Genomic analysis of water use efficiency

Boyce Thompson Institute for Plant Science

Cornell University

Oklahoma State University

University of North Carolina at Chapel Hill

http://isotope.bti.cornell.edu/

Collaborators• Cornell/Boyce Thompson: Jonathan Comstock, Susan

McCouch– Christine Fleet– Roman Pausch– Wendy Vonhof– Shiqin Xu– Yunbi Xu

• Oklahoma State: Bjorn Martin, Chuck Tauer– Shakuntala Fathepure– Baige Zhao

• UNC Chapel Hill: Todd Vision– Maria Tsompana– Lindsey Swanson

Water use efficiency• A fundamental trade-off for plants

– Open stomates allow photosynthesis– But also result in water loss

• WUE is the ratio of carbon fixed to water lost– Somewhat related to drought tolerance– More closely to yield potential under irrigation

• Water is the most limiting resource to global agricultural production

• In some crops, and under some conditions, greater WUE would be desirable and in others less

Three levels of WUE

• Whole-field (under agronomic control)

• Whole-plant (driven by respiration)• Single-leaf (focus here)

WUE photosynthesis

transpiration

ca c i1.6 wa wi

Leaf-level WUE

ci wi

ca wa

CO2H2O

wind

sun

The challenges of working with WUE

• WUE is a complex trait– Rarely if ever controlled by a single gene– Very sensitive to environment

• Breeding for WUE has not worked– Too many deleterious side-effects

• We know almost nothing about the molecular biology of how plants adjust their WUE– Could we engineer WUE if we knew more?

• QTL mapping as a “foot in the door” to discover the pathways involved in WUE

Quantitative trait loci (QTL)

P1 (+) P2 (-)

F1 (0)

F20

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LOD

Stable carbon isotopes

• Direct physiological measurement of WUE is not quick and cheap enough for QTL studies - a proxy is needed

• Stable isotopes are naturally occuring– Atmospheric CO2 is 99 12C : 1 13C

• Rubisco, the key enzyme in carbon fixation, discriminates against 13C

• Easily measured by mass spectrometry

Isotope measurements

• Isotopic ratioR = 13C/12C

• Discrimination index = (Rair/Rplant) – 1

and WUE

• Both ∆ & WUE depend on the CO2 diffusion gradient

• In C3 plants, variation in this gradient is the primary determinant of and leaf-level WUE.

• provides a high-throughput proxy for ci– Values of are typically negative– Values closer to zero represent greater WUE

(more carbon fixed per unit of water)

Goals• To dissect natural variation in WUE• Discovery and characterization of WUE

quantitative trait loci (QTL) – Rice (upland vs rice paddy cultivation)– Tomato (desert versus cultivated species)

• Lay ground-work for positional cloning– Fine mapping– Introgression lines

Survey of variability in rice• Assayed variation in among

– Landraces and elite cultivars– Related wild species– The offspring of four wide crosses

• Lamont x Teqing• Kasalath x Nipponbare• IR64 x Nipponbare• O. rufipogon x Jefferson

• Variation in the offspring of a single cross can be as wide as the variation among all cultivated/wild accessions!

• Upland/lowland distinction not that helpful…

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Kasalath x NipponbareLemont x TeqingOryza wild speciesO.sativaRufipogon x JeffersonIR64 x Nipponbare

Survey of variability in rice

www.gramene.org

Genomic sequence

Genetic Map

LOD=8.60

WUE QTL On Chromosome 1

Mapping WUE QTL in tomato

• Wild desert species of tomato (e.g. Solanum pennellii) have high WUE relative to cultivated species (S. lycopersicon)

• On the minus side– The genome sequence is not available yet

• On the plus side– Zamir introgression lines for S. lycopersicon

x S. pennellii greatly facilitate mapping

QTL in pennellii population

Possible physiological basis for WUE

• Several of the candidate QTL lines have– High nitrogen content = abundant

protein– Low specific leaf area (m2/g)

• These correlates suggest that increased carboxylation capacity may be responsible for greater WUE in these QTL

Finding crossovers within IL5-4

• QTL can be located more precisely if IL5-4 introgression can be broken up

• Backcrossed IL5-4 to cultivated parent• Genotyped F2 progeny for flanking markers

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are needed to see this picture.

Principle of fine-mapping(Mendelization)

flankingmarker 1

flankingmarker 2

internalmarker 1

QTL

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Fine-mapping IL5-4 QTL

• 16 crossovers obtained from ~2000 backcross F2 plants

• These were selfed to produce backcross F3s– values obtained for F3 plants

• Scoring internal STS markers– These allow us to align to the tomato physical map– One internal STS marker done– Several more in development

• AFLP markers are currently being mapped– Not physically mapped, but abundant and easy to

score

TG35172.7

TG60, CT8075

CP58B, CHS377.2

CD7884.9

TG6987.5

SSR590, T1541

TG60104

T1777105

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T1584108

TG69111

F2 1992 F2 2000

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-5TG35173.9

TG60, CT8076.2

CP58B, CHS378.4

CD7886.1

TG6988.7

IL Population

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PCR length polymorphism already scoredSSR marker availabledCAPS marker availableScreening for polymorphisms (1 or more introns predicted)Screening for polymorphisms (no intron predicted)Primers under development

QTL

TG69 physical contig

Now what?• Adding additional STS to IL5-4 (UNC)

– Goal is <1cM (=1 Mb) resolution

• Identifying BAC contigs containing markers in QTL candidate region (UNC)– BAC skimming to obtain high density markers– Comparative mapping in Arabidopsis for candidate

gene analysis

• Generating overlapping congenic lines in IL5-4 by marker assisted selection (OSU)