1 / 29

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:

viveka
Télécharger la présentation

ChIP-seq and related applications

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related