Light Affects the Entire Plant Life Cycle

1. Genomic Systems underlying the genetics of adaptation in Arabidopsis thalianaJustin BorevitzEcology & EvolutionUniversity of Chicagohttp://naturalvariation.org/

2. Light Affects the Entire Plant Life Cycle de-etiolation } hypocotyl

4. Talk Outline Talk Outline • Predictable to Seasonal Variation • Local Adaptation in the Lab • Population Genetics • Population structure • Extant diversity and new mutation • Arrays • Genetic, epigenetic, expression, splicing, and allelic variation • Ecological context • Arabidopsis and Aquilegia • Predictable to Seasonal Variation • Local Adaptation in the Lab • Population Genetics • Population structure • Extant diversity and new mutation • Arrays • Genetic, epigenetic, expression, splicing, and allelic variation • Ecological context • Arabidopsis and Aquilegia

5. Begin with regions spanning the native geographic range Nordborg et al PLoS Biology 2005

6. Regional/Seasonal Variation • What is Local Adaptation? • Predictable Seasonal changes unique to each location. Tossa Del Mar Spain Lund Sweden

7. Seasons in the Growth Chamber Seasons in the Growth Chamber Developmental Plasticity == Behavior Developmental Plasticity == Behavior Sweden Spain • Changing Day length • Cycle Light Intensity • Cycle Light Colors • Cycle Temperature • Changing Day length • Cycle Light Intensity • Cycle Light Colors • Cycle Temperature Geneva Scientific/ Percival

8. Solar Calc II • Kurt Spokas • Version 2.0a June 2006 • USDA-ARS Website Midwest Area (Morris,MN) • http://www.ars.usda.gov/mwa/ncscrl

9. Col-gl1 Col-gl1 Number of RILs Sweden 2 Sweden 1 FLM Kas1 Kas1 FRI Col-gl1 Col-gl1 Spain 1 Spain 2 Number of RILs Kas1 Kas1 Flowering time QTL, Kas/Col RILs Flowering time QTL, Kas/Col RILs

10. Kas/Col flowering time QTL GxE Chr4 FRI Chr1 FLM Chr4 FRI

11. Environment and Epistasis

12. Globally Distributed Olivier Loudet http://www.inra.fr/qtlat/NaturalVar/NewCollection.htm

13. Current collections • 807 Lines from 25 Midwest Populations • (Diane Byers IL state) – pics published! • 1101 Lines from UK, 51 populations • (Eric Holub Warwick, UK) – growing! • > 500 lines N and S Sweden (Nordborg) • > 400 Lines France and Midwest (Bergelson) • 400 lines Midwest (Borevitz) • 857 Accessions stock center (Randy Scholl) • pics published • Others welcome… Genotyped with Sequenom 149 SNPs $0.03 per

14. Local Population Structure common haplotypes 134 Non singleton SNPs of 1234 accessions Global, Midwest, and UK Megan Dunning, Yan Li

15. Diversity within and between populations 17 Major Haplotypes 80 Major Haplotypes

19. Variation within a field http://naturalvariation.org/hapmap Variation within a field http://naturalvariation.org/hapmap

20. Universal Whole Genome Array DNA RNA Gene/Exon Discovery Gene model correction Non-coding/ micro-RNA Chromatin Immunoprecipitation ChIP chip Alternative Splicing Methylation Antisense transcription Polymorphism SFPs Discovery/Genotyping Transcriptome Atlas Expression levels Tissues specificity Comparative Genome Hybridization (CGH) Insertion/Deletions Copy Number Polymorphisms RNA Immunoprecipitation RIP chip Allele Specific Expression Control for hybridization/genetic polymorphisms to understand TRUE expression variation

21. Improved Genome Annotation ORFa Transcriptome Atlas ORFb start AAAAA deletion M M M M M M M M M M M M SFP SNP SNP SFP SFP conservation Chromosome (bp)

22. Which arrays should be used? BAC array cDNA array Long oligo array

23. Which arrays should be used? Gene array Exon array Tiling array 35bp tile, 25mers 10bp gaps

24. Which arrays should be used? SNP array How about multiple species? Microbial communities? Pst,Psm,Psy,Psx, Agro, Xanthomonas, H parasitica, 15 virus, Ressequencing array Tiling/SNP array 2007 250k SNPs, 1.6M tiling probes

25. Global Allele Specific Expression 65,000 SNPs Transcribed Accession Pairs 12,000 genes >= 1 SNP 6,000 >= 2 SNPs

26. Potential Deletions

27. SFP mSFP Van Van Col Van Col Van Hpa msp Hpa msp Hpa msp SFPs and CC*GG Methylome * * * * A) HpaII digestion Extract genomic 100ng DNA (single leaf) Digest with either msp1 or hpa2 CC*GG Label with biotin Random primers Hybridize to array * * * Random labeling * B) * * * MspI digestion Random labeling Intensity Col Col Hpa msp

28. Experimental design Van ♀ x Col ♂ Col♀ x Col♂ Col ♀ x Van ♂ Van ♀ x Van ♂ Four genotypes, each with four biological replicates 4 day old seedlings, white light

29. Methylation Polymorphisms, mSFPs Fit model Intensity ~ additive + dominant + maternal + additive:enzyme + dominant:enzyme + maternal:enzyme

30. SFP detection on tiling arrays Delta p0 FALSE Called FDR 1.00 0.95 18865 160145 11.2% 1.25 0.95 10477 132390 7.5% 1.50 0.95 6545 115042 5.4% 1.75 0.95 4484 102385 4.2% 2.00 0.95 3298 92027 3.4%

31. methylated features and mSFPs Enzyme effect, on CCGG features GxE mQTL? >10,000 of 100,000 at 5% FDR 276 at 15% FDR

32. Genomic Distribution of nonPolymorphic methylation sites

33. AT1G27320 tu9 AT1G51790 intron9 Col Van F1v F1c Col Van F1v F1c Col Van F1v F1c AT2G37080 tu1 AT4G19020 tu19 AT4G27910 tu9 AT1G53240 intron4 AT2G01220 tu5 AT5G14600 intron3 AT1G49730 tu10 AT2G45620 intron5 AT1G79990 intron9 AT1G20780 tu4 Control HpaII MspI AT2G45270 intron9 AT2G35350 tu2 AT3G11460 tu1 AT4G04340 tu15 AT4G31140 tu2 AT2G18100 tu9 AT5G56370 tu3 AT3G07740 tu2 AT3G48730 tu3 AT5G63190 tu6 AT5G13960 intron8 AT1G27900 intron7 Verification of additive x enzyme by genomic PCR

34. Col Van F1v F1c Col Van F1v F1c Col Van F1v F1c AT1G19450 tu10 AT5G14950 tu1 AT1G19715 intron2 AT5G04710 tu1 AT5G67130 tu7 AT2G32730 tu3 AT2G45670 tu11 AT3G04820 tu1 AT3G04610 intron5 AT3G53100 tu2 AT3G23590 intron4 AT1G10910 intron9 Control HpaII MspI AT3G28880 tu8 AT4G23570 tu9 AT4G02500 tu1 AT4G17140 tu8 AT1G73730 tu2 Verification of additive x enzyme by genomic PCR

35. Verification of additive x enzyme by epiTyper Col Col Col Van Van Van Col♂ x Van♀ Col♂ x Van ♀ Van♂ x Col♀ Van ♂ x Col ♀ Van♂ x Col ♀ CC*GG CC*GG chromomethylase 2 (CMT2) exon19

36. Next Questions • What is the genetic architecture of methylation variation? • How does it change with the environment and through development? • Regional patterns, eg chromatin remodeling • When does methylation effect expression?

37. Expression Analysis with Annotation Transcription subUnits (TUs)Intensity(gene/tu) ~ add + dom+mat + error Intron1 Exon1 ? Exon2 cDNA1 cDNA2 cDNA3 X Tu1 Tu2 Tu3

38. Additive, Dominant, Maternal, Genotype Variation D E

39. Col Van Alternative spliced introns v v v c c c v c RT-PCR gDNA PCR

40. Col Van Alternative spliced exons - verification v v v c c c v c RT-PCR gDNA PCR

41. Ecological and Evolutionary context • Abiotic conditions • Light, temperature, humidity • Soil, water • Biotic conditions • Pathogens and polinators • Conspecifics, grasses trees

42. Local Population Variation

43. Local adaptation under strong selection

44. Seasonal Variation Matt Horton Megan Dunning

45. Aquilegia (Columbines) Recent adaptive radiation, 350Mb genome

46. Genetics of Speciationalong a Hybrid Zone

47. NSF Genome Complexity • Microarray development • QTL candidates • Physical Map (BAC tiling path) • Physical assignment of ESTs • QTL for pollinator preference • ~400 RILs, map abiotic stress • QTL fine mapping/ LD mapping • Develop transformation techniques • VIGS • Whole Genome Sequencing (JGI?) Scott Hodges (UCSB) Elena Kramer (Harvard) Magnus Nordborg (USC) Justin Borevitz (U Chicago) Jeff Tompkins (Clemson)

48. http://www.plosone.org/

49. NaturalVariation.org NaturalVariation.org USC Magnus Nordborg Paul Marjoram Max Planck Detlef Weigel Scripps Sam Hazen University of Michigan Sebastian Zoellner USC Magnus Nordborg Paul Marjoram Max Planck Detlef Weigel Scripps Sam Hazen University of Michigan Sebastian Zoellner University of Chicago Xu Zhang Yan Li Peter Roycewicz Evadne Smith Megan Dunning Joy Bergelson Michigan State Shinhan Shiu Purdue Ivan Baxter University of Chicago Xu Zhang Yan Li Peter Roycewicz Evadne Smith Megan Dunning Joy Bergelson Michigan State Shinhan Shiu Purdue Ivan Baxter