genetic diversity studies in cultivated sweet potato ipomoea … · 2017-10-22 · dna was...

International Journal of Advanced Biotechnology Research.

ISSN 2249-3166 Volume 7, Number 1 (2017), pp. 33-48

© Research India Publications

http://www.ripublication.com

Genetic diversity studies in cultivated sweet potato

(Ipomoea batatas (L.) Lam) revealed by simple

sequence repeat markers

Aswathy G.H. Nair, P. Vidya, V. Ambu, J. Sreekumar and *C. Mohan

ICAR-Central Tuber Crops Research Institute, Sreekariyam, Thiruvananthapuram, 695 017, Kerala, India

Corresponding author :*C. Mohan

Abstract

Sweet potato (Ipomoea batatas (L.) Lam) is widely considered to be the

world’s most important crop with great diversity in morphological and

phenotypic traits. Assessment of genetic diversity is an essential component in

germplasm characterization and utilization. In this study, we determined

genetic diversity of 40 sweet potato accessions from ICAR-CTCRI and CIP by

using microsatellite markers. They were analyzed for diversity using 10

simple sequence repeat (SSR) primers. The presence of bands was scored for

each SSR and for each accession and the data were analysed by principal

coordinate analysis. The polymorphic SSR loci revealed diverse relationship

among the sweet potato cultivars, which was grouped into seven major

clusters by unweighted pair group method analysis (UPGMA) method. Cluster

analysis showed a Jaccard co-efficient ranging from 0.5 to 1.0 indicating high

genetic diversity. The results were also subjected to analysis of molecular

variance (AMOVA). AMOVA data showed that the majority 82.17% of the

diversity were present within populations and 17.83% among the population

of I. batatas.

Keywords: sweet potato, genetic diversity, simple sequence repeat, CIP,

ICAR-CTCRI

34 Aswathy G.H. Nair, P. Vidya, V. Ambu, J. Sreekumar and C. Mohan

INTRODUCTION

Sweet potato (Ipomoea batatas (L.) Lam) is a hexaploid crop, usually clonally

propagated by stem cuttings, but true seed production easily occurs by open

pollination (Martin and Jones, 1986). It is of neotropical origin and crossed the Pacific

via Polynesia before the discovery of the New World (Huaman et al., 1999; Zhang et al., 2000). In Africa it was introduced by explorers from Spain and Portugal during

the 16th century (O’Brien, 1972; Zhang et al., 2000, 2004).

Molecular markers have been used for phylogenetics and germplasm evaluation to

study the origin of sweet potato and its dissemination into the Pacific and Asia (He et al., 1995, Hu et al., 2003, Prakash et al., 1996, and Zhang et al., 2004). It has showed

important potential to improve the efficiency and precision of conventional breeding

techniques (Acquaah, 2007). The large number of quantitative trait loci (QTLs)

mapping studies for diverse crops species have provided an abundance of DNA

marker-trait associations. The most widely used molecular markers are SSRs because

they are highly reliable, co-dominant in inheritance, relatively simple and cheap, and

generally high polymorphic (Collard and Mackill, 2008; Gupta et al., 1999). The

disadvantages of SSRs markers are that it requires polyacrylamide gel electrophoresis

and give generally the information of a single locus per assay. These problems have

been handled by developing SSR markers that present large size differences for

detection in agarose gels and multiplexing several markers in a single reaction

(Collard and Mackill, 2008; Korzun, 2003).

SSR markers exhibit high levels of polymorphism, and several such markers have

been developed for sweet potato (Jarret and Bowen, 1994; Buteler et al., 1999; Hu et al., 2004) and used successfully for determining the genetic relationship between

cultivars derived from hybrid or polycross breeding programs (Hwang et al., 2002)

and for analyzing the genetic diversity of Latin American and East African sweet

potato landraces (Zhang et al., 2001; Gichuru et al., 2006). Understanding this genetic

diversity is important to the establishment of conservation efforts and to warrant the

adequate use of the germplasm. In the present study, the genetic diversity of sweet

potato accessions assessed using SSR markers.

MATERIALS AND METHODS

Plant material

A total of 40 sweet potato genotypes (Table 1) were taken from the germplasm

collection viz., orange fleshed sweet potato (OFSP) hybrid clones from International

Centre for Potato (CIP) and released varieties of ICAR-Central Tuber Crops Research

Institute (ICAR-CTCRI), India to analyze the level of genetic variability among them.

Genetic diversity studies in cultivated sweet potato (Ipomoea batatas (L.) Lam)… 35

Table 1. List of the sweet potato accessions evaluated in this study

No. Accession name Origin Sl

No.

Accession name Origin

1 162-5 CIP 21 75-3 CIP

2 58-3 CIP 22 309-9 CIP

3 97-13 CIP 23 196-2 CIP

4 35-9 CIP 24 148-26 CIP

5 98-1 CIP 25 148-22 CIP

6 160-2 CIP 26 Sree Varsha ICAR-CTCRI

7 130-8 CIP 27 Sree Nandhini ICAR-CTCRI

8 390-3 CIP 28 Sree Vardhini ICAR-CTCRI

9 130-17 CIP 29 Sree Ratna ICAR-CTCRI

10 130-3 CIP 30 Gowri ICAR-CTCRI

11 281-9 CIP 31 Sankar ICAR-CTCRI

12 526-12 CIP 32 Sree Arun ICAR-CTCRI

13 581-6 CIP 33 Sree Varun ICAR-CTCRI

14 130-2 CIP 34 Kalinga ICAR-CTCRI

15 64-1 CIP 35 Gautham ICAR-CTCRI

16 261-4 CIP 36 Sourin ICAR-CTCRI

17 327-16 CIP 37 Kishan ICAR-CTCRI

18 427-10 CIP 38 ST-14 ICAR-CTCRI

19 582-46 CIP 39 S1 ICAR-CTCRI

20 148-7 CIP 40 ST -13 ICAR-CTCRI

Extraction of DNA

DNA was extracted from 500 mg of young leaves collected from each accession using

the cetyl trimethyl ammonium bromide (CTAB) method according to Doyle and

Doyle (1990) with minor modifications. DNA samples were stored at -20°C and the

genomic DNA were run on a 0.8% agarose gel which was stained by ethidium

bromide solution and visualized using UV illumination and documented by Gel


documentation system (Alpha Imager). The DNA were quantified by

spectrophotometry. The final DNA concentration of each template stock was adjusted

to 50 ng/μl.

Table 2. SSR primers used for the analysis of 40 sweet potato accessions

No. Primer Forward (F) and reverse (R) primer

Sequences

Expected

Size (bp)

Tm

1 Ib255 TGGGCATTCTCATATTTTGCT

AAGGACCACCGTAAATCCAA

210-245 57.5

2 Ib242 GCGGAACGGACGAGAAAA

ATGGCAGAGTGAAAATGGAACA

105-142 59.5

3 IBSSR20 CCACTTCTCCTCTAACTTGATTCGC

TTTGAGGGATGTGGTGTTGAGG

271 51.0

4 IBSSR21 AAACAACCAACGGGTCTTTGC

CTCTAGGGTCGCCATAAAAATCAC

227 54.5

5 GDAAS0047 TTCTGACCTGCGAAATCG

TGGACTTCCTCTGCCTTG

236 50.1

6 GDAAS0049 GTTCAAGATCAACAACCAGAG

GCCAATCCTCCAACTTTC

218 50.1

7 GDAAS0212 GCCGCCAACAGACATCATCA

CTCCTCAGTTTCCTCGTTCACA

245 49.3

8 GDAAS0252 GTCTCATCGCTGTTCACTGTT

CGAGCAAACCAACCATCCAA

178 47.3

9 GDAAS0542 CTGTTCGCTCATAGATAATCATCG

GTTCTCTCCCATACTTCAATTTCC

289 49.3

10 GDAAS0809 CGGGTTATGCTTGGTTCTCC

TGTGGACGAGGATGCTGTG

214 49.3


Table 3. List of SSR primer polymorphism

Primer No. of

amplified

bands

No. of

polymorphic

bands

Polymorphic ratio

(%)

Ib255 4 3 75.0

Ib242 6 5 83.3

IBSSR20 2 1 50.0

IBSSR21 3 2 66.6

GDAAS0047 3 2 66.6

GDAAS0049 4 3 75.0

GDAAS0212 4 3 75.0

GDAAS0252 5 4 80.0

GDAAS0542 3 2 66.6

GDAAS0809 5 4 80.0

Total 39 29 71.81

Simple Sequence Repeat Amplification

DNA samples were quantified and a total of 50 ng of total genomic DNA from each

of the samples was used for polymerase chain reactions (PCR). Ten pairs of SSR

primers (Table 2) were used for the sweet potato DNA amplification reactions. The

final volume of reaction mixture of 20 μl containing 10X buffer, 10 mM dNTPs each,

2 μM primer, 3 U/μl Taq DNA Polymerase, 50 ng/μl DNA, and ddH2O was used for

the PCR. The amplification conditions were as follows: 94°C for 5 min, denaturation

at 94°C for 1 min; annealing at between 50.0 and 66.0°C (depending on the annealing

temperature of the primer); polymerization at 72°C for 2 min; repeated step 2 to 4 for

30 cycles, and a final extension at 72°C for 5 min. Amplification products were

analyzed using Gel documentation for 10 pairs of SSR primers.

Separation and staining of PCR products

The amplified PCR products were run in 6% polyacrylamide gel (40% acrylamide/

bis-acrylamide, 10% ammonium per sulfate, 1X TBE buffer and Gel loading dye).

For obtaining better resolution of polymorphic bands, amplified PCR products were

subjected to PAGE which was carried out in 1X TBE buffer at 100 W for about 1

hour. The silver stained gel shows the banding pattern. The amplified products were


scored for further analysis. During scoring, only intense and clearly resolved

amplification products were considered. Polymorphism was scored for length

variation of bands on PAGE gels.

Fig. 1 Silver-stained PCR products amplified with SSR primer GDAAS0542

Data analysis

All the genotypes were scored for the presence and absence of the SSR bands. And

the data were entered into a binary matrix as discrete variables, 1 for presence and 0

for absence of the character and this data matrix was subjected to further analysis. The

Excel file containing the binary data was imported into NT Edit of NTSYS-pc 2.02J.

The resultant similarity matrix was employed to construct dendrograms using

Sequential Agglomerative Hierarchical Nesting (SAHN) based Unweighted Pair

Group Method with Arithmetic Means (UPGMA) to infer genetic relationships and

phylogeny. The similarity matrix was also used to perform a hierarchical analysis of

molecular variance (AMOVA) (Excoffier et al., 1992) by using FAMD Software

v.1.25 (Schluter and Harris, 2006).

Polymorphism information content (PIC) were calculated according to Anderson et al. (1993) using the following simplified formula:

PICi = 1 - ∑ p2ij

where pi is the frequency of the jth allele for marker ith summed across all alleles for

the locus.

RESULTS

Genetic variability

In the 40 sweet potato accessions tested with the 10 SSR primer pairs were evaluated,

scored 29 polymorphic bands (71.81%) and a total of 39 bands, with an average of 4

bands per primer and a range from 2 to 6 bands per primer (Table 3). The high level

of polymorphism indicated wide genetic diversity. Primer Ib242 produced the highest

number of bands (6) while the primer IBSSR20 showed the lowest number of 2

bands.


Among the 40 genotypes studied, the similarity index ranged from 0.5 to 1.0, with an

average of 0.77 accounting for 52% variation. Similarity values obtained for each

pair-wise comparison of SSR allele among the 40 sweet potato accessions were used

to construct a dendrogram based on hierarchical clustering and the results are

presented in (Fig. 2).

Cluster analysis

A similarity coefficient matrix was used for cluster analysis following UPGMA

(unweighted pair group method with arithmetic averages), which is one of the several

SAHN clustering methods that are available (Sneath and Sokal, 1973). NTSYS-pc

software was used for analysis and the resulting clusters were represented in the form

of a dendrogram.

Based on the UPGMA clustering algorithm from SSR marker, 40 genotypes were

grouped into three main clusters (I, II and III) at 60% with a short index length of

0.53-1.00. The first cluster (I) is subdivided into three subclusters IA, IB and IC

composed majority of which are the CIP varieties and ICAR-CTCRI released

varieties. The subcluster (IA) contains orange fleshed varieties of CIP, ICAR-CTCRI

released varieties such as Sree Varun, Kishan and ST-14. The subcluster (IB) also

contains CIP varieties including the CTCRI released varieties such as Sree Rethna,

Sree Vardhini, Gowri, Sourin, Sree Nandhini, Sree Arun, Sankar, Sree Varsha and

Kalinga. The subcluster (IC) includes CIP variety 98-1 and Gautham. The second

cluster (II) and the third cluster (III) contains the S1, the white fleshed sweet potato

and the ST-13, the purple fleshed sweet potato.

Polymorphic information content (PIC)

The genetic diversity analysis was based on band patterns observed for each

accessions using a single pair of primers. The number of bands detected in non-

denaturing conditions was based on DNA sequence variation and SSR length

variation. The ten SSR primer pairs employed in this study generated amplification

products in all accessions analyzed. The polymorphic information content (PIC) of the

markers varied from 0.31 to 0.98 with a mean of 0.76. Marker (Ib255) revealed the

highest PIC of 0.98, while marker (GDAAS0212) had the lowest PIC of 0.31.

Observed heterozygosity ranged from 0.02 to 0.69 with a mean of 0.24 across the ten

loci. The highest observed heterozygosity was in marker (GDAAS0212) with a value

of 0.69, while the lowest was in the marker (Ib 255) with a value of 0.02 (Table 4).

Polymorphism was scored for size variation of bands on polyacrylamide gels. The

size of the SSR markers varied from ~100 -300 bp.


Table 4. Characteristics of amplified fragments in 40 sweet potato genotypes using 10

SSR markers

Marker

Name

aPIC

values

bObserved

heterozygosity

Ib255 0.98 0.02

Ib242 0.97 0.03

IBSSR20 0.47 0.53

IBSSR21 0.58 0.41

GDAAS0047 0.93 0.07

GDAAS0049 0.84 0.16

GDAAS0212 0.31 0.69

GDAAS0252 0.97 0.04

GDAAS0542 0.72 0.28

GDAAS0809 0.79 0.21

Mean 0.76 0.24

aPIC=1-Σ(pi2) (where Pi is the frequency of the ith allele detected) and bFrequency at

which heterozygous individuals occur in a population at a given locus

Analysis of molecular variance

To quantify the diversity level and the genetic relationship among the 40 accessions,

analysis of molecular variance (AMOVA) was done. AMOVA data showed that the

majority 82.17% of the diversity were present within populations and 17.83% among

the population of I. batatas.

Principal component analysis (PCA)

The original 1-0 data matrix was used for calculating a correlation matrix between

pairs of markers. The correlation matrix was employed for the calculation of eigen

values, which were then used for determining the coordinates for each genotype that

were used for PCA.


Based on the PCA scatter plot of SSR marker analysis grouped the 40 genotypes into

four main groups I, II, III and IV (Fig. 3). The first group (I) is composed of 12

accessions, in which majority of them is ICAR-CTCRI released varieties. The CIP

and highly carotene clones were grouped under II (20%) and III (40%) including Sree

Nandhini and Sree Vardhini. The fourth cluster group (IV) included 4 lines of CIP-

orange fleshed hybrids. These results also indicated that SSR markers could detect

polymorphism among sweet potato lines.

Fig 2. UPGMA dendrogram (based on Jaccard’s similarity coefficient) of sweet

potato accessions based on SSR marker analysis


Fig. 3. Principal coordinate analysis (PCA) for the SSR evaluation of the 40 sweet

potato accessions

Table 5. Analysis of molecular variance (AMOVA) of 40 genotypes of sweet

potato using SSR markers

Marker Source Df SSD Φ statistics Variance

components

Proportion of variation

components (%)

SSR Among populations 5 0.38 0.178 0.010 17.82

Within populations 35 1.64 0.047 82.17

Total 40 2.03 0.057

df - degrees of freedom; SSD - sums of squared deviations

DISCUSSION

Genetic diversity

Extensive diversity exists among cultivated sweet potato both inter or intra variety

accessions in morphological, physiological, and agronomic traits. This is the base for

modern cultivar improvement by hybridization. The present study detected a wide

range of diversity in cultivated sweet potato at the molecular level among the tested

accessions, using the SSR primers.


Evaluation of molecular genetic diversity is useful for conservation of genetic

resources, identification of cultivars, and the selection of parents for hybridization. A

high level of polymorphism was observed, with an average of four polymorphic bands

per SSR primer. In the present study, ten SSR primers yielded a total of 39 bands,

among which 29 were polymorphic with a mean of 4 bands per primer with 71.81%

polymorphism. Hwang et al. (2002) used eight SSR primers to analyze 22 sweet

potato landraces as well as cultivars derived from hybrids or polycross breeding in

Taiwan and reported 17 polymorphic bands, corresponding to 85% of total

polymorphism. These results were comparable with Tumwegamire et al., 2011 who

analyzed 92 African accessions with 26 SSR markers and found a mean value of 6.1

alleles per locus ranging from 2 to 11. Similarly, Gwandu et al., 2012 analyzed 57

sweet potato genotypes in Tanzania with 4 SSRs and found alleles from 11 to 22. The

SSR marker analysis of the 23 loci showed a total of 255 alleles, ranging from 4 to 25

alleles per locus with a mean value of 11.08 alleles per locus (Rodriguez-Bonilla et al., 2014). The high number of alleles found in sweet potato can be explained by the

hexaploidy nature of sweet potato.

The six SSR markers were able to discriminate between the different genotypes.

Studies have shown that SSR loci give good discrimination between closely related

individuals in some cases even, when only a few loci are employed (Powell et al., 1996). High levels of genetic diversity are present in sweet potato genotypes as

revealed by the high number of alleles observed. This may be due to the mating

system of the crop and natural cross-pollination. A measure of the amount of

heterozygosity can be used as a general indicator of the amount of genetic variability

in a population. The genotypes used in this study showed high levels of observed

heterozygosity ranging from 0.02 to 0.69. Previous studies in sweet potato also found

high levels of heterozygosity with values of 0.37 for Tropical America, 0.60 for Latin

American and 0.75 for Kenyan accessions (Karuri et al., 2009; Roullier et al., 2013).

In sweet potato high levels of heterozygosity and genetic diversity could be explained

by the outcrossing and self-incompatible nature of the plant (Zhang et al., 1999). For

instance, this self-incompatibility in the field might result in chance seedlings from

crossings, providing another path to increase genetic diversity (Yada et al., 2010). The

average PIC value was 0.76 with SSRs Ib255 (0.98), Ib242 (0.97) and GDAAS0252

(0.97) having the highest values. The loci with the lowest PIC values were

GDAAS0212 (0.31) and IBSSR20 (0.47) (Table 4).

Microsatellites have become one of the most widely used molecular markers in recent

years. Each set of the 24 peanut accessions from the four botanical varieties could be

distinguished from each other with the SSR markers and can be further classified into

different sub-groups. As DNA markers, SSRs are more advantageous over many other

markers, as they are highly polymorphic, highly abundant, genetically codominant,

and analytically simple. The genotypes belonging to var. hirsuta, which are all from


Guangxi province in southern China, are difficult to be identified by morphologically

or agronomically because of their similar growing habits, plant height, leaf shape, pod

shape, and so on. However, they can be distinguished from one another by the SSR

markers. It is believed from this study and present knowledge that SSR markers are

very useful molecular markers in sweet potato genetic studies and in large-scale

breeding programs.

The existence of intravarietal polymorphism was also evidenced when analyzing the

vines collected as clones of a particular landrace, some showing different banding

patterns. Sweet potato is asexually propagated via stem cuttings and adventitious buds

arising from storage roots, which may result in the accumulation of random

mutations. Therefore, this intravariety variability may be related to the high somatic

mutation reported in this crop (Hernandez et al., 1964). Intravarietal polymorphism

related to vegetative crop species has also been reported for potato (Solanum tuberosum) by Quiroz et al. (1990) and cassava (M. esculenta) by Colombo et al. (2000) and Sambatti et al. (2001).

Genetic structure and analysis of molecular variance

The AMOVA results indicated that the high diversity discussed above was mostly

distributed within the population for sweet potato accessions (82.17%) and 17.82%

among the populations. A similar result (64.4% variation within households) was

obtained by Veasey et al. (2007) when studying morphological traits of the sweet

potato accessions. This same pattern of a greater portion of variation being due to

differences between accessions within households has also been reported for cassava

(Sambatti et al. 2000), as well as within groups or regions (Faraldo et al., 2000;

Cabral et al., 2002). Other studies with sweet potatoes using AMOVA have also

shown higher diversity within rather than between regions, which could, on a much

smaller scale, be compared to the higher diversity found within rather than between

households and communities. Zhang et al. (2000) used AFLP to study the genetic

diversity of 69 sweet potato landraces from tropical America collected in 13

countries, reporting a high variation (90%) within regions and a statistically

significant variation of 10% between regions (Central America, Colombia-Venezuela,

Caribbean, Peru-Ecuador).

Furthermore, Zhang et al. (2004) found a highly significant variation of 86.7% within

regions and 12.4% among regions when studying 75 sweet potato landraces from

Latin America and Pacific areas with AFLP markers.

Principal component analysis was also conducted to analyze the genetic relationships

among the individual accessions. Similar to the cluster analysis results, PCA did not

result in a discernible grouping of genotypes. Tseng et al. (2002) observed similar

results between UPGMA clustering and PCA in the genotyping and assessment of


genetic relationships among elite polycross breeding cultivars of sweet potato in

Taiwan using SAMPL polymorphisms.

In summary, SSR markers successfully evaluated the genetic relationships among the

sweet potato accessions used and generated a high level of polymorphism. The 40

genotypes were clustered into four clusters using the UPGMA dendrogram. The

results of the present study will be useful for the management of germplasm,

improvement of the current breeding strategies and for the release of new cultivar.

ACKNOWLEDGEMENTS

The authors are grateful to the Director, Head, Division of Crop Improvement, ICAR-

CTCRI, Thiruvananthapuram, for providing the laboratory facilities to do the work

and the Department of Science and Technology (INSPIRE fellowship), for providing

the financial support.

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