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ChIP-seq and related applications

ChIP-seq and related applications. I dentifying regulatory functions in genomes. Chr5: 133,876,119 – 134,876,119. Genes. Transcription. Regulatory elements are not easily detected by sequence analysis Examine biochemical correlates of RE activity in cells/tissues:

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ChIP-seq and related applications

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  1. ChIP-seq and related applications

  2. Identifying regulatory functions in genomes Chr5: 133,876,119 – 134,876,119 Genes Transcription • Regulatory elements are not easily detected by sequence analysis • Examine biochemical correlates of RE activity in cells/tissues: • Chromatin Immunoprecipitation (ChIP-seq) • DNase-seq and FAIRE • Methylated DNA immunoprecipitation (MeDIP)

  3. Identifying regulatory functions in genomes Noonan and McCallion, Ann Rev Genomics Hum Genet 11:1 (2010)

  4. Biochemical indicators of regulatory function 1. TF binding 2. Histone modification • H3K27ac • H3K4me3 3. Chromatin modifiers & coactivators p300 MLL 4. DNA looping factors cohesin

  5. Regulatory functions are tissue/cell type/time point-specific From Visel et al. (2009) Nature 461:199

  6. Identifying regulatory functions in genomes Chr5: 133,876,119 – 134,876,119 Genes Transcription Histone mods TF binding

  7. Methods ChIP-seq Chromatin accessibility TFs Histone mods DNase FAIRE From Furey (2012) Nat Rev Genet 13:840

  8. ChIP-seq ChIP Peak call Signal Input Align reads to reference Use peaks of mapped reads to identify binding events PCR

  9. Calling peaks in ChIP-seq data ChIP Peak call Enrichment relative to control Input ChIP-seq is an enrichment method Requires a statistical framework for determining the significance of enrichment ChIP-seq ‘peaks’ are regions of enriched read density relative to an input control Input = sonicated chromatin collected prior to immunoprecipitation

  10. There are many ChIP-seq peak callers available Wilbanks and Facciotti PLoS ONE 5:e11471 (2010)

  11. Generating ChIP-seq peak profiles • Artifacts: • Repeats • PCR duplicates From Park (2009) Nat Rev Genet 10:669

  12. Assessing statistical significance Assume read distribution follows a Poissondistribution Many sites in input data will have some reads by chance Some sites will have many reads # of reads at a site (S) Empirical FDR: Call peaks in input (using ChIP as control) FDR = ratio of # of peaks of given enrichment value called in input vsChIP From Pepke et al (2009) Nat Meth 6:S22

  13. Assessing statistical significance Sequencing depth matters: # of reads at a site (S) From Park (2009) Nat Rev Genet 10:669

  14. ChIP-seq signal profiles vary depending on factor Transcription factors Pol II Histone mods From Park (2009) Nat Rev Genet 10:669

  15. Quantitative analysis of ChIP-seq signal profiles HeLa K562 HeLa Sites strongly marked in HeLa Sites strongly marked in both Clustering Signal at 20,000 bound sites ChIP-seq signal Sites strongly marked in K562

  16. ChIP-seq analysis workflow From Park (2009) Nat Rev Genet 10:669

  17. Interpreting ChIP-seq datasets • Requires some prior knowledge • TF function • Histone modification • Potential target genes • Exploit existing annotation • Promoter locations • Known binding sites • Known histone modification maps

  18. Example from PS1: CTCF and RAD21 (cohesin)

  19. CTCF and cohesin co-occupy many sites Promoters Insulators Enhancers From Kagey et al (2010) Nature 467:430

  20. Promoter Enhancers? CTCF: marks insulators and promoters RAD21 (cohesin): marks insulators, promoters and enhancers

  21. Discovering regulatory functions specific to a biological state Limb Brain Function? Assign enhancers to genes based on proximity (not ideal) GREAT: bejerano.stanford.edu/great/ Gene ontology annotation assigned to regulatory sequences

  22. TF motif elicitation from ChIP-seq data CTCF ~20,000 binding sites identified by ChIP: MEME suite: http://meme.nbcr.net/meme/ From Furey (2012) Nat Rev Genet 13:840

  23. Single TF binding events may not indicate regulatory function • Many TFs are present at high concentrations • in the nucleus • TF motifs are abundant in the genome • Single TF binding events may be incidental Enhancer-associated histone modification

  24. Mapping chromatin accessibility DNase I FAIRE From Furey (2012) Nat Rev Genet 13:840

  25. DNase I hypersensitivity identifies TF binding events From Furey (2012) Nat Rev Genet 13:840

  26. DNase I hypersensitivity identifies regulatory elements DNase I hypersensitive sites Song et al., Genome Res 21:1757 (2011)

  27. De novo TF motif discovery by DNase I hypersensitivity mapping In human ES cells: From Neph (2012) Nature 489:83

  28. De novo TF motif discovery by DNase I hypersensitivity mapping Across tissue types: From Neph (2012) Nature 489:83

  29. Summary • Relevant overview papers on ChIP-seq and DNase-seq posted on class wiki • Monday: Epigenetics and the histone code • Wednesday: Regulatory architecture of the genome

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