TODO Reading List

  • Ziller, M. J., et al. (2015). “Dissecting neural differentiation regulatory networks through epigenetic footprinting.” Nature 518(7539): 355-359.
  • Polak, P., et al. (2015). “Cell-of-origin chromatin organization shapes the mutational landscape of cancer.” Nature 518(7539): 360-364.
  • Gjoneska, E., et al. (2015). “Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease.” Nature 518(7539): 365-369.

Not Related to Our Research (mostly methylation related)#

  • Farh, K. K., et al. (2015). “Genetic and epigenetic fine mapping of causal autoimmune disease variants.” Nature 518(7539): 337-343.
  • Delahaye, F., et al. (2014). “Sexual dimorphism in epigenomic responses of stem cells to extreme fetal growth.” Nat Commun 5: 5187. (DNA methylation only)
  • Wijetunga, N. A., et al. (2014). “The meta-epigenomic structure of purified human stem cell populations is defined at cis-regulatory sequences.” Nat Commun 5: 5195. (about DNA methylation, in the same cell type between different individuals)
  • Reynolds, L. M., et al. (2014). “Age-related variations in the methylome associated with gene expression in human monocytes and T cells.” Nat Commun 5: 5366. (DNA methylation, Age-related)
  • De Jager, P. L., et al. (2014). “Alzheimer’s disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci.” Nat Neurosci 17(9): 1156-1163. (DNA methylation related)
  • Lunnon, K., et al. (2014). “Methylomic profiling implicates cortical deregulation of ANK1 in Alzheimer’s disease.” Nat Neurosci 17(9): 1164-1170.

Notes from literature#

Gascard, P., et al. (2015). “Epigenetic and transcriptional determinants of the human breast.” Nat Commun 6: 6351.

sequence-specific DNA-binding proteins act in concert with epigenetic regulatory cofactors to orchestrate a process of cellular differentiation accompanied by ordered and directional lineage restriction.

the earliest stages of cellular differentiation where pluripotent potential is lost (currently most literature discuss about the differentiation (or in other words real cell line specific patterns) are focusing on STEM to 4 tissues)

reveals a striking asymmetry in epigenomic reprogramming between luminal and myoepithelial cell types (to find conditional patterns among different cell types, first we might start with choosing two close but different cell types as in this literature), so that we can find some conditional patterns and then check whether there are same/similar patterns among other cell types.

We observed an average of 1,211 differentially expressed (DE) genes (how to determine differentially expressed genes are important, since they have higher possibility to show conditional specific patterns, also should read a paper about differential gene expression in cancer cell lines, previously no differential of cancer related genes in K562 and GM12878 are observed)

Yao, L., et al. (2014). “Functional annotation of colon cancer risk SNPs.” Nat Commun 5: 5114.

certain genes and pathways, such as WNT, RAS, PI3K, TGF-B, p53 and mismatch repair proteins, are important in the initiation and progression of CRC

(position and/or signal intensity of histone peaks may be correlated with these cancer related genes)

the ENCODE Consortium has made major progress in defining hundreds of thousands of cell-type-specific distal enhancer regions. (The chromatin fingerprint of gene enhancer elements)

We chose to include 2 kb upstream and downstream of the start site as the promoter-proximal regions because several studies, as well as visual inspection of the ENCODE TF Chromatin Immunoprecipitation sequencing (ChIP-seq) tracks, have shown that transcription factors can bind on either side of a TSS (can also be used to justify why we used +- 2kb in the LDA project, lol)

A comparison of the H3K27Ac peaks from normal and tumour cells indicated that the patterns are very similar; in fact, B24,000 H3K27Ac peaks are in common in the normal and tumour cells.

Lowdon, R. F., et al. (2014). “Regulatory network decoded from epigenomes of surface ectoderm-derived cell types.” Nat Commun 5: 5442.

Epigenomic patterns have been broadly attributed to the three embryonic germ layers. (interesting notion: developmental origin influences epigenomes).

surface ectoderm; neural crest; mesoderm

differentially methylated regions enriched for enhancer- and promoter-associated histone modifications in SE-derived cells, and for binding motifs of transcription factors important in keratinocyte and mammary gland biology

embryonic origin and tissue environment may influence normal cellular epigenomic states (only DNA methylation is analysized here, so maybe histone marks will also show such kind of orgin-related pattern) To investigate how developmental origin and tissue environment contribute to cell type-specific epigenetic patterns

How current work to find cell-specific histone patter: To determine whether skin tissue also lacks a shared histone modification signature, we identified cell type-specific chromatin states from H3K4me1, H3K4me3 and H3k27ac chromatin immunoprecipitation sequencing (ChIP-seq) data for each skin cell type, as well as for breast, brain and blood samples. Among the 259,297 enhancer-associated H3K4me1 peaks and 55,859 promoter-associated H3K4me3 peaks identified in the above samples, only 997 H3K4me1 and 57 H3K4me3 peaks are present in all three skin cell types and absent in the other samples. (In other words, they simply find cell-specific histone peaks, so at least one thing we can do is to find frequent cell-specific histone combinations and then transitions. Peak calling may not be a good way, since different marks have different properties (narrow or broad)).

Seumois, G., et al. (2014). “Epigenomic analysis of primary human T cells reveals enhancers associated with TH2 memory cell differentiation and asthma susceptibility.” Nat Immunol 15(8): 777-788.

we identified enhancers with known and potential roles in the normal differentiation, and discovered disease-specific enhancers in T cells

Enhancers that gained the histone H3 Lys4 dimethyl (H3K4me2) mark during TH2 cell development showed the highest enrichment for asthma-associated single nucleotide polymorphisms

To identify cis-regulatory DNA regions differentially enriched for H3K4me2 in pairwise comparisons between cell types (differentially enriched regions; DERs),

Over 90% of the ~71,000 cell-specific DERs were localized to intergenic and intronic regions; only 4% were present in promoter regions (defined as transcription start site (TSS) ± 1 kilobase (kb)) of annotated RefSeq genes

all DERs outside promoter regions ‘putative differentiation-related enhancers’14,15 and classified them into three subgroups:

  • ~30,263 ‘TH2 enhancers’ that exhibited the strongest H3K4me2 gain or loss in memory T cells enriched for the TH2 cell subset;
  • ~17,483 ‘TH1 enhancers’ that exhibited the strongest H3K4me2 gain or loss in memory T cells enriched for the TH1 cell subset;
  • ~21,659 ‘shared memory enhancers’ that displayed equivalent H3K4me2 gain or loss in both TH2 and TH1 memory cells when compared to naive T cells.

(Need to check how the gain and loss, and differential enrichment are calculated)

Leung, D., et al. (2015). “Integrative analysis of haplotype-resolved epigenomes across human tissues.” Nature 518(7539): 350-354.