1. Arrays as tools for Natural Variation studies: Mapping, Haplotyping, and gene expression Justin Borevitz University of Chicago naturalvariation.org`

2. Talk Outline Single Feature Polymorphisms (SFPs) –Potential deletions Bulk Segregant Mapping –Extreme Array Mapping Haplotyping –Selection Transcriptional profiling – for QTL candidate genes

3. What is Array Genotyping? Affymetrix expression GeneChips contain 202,806 unique 25bp oligo nucleotides. 11 features per probset for 21546 genes New array’s have even more Genomic DNA is randomly labeled with biotin, product ~50bp. 3 independent biological replicates compared to the reference strain Col GeneChip

4. Potential Deletions

5. Spatial Correction Spatial Artifacts Improved reproducibility Next: Quantile Normalization

9. False Discovery and Sensitivity PM only SAM threshold 5% FDR GeneChip SFPs nonSFPs Cereon marker accuracy 3806 89118 100% Sequence 817 121 696 Sensitivity Polymorphic 340 117 223 34% Non-polymorphic 477 4 473 False Discovery rate: 3% Test for independence of all factors: Chisq = 177.34, df = 1, p-value = 1.845e-40 SAM threshold 18% FDR GeneChip SFPs nonSFPs Cereon marker accuracy 10627 82297 100% Sequence 817 223 594 Sensitivity Polymorphic 340 195 145 57% Non-polymorphic 477 28 449 False Discovery rate: 13% Test for independence of all factors: Chisq = 265.13, df = 1, p-value = 1.309e-59 3/4 Cvi markers were also confirmed in PHYB 90%80%70% 41%53%85% 90%80%70% 67%85%100% Cereon may be a sequencing Error TIGR match is a match

10. Chip genotyping of a Recombinant Inbred Line 29kb interval Discovery 6 replicates X $500 12,000 SFPs = $0.25 Typing 1 replicate X $500 12,000 SFPs = $0.041

11. LIGHT1 NIL

12. Potential Deletions >500 potential deletions 45 confirmed by Ler sequence 23 (of 114) transposons Disease Resistance (R) gene clusters Single R gene deletions Genes involved in Secondary metabolism Unknown genes

13. Potential Deletions Suggest Candidate Genes FLOWERING1 QTL Chr1 (bp) Flowering Time QTL caused by a natural deletion in MAF1 MAF1 MAF1 natural deletion

14. Fast Neutron deletions FKF1 80kb deletion CHR1cry2 10kb deletion CHR1 Het

15. Map bibb 100 bibb mutant plants 100 wt mutant plants

16. bibb mapping ChipMap AS1 Bulk segregant Mapping using Chip hybridization bibb maps to Chromosome2 near ASYMETRIC LEAVES1

17. BIBB = ASYMETRIC LEAVES1 Sequenced AS1 coding region from bib-1 …found g -> a change that would introduce a stop codon in the MYB domain bibbas1-101 MYB bib-1 W49* as-101 Q107* as1 bibb AS1 (ASYMMETRIC LEAVES1) = MYB closely related to PHANTASTICA located at 64cM

18. stamenstay Ler Sarah Liljegren Mapping confirmed

19. ein6een double mutant Ramlah Nehring Mapping confirmed

20. eXtreme Array Mapping 15 tallest RILs pooled vs 15 shortest RILs pooled

21. LOD eXtreme Array Mapping Red light QTL RED2 from 100 Kas/ Col RILs Allele frequencies determined by SFP genotyping. Thresholds set by simulations 15 tallest RILs pooled vs 15 shortest RILs pooled 0 4 8 12 16 020406080100 cM LOD Composite Interval Mapping RED2 QTL Chromosome 2 RED2 QTL 12cM

22. Fine Mapping with Arrays Single Additive Gene 1000 F2s Select recombinants by PCR 1Mb region

23. Barley SFPs gDNA 9 arrays, random labeled genomic DNA 3 wild type, 3 parent 1, 3 parent 2 Hope to verify some RNA SFPs Pairs plots, correlation matrix SFP table

24. Just better than permutations delta ori.data perm.data difference FDR 0.10 2866 2114.2 751.8 0.74 0.15 1870 578.4 1291.6 0.31 0.20 1274 269.3 1004.7 0.21 0.25 991 174.7 816.3 0.18 0.30 816 126.8 689.2 0.16 0.35 660 95.8 564.2 0.15 0.40 554 75.8 478.2 0.14 Increase specific activity with other labeling methods Perform more replicates

25. Single Feature Polymorphisms –Improve with replicates (easy) –Improved statistical models Genotyping –Precisely define recombination breakpoints –Fine mapping Potential Deletions –Candidate genes/ induced mutations Bulk segregant Mapping –eXtreme Array Mapping, F2s etc

26. Array Haplotyping What about Diversity/selection across the genome? A genome wide estimate of population genetics parameters, θ w, π, Tajima’D, ρ LD decay, Haplotype block size Deep population structure? Col, Lz, Ler, Bay, Shah, Cvi, Kas, C24, Est, Kin, Mt, Nd, Sorbo, Van, Ws2

27. Pairwise Correlation between and within replicates

28. Array Haplotyping Inbred lines Low effective recombination due to partial selfing Extensive LD blocks ColLerCviKasBayShahLzNd Chromosome1 ~500kb

29. Distribution of T-stats null (permutation) actual Not ColColNANA duplications 32,427 Calls 208,729 12,250 SFPs

30. Sequence confirmation of SFPs

31. SFPs for reverse genetics http://naturalvariation.org/sfp 14 Accessions 30,950 SFPs`

32. Chromosome Wide Diversity

33. Self Incompatibility-locus

35. Diversity 50kb windows

36. Tajima’s D like 50kb windows RPS4 unknown

37. R genes vs bHLH Theta W RPS4

38. Rgenes vs bHLH Tajimas’ D RPS4

39. R genes vs bHLH

40. Summery Haplotyping Patterns of variation across accessions Natural reverse genetics –Polymorphism database Increased polymorphism in centromere Selection on R/genes

41. Look for gene expression differences between genotypes Identify candidate genes that map to mutation Downstream targets that map elsewhere Transcription based cloning

44. differences may be due to expression or hybridization

45. PAG1 down regulated in Cvi PLALE GREEN1 knock out has long hypocotyl in red light

46. SFPs from RNA Barley Affy array 22801 probe sets –Most probes sets 11 probes –Background correction “rma2” –Quantile normalization 36 arrays total –3 replicates –6 tissues, leaf, crown, root, radical, gem, col? –2 genotypes (Golden Promise 7,459 ESTs) – (Morex 52,695 ESTs)

47. Look at some plots raw data

48. Remove probe effect

49. Remove Tissue + Genotype effect

50. Look at some plots raw data

51. Remove probe effect

52. Remove Tissue + Genotype effect

53. SAM False Discovery Rate delta ori.data perm.data difference FDR 0.1 13210 1210.34 11999.66 0.091623013 0.2 7903 183.95 7719.05 0.023275971 0.3 5462 49.18 5412.82 0.009004028 0.4 4036 18.31 4017.69 0.004536670 0.5 3024 8.49 3015.51 0.002807540 0.6 2285 3.85 2281.15 0.001684902 Both + and – SFPs since no reference comparison Need to compare with ESTs

54. Review Single Feature Polymorphisms (SFPs) can be used to identify recombination breakpoints, potential deletions, for eXtreme Array mapping, and haplotyping Expression analysis to identify QTL candidate genes and downstream responses that consider polymorphisms

55. RNADNA Universal Whole Genome Array Transcriptome Atlas Expression levels Tissues specificity Transcriptome Atlas Expression levels Tissues specificity Gene Discovery Gene model correction Non-coding/ micro-RNA Antisense transcription Gene Discovery Gene model correction Non-coding/ micro-RNA Antisense transcription Alternative Splicing Comparative Genome Hybridization (CGH) Insertion/Deletions Comparative Genome Hybridization (CGH) Insertion/Deletions Methylation Chromatin Immunoprecipitation ChIP chip Chromatin Immunoprecipitation ChIP chip Polymorphism SFPs Discovery/Genotyping Polymorphism SFPs Discovery/Genotyping ~19 bp tile,eliminate repeat regions both strands“good” binding oligos

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

57. ChipViewer: Mapping of transcriptional units of ORFeome From 2000v At1g09750 (MIPS) to the latest AGI At1g09750 2000 v Annotation (MIPS) The latest AGI Annotation

58. NaturalVariation.org Syngenta Hur-Song Chang Tong Zhu Syngenta Hur-Song Chang Tong Zhu University of Guelph, Canada Dave Wolyn University of Guelph, Canada Dave Wolyn Salk Jon Werner Todd Mockler Sarah Liljegren Ramlah Nehring Joanne Chory Detlef Weigel Joseph Ecker UC Davis Julin Maloof UC San Diego Charles Berry Scripps Sam Hazen Elizabeth Winzeler NaturalVariation.org Salk Jon Werner Todd Mockler Sarah Liljegren Ramlah Nehring Joanne Chory Detlef Weigel Joseph Ecker UC Davis Julin Maloof UC San Diego Charles Berry Scripps Sam Hazen Elizabeth Winzeler