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Chromatin Features and Gene Expression

This article explores the relationship between chromatin marks and gene expression, specifically in transcription and splicing. It provides evidence for the connection between transcription and splicing, as well as predictions of transcription levels based on chromatin modifications. The study also discusses the impact of different RNA fractions and technologies on measuring transcription levels. The future work focuses on comparing different models and investigating additional features that may affect the expression of genes.

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Chromatin Features and Gene Expression

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  1. Chromatin Features and Gene Expression ENCODE AWG, March 2011 Zhiping, Gernstein, Guigo

  2. goals • 1 figure with panels in the main paper • Chromatin marks in transcription • Chromatin marks in splicing • Evidence for the relationship between transcription and splicing • Companion paper(s) • Specific calls. Gernstein, Zhiping, Guigo, everybody interested.

  3. messages • Expression (transcription) levels from chromatin status can be predicted quite accurately • Even with very simple linear models involving few modifictions • In same cases, quite impressively (?) • The model relating chromatin modifications with gene expression is broadly independent from cell line • H3K79me2 • H3K9ac • H3K27ac • H3K4me3

  4. messages • Chromatin status plays a role (maybe weak, but a role) in alternative splicing • Splicing is intimately coupled to transcription (can we quantify this?)

  5. Prediction transcription levels based on chromatin marks • Transcription levels can be measured • Different RNA fractions • polyA+, polyA-, nuclear, cytosol, whole cell • Different technologies • CAGE, RNASeq, ditags • Different cell lines • In principle, CAGE in nuclear polyA- should provide the most accurate read out of the action of transcription

  6. Future work • Gernstein/Zhiping model on exactly the same RNA datasets. Compare SVM with linear model • Train model in one cell line and test in all others • Subdivide gene classes according to regulation model • Protein coding genes vs long non coding RNAs • Investigate features that may impact the model • Levels of gene expression, GC content, etc • Investigate behaviour in novel TSS • CAGE clusters classified in TSS or post-processing sites (Timo Lassmann). • Can we use histone marks to identify novel promoters?

  7. Future work • Model expression as a function of TF binding. • How to relate TF binding with chromatin modifications with transcription/expresion.

  8. Promoter vs Enhancer A Basal Promoter Model B Enhancer Model C Chroperon Model p g e p g p g e p g chr1:173829000-173844000 chr6:28850000-28961000 chr2:220000000-220180000 1 2 • Identify promoter to promoter connections by ChIA-PET • Correlate chromatin marks in the distal promoter with gene expresion. • Cooperativity beetween the proximal and distal promoters trigering transcription 3 F Number of chromatin structures D 930 (15%) E BP e p g p g g p g p e chr17:80150000-80430000 C 3967 (64%) 1329 (21%) 1 Number of genes involved 2 1103 (6%) E 11778 (66%) C 3 BP 4973 (28%) 200 C 00 50 1M 10K 100K 10M

  9. Differential exon inclusion correlates with differential histone modifications EXON INCUSION BLUE: GM12878 > K562 RED: K562 > GM12878 DIFFERENTIAL H3k9ac OCCUPANCYacross the Acceptor Site GM12878-K562 “CONSTITUTIVE” EXON “CONSTITUTIVE” EXON ALTERNATIVE EXON

  10. Chromatin marks in alternative splicing

  11. Predicting exon inclusion from histone modifications

  12. Quantitative predictions: Linear models

  13. Future work • For each histone mark, identify the region across the exon that has major influence in • Exon specific models. Histone Modifiations may play a role only on the inclusion of a subset of exons

  14. Qualitative predictionsDecission Trees

  15. Evidence for co-transcriptional splicing

  16. Evidence for co-transriptional splicing • Compare COSI in polyA- nuclear and PolyA+ cytosol. Across all cell lines d e c

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