Regulatory genomic circuitry of human disease loci by integrative epigenomics

被引:218
作者
Boix, Carles A. [1 ,2 ,3 ]
James, Benjamin T. [1 ,2 ]
Park, Yongjin P. [1 ,2 ,4 ]
Meuleman, Wouter [5 ]
Kellis, Manolis [1 ,2 ]
机构
[1] MIT, Comp Sci & Artificial Intelligence Lab, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[2] Broad Inst MIT & Harvard, Cambridge, MA 02142 USA
[3] MIT, Computat & Syst Biol Program, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[4] Univ British Columbia, Dept Pathol & Lab Med, Vancouver, BC, Canada
[5] Altius Inst Biomed Sci, Seattle, WA USA
基金
美国国家卫生研究院;
关键词
WIDE ASSOCIATION; PARTITIONING HERITABILITY; SYSTEMATIC ANNOTATION; CHROMATIN STATES; DISCOVERY; EXPRESSION; VARIANTS; HEART;
D O I
10.1038/s41586-020-03145-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Annotating the molecular basis of human disease remains an unsolved challenge, as 93% of disease loci are non-coding and gene-regulatory annotations are highly incomplete(1-3). Here we present EpiMap, a compendium comprising 10,000 epigenomic maps across 800 samples, which we used to define chromatin states, high-resolution enhancers, enhancer modules, upstream regulators and downstream target genes. We used this resource to annotate 30,000 genetic loci that were associated with 540 traits(4), predicting trait-relevant tissues, putative causal nucleotide variants in enriched tissue enhancers and candidate tissue-specific target genes for each. We partitioned multifactorial traits into tissue-specific contributing factors with distinct functional enrichments and disease comorbidity patterns, and revealed both single-factor monotropic and multifactor pleiotropic loci. Top-scoring loci frequently had multiple predicted driver variants, converging through multiple enhancers with a common target gene, multiple genes in common tissues, or multiple genes and multiple tissues, indicating extensive pleiotropy. Our results demonstrate the importance of dense, rich, high-resolution epigenomic annotations for the investigation of complex traits.
引用
收藏
页码:300 / 307
页数:28
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