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Talk Outline

Identification and Genotyping of Single Feature Polymorphisms in Complex Genomes Justin Borevitz University of Chicago naturalvariation.org. Talk Outline. Intro/QTL mapping Single Feature Polymorphisms (SFPs) Potential deletions Bulk Segregant Mapping Extreme Array Mapping

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Talk Outline

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  1. Identification and Genotyping ofSingle Feature Polymorphismsin Complex GenomesJustin BorevitzUniversity of Chicagonaturalvariation.org

  2. Talk Outline • Intro/QTL mapping • Single Feature Polymorphisms (SFPs) • Potential deletions • Bulk Segregant Mapping • Extreme Array Mapping • Transcriptional profiling • for QTL candidate genes

  3. Quantitative Trait Loci EPI1 EPI2

  4. Marker Mb SM184 5.50 SM50 5.87 SM35 6.34 SM106 7.01 G2395 7.30 SNP377 7.44 CER45 7.60 MAT7787 7.79 MSAT7964 7.96 TH1 8.13 8.29 SEQ8298 8.65 SM40 SNP65 9.32 mm Near-Isogenic Lines for LIGHT1 Ler / Cvi #3 RVE7 GI Ler 81N-J 17A-A/J 114 124 189 Line 194 6 2 4 3 3 3 Plants 3 5.8 5.8 5.1 5.9 5.7 5.8 Phenotype 5.0

  5. 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

  6. Potential Deletions

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

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

  9. Effect of SNP position 340 Candidate Polymorphisms False negative True Positive

  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. LIGHT1NIL

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

  14. Het Fast Neutron deletions FKF1 80kb deletion CHR1 cry2 10kb deletion CHR1

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

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

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

  18. arythmic11 Mapping confirmed Sam Hazen

  19. arythmic21 Allelic to arr90 Sam Hazen arythmic90 Gene cloned Sam Hazen

  20. stamenstay Ler Sarah Liljegren Mapping confirmed

  21. ein6een double mutant Ramlah Nehring Mapping confirmed

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

  23. Chromosome 2 16 12 RED2 QTL LOD 8 4 0 0 20 40 60 80 100 cM RED2 QTL 12cM Composite Interval Mapping eXtreme Array Mapping LOD 15 tallest RILs pooled vs 15 shortest RILs pooled Allele frequencies determined by SFP genotyping. Thresholds set by simulations Red light QTL RED2 from 100 Kas/ Col RILs

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

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

  26. 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

  27. 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

  28. 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

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

  30. differences may be due to expression or hybridization

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

  32. 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)

  33. Look at some plots raw data

  34. Remove probe effect

  35. Remove tissue effect

  36. Remove Genotype effect

  37. 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

  38. 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

  39. Universal Whole Genome Array RNA DNA Chromatin Immunoprecipitation ChIP chip Gene Discovery Gene model correction Non-coding/ micro-RNA Antisense transcription Methylation Transcriptome Atlas Expression levels Tissues specificity Polymorphism SFPs Discovery/Genotyping Comparative Genome Hybridization (CGH) Insertion/Deletions Alternative Splicing ~35 bp tile, non-repetitive regions, “good” binding oligos, evenly spaced

  40. 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 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 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

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