genomic analysis of water use efficiency
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Boyce Thompson Institute for Plant Science. Cornell University. Oklahoma State University. University of North Carolina at Chapel Hill. Genomic analysis of water use efficiency. http://isotope.bti.cornell.edu/. Cornell/Boyce Thompson: Jonathan Comstock, Susan McCouch Christine Fleet - PowerPoint PPT PresentationTRANSCRIPT
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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/
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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
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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
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Three levels of WUE
• Whole-field (under agronomic control)
• Whole-plant (driven by respiration)• Single-leaf (focus here)
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WUE photosynthesis
transpiration
ca c i1.6 wa wi
Leaf-level WUE
ci wi
ca wa
CO2H2O
wind
sun
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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
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Quantitative trait loci (QTL)
P1 (+) P2 (-)
F1 (0)
F20
-
+
+
LOD
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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
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Isotope measurements
• Isotopic ratioR = 13C/12C
• Discrimination index = (Rair/Rplant) – 1
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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)
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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
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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
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www.gramene.org
Genomic sequence
Genetic Map
LOD=8.60
WUE QTL On Chromosome 1
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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
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QTL in pennellii population
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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
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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
QuickTime™ and aTIFF (LZW) decompressor
are needed to see this picture.
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Principle of fine-mapping(Mendelization)
flankingmarker 1
flankingmarker 2
internalmarker 1
QTL
mm
mm mm
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mmmm
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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
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TG35172.7
TG60, CT8075
CP58B, CHS377.2
CD7884.9
TG6987.5
SSR590, T1541
TG60104
T1777105
106
T1584108
TG69111
F2 1992 F2 2000
IL5
-4
IL5
-5TG35173.9
TG60, CT8076.2
CP58B, CHS378.4
CD7886.1
TG6988.7
IL Population
IL5
-3
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
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TG69 physical contig
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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)