Insect resistance in Arabidopsis,Epistasis and growth rate,Insect resistance in the field,Approaches to drought tolerance in rice

1. Background, and why I am here Insect resistance in Arabidopsis Epistasis and growth rate Insect resistance in the field Approaches to drought tolerance in rice Thomas Mitchell-Olds Institute for Genome Sciences & Policy Department of Biology Duke University [email_address] Advances in biotic and abiotic stress tolerance

2. University of Wisconsin : Ph.D. in Botany; Plant Breeding & Plant Genetics Postdoc in Human Genetics

3. Department of Genetics and Evolution Max Planck Institute of Chemical Ecology

4. Duke University

5. Complex trait variation for Insect resistance Flowering time Drought tolerance NSF NIH

6. Why am I here? 1) Research to benefit human welfare 2) Rice is similar to Arabidopsis 3) Phenotypes in the field 146 276 150 Undernourished population in millions

7. Why are quantitative traits polymorphic?

8. Correspondence of QTLs for insect resistance & glucosinolate levels Insect Resistance in Arabidopsis LOD score Insect resistance Position on Chromosome V Position on Chromosome V Glucosinolates R S-Glucose NOSO 3 -

9. Myrosinase Other products Thiocyanates (RSCN) Nitriles (RCN + S) Isothiocyanates (RNCS) R S-H NOSO 3 - Insect resistance and chemical defense R S- Glucose NOSO 3 - Arabidopsis glucosinolates: From amino acid precursor Influence insect resistance Genetically variable Evolve non-neutrally Breakdown of glucosinolates leads to toxic products

10. Cloning QTL for insect resistance and glucosinolates LOD score Position on Chromosome V Position on Chromosome V Initial QTL mapping Fine scale mapping of GS QTL Positional cloning Verification by transformation QTL cloning is easier for secondary traits (like GS) than for insect damage or yield under drought Insect resistance Glucosinolates

11. MAM2 gene controls Kroymann et al . 2003 PNAS glucosinolate concentration & resistance to generalist herbivores but not specialist herbivores, and does not impact growth rate

12. Why are complex traits polymorphic? Data come from cloned QTLs Hence no information on small effect QTL Growth rate QTL in Arabidopsis thaliana Kroymann & Mitchell-Olds, Nature, 2005 Epistasis and growth rate Juergen Kroymann

13. Growth rate QTL in the MAM region 0 1 2 3 4 5 6 7 8 0 25 50 75 100 125 150 175 200 225 250 0 1 2 3 4 5 6 7 8 0 25 50 75 100 125 150 175 200 225 250 F ratio 0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8 0 25 50 75 100 125 150 175 200 225 250 position [kb] MAM2 gene does not impact growth rate

14. 0 25 50 75 100 125 150 175 200 225 250 0 1 2 3 4 5 6 7 8 0 25 50 75 100 125 150 175 200 225 250 F ratio 0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8 0 25 50 75 100 125 150 175 200 225 250 position [kb] Two Growth rate QTL in the MAM region 0 1 2 3 4 5 6 7 8 Right QTL: gr Left QTL: gl - 0.06 - 0.03 0 0.03 0.06 Mass (L er - Col) [mg] - 0.06 - 0.03 0 0.03 0.06 Mass (L er - Col) [mg] - 0.06 - 0.03 0 0.03 0.06 Mass (L er - Col) [mg] Tightly linked QTL show opposite effects Ler > Col Col > Ler

15. gr LC: gr CL: gr LC: gr CL: Crosses to identify the QTL on the right Segregating region Reciprocal flanking backgrounds at5g23140 at5g23180 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 LJ47C LJ01C CJ10L CJ45L CJ36L LJ52C LJ30C CJ40L CJ26L LJ32C LJ35C 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] gr LC: 1 2 3 4 5 6 7 8 9 gr CL: at5g23140 at5g23180 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 LJ47C LJ01C CJ10L CJ45L CJ36L LJ52C LJ30C CJ40L CJ26L LJ32C LJ35C 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] gr LC: 1 2 3 4 5 6 7 8 9 gr CL: Recombination Breakpoints Right QTL: gr

16. Recombination Breakpoints    N > 7000

17. Interval 7 is significant in both reciprocal crosses 189 161 Ler 199 140 Col n.s. n.s. P<0.05 n.s. n.s. n.s. n.s. P<0.05 n.s. P value 9 8 7 6 5 4 3 2 1 Interval at5g23140 at5g23180 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 LJ47C LJ01C CJ10L CJ45L CJ36L LJ52C LJ30C CJ40L CJ26L LJ32C LJ35C 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] gr LC: 1 2 3 4 5 6 7 8 9 gr CL: at5g23140 at5g23180 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 LJ47C LJ01C CJ10L CJ45L CJ36L LJ52C LJ30C CJ40L CJ26L LJ32C LJ35C 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] gr LC: 1 2 3 4 5 6 7 8 9 gr CL:

18. Epistatic QTL serine/threonine protein kinase at5g23140 at5g23180 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 LJ47C LJ01C CJ10L CJ45L CJ36L LJ52C LJ30C CJ40L CJ26L LJ32C LJ35C 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] gr LC: 1 2 3 4 5 6 7 8 9 gr CL: at5g23140 at5g23180 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 LJ47C LJ01C CJ10L CJ45L CJ36L LJ52C LJ30C CJ40L CJ26L LJ32C LJ35C 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] gr LC: 1 2 3 4 5 6 7 8 9 gr CL: No QTL No QTL 1 - synonymous SNP 1 - intergenic SNP 1 - intron indel of 1 bp QTL

19. Allelic effect is reversed depending on genetic background Epistatic growth rate QTL 189 161 Ler 199 140 Col n.s. n.s. P<0.05 n.s. n.s. n.s. n.s. P<0.05 n.s. P value 9 8 7 6 5 4 3 2 1 Interval at5g23140 at5g23180 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 LJ47C LJ01C CJ10L CJ45L CJ36L LJ52C LJ30C CJ40L CJ26L LJ32C LJ35C 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] gr LC: 1 2 3 4 5 6 7 8 9 gr CL: at5g23140 at5g23180 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 at5g23150 at5g23160 at5g23170 at5g23190 at5g23200 at5g23210 LJ47C LJ01C CJ10L CJ45L CJ36L LJ52C LJ30C CJ40L CJ26L LJ32C LJ35C 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 222 236 230 234 232 224 228 226 218 220 212 216 214 206 210 208 [kb] gr LC: 1 2 3 4 5 6 7 8 9 gr CL:

21. Insect resistance in natural environments Why are quantitative traits polymorphic?

22. Ecological model systems Clone QTLs Measure fitness of alleles in natural populations

23. Genus Boechera (formerly Arabis) Close relative of Arabidopsis Genome ~ 250 Mb Positional cloning Transformation Undisturbed natural populations Diploid apomixis

24. Resistance variation in Boechera stricta 0 20 40 60 80 100 Percent Leaf Damage 0 20 40 60 80 100 Frequency Trichoplusia ni

25. Glucosinolate quantity in Boechera stricta About 30% of variation is under genetic control

26. BCAA: branched chain amino acids: Val, Leu, Ile 0.0 0.2 0.4 0.6 0.8 1.0 Proportion of GS from BCAA 0 10 20 30 40 50 60 Frequency Glucosinolate type in Boechera stricta Met-GS BC-GS Met allele is more resistant BCMA locus: Branched Chain Methionine Allocation T. ni : generalist herbivore BCMA controls resistance to generalist herbivore

27. Montana Colorado

28. Montana Colorado Near Isogenic lines for BCMA : 2304 plants into original populations Measure herbivore damage & fitness Today: phenotypic selection (Still scoring BCMA genotypes)

29. Fitness of alleles in their ancestral environments Montana Colorado

30. Susceptible BC allele Resistant Met allele N = 2,032 plants; 47,109 leaves CO MT 0 5 10 15 Percent Leaf Damage High herbivore pressure Lower herbivore pressure

31. ANOVA: significant natural selection in the wild, P < 10 -9 Colorado: Herbivory reduces survival Montana: No natural selection on herbivore resistance Survival 993 plants in Colorado Selection gradient: 1% of leaf area removed reduces fitness by 1.1% How does insect resistance influence fitness? How does insect resistance influence fitness? How do secondary traits influence yield under drought?

32. Susceptible BC allele Resistant Met allele Strong selection for resistance No selection for resistance CO MT 0 5 10 15 Percent Leaf Damage High herbivore pressure Lower herbivore pressure

33. BCMA summary Positional cloning of BCMA Influence of trait on fitness in field environment

34. Approaches to drought tolerance in rice 1) Yield in managed stress environments 2) Trait dissection into component traits

35. Benfey lab Duke Univ Nondestructive, automated analysis of root architecture 360 degrees using computer controlled motorized turntable

36. Indicas Teqing 93-11 IR64 Benfey Lab Caipo Jefferson Japonicas

37. Topology-based image analysis High throughput phenotyping enables cloning of QTLs Benfey Lab

38. Approaches to drought tolerance in rice 1) Yield in managed stress environments 2) Trait dissection into component traits 3) Dissecting drought environments Develop laboratory models of drought environments Understand their effects on drought tolerance Quantify axes of environmental variation Photo by J. Lamo & O. Michael

39. Ruiz Corral, et al. 2008, Crop Sci 48: 1502 Different maize races are grown in different environments Quantify axes of environmental variation Environmental Conditions PC1 Environmental Conditions PC2 Shapes indicate genetic groups

40. Hypothetical example: environmental dependence of drought tolerance Plot nurseries based on environments Measure yield advantage at each site 3D plot: yield advantage vs. environment Grow NILs in multiple environments

41. Hypothetical example: environmental dependence of drought tolerance Develop laboratory models of drought environments What aspects of the environment control the yield advantage?

42. Approaches to drought tolerance in rice 1) Yield in managed stress environments 2) Trait dissection into component traits 3) Dissecting drought environments 4) Integrated pedigrees for QTL & association analysis - Cannot use association approach for traits that differ between indica, japonica, or other groups - Epistasis is a major problem for association studies

43. Bao-Hua Song Kasavajhala Prasad Antonio Manzaneda Carrie Olson-Manning Philip Benfey Eric Schranz Aaron Windsor Juergen Kroymann Maria Clauss Karl Schmid Dan Kliebenstein Jonathan Gershenzon Kathy Springer Toyin Aremu-Cole Molly Mitchell-Olds Sara Mitchell-Olds Janoo Naqvi Slater Hurst Michael Cameron J. Lutkenhaus Laura Saucier Elizabeth Ballweg Cheng-Ruei Lee Antje Figuth Susi Donnerhacke Kerstin Weniger Sylke Dietel Marion Kupper Sylke Dietel Grit Schubert Katja Schwarzer Nancy Richter D. Schnabelrauch Tabea Birk Kerstin Weniger NSF NIH Duke MPG