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

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Presentation on theme: "Epigenetics Xiaole Shirley Liu STAT115, STAT215, BIO298, BIST520."— Presentation transcript:

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

2 Epigenetics Heritable changes in gene function that occur without a change in the DNA sequence –How come not all the motif sites are bound by the factor? –How come TF binding only regulate some of the nearby genes?

3 Epigenetics The study of heritable (transgenerational) changes in gene activity that are not caused by changes in the DNA sequence The study of stable, long-term alterations in the transcriptional potential of a cell that are not necessarily heritable Functionally relevant changes to the genome that do not involve a change in the nucleotide sequence

4 In Human Nature vs nurture Zygotic twins: same DNA different epigenome North American Ice Storm of 1998

5 Agouti Mice and DNA Methylation

6 The Making of a Queen Larvae Queen Worker From Ting Wang, Wash U

7 Conrad Hal Waddington (1905–1975) Developmental biologist Paleontologist Geneticist Embryologist Philosopher Founder for systems biology Epigenetic Landscape

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

9 DNA Methylation Distribution in Mammalian Genomes In human somatic cells, 60%-80% of all CpGs (~1% of total DNA bases) are methylated –Most methylation is found in “repetitive” elements “CpG islands”, GC-rich regions that possess a high density of CpGs, remain methylation-free –The promoter regions of ~70% of genes have CpG islands From Ting Wang, Wash U

10 Two classes of DNA methyltransferases (DNMTs) Jones and Liang, 2009 Nature Review Genetics

11 Inheritance of DNA Methylation From Ting Wang, Wash U

12 DNA Methylation Detection Bisulfite sequencing –Unmethyl C  T –High resolution, quantitative, but expensive!

13 From Wei Li, Baylor

14 BS-seq Methylation Call Most regions are either mostly methylated or mostly unmethylated (dichotomy) Methylation level within a short distance is consistent ACGGGCTTACTTGCTTTCCTACGGGCTTACTTGCTTTCCTACGGGCTTACTTGCTTTCCTACGGGC TTACTTGC CGGGTTTATTTGCTTTTTTATGGGC TGGGTTTATTTGCTTTTTTATGGGC TGGGTTTATTTGCTTTCCTATGGGC CGGGCTTATTTGCTTTCCTATGGGC 3/50/5 60% methylated 0% methylated From Ting Wang, Wash U

15 DNA Methylation Controls Gene Expression Methylation at CpG islands often repress nearby gene expression Many highly expressed genes have CpG methylation on their exons Some genes could be imprinted, so maternal and paternal copies have different DNA methylation From Ting Wang, Wash U

16 DNA Methylation in Cancer Prevalent misregulation of DNA methylation in cancer: global hypomethylation and CpG island hypermethylation Methylation variable regions in cancer

17 DNA Demethylation Recently, another type of DNA methylation called hydroxyl methylation (hmC) is found hmC is an intermediate step between mC and C. TET family of proteins are important for DNA demethylation Mutation in TET is linked to many cancers

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

19 Nucleosome Occupancy & Histone Modification Influence Factor Binding TF

20 Histone Modifications Different modifications at different locations by different enzymes

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

22 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 promoter mark: H3K27me3 Repressive mark for DNA methylation: H3K9me3

23 lncRNA Identification H3K4me3 active promoters H3K36me3 transcription elongation Guttman et al, Nat 2009 23

24 24

25 25

26 Nucleosome Occupancy & Histone Modification Influence Factor Binding Antibody for MNase digest TF

27 Combine Tags From All ChIP-Seq

28 Extend Tags 3’ to 146 nt Check Tag Count Across Genome

29 Take the middle 73 nt

30 Nucleosome Stabilization-Destabilization (NSD) Score Condition 1 Condition 2 Use H3K4me2 / H3K27ac Nucleosome Dynamics to Infer TF Binding Events 30 /ac He et al, Nat Genet, 2010; Meyer et al, Bioinfo 2011

31 Condition-Specific Binding, Epigenetics and Gene Expression 31 GenesTF1TF2TF3 Epigenetics 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? C1 C2 C1 C2

32 Predict Driving TFs and Bindings for Gut Differentiation 32

33 Identify Major TF Modules Regulating Gut Differentiation and Function Nucleosome dynamics now applied to hematopoiesis and cancer cell reprogramming Verzi et al, Dev Cell, 2010 33 GATA6 Cdx2 Embryonic and organ development genes HNF4 Metabolic and digestive genes Cdx2

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

35 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

36 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

37 TF Network from DNase Footprint 37

38 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 38 GAT ACA CTA TGT L C R

39 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 39 GAT ACA CTA TGT CAGATA0.004 CAGATC0.004 … ACTTAC1.225 ACTTGT1.273 L C R

40 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 40

41 Using DNaseI “Footprint” to Predict Novel TF Motifs 41 He et al, Nat Meth 2013

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

43 HiC In situ HiC has excellent resolution Domains conserved between cells and even species 43

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

45 Epigenetics and Chromatin 45

46 Transcription and Epigenetic Regulation Stem cell differentiation Aging brain Cancer


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