| dc.contributor.author | Boix, Carles A | |
| dc.contributor.author | James, Benjamin T | |
| dc.contributor.author | Park, Yongjin P | |
| dc.contributor.author | Meuleman, Wouter | |
| dc.contributor.author | Kellis, Manolis | |
| dc.date.accessioned | 2022-07-13T17:12:04Z | |
| dc.date.available | 2022-07-13T17:12:04Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/143720 | |
| dc.description.abstract | © 2021, The Author(s). 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 incomplete1–3. 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 traits4, 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. | en_US |
| dc.language.iso | en | |
| dc.publisher | Springer Science and Business Media LLC | en_US |
| dc.relation.isversionof | 10.1038/S41586-020-03145-Z | en_US |
| dc.rights | Creative Commons Attribution 4.0 International license | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | Nature | en_US |
| dc.title | Regulatory genomic circuitry of human disease loci by integrative epigenomics | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Boix, Carles A, James, Benjamin T, Park, Yongjin P, Meuleman, Wouter and Kellis, Manolis. 2021. "Regulatory genomic circuitry of human disease loci by integrative epigenomics." Nature, 590 (7845). | |
| dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | |
| dc.contributor.department | Massachusetts Institute of Technology. Computational and Systems Biology Program | |
| dc.relation.journal | Nature | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2022-07-13T17:05:34Z | |
| dspace.orderedauthors | Boix, CA; James, BT; Park, YP; Meuleman, W; Kellis, M | en_US |
| dspace.date.submission | 2022-07-13T17:05:44Z | |
| mit.journal.volume | 590 | en_US |
| mit.journal.issue | 7845 | en_US |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |