Ernst J, Kellis M.ChromHMM: automating chromatin-state discovery and characterization. Nat Methods 9:215-216

1] Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA. [3] Department of Biological Chemistry, University of California Los Angeles, Los Angeles, California, USA.
Nature Methods (Impact Factor: 32.07). 02/2012; 9(3):215-6. DOI: 10.1038/nmeth.1906
Source: PubMed


To the Editor:
Chromatin-state annotation using combinations of chromatin modification patterns has emerged as a powerful approach for discovering regulatory regions and their cell type–specific activity patterns and for interpreting disease-association studies1, 2, 3, 4, 5. However, the computational challenge of learning chromatin-state models from large numbers of chromatin modification datasets in multiple cell types still requires extensive bioinformatics expertise. To address this challenge, we developed ChromHMM, an automated computational system for learning chromatin states, characterizing their biological functions and correlations with large-scale functional datasets and visualizing the resulting genome-wide maps of chromatin-state annotations.

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    • "The input information used to segment the genome into different chromatin states was that derived from the three cytosine modifications, the 13 histone marks, and the insulator protein CTCF—which has been previously shown to define a particular chromatin state per se (Ernst and Kellis, 2010). We used the ChromHmm software (Ernst and Kellis, 2012; v1.03) to define a 20-chromatin- states model consistent with prior knowledge regarding the function of these features (Figure S3). Only intervals with a probability higher than 0.95 were considered for further analysis. "
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    ABSTRACT: Epigenetic communication through histone and cytosine modifications is essential for gene regulation and cell identity. Here, we propose a framework that is based on a chromatin communication model to get insight on the function of epigenetic modifications in ESCs. The epigenetic communication network was inferred from genome-wide location data plus extensive manual annotation. Notably, we found that 5-hydroxymethylcytosine (5hmC) is the most-influential hub of this network, connecting DNA demethylation to nucleosome remodeling complexes and to key transcription factors of pluripotency. Moreover, an evolutionary analysis revealed a central role of 5hmC in the co-evolution of chromatin-related proteins. Further analysis of regions where 5hmC co-localizes with specific interactors shows that each interaction points to chromatin remodeling, stemness, differentiation, or metabolism. Our results highlight the importance of cytosine modifications in the epigenetic communication of ESCs.
    Full-text · Article · Jan 2016 · Cell Reports
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    • "The two CpGs highlighted are located in intron 1 which is an active regulatory region according to ENCODE[27]. This region is a 4 kb promoter-associated region surrounding the transcription start site (TSS) of CPT1A in the HepG2 cell line ( " Active TSS " according to chromHMM)[28]. There are several transcription factor binding sites near our highlighted CpGs. "
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    ABSTRACT: In this study, we conducted an epigenome-wide association study of metabolic syndrome (MetS) among 846 participants of European descent in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN). DNA was isolated from CD4+ T cells and methylation at ~470,000 cytosine-phosphate-guanine dinucleotide (CpG) pairs was assayed using the Illumina Infinium HumanMethylation450 BeadChip. We modeled the percentage methylation at individual CpGs as a function of MetS using linear mixed models. A Bonferroni-corrected P-value of 1.1 x 10-7 was considered significant. Methylation at two CpG sites in CPT1A on chromosome 11 was significantly associated with MetS (P for cg00574958 = 2.6x10-14 and P for cg17058475 = 1.2x10-9). Significant associations were replicated in both European and African ancestry participants of the Bogalusa Heart Study. Our findings suggest that methylation in CPT1A is a promising epigenetic marker for MetS risk which could become useful as a treatment target in the future.
    Full-text · Article · Jan 2016 · PLoS ONE
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    • "mouse limb (Visel et al. 2007); and TSAR.1586, expression in e14.5 brain (Shen et al. 2012). Using ENCODE data, chromHMM (Ernst and Kellis 2012) predicted that eight others are also enhancers. While both Lhx1 and Mrm1 are widely expressed, the LIM-homeodomain transcription factors are important for mammalspecific forebrain development and many of them are expressed together in specific subregions (Abellan et al. 2010). "
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    ABSTRACT: Mammals have evolved remarkably different sensory, reproductive, metabolic, and skeletal systems. To explore the genetic basis for these differences, we developed a comparative genomics approach to scan whole-genome multiple sequence alignments to identify regions that evolved rapidly in an ancestral lineage but are conserved within extant species. This pattern suggests that ancestral changes in function were maintained in descendants. After applying this test to therian mammals, we identified 4797 accelerated regions, many of which are non-coding and located near developmental transcription factors. We then used mouse transgenic reporter assays to test if non-coding accelerated regions are enhancers and to determine how therian-specific substitutions affect their activity in vivo. We discovered enhancers with expression specific to the therian version in brain regions involved in the hormonal control of milk ejection, uterine contractions, blood pressure, temperature, and visual processing. This work underscores the idea that changes in developmental gene expression are important for mammalian evolution, and it pinpoints candidate genes for unique aspects of mammalian biology.
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