Discovery and characterization of chromatin states for systematic annotation of the human genome

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A plethora of epigenetic modifications have been described in the human genome and shown to play diverse roles in gene regulation, cellular differentiation and the onset of disease. Although individual modifications have been linked to the activity levels of various genetic functional elements, their combinatorial patterns are still unresolved and their potential for systematic de novo genome annotation remains untapped. Here, we use a multivariate Hidden Markov Model to reveal 'chromatin states' in human T cells, based on recurrent and spatially coherent combinations of chromatin marks. We define 51 distinct chromatin states, including promoter-associated, transcription-associated, active intergenic, large-scale repressed and repeat-associated states. Each chromatin state shows specific enrichments in functional annotations, sequence motifs and specific experimentally observed characteristics, suggesting distinct biological roles. This approach provides a complementary functional annotation of the human genome that reveals the genome-wide locations of diverse classes of epigenetic function.

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Figure 1: Example of chromatin state annotation.
Figure 2: Chromatin state definition and functional interpretation.
Figure 3: Promoter and transcribed chromatin states show distinct functional and positional enrichments.
Figure 4: SNP and GWAS enrichments for chromatin states.
Figure 5: Discovery power of chromatin states for genome annotation.
Figure 6: Recovery of chromatin states with subsets of marks.


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We thank P. Kheradpour for regulatory motif instances and M.F. Lin for predicted new exons. We thank M. Garber, A. Siepel, K. Lindblad-Toh, and E. Lander for use of comparative information on 29 mammals. We thank B. Bernstein, N. Shoresh, C. Epstein and T. Mikkelsen for helpful discussions. We thank L. Goff, C. Bristow, R. Sealfon and all members of the MIT CompBio Group for comments, feedback and support. This material is based upon work supported by the National Science Foundation under award no. 0905968 and funding from the US National Human Genome Research Institute (NHGRI) under awards U54-HG004570 and RC1-HG005334.

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J.E. and M.K. developed the method, analyzed results and wrote the paper.

Correspondence to Manolis Kellis.

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The authors declare no competing financial interests.

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Supplementary Tables 1 and 2, Supplementary Notes and Supplementary Figs. 1–41 (PDF 5184 kb)

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