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

被引:734
作者
Ernst, Jason [1 ,2 ]
Kellis, Manolis [1 ,2 ]
机构
[1] MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USA
[2] MIT & Harvard, Broad Inst, Cambridge, MA USA
基金
美国国家科学基金会;
关键词
IDENTIFICATION; METHYLATIONS; ORGANIZATION; PREDICTION; VERTEBRATE; SIGNATURES; ENHANCERS; ELEMENTS; DISTINCT; BROWSER;
D O I
10.1038/nbt.1662
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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.
引用
收藏
页码:817 / U94
页数:11
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