Epigenetics Continued Xiaole Shirley Liu STAT115, STAT215, BIO298, BIST520

Components DNA-methylation Nucleosome position Histone modifications Chromatin accessibility Higher order chromatin interactions Analogy

Nucleosome Occupancy & Histone Modification Influence Factor Binding MNase-seq Zentner & Henikoff, Nat Rev Genet 2014

MNase-seq Analysis Park, Nat Rev Genet 2009

MNase-seq Analysis Park, Nat Rev Genet 2009

Factors Influencing Nucleosome Positioning Rotational positioning from sequence Statistical positioning from trans-factors (e.g. TF binding) Break Jiang & Pugh, Nat Rev Genet 2009

Components DNA-methylation Nucleosome position Histone modifications Chromatin accessibility Higher order chromatin interactions Analogy

Mapping Histone Modifications Histone tails Histone mark ChIP-seq Park, Nat Rev Genet 2009

Histone Modifications Different modifications at different locations by different enzymes

Histone Modifications in Relation to Gene Transcription From Ting Wang, Wash U

Histone Modifications Gene body mark: H3K36me3, H3K79me3 Active promoter (TSS) mark: H3K4me3 Active enhancer (TF binding) mark: H3K4me1, H3K27ac Both enhancers and promoters: H3K4me2, H3/H4ac, H2AZ Repressive mark: H3K27me3, H3K9me3 Annotate / segment the genome based on histone marks

lncRNA Identification H3K4me3 active promoters H3K36me3 transcription elongation Guttman et al, Nat 2009

Nucleosome Occupancy & Histone Modification Influence Factor Binding Antibody for MNase digest TF Last year, Keji Zhao’s group published a pioneering studying using Solexa to conduct ChIP-seq of 21 histone marks in human CD4 T cells. In the study, chromatin was digested with MNase and mononucleosomes carrying specific histone mark was enriched using IP. Solexa sequencing was used to read 25-mer from either end of the nucleosomal DNA. Although an unprecedented 185 million nucleosome tags were sequenced, no analysis to-date aims to use them to study nucleosome position at specific locations in the genome.

Combine Tags From All ChIP-Seq So we went about looking at the data more. For each specific region, we combined all the tags from all marks, because they are all nucleosome ends.

Extend Tags 3’ to 146 nt Check Tag Count Across Genome Then at each position, we counted the number of extended tags that landed there. The sequenced nucleosomes were not always 150bp. To better locate the center of positioned nuclesomes, we took the center 75 bp of each extended tag.

Take the middle 73 nt

Use H3K4me2 / H3K27ac Nucleosome Dynamics to Infer TF Binding Events Nucleosome Stabilization-Destabilization (NSD) Score Condition 1 Condition 2 In a proof of concept study we collaborated with Myles Brown’s lab, and found that very often, a cell will anticipate the stimulus it might get, and mark the potential TF binding sites before the TF is stably bound. Upon…. We devised a simple scoring function to measure how much the middle down vs flanking up, and we call it NSD. Positive NSD is nucleosome depletion, negative NSD is nucleosome moving back, NSD of 0 means no nucleosome moving. He et al, Nat Genet, 2010; Meyer et al, Bioinfo 2011

Condition-Specific Binding, Epigenetics and Gene Expression Condition-specific TF bindings are associated with epigenetic signatures Can we use the epigenetic profile and TF motif analysis to simultaneous guess the binding of many TFs together? Genes TF1 TF2 TF3 Epigenetics

Predict Driving TFs and Bindings for Gut Differentiation

Identify Major TF Modules Regulating Gut Differentiation and Function GATA6 Cdx2 Embryonic and organ development genes HNF4 Metabolic and digestive genes Cdx2 Nucleosome dynamics now applied to hematopoiesis and cancer cell reprogramming Break Verzi et al, Dev Cell, 2010

Components DNA-methylation Nucleosome position and histone modifications Chromatin accessibility Higher order chromatin interactions Analogy

DNase Hypersensitive (HS) Mapping DNase randomly cuts genome (more often in open chromatin region) Select short fragments (two nearby cuts) to sequence Map to active promoters and enhancers Ling et al, MCB 2010

DHS Peaks Capture Most TF Binding Sites Motif occurrence in the DHS peaks suggest TF binding Quantitative signal strength also suggest binding stability Thurman et al, Nat 2012

TF Network from DNase Footprint

DnaseI Cleavage vs Footprint Footprint occupancy score: FOS = (C + 1)/L + (C + 1)/R Smaller FOS value better footprint, for predicting base resolution TF binding L C R GAT ACA CTA TGT

DnaseI Cleavage vs Footprint Footprint occupancy score: FOS = (C + 1)/L + (C + 1)/R Smaller FOS value better footprint, for predicting base resolution TF binding Intrinsic DNase cutting bias could have 300-fold difference, creating fake footprints L C R GAT ACA CTA TGT CAGATA 0.004 CAGATC 0.004 … ACTTAC 1.225 ACTTGT 1.273

Using DNaseI “Footprint” to Predict TF Binding Using base-pair resolution cleavage pattern (“footprint”) hurts TF binding prediction when it is similar to intrinsic DNaseI cutting bias

Using DNaseI “Footprint” to Predict Novel TF Motifs Break He et al, Nat Meth 2013

Components DNA-methylation Nucleosome position and histone modifications Chromatin accessibility Higher order chromatin interactions Analogy

HiC In situ HiC has excellent resolution Domains conserved between cells and even species

HiC Loops are condition-specific Assign binding to genes Convergent CTCF at domain anchors CTCF as insulators

Epigenetics and Chromatin

Transcription and Epigenetic Regulation Stem cell differentiation Aging brain Cancer