Potocky M Jones MA Bezvoda R Smirnoff N Zarsky V (2007) Reactive oxygen

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Qadir M Quillerou E Nangia V Murtaza G Singh M Thomas RJ Drechsel P

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Raha S Robinson BH (2000) Mitochondria oxygen free radicals disease and

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Rengasamy P (2006) World salinization with emphasis on Australia J Exp Bot 57

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Ren ZH Gao JP Li LG Cai XL Huang W Chao DY Zhu MZ Wang ZY Luan

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Richards SL Laohavisit A Mortimer JC Shabala L Swarbreck SM Shabala S

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Rizhsky L Hallak-Herr E Van Breusegem F Rachmilevitch S Barr JE Rodermel S

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Rodrıguez AA Grunberg KA Taleisnik EL (2002) Reactive oxygen species in the

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Rodriacuteguez-Rosales MP Gaacutelvez FJ Huertas R Aranda MN Baghour M Cagnac O

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Roy SJ Negratildeo S Tester M (2014) Salt resistant crop plants Curr Opin Biotechnol

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Schachtman DP Kumar R Schroeder JI Marsh EL (1997) Molecular and

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Schleiff U (2008) Analysis of water supply of plants under saline soil conditions

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Schmidt R Schippers JHM (2015) ROS-mediated redox signaling during cell

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Senthil‐Kumar M Srikanthbabu V Mohan Raju B Shivaprakash N Udayakumar

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Shabala S (2009) Salinity and programmed cell death unravelling mechanisms for

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Shabala S (2013) Learning from halophytes physiological basis and strategies to

improve abiotic stress tolerance in crops Ann Bot 112 1209-1221

Shabala S (2017) Signalling by potassium another second messenger to add to the list

J Exp Bot 68 4003ndash4007

Shabala S Bose J Fuglsang AT Pottosin I (2016) On a quest for stress tolerance

genes membrane transporters in sensing and adapting to hostile soils J Exp

Bot 67 1015ndash1031

Shabala S Bose J Hedrich R (2014) Salt bladders do they matter Trends Plant

Sci 19 687ndash691

Shabala S Cuin TA (2008) Potassium transport and plant salt tolerance Physiol


Shabala S Cuin TA Prismall L Nemchinov LG (2007) Expression of animal CED-

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Shabala S Demidchik V Shabala L Cuin TA Smith SJ Miller AJ Davies JM

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Shabala S Shabala S Cuin TA Pang J Percey W Chen Z Conn S Eing C Wegner

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Shabala S Wu HH Bose J (2015) Salt stress sensing and early signalling events in

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Shewry PR (2009) Wheat J Exp Bot 60 1537-1553

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124

Shi H Lee BH Wu SJ Zhu JK (2003) Overexpression of a plasma membrane

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Sitnicka D Figurska K Orzechowski S (2010) Functional analysis of genes Adv

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Slama I Abdelly C Bouchereau A Flowers T Savoure A (2015) Diversity

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Smethurst CF Rix K Garnett T Auricht G Bayart A Lane P Wilson SJ Shabala

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Sun J Dai S Wang R Chen S Li N Zhou X Lu C Shen X Zheng X Hu Z Zhang

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125

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Suzuki N Mittler R (2006) Reactive oxygen species and temperature stresses a

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Suzuki K Yamaji N Costa A Okuma E Kobayashi NI Kashiwagi T Katsuhara

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Tester M Davenport R (2003) Na+ tolerance and Na+ transport in higher plants

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126

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Veacutery AA Nieves-Cordones M Daly M Khan I Fizames C Sentenac H (2014)

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127

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Wu H Shabala L Liu X Azzarello E Zhou M Pandolfi C Chen ZH Bose J Mancuso

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Wu H Shabala L Zhou M Stefano G Pandolfi C Mancuso S Shabala S (2015)

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Wu H Zhu M Shabala L Zhou M Shabala S (2015) K+ retention in leaf

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Wu J Shang Z Wu J Jiang X Moschou PN Sun W Roubelakis-Angelakis KA

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Xie Y Xu S Han B Wu M Yuan X Han Y Gu Q Xu D Yang Q Shen W (2011)

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Xu H Jiang X Zhan K Cheng X Chen X Pardo JM Cui D (2008) Functional

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Xu R Wang J Li C Johnson P Lu C Zhou M (2012) A single locus is responsible

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Xu S Zhu S Jiang Y Wang N Wang R Shen W Yang J (2013) Hydrogen-rich

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Yadav D Ahmed I Shukla P Boyidi P Kirti PB (2016) Overexpression of

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Yamaguchi T Blumwald E (2005) Developing salt-tolerant crop plants challenges

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Yamauchi Y Furutera A Seki K Toyoda Y Tanaka K Sugimoto Y (2008)

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modification in heat-stressed plants Plant Physiol Bioch 46 786ndash793

Yancey PH (2005) Organic osmolytes as compatible metabolic and counteracting

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2830

Yang Q Chen ZZ Zhou XF Yin HB Li X Xin XF Hong XH Zhu JK Gong Z

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Yan J Tsuichihara N Etoh T Iwai S (2007) Reactive oxygen species and nitric

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Yazici EY Deveci H (2010) Factors affecting decomposition of hydrogen

peroxide In Proceedings of the XIIth International Mineral Processing

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Yin XY Yang AF Zhang KW Zhang JR (2004) Production and analysis of

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Yokoi S Quintero FJ Cubero B Ruiz MT Bressan RA Hasegawa PM Pardo JM

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Yue SU Zhang W Li FL Guo YL Liu TL Huang H (2000) Identification and

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Yue Y Zhang M Zhang J Duan L Li Z (2012) SOS1 gene overexpression

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Zeng H Xu L Singh A Wang H Du L Poovaiah BW (2015) Involvement of

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Zepeda-Jazo I Velarde-Buendia AM Enriquez-Figueroa R Bose J Shabala S

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Zhang F Li S Yang S Wang L Guo W (2015) Overexpression of a cotton annexin

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Zhang G Sun Y Li Y Dong Y Huang X Yu Y Wang J Wang X Wang X Kang

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12836

Zhang JX Nguyen HT Blum A (1999) Genetic analysis of osmotic adjustment in

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Zhang X Shabala S Koutoulis A Shabala L Zhou M (2017) Meta-analysis of

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Zhu JK (2003) Regulation of ion homeostasis under salt stress Curr Opin Plant

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Zhu M Zhou M Shabala L Shabala S (2015) Linking osmotic adjustment and

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Zhu M Zhou M Shabala L Shabala S (2017) Physiological and molecular

mechanisms mediating xylem Na+ loading in barley in the context of salinity

stress tolerance Plant Cell Environ 40 1009ndash1020

Preliminaries

i

Declarations and statements

Declaration of originality

This thesis contains no material which has been accepted for a degree or diploma

by the University or any other institution except by way of background information

and duly acknowledged in the thesis and to the best of my knowledge and belief

no material previously published or written by another person except where due

acknowledgement is made in the text of the thesis nor does the thesis contain any

material that infringes copyright

Authority of access

This thesis is not to be made available for loan or copying for two years following

the date this statement was signed Following that time the thesis may be made

available for loan and limited copying and communication in accordance with the

Copyright Act 1968

Statement regarding published work contained in thesis

The publishers of the papers comprising Chapters 3 to 6 hold the copyright for that

content and access to the material should be sought from the respective journals

The remaining non-published content of the thesis may be made available for loan

and limited copying and communication in accordance with the Copyright Act

1968

Haiyang Wang


August 2018

Preliminaries

ii












in chapter 3













Preliminaries

iii

Signed


Supervisor Director



Date 31072018 ____________________

Preliminaries

iv













Conference papers










Tasmania




Israel

Preliminaries

v

Acknowledgements
























remember them all








near future

Preliminaries

vi

Table of Contents







Acknowledgements v



Abstract xvii









126 K+ retention 5








context 11

Preliminaries

vii














222 Paper rolls 24







31 Introduction 26





measurements 29



33 Results 30




Preliminaries

viii


barley 37

34 Discussion 39











41 Introduction 45



measurements 46



43 Results 47












44 Discussion 54





Preliminaries

ix





51 Introduction 59



60

522 QTL analysis 61


53 Results 62





65

54 Discussion 66





61 Introduction 71






63 Results 76




oxidative stress 80

Preliminaries

x


tolerance 81

64 Discussion 82


roots 82







References 93

Preliminaries

xi





























Preliminaries

xii






























Preliminaries

xiii























Preliminaries

xiv



1O2 Singlet oxygen

ABA Abscisic acid

AO Antioxidant


Asc Ascorbate

BR Brassinosteroid




CAT Catalase

CML Calmodulin like



crRNA CRISPR RNA


CuA CopperAscorbate

Cys Cysteine


DH Double haploid






ET Ethylene





GA Gibberellin




Preliminaries

xv


gRNA Guide RNA



H2 Hydrogen gas





IM Interval mapping


JA Jasmonate






MDA Malondialdehyde






NHX Na+H+ exchanger

NO Nitric oxide





PI Propidium iodide


PM Plasma membrane

POX Peroxidase


PSI Photosystem I

Preliminaries

xvi

PSII Photosystem II










SA Salicylic acid

SE Standard error


SL Strigolactone









UQ Ubiquinone




W-W Waterndashwater


Abstract

xvii

Abstract














were addressed


cereals

















Abstract

xviii



















tolerance















genes

Abstract

xix



























genotypes


1
































2























Satyawati 2008)












3


































4












al 2015)




















5













126 K+ retention




















6
































7







et al 2014)



























8



































9









65 1242-1257








10




























11











stress context


















12


































13


































14








conditions



























15




































16













Baucher et al 2012)







17


































18













tolerance





















19



































20


































21



























in cereal crops




cereals


22













tolerance in barley


















barley


23


tolerance in barley





24


21 Plant materials





and Gairdner








222 Paper rolls






for another 3 d








25


























26




31 Introduction

















2012)












27




































28























details)


29




Barley Wheat













(MIFE) measurements















30















33 Results







31
























32



32A 32B and 33A 33B)














TX9425


33







shown for TX9425


barley













34




















mature zone


35









wheat










36












mature zone


37












K+ fluxes in barley






38






















39


39F)








34 Discussion









40

































41


































42
























2007)












43


































44























plant roots


45




wheat and barley

41 Introduction



























46










measurements





















47

43 Results

























48

















al 2015




CM72 125 YU6472 200 93-3143 C60 300 YPSLDM 500










49









wheat










genotypes


50





et al 2014













51









wheat




52





















53




















54













44 Discussion



tolerance




55




































56







stress



























57


































58




























59



51 Introduction






























60











al 2014b)














measurements








61

522 QTL analysis
































62


tolerance

53 Results









101 DH lines










treatment


63
















Traits QTL

Linkage

group

Nearest

marker

Position

(cM) LOD

R2

() Covariate

KF

QKFCG2H 2H bPb-4482 126 312 92

QKFCG5H 5H bPb-5506 507 348 103 NA

QKFCG7H 7H bPb-0773 166 391 117

CaF QCaFCG2H 2H bPb-0827 1128 369 113

NA QCaFCG7H 7H bPb-8823 156 425 148

KF

QKFCG2H 2H

NS NS

CaF QKFCG5H 5H bPb-0616 47 514 145

QKFCG7H 7H

NS NS



64
















65






and 7H








the near future


66




protein 1

Annexin 8 1



7H






54 Discussion


Ca2+ flux














67




































68



































69




































70






2H in this study












responses











71



in cereal roots

61 Introduction










land (Shabala 2013)



















72



































73









for details)











SYR01 025

TX9425 100

CM72 120

YYXT 145

Numar 170

ZUG293 170

Hu93-045 325

ZUG403 570

Naso Nijo 750

Kinu Nijo 6 845

Unicorn 945


74

622 Viability assay
























background


75













76






63 Results


manner












77
















H2O2







64)


78











(Figure 65C)


79



















80



















81



















82








64 Discussion


in barley roots























83


































84






2017)























tolerance





85




















86

































87




































88




































89



























by anyone

72 Future prospects






90



































91




































92







References

93

References









253 245ndash256



30 161-175












Res 29 75-112




4099ndash4121

References

94








1256-1258















J Biol Chem 279 18583-18591







References

95





























References

96



57 101-107



Sci 101 47ndash56





Biol 12 431-434









366




952







References

97










761ndash767


580-581









516ndash526









References

98




67 4611ndash4625





5 250-257





















References

99













557-572


















References

100







Environ Sci 2 53






140















References

101
















175 387ndash404












19 1263

References

102






40 84ndash87









Bot 65 1259-1270



2559-2569






165






303

References

103



203




128ndash143




Crop Sci 200 261-272
















119 355-364



861-905

References

104

















146-159



169



181-192






Cell 94 647ndash655

References

105










Sci 8 1941









800












References

106



Biol 18 125ndash133






2014





Sci 7 1787












Plant Cell 17 2142-2155




831

References

107






Sci 14 660-668












447-453












References

108






2939ndash2947




1019-1030




2268








6 275-286









References

109





396














30 81ndash89










References

110



427




22 2623-2633














1305-1312








References

111































References

112




Plant Sci 5 467

























References

113







18952



1065













67 3831ndash3844








References

114








Sci 7 405ndash410





















2163ndash2178

References

115




702-708





1103ndash1113







59 651-681










Mech 1819 97-103



129 185-195

References

116







Environ 24 1ndash14







Cell Longev 2016














Microbiol 4 248



References

117














847
















References

118




89








1310







5853-5866





50 2-18






1380-1389

References

119






1027


1017-1023












2105-2110







912



References

120









844-855



e23425



Physiol 129 1627-1632





4 265-276


26 115ndash124







References

121









38 1011ndash1019


7-12








8












References

122











2445-2458











Sci 19 687ndash691








References

123













839-853







Exp Bot 38 254-269




112 487-494





References

124






J Biol Sci 22 123-131






Cell Bio 2 1-6

















References

125






45-51
















234


Ann Bot 91 503-527







References

126






175-235













769











References

127



















157ndash165











813

References

128





Plant Sci 4 245-246
























References

129













PLoS One 7e43079



47-57



tobacco Plants 5 18








2830




References

130



30 1320-1325


























References

131









12836







Biol 6 441-445







Preliminaries

ii












in chapter 3













Preliminaries

iii

Signed


Supervisor Director



Date 31072018 ____________________

Preliminaries

iv













Conference papers










Tasmania




Israel

Preliminaries

v

Acknowledgements
























remember them all








near future

Preliminaries

vi

Table of Contents







Acknowledgements v



Abstract xvii









126 K+ retention 5








context 11

Preliminaries

vii














222 Paper rolls 24







31 Introduction 26





measurements 29



33 Results 30




Preliminaries

viii


barley 37

34 Discussion 39











41 Introduction 45



measurements 46



43 Results 47












44 Discussion 54





Preliminaries

ix





51 Introduction 59



60

522 QTL analysis 61


53 Results 62





65

54 Discussion 66





61 Introduction 71






63 Results 76




oxidative stress 80

Preliminaries

x


tolerance 81

64 Discussion 82


roots 82







References 93

Preliminaries

xi





























Preliminaries

xii






























Preliminaries

xiii























Preliminaries

xiv



1O2 Singlet oxygen

ABA Abscisic acid

AO Antioxidant


Asc Ascorbate

BR Brassinosteroid




CAT Catalase

CML Calmodulin like



crRNA CRISPR RNA


CuA CopperAscorbate

Cys Cysteine


DH Double haploid






ET Ethylene





GA Gibberellin




Preliminaries

xv


gRNA Guide RNA



H2 Hydrogen gas





IM Interval mapping


JA Jasmonate






MDA Malondialdehyde






NHX Na+H+ exchanger

NO Nitric oxide





PI Propidium iodide


PM Plasma membrane

POX Peroxidase


PSI Photosystem I

Preliminaries

xvi

PSII Photosystem II










SA Salicylic acid

SE Standard error


SL Strigolactone









UQ Ubiquinone




W-W Waterndashwater


Abstract

xvii

Abstract














were addressed


cereals

















Abstract

xviii



















tolerance















genes

Abstract

xix



























genotypes


1
































2























Satyawati 2008)












3


































4












al 2015)




















5













126 K+ retention




















6
































7







et al 2014)



























8



































9









65 1242-1257








10




























11











stress context


















12


































13


































14








conditions



























15




































16













Baucher et al 2012)







17


































18













tolerance





















19



































20


































21



























in cereal crops




cereals


22













tolerance in barley


















barley


23


tolerance in barley





24


21 Plant materials





and Gairdner








222 Paper rolls






for another 3 d








25


























26




31 Introduction

















2012)












27




































28























details)


29




Barley Wheat













(MIFE) measurements















30















33 Results







31
























32



32A 32B and 33A 33B)














TX9425


33







shown for TX9425


barley













34




















mature zone


35









wheat










36












mature zone


37












K+ fluxes in barley






38






















39


39F)








34 Discussion









40

































41


































42
























2007)












43


































44























plant roots


45




wheat and barley

41 Introduction



























46










measurements





















47

43 Results

























48

















al 2015




CM72 125 YU6472 200 93-3143 C60 300 YPSLDM 500










49









wheat










genotypes


50





et al 2014













51









wheat




52





















53




















54













44 Discussion



tolerance




55




































56







stress



























57


































58




























59



51 Introduction






























60











al 2014b)














measurements








61

522 QTL analysis
































62


tolerance

53 Results









101 DH lines










treatment


63
















Traits QTL

Linkage

group

Nearest

marker

Position

(cM) LOD

R2

() Covariate

KF

QKFCG2H 2H bPb-4482 126 312 92

QKFCG5H 5H bPb-5506 507 348 103 NA

QKFCG7H 7H bPb-0773 166 391 117

CaF QCaFCG2H 2H bPb-0827 1128 369 113

NA QCaFCG7H 7H bPb-8823 156 425 148

KF

QKFCG2H 2H

NS NS

CaF QKFCG5H 5H bPb-0616 47 514 145

QKFCG7H 7H

NS NS



64
















65






and 7H








the near future


66




protein 1

Annexin 8 1



7H






54 Discussion


Ca2+ flux














67




































68



































69




































70






2H in this study












responses











71



in cereal roots

61 Introduction










land (Shabala 2013)



















72



































73









for details)











SYR01 025

TX9425 100

CM72 120

YYXT 145

Numar 170

ZUG293 170

Hu93-045 325

ZUG403 570

Naso Nijo 750

Kinu Nijo 6 845

Unicorn 945


74

622 Viability assay
























background


75













76






63 Results


manner












77
















H2O2







64)


78











(Figure 65C)


79



















80



















81



















82








64 Discussion


in barley roots























83


































84






2017)























tolerance





85




















86

































87




































88




































89



























by anyone

72 Future prospects






90



































91




































92







References

93

References









253 245ndash256



30 161-175












Res 29 75-112




4099ndash4121

References

94








1256-1258















J Biol Chem 279 18583-18591







References

95





























References

96



57 101-107



Sci 101 47ndash56





Biol 12 431-434









366




952







References

97










761ndash767


580-581









516ndash526









References

98




67 4611ndash4625





5 250-257





















References

99













557-572


















References

100







Environ Sci 2 53






140















References

101
















175 387ndash404












19 1263

References

102






40 84ndash87









Bot 65 1259-1270



2559-2569






165






303

References

103



203




128ndash143




Crop Sci 200 261-272
















119 355-364



861-905

References

104

















146-159



169



181-192






Cell 94 647ndash655

References

105










Sci 8 1941









800












References

106



Biol 18 125ndash133






2014





Sci 7 1787












Plant Cell 17 2142-2155




831

References

107






Sci 14 660-668












447-453












References

108






2939ndash2947




1019-1030




2268








6 275-286









References

109





396














30 81ndash89










References

110



427




22 2623-2633














1305-1312








References

111































References

112




Plant Sci 5 467

























References

113







18952



1065













67 3831ndash3844








References

114








Sci 7 405ndash410





















2163ndash2178

References

115




702-708





1103ndash1113







59 651-681










Mech 1819 97-103



129 185-195

References

116







Environ 24 1ndash14







Cell Longev 2016














Microbiol 4 248



References

117














847
















References

118




89








1310







5853-5866





50 2-18






1380-1389

References

119






1027


1017-1023












2105-2110







912



References

120









844-855



e23425



Physiol 129 1627-1632





4 265-276


26 115ndash124







References

121









38 1011ndash1019


7-12








8












References

122











2445-2458











Sci 19 687ndash691








References

123













839-853







Exp Bot 38 254-269




112 487-494





References

124






J Biol Sci 22 123-131






Cell Bio 2 1-6

















References

125






45-51
















234


Ann Bot 91 503-527







References

126






175-235













769











References

127



















157ndash165











813

References

128





Plant Sci 4 245-246
























References

129













PLoS One 7e43079



47-57



tobacco Plants 5 18








2830




References

130



30 1320-1325


























References

131









12836







Biol 6 441-445







Preliminaries

iii

Signed


Supervisor Director



Date 31072018 ____________________

Preliminaries

iv













Conference papers










Tasmania




Israel

Preliminaries

v

Acknowledgements
























remember them all








near future

Preliminaries

vi

Table of Contents







Acknowledgements v



Abstract xvii









126 K+ retention 5








context 11

Preliminaries

vii














222 Paper rolls 24







31 Introduction 26





measurements 29



33 Results 30




Preliminaries

viii


barley 37

34 Discussion 39











41 Introduction 45



measurements 46



43 Results 47












44 Discussion 54





Preliminaries

ix





51 Introduction 59



60

522 QTL analysis 61


53 Results 62





65

54 Discussion 66





61 Introduction 71






63 Results 76




oxidative stress 80

Preliminaries

x


tolerance 81

64 Discussion 82


roots 82







References 93

Preliminaries

xi





























Preliminaries

xii






























Preliminaries

xiii























Preliminaries

xiv



1O2 Singlet oxygen

ABA Abscisic acid

AO Antioxidant


Asc Ascorbate

BR Brassinosteroid




CAT Catalase

CML Calmodulin like



crRNA CRISPR RNA


CuA CopperAscorbate

Cys Cysteine


DH Double haploid






ET Ethylene





GA Gibberellin




Preliminaries

xv


gRNA Guide RNA



H2 Hydrogen gas





IM Interval mapping


JA Jasmonate






MDA Malondialdehyde






NHX Na+H+ exchanger

NO Nitric oxide





PI Propidium iodide


PM Plasma membrane

POX Peroxidase


PSI Photosystem I

Preliminaries

xvi

PSII Photosystem II










SA Salicylic acid

SE Standard error


SL Strigolactone









UQ Ubiquinone




W-W Waterndashwater


Abstract

xvii

Abstract














were addressed


cereals

















Abstract

xviii



















tolerance















genes

Abstract

xix



























genotypes


1
































2























Satyawati 2008)












3


































4












al 2015)




















5













126 K+ retention




















6
































7







et al 2014)



























8



































9









65 1242-1257








10




























11











stress context


















12


































13


































14








conditions



























15




































16













Baucher et al 2012)







17


































18













tolerance





















19



































20


































21



























in cereal crops




cereals


22













tolerance in barley


















barley


23


tolerance in barley





24


21 Plant materials





and Gairdner








222 Paper rolls






for another 3 d








25


























26




31 Introduction

















2012)












27




































28























details)


29




Barley Wheat













(MIFE) measurements















30















33 Results







31
























32



32A 32B and 33A 33B)














TX9425


33







shown for TX9425


barley













34




















mature zone


35









wheat










36












mature zone


37












K+ fluxes in barley






38






















39


39F)








34 Discussion









40

































41


































42
























2007)












43


































44























plant roots


45




wheat and barley

41 Introduction



























46










measurements





















47

43 Results

























48

















al 2015




CM72 125 YU6472 200 93-3143 C60 300 YPSLDM 500










49









wheat










genotypes


50





et al 2014













51









wheat




52





















53




















54













44 Discussion



tolerance




55




































56







stress



























57


































58




























59



51 Introduction






























60











al 2014b)














measurements








61

522 QTL analysis
































62


tolerance

53 Results









101 DH lines










treatment


63
















Traits QTL

Linkage

group

Nearest

marker

Position

(cM) LOD

R2

() Covariate

KF

QKFCG2H 2H bPb-4482 126 312 92

QKFCG5H 5H bPb-5506 507 348 103 NA

QKFCG7H 7H bPb-0773 166 391 117

CaF QCaFCG2H 2H bPb-0827 1128 369 113

NA QCaFCG7H 7H bPb-8823 156 425 148

KF

QKFCG2H 2H

NS NS

CaF QKFCG5H 5H bPb-0616 47 514 145

QKFCG7H 7H

NS NS



64
















65






and 7H








the near future


66




protein 1

Annexin 8 1



7H






54 Discussion


Ca2+ flux














67




































68



































69




































70






2H in this study












responses











71



in cereal roots

61 Introduction










land (Shabala 2013)



















72



































73









for details)











SYR01 025

TX9425 100

CM72 120

YYXT 145

Numar 170

ZUG293 170

Hu93-045 325

ZUG403 570

Naso Nijo 750

Kinu Nijo 6 845

Unicorn 945


74

622 Viability assay
























background


75













76






63 Results


manner












77
















H2O2







64)


78











(Figure 65C)


79



















80



















81



















82








64 Discussion


in barley roots























83


































84






2017)























tolerance





85




















86

































87




































88




































89



























by anyone

72 Future prospects






90



































91




































92







References

93

References









253 245ndash256



30 161-175












Res 29 75-112




4099ndash4121

References

94








1256-1258















J Biol Chem 279 18583-18591







References

95





























References

96



57 101-107



Sci 101 47ndash56





Biol 12 431-434









366




952







References

97










761ndash767


580-581









516ndash526









References

98




67 4611ndash4625





5 250-257





















References

99













557-572


















References

100







Environ Sci 2 53






140















References

101
















175 387ndash404












19 1263

References

102






40 84ndash87









Bot 65 1259-1270



2559-2569






165






303

References

103



203




128ndash143




Crop Sci 200 261-272
















119 355-364



861-905

References

104

















146-159



169



181-192






Cell 94 647ndash655

References

105










Sci 8 1941









800












References

106



Biol 18 125ndash133






2014





Sci 7 1787












Plant Cell 17 2142-2155




831

References

107






Sci 14 660-668












447-453












References

108






2939ndash2947




1019-1030




2268








6 275-286









References

109





396














30 81ndash89










References

110



427




22 2623-2633














1305-1312








References

111































References

112




Plant Sci 5 467

























References

113







18952



1065













67 3831ndash3844








References

114








Sci 7 405ndash410





















2163ndash2178

References

115




702-708





1103ndash1113







59 651-681










Mech 1819 97-103



129 185-195

References

116







Environ 24 1ndash14







Cell Longev 2016














Microbiol 4 248



References

117














847
















References

118




89








1310







5853-5866





50 2-18






1380-1389

References

119






1027


1017-1023












2105-2110







912



References

120









844-855



e23425



Physiol 129 1627-1632





4 265-276


26 115ndash124







References

121









38 1011ndash1019


7-12








8












References

122











2445-2458











Sci 19 687ndash691








References

123













839-853







Exp Bot 38 254-269




112 487-494





References

124






J Biol Sci 22 123-131






Cell Bio 2 1-6

















References

125






45-51
















234


Ann Bot 91 503-527







References

126






175-235













769











References

127



















157ndash165











813

References

128





Plant Sci 4 245-246
























References

129













PLoS One 7e43079



47-57



tobacco Plants 5 18








2830




References

130



30 1320-1325


























References

131









12836







Biol 6 441-445







Preliminaries

iv













Conference papers










Tasmania




Israel

Preliminaries

v

Acknowledgements
























remember them all








near future

Preliminaries

vi

Table of Contents







Acknowledgements v



Abstract xvii









126 K+ retention 5








context 11

Preliminaries

vii














222 Paper rolls 24







31 Introduction 26





measurements 29



33 Results 30




Preliminaries

viii


barley 37

34 Discussion 39











41 Introduction 45



measurements 46



43 Results 47












44 Discussion 54





Preliminaries

ix





51 Introduction 59



60

522 QTL analysis 61


53 Results 62





65

54 Discussion 66





61 Introduction 71






63 Results 76




oxidative stress 80

Preliminaries

x


tolerance 81

64 Discussion 82


roots 82







References 93

Preliminaries

xi





























Preliminaries

xii






























Preliminaries

xiii























Preliminaries

xiv



1O2 Singlet oxygen

ABA Abscisic acid

AO Antioxidant


Asc Ascorbate

BR Brassinosteroid




CAT Catalase

CML Calmodulin like



crRNA CRISPR RNA


CuA CopperAscorbate

Cys Cysteine


DH Double haploid






ET Ethylene





GA Gibberellin




Preliminaries

xv


gRNA Guide RNA



H2 Hydrogen gas





IM Interval mapping


JA Jasmonate






MDA Malondialdehyde






NHX Na+H+ exchanger

NO Nitric oxide





PI Propidium iodide


PM Plasma membrane

POX Peroxidase


PSI Photosystem I

Preliminaries

xvi

PSII Photosystem II










SA Salicylic acid

SE Standard error


SL Strigolactone









UQ Ubiquinone




W-W Waterndashwater


Abstract

xvii

Abstract














were addressed


cereals

















Abstract

xviii



















tolerance















genes

Abstract

xix



























genotypes


1
































2























Satyawati 2008)












3


































4












al 2015)




















5













126 K+ retention




















6
































7







et al 2014)



























8



































9









65 1242-1257








10




























11











stress context


















12


































13


































14








conditions



























15




































16













Baucher et al 2012)







17


































18













tolerance





















19



































20


































21



























in cereal crops




cereals


22













tolerance in barley


















barley


23


tolerance in barley





24


21 Plant materials





and Gairdner








222 Paper rolls






for another 3 d








25


























26




31 Introduction

















2012)












27




































28























details)


29




Barley Wheat













(MIFE) measurements















30















33 Results







31
























32



32A 32B and 33A 33B)














TX9425


33







shown for TX9425


barley













34




















mature zone


35









wheat










36












mature zone


37












K+ fluxes in barley






38






















39


39F)








34 Discussion









40

































41


































42
























2007)












43


































44























plant roots


45




wheat and barley

41 Introduction



























46










measurements





















47

43 Results

























48

















al 2015




CM72 125 YU6472 200 93-3143 C60 300 YPSLDM 500










49









wheat










genotypes


50





et al 2014













51









wheat




52





















53




















54













44 Discussion



tolerance




55




































56







stress



























57


































58




























59



51 Introduction






























60











al 2014b)














measurements








61

522 QTL analysis
































62


tolerance

53 Results









101 DH lines










treatment


63
















Traits QTL

Linkage

group

Nearest

marker

Position

(cM) LOD

R2

() Covariate

KF

QKFCG2H 2H bPb-4482 126 312 92

QKFCG5H 5H bPb-5506 507 348 103 NA

QKFCG7H 7H bPb-0773 166 391 117

CaF QCaFCG2H 2H bPb-0827 1128 369 113

NA QCaFCG7H 7H bPb-8823 156 425 148

KF

QKFCG2H 2H

NS NS

CaF QKFCG5H 5H bPb-0616 47 514 145

QKFCG7H 7H

NS NS



64
















65






and 7H








the near future


66




protein 1

Annexin 8 1



7H






54 Discussion


Ca2+ flux














67




































68



































69




































70






2H in this study












responses











71



in cereal roots

61 Introduction










land (Shabala 2013)



















72



































73









for details)











SYR01 025

TX9425 100

CM72 120

YYXT 145

Numar 170

ZUG293 170

Hu93-045 325

ZUG403 570

Naso Nijo 750

Kinu Nijo 6 845

Unicorn 945


74

622 Viability assay
























background


75













76






63 Results


manner












77
















H2O2







64)


78











(Figure 65C)


79



















80



















81



















82








64 Discussion


in barley roots























83


































84






2017)























tolerance





85




















86

































87




































88




































89



























by anyone

72 Future prospects






90



































91




































92







References

93

References









253 245ndash256



30 161-175












Res 29 75-112




4099ndash4121

References

94








1256-1258















J Biol Chem 279 18583-18591







References

95





























References

96



57 101-107



Sci 101 47ndash56





Biol 12 431-434









366




952







References

97










761ndash767


580-581









516ndash526









References

98




67 4611ndash4625





5 250-257





















References

99













557-572


















References

100







Environ Sci 2 53






140















References

101
















175 387ndash404












19 1263

References

102






40 84ndash87









Bot 65 1259-1270



2559-2569






165






303

References

103



203




128ndash143




Crop Sci 200 261-272
















119 355-364



861-905

References

104

















146-159



169



181-192






Cell 94 647ndash655

References

105










Sci 8 1941









800












References

106



Biol 18 125ndash133






2014





Sci 7 1787












Plant Cell 17 2142-2155




831

References

107






Sci 14 660-668












447-453












References

108






2939ndash2947




1019-1030




2268








6 275-286









References

109





396














30 81ndash89










References

110



427




22 2623-2633














1305-1312








References

111































References

112




Plant Sci 5 467

























References

113







18952



1065













67 3831ndash3844








References

114








Sci 7 405ndash410





















2163ndash2178

References

115




702-708





1103ndash1113







59 651-681










Mech 1819 97-103



129 185-195

References

116







Environ 24 1ndash14







Cell Longev 2016














Microbiol 4 248



References

117














847
















References

118




89








1310







5853-5866





50 2-18






1380-1389

References

119






1027


1017-1023












2105-2110







912



References

120









844-855



e23425



Physiol 129 1627-1632





4 265-276


26 115ndash124







References

121









38 1011ndash1019


7-12








8












References

122











2445-2458











Sci 19 687ndash691








References

123













839-853







Exp Bot 38 254-269




112 487-494





References

124






J Biol Sci 22 123-131






Cell Bio 2 1-6

















References

125






45-51
















234


Ann Bot 91 503-527







References

126






175-235













769











References

127



















157ndash165











813

References

128





Plant Sci 4 245-246
























References

129













PLoS One 7e43079



47-57



tobacco Plants 5 18








2830




References

130



30 1320-1325


























References

131









12836







Biol 6 441-445







Preliminaries

v

Acknowledgements
























remember them all








near future

Preliminaries

vi

Table of Contents







Acknowledgements v



Abstract xvii









126 K+ retention 5








context 11

Preliminaries

vii














222 Paper rolls 24







31 Introduction 26





measurements 29



33 Results 30




Preliminaries

viii


barley 37

34 Discussion 39











41 Introduction 45



measurements 46



43 Results 47












44 Discussion 54





Preliminaries

ix





51 Introduction 59



60

522 QTL analysis 61


53 Results 62





65

54 Discussion 66





61 Introduction 71






63 Results 76




oxidative stress 80

Preliminaries

x


tolerance 81

64 Discussion 82


roots 82







References 93

Preliminaries

xi





























Preliminaries

xii






























Preliminaries

xiii























Preliminaries

xiv



1O2 Singlet oxygen

ABA Abscisic acid

AO Antioxidant


Asc Ascorbate

BR Brassinosteroid




CAT Catalase

CML Calmodulin like



crRNA CRISPR RNA


CuA CopperAscorbate

Cys Cysteine


DH Double haploid






ET Ethylene





GA Gibberellin




Preliminaries

xv


gRNA Guide RNA



H2 Hydrogen gas





IM Interval mapping


JA Jasmonate






MDA Malondialdehyde






NHX Na+H+ exchanger

NO Nitric oxide





PI Propidium iodide


PM Plasma membrane

POX Peroxidase


PSI Photosystem I

Preliminaries

xvi

PSII Photosystem II










SA Salicylic acid

SE Standard error


SL Strigolactone









UQ Ubiquinone




W-W Waterndashwater


Abstract

xvii

Abstract














were addressed


cereals

















Abstract

xviii



















tolerance















genes

Abstract

xix



























genotypes


1
































2























Satyawati 2008)












3


































4












al 2015)




















5













126 K+ retention




















6
































7







et al 2014)



























8



































9









65 1242-1257








10




























11











stress context


















12


































13


































14








conditions



























15




































16













Baucher et al 2012)







17


































18













tolerance





















19



































20


































21



























in cereal crops




cereals


22













tolerance in barley


















barley


23


tolerance in barley





24


21 Plant materials





and Gairdner








222 Paper rolls






for another 3 d








25


























26




31 Introduction

















2012)












27




































28























details)


29




Barley Wheat













(MIFE) measurements















30















33 Results







31
























32



32A 32B and 33A 33B)














TX9425


33







shown for TX9425


barley













34




















mature zone


35









wheat










36












mature zone


37












K+ fluxes in barley






38






















39


39F)








34 Discussion









40

































41


































42
























2007)












43


































44























plant roots


45




wheat and barley

41 Introduction



























46










measurements





















47

43 Results

























48

















al 2015




CM72 125 YU6472 200 93-3143 C60 300 YPSLDM 500










49









wheat










genotypes


50





et al 2014













51









wheat




52





















53




















54













44 Discussion



tolerance




55




































56







stress



























57


































58




























59



51 Introduction






























60











al 2014b)














measurements








61

522 QTL analysis
































62


tolerance

53 Results









101 DH lines










treatment


63
















Traits QTL

Linkage

group

Nearest

marker

Position

(cM) LOD

R2

() Covariate

KF

QKFCG2H 2H bPb-4482 126 312 92

QKFCG5H 5H bPb-5506 507 348 103 NA

QKFCG7H 7H bPb-0773 166 391 117

CaF QCaFCG2H 2H bPb-0827 1128 369 113

NA QCaFCG7H 7H bPb-8823 156 425 148

KF

QKFCG2H 2H

NS NS

CaF QKFCG5H 5H bPb-0616 47 514 145

QKFCG7H 7H

NS NS



64
















65






and 7H








the near future


66




protein 1

Annexin 8 1



7H






54 Discussion


Ca2+ flux














67




































68



































69




































70






2H in this study












responses











71



in cereal roots

61 Introduction










land (Shabala 2013)



















72



































73









for details)











SYR01 025

TX9425 100

CM72 120

YYXT 145

Numar 170

ZUG293 170

Hu93-045 325

ZUG403 570

Naso Nijo 750

Kinu Nijo 6 845

Unicorn 945


74

622 Viability assay
























background


75













76






63 Results


manner












77
















H2O2







64)


78











(Figure 65C)


79



















80



















81



















82








64 Discussion


in barley roots























83


































84






2017)























tolerance





85




















86

































87




































88




































89



























by anyone

72 Future prospects






90



































91




































92







References

93

References









253 245ndash256



30 161-175












Res 29 75-112




4099ndash4121

References

94








1256-1258















J Biol Chem 279 18583-18591







References

95





























References

96



57 101-107



Sci 101 47ndash56





Biol 12 431-434









366




952







References

97










761ndash767


580-581









516ndash526









References

98




67 4611ndash4625





5 250-257





















References

99













557-572


















References

100







Environ Sci 2 53






140















References

101
















175 387ndash404












19 1263

References

102






40 84ndash87









Bot 65 1259-1270



2559-2569






165






303

References

103



203




128ndash143




Crop Sci 200 261-272
















119 355-364



861-905

References

104

















146-159



169



181-192






Cell 94 647ndash655

References

105










Sci 8 1941









800












References

106



Biol 18 125ndash133






2014





Sci 7 1787












Plant Cell 17 2142-2155




831

References

107






Sci 14 660-668












447-453












References

108






2939ndash2947




1019-1030




2268








6 275-286









References

109





396














30 81ndash89










References

110



427




22 2623-2633














1305-1312








References

111































References

112




Plant Sci 5 467

























References

113







18952



1065













67 3831ndash3844








References

114








Sci 7 405ndash410





















2163ndash2178

References

115




702-708





1103ndash1113







59 651-681










Mech 1819 97-103



129 185-195

References

116







Environ 24 1ndash14







Cell Longev 2016














Microbiol 4 248



References

117














847
















References

118




89








1310







5853-5866





50 2-18






1380-1389

References

119






1027


1017-1023












2105-2110







912



References

120









844-855



e23425



Physiol 129 1627-1632





4 265-276


26 115ndash124







References

121









38 1011ndash1019


7-12








8












References

122











2445-2458











Sci 19 687ndash691








References

123













839-853







Exp Bot 38 254-269




112 487-494





References

124






J Biol Sci 22 123-131






Cell Bio 2 1-6

















References

125






45-51
















234


Ann Bot 91 503-527







References

126






175-235













769











References

127



















157ndash165











813

References

128





Plant Sci 4 245-246
























References

129













PLoS One 7e43079



47-57



tobacco Plants 5 18








2830




References

130



30 1320-1325


























References

131









12836







Biol 6 441-445







Preliminaries

vi

Table of Contents







Acknowledgements v



Abstract xvii









126 K+ retention 5








context 11

Preliminaries

vii














222 Paper rolls 24







31 Introduction 26





measurements 29



33 Results 30




Preliminaries

viii


barley 37

34 Discussion 39











41 Introduction 45



measurements 46



43 Results 47












44 Discussion 54





Preliminaries

ix





51 Introduction 59



60

522 QTL analysis 61


53 Results 62





65

54 Discussion 66





61 Introduction 71






63 Results 76




oxidative stress 80

Preliminaries

x


tolerance 81

64 Discussion 82


roots 82







References 93

Preliminaries

xi





























Preliminaries

xii






























Preliminaries

xiii























Preliminaries

xiv



1O2 Singlet oxygen

ABA Abscisic acid

AO Antioxidant


Asc Ascorbate

BR Brassinosteroid




CAT Catalase

CML Calmodulin like



crRNA CRISPR RNA


CuA CopperAscorbate

Cys Cysteine


DH Double haploid






ET Ethylene





GA Gibberellin




Preliminaries

xv


gRNA Guide RNA



H2 Hydrogen gas





IM Interval mapping


JA Jasmonate






MDA Malondialdehyde






NHX Na+H+ exchanger

NO Nitric oxide





PI Propidium iodide


PM Plasma membrane

POX Peroxidase


PSI Photosystem I

Preliminaries

xvi

PSII Photosystem II










SA Salicylic acid

SE Standard error


SL Strigolactone









UQ Ubiquinone




W-W Waterndashwater


Abstract

xvii

Abstract














were addressed


cereals

















Abstract

xviii



















tolerance















genes

Abstract

xix



























genotypes


1
































2























Satyawati 2008)












3


































4












al 2015)




















5













126 K+ retention




















6
































7







et al 2014)



























8



































9









65 1242-1257








10




























11











stress context


















12


































13


































14








conditions



























15




































16













Baucher et al 2012)







17


































18













tolerance





















19



































20


































21



























in cereal crops




cereals


22













tolerance in barley


















barley


23


tolerance in barley





24


21 Plant materials





and Gairdner








222 Paper rolls






for another 3 d








25


























26




31 Introduction

















2012)












27




































28























details)


29




Barley Wheat













(MIFE) measurements















30















33 Results







31
























32



32A 32B and 33A 33B)














TX9425


33







shown for TX9425


barley













34




















mature zone


35









wheat










36












mature zone


37












K+ fluxes in barley






38






















39


39F)








34 Discussion









40

































41


































42
























2007)












43


































44























plant roots


45




wheat and barley

41 Introduction



























46










measurements





















47

43 Results

























48

















al 2015




CM72 125 YU6472 200 93-3143 C60 300 YPSLDM 500










49









wheat










genotypes


50





et al 2014













51









wheat




52





















53




















54













44 Discussion



tolerance




55




































56







stress



























57


































58




























59



51 Introduction






























60











al 2014b)














measurements








61

522 QTL analysis
































62


tolerance

53 Results









101 DH lines










treatment


63
















Traits QTL

Linkage

group

Nearest

marker

Position

(cM) LOD

R2

() Covariate

KF

QKFCG2H 2H bPb-4482 126 312 92

QKFCG5H 5H bPb-5506 507 348 103 NA

QKFCG7H 7H bPb-0773 166 391 117

CaF QCaFCG2H 2H bPb-0827 1128 369 113

NA QCaFCG7H 7H bPb-8823 156 425 148

KF

QKFCG2H 2H

NS NS

CaF QKFCG5H 5H bPb-0616 47 514 145

QKFCG7H 7H

NS NS



64
















65






and 7H








the near future


66




protein 1

Annexin 8 1



7H






54 Discussion


Ca2+ flux














67




































68



































69




































70






2H in this study












responses











71



in cereal roots

61 Introduction










land (Shabala 2013)



















72



































73









for details)











SYR01 025

TX9425 100

CM72 120

YYXT 145

Numar 170

ZUG293 170

Hu93-045 325

ZUG403 570

Naso Nijo 750

Kinu Nijo 6 845

Unicorn 945


74

622 Viability assay
























background


75













76






63 Results


manner












77
















H2O2







64)


78











(Figure 65C)


79



















80



















81



















82








64 Discussion


in barley roots























83


































84






2017)























tolerance





85




















86

































87




































88




































89



























by anyone

72 Future prospects






90



































91




































92







References

93

References









253 245ndash256



30 161-175












Res 29 75-112




4099ndash4121

References

94








1256-1258















J Biol Chem 279 18583-18591







References

95





























References

96



57 101-107



Sci 101 47ndash56





Biol 12 431-434









366




952







References

97










761ndash767


580-581









516ndash526









References

98




67 4611ndash4625





5 250-257





















References

99













557-572


















References

100







Environ Sci 2 53






140















References

101
















175 387ndash404












19 1263

References

102






40 84ndash87









Bot 65 1259-1270



2559-2569






165






303

References

103



203




128ndash143




Crop Sci 200 261-272
















119 355-364



861-905

References

104

















146-159



169



181-192






Cell 94 647ndash655

References

105










Sci 8 1941









800












References

106



Biol 18 125ndash133






2014





Sci 7 1787












Plant Cell 17 2142-2155




831

References

107






Sci 14 660-668












447-453












References

108






2939ndash2947




1019-1030




2268








6 275-286









References

109





396














30 81ndash89










References

110



427




22 2623-2633














1305-1312








References

111































References

112




Plant Sci 5 467

























References

113







18952



1065













67 3831ndash3844








References

114








Sci 7 405ndash410





















2163ndash2178

References

115




702-708





1103ndash1113







59 651-681










Mech 1819 97-103



129 185-195

References

116







Environ 24 1ndash14







Cell Longev 2016














Microbiol 4 248



References

117














847
















References

118




89








1310







5853-5866





50 2-18






1380-1389

References

119






1027


1017-1023












2105-2110







912



References

120









844-855



e23425



Physiol 129 1627-1632





4 265-276


26 115ndash124







References

121









38 1011ndash1019


7-12








8












References

122











2445-2458











Sci 19 687ndash691








References

123













839-853







Exp Bot 38 254-269




112 487-494





References

124






J Biol Sci 22 123-131






Cell Bio 2 1-6

















References

125






45-51
















234


Ann Bot 91 503-527







References

126






175-235













769











References

127



















157ndash165











813

References

128





Plant Sci 4 245-246
























References

129













PLoS One 7e43079



47-57



tobacco Plants 5 18








2830




References

130



30 1320-1325


























References

131









12836







Biol 6 441-445







oxidative stress tolerance as a component of the tissue

Documents