Whole genome transcriptome variation in Arabidopsis thaliana Xu Zhang Borevitz Lab

1. Whole genome transcriptome variation in Arabidopsis thaliana Xu Zhang Borevitz Lab

2. Arabidopsis thaliana have been adapted to highly variable environments

3. Transcription and splicing Chromosomal DNA Exon 1 Exon 3 Exon 2 Intron 1 Intron 2 Transcription Nuclear RNA RNA splicing Messenger RNA Exon 1 Exon 2 Exon 3 Exon 1 Exon 3

4. Whole genome tiling array • High density and resolution: 1.6M unique probes at 35bp spacing • Without bias toward known transcripts Genetic hybridization polymorphisms could affect the estimation of gene expression

5. The experiment Col♀ x Col♂ Van ♀ x Van ♂ Van ♀ x Col ♂ Col ♀ x Van ♂ • parental strains and reciprocal F1 hybrids • mRNA from total RNA; genomic DNA

6. Double-stranded random labeling AAAAA Random reverse transcription AAAAA Double-stranded cDNA Random priming

7. Outlines • Sequence polymorphisms • Gene expression variation • Splicing variation • A functional network of differentially spliced genes • HMM for a de novo transcription profiling

8. Outlines • Sequence polymorphisms • Gene expression variation • Splicing variation • A functional network of differentially spliced genes • HMM for a de novo transcription profiling

9. Single Feature Polymorphisms and indels SFP SFP SFPs deletion or duplication in Van

10. Sequence polymorphisms SPFs and indels (>200bp) were removed before gene expression analysis

11. Deletions vs duplications

12. Distribution of indels along chromosomes

13. Outlines • Sequence polymorphisms • Gene expression variation • Splicing variation • A functional network of differentially spliced genes • HMM for a de novo transcription profiling

14. Additive, dominant and maternal effects of gene expression

15. maternal dominant additive Col F1c intensity F1v Van genotypes The linear model Gene probe Intensity ~ additive + dominant + maternal + ε

16. Gene expression variation between genotypes

17. The pattern of gene expression inheritance Mean gene intensity paternal Maternal Col dominant over dominant F1v dominant F1c dominant Van dominant Col Van F1v F1c

18. The pattern of gene expression inheritance

19. Enrichment in GO functional categories GO enrichment for additive dominant maternal effect genes Defense response genes are highly expressed in F1 hybrid lines, while many growth related pathway are down-regulated

20. Outlines • Sequence polymorphisms • Gene expression variation • Splicing variation • A functional network of differentially spliced genes • HMM for a de novo transcription profiling

21. Default expression status of exon and intron • Exons: correction for gene expression corrected by gene mean corrected by a gene median splicing index (Meanexon/Meangene) • Introns: direct comparison Exon/intron probe Intensity ~ additive + dominant + maternal + ε

22. Differential exon splicing Exon probe Intensity ~ additive + dominant + maternal + ε

23. Differential intron splicing Intron probe Intensity ~ additive + dominant + maternal + ε

24. Differential exon splicing is predominantly additive in F1 hybrids

25. Some dominant effect in differential intron splicing in F1 hybrids

26. Comparison for enrichment in known alternatively spliced exons

27. AT1G07350 AT1G80960 AT1G21350 AT1G51350 AT1G29120 AT1G34180 AT1G76170 Experimental determined FDR for differential splicing

28. Outlines • Sequence polymorphisms • Gene expression variation • Splicing variation • A functional network of differentially spliced genes • HMM for a de novo transcription profiling

29. Enrichment of differentially spliced genes in chloroplast thylakoid enrichment of differentially spliced genes

30. Chloroplast thylakoid

31. Photosynthesis related genes Differrentially spliced genes which are located in chloroplast thylakoid AT5G38660 APE1 (Acclimation of Photosynthesis to Environment) mutant has altered acclimation responses

32. Splicing regulator tend to be differentially spliced

33. Outlines • Sequence polymorphisms • Gene expression variation • Splicing variation • A functional network of differentially spliced genes • HMM for a de novo transcription profiling

34. Generalized tiling array HMM (by Jake Byrnes) • 3-state HMM • Discrete distribution for emission probability • Transition probability counts for probe spacing • Baum-Welch parameter estimation

35. An example of HMM detected segments

36. A nice model also needs better array • Array density is not enough to distinguish exon/intron boundaries • Probe quality

37. Differential segments >=3 continuous probes with posterior probability >0.99. Differentially expressed genes annotated genes for which ≥33% of their probes reside within the observed differential segments. Differentially spliced genes annotated genes for which <33% of probes resided within the differential segment, or annotated genes containing ≥2 differential segments with different states. Novel gene boundaries differential segments with >= 5 probes extending beyond annotated gene boundary Novel transcripts differential segments with >= 5 probes and outside any annotated gene boundary.

38. Length distribution of segments called by HMM

39. Comparison of annotation-based analysis and HMM

40. Comparison of annotation-based analysis and HMM

41. Acknowledgements Justin Borevitz Yan Li Christos Noutsos Geoff Morris Andy Cal Jake Byrnes Josh Rest