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Reading circle of Epigenome Roadmap doi:10.1038/nature14248
Roadmap Epigenomics Consortium et. al. Integrative analysis of 111 reference human epigenomesItoshi NIKAIDO, Ph.D. <[email protected]> Unit Leader, Bioinformatics Research Unit RIKEN Advanced Center for Computer and Communication http://bit.accc.riken.jp/
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Main figure: 9 Extended Data Figure: 12 Supplementary Figure: 13
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1. Reference epigenome mapping across tissues and cell types 2. Chromatin states, DNA methylation and DNA accessibility 3. Epigenomic differences during lineage specification 4. Most variable states and distinct chromosomal domains 5. Relationships between marks and lineages 6. Imputation and completion of epigenomic data sets 7. Enhancer modules and their putative regulators 8. Impact of DNA sequence and genetic variation 9. Trait-associated variants enrich in tissue-specific marks 10. Discussion
HeadlinesIntegrative analysis of 111 reference human epigenomes
![Page 4: Reading circle of Epigenome Roadmap: Roadmap Epigenomics Consortium et. al. Integrative analysis of 111 reference human epigenomes](https://reader035.fdocuments.net/reader035/viewer/2022062406/55a51e441a28ab5e5a8b48c3/html5/thumbnails/4.jpg)
1. Histone mark combinations show distinct levels of DNA methylation and accessibility, and predict differences in RNA expression levels that are not reflected in either accessibility or methylation.
2. Megabase-scale regions with distinct epigenomic signatures show strong differences in activity, gene density and nuclear lamina associations, suggesting distinct chromosomal domains.
3. Approximately 5% of each reference epigenome shows enhancer and promoter signatures, which are twofold enriched for evolutionarily conserved non-exonic elements on average.
4. Epigenomic data sets can be imputed at high resolution from existing data, completing missing marks in additional cell types, and providing a more robust signal even for observed data sets.
5. Dynamics of epigenomic marks in their relevant chromatin states allow a data-driven approach to learn biologically meaningful relationships between cell types, tissues and lineages.
6. Enhancers with coordinated activity patterns across tissues are enriched for common gene functions and human phenotypes, suggesting that they represent coordinately regulated modules.
7. Regulatory motifs are enriched in tissue-specific enhancers, enhancer modules and DNA accessibility footprints, providing an important resource for gene-regulatory studies.
8. Genetic variants associated with diverse traits show epigenomic enrichments in trait-relevant tissues, providing an important resource for understanding the molecular basis of human disease.
Summary: 8 findingsIntegrative analysis of 111 reference human epigenomes
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Pegs and guy-rope modelFigure 1Tissues and cell types profiled in the Roadmap Epigenomics
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127 reference epigenome = 111 epigenome roadmap + 26 ENCODE ! 2,805 genome-wide data sets = 1,821 histone modification data sets 360 DNA accessibility data sets 277 DNA methylation data sets 166 RNA-seq !Chromatin immunoprecipitation (ChIP) DNA digestion by DNase I (DNase) Bisulfite treatment Methylated DNA immunoprecipitation (MeDIP) Methylation-sensitive restriction enzyme digestion (MRE) RNA profiling
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Figure 2Data sets available for each reference epigenome.
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What is chomatin states?Prediction of 51 chromatin states from epigenome data set
• 51 chromatin states •11 Promoter states
•high/mid/low expression, repressed, high/mid/low GC, … • 17 Transcribed States
•5’ proximal high/mid expression, open chromatin, TF binding, spliced exon,…
• 11 Active intergenic states • strong/weaker/distal/proximal enhancer, CTCF, H2AZ,…
• 6 Repressed states • unmappble, A/T rich, ERVL, heterochromatin…
• 6 Repetitive states • (CA)n, (TG)n, L1/LTR, Satellite repeats
http://www.nature.com/nbt/journal/v28/n8/extref/nbt.1662-S1.pdf
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What is chomatin states?Prediction of 51 chromatin states from epigenome data set
Epigenome Marks (observed)
Chromatin States (Predicted)
http://www.nature.com/nbt/journal/v28/n8/fig_tab/nbt.1662_F1.html
Circles are 200 bp windows of chromatin c.
Pt-1 Pt Pt+1
Vt-1 Vt-1 Vt+1
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What is chomatin states?ChromHMM: automating chromatin-state discovery and characterization
http://www.nature.com/nbt/journal/v28/n8/extref/nbt.1662-S1.pdf
http://www.nature.com/nbt/journal/v28/n8/full/nbt.1662.html#supplementary-information
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Figure 3Epigenomic information across tissues and marks
Red: constitutive promoter Yellow: active enhancer
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Figure 4a-eChromatin states and DNA methylation dynamics
15 states model: 5 histone modification, 127 epigenomes
1. High expression = low methylation + high accessibility 2. Low expression = high methylation + low accessibility 3. Enhancer = intermediate methylation + intermediate accessibility
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Figure 4a-eChromatin states and DNA methylation dynamics
• TxFlnk, Enh, TssBiv and BivFlnk states show similar distributions of DNA accessibility but different distributions of gene expression and DNA methylation.
• Enh and PeprPC states show similar distributions of DNA methylation but different distributions of DNA accessibility
• etc…
Complex relationship: active or repressive region << chromatin states
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Figure 4gChromatin states and DNA methylation dynamics
Methylation, 95 epigenomes
• TssAFlnk: unmethylated in differentiated cells and tissues • Enh: Highly methylated in ES and iPS • EnhBiv: broad distribution in ES and iPS (cell-to-cell variability) • PeprPC: varying methylation levels among cell and tissues
DNA methylation changes during ESC differentiation
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Figure 5abCell-type differences in chromatin states
constitutive
Cell specific
• HSC: ↑TxWk, ↓TssA/TssBiv • ESC: ↑TssBiv, ↓PeprPCWk (restriction of
H2K27me3-establishing Polycomb at promoter) • IMR90: ↑Het/ReprPC/EhnG, ↓Quies
Variability of chromatin states Chromatin state frequency
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Figure 5cdCell-type differences in chromatin states
Transition of chromatin state Chromatin states at a larger resolution (2Mb)
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Figure 6Epigenome relationships
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Figure 7Regulatory modules from epigenome dynamics
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Figure 8Linking regulators to target tissues and cell types
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Figure 9Linking regulators to target tissues and cell types
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1. Reference epigenome mapping across tissues and cell types 2. Chromatin states, DNA methylation and DNA accessibility 3. Epigenomic differences during lineage specification 4. Most variable states and distinct chromosomal domains 5. Relationships between marks and lineages 6. Imputation and completion of epigenomic data sets 7. Enhancer modules and their putative regulators 8. Impact of DNA sequence and genetic variation 9. Trait-associated variants enrich in tissue-specific marks 10. Discussion
HeadlinesIntegrative analysis of 111 reference human epigenomes
![Page 22: Reading circle of Epigenome Roadmap: Roadmap Epigenomics Consortium et. al. Integrative analysis of 111 reference human epigenomes](https://reader035.fdocuments.net/reader035/viewer/2022062406/55a51e441a28ab5e5a8b48c3/html5/thumbnails/22.jpg)
1. Histone mark combinations show distinct levels of DNA methylation and accessibility, and predict differences in RNA expression levels that are not reflected in either accessibility or methylation.
2. Megabase-scale regions with distinct epigenomic signatures show strong differences in activity, gene density and nuclear lamina associations, suggesting distinct chromosomal domains.
3. Approximately 5% of each reference epigenome shows enhancer and promoter signatures, which are twofold enriched for evolutionarily conserved non-exonic elements on average.
4. Epigenomic data sets can be imputed at high resolution from existing data, completing missing marks in additional cell types, and providing a more robust signal even for observed data sets.
5. Dynamics of epigenomic marks in their relevant chromatin states allow a data-driven approach to learn biologically meaningful relationships between cell types, tissues and lineages.
6. Enhancers with coordinated activity patterns across tissues are enriched for common gene functions and human phenotypes, suggesting that they represent coordinately regulated modules.
7. Regulatory motifs are enriched in tissue-specific enhancers, enhancer modules and DNA accessibility footprints, providing an important resource for gene-regulatory studies.
8. Genetic variants associated with diverse traits show epigenomic enrichments in trait-relevant tissues, providing an important resource for understanding the molecular basis of human disease.
Summary: 8 findingsIntegrative analysis of 111 reference human epigenomes