Improved regulatory element prediction based on tissue-specific local epigenomic signatures
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037,, Bioinformatics Program, University of California, San Diego, La Jolla, CA 92093,
- Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA 92093,
- Lawrence Berkeley National Laboratory, Berkeley, CA 94720,
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037,
- Institute for Human Genetics, University of California, San Francisco, CA 94143,, Department of Neurology, University of California, San Francisco, CA 94143,
- Lawrence Berkeley National Laboratory, Berkeley, CA 94720,, US Department of Energy Joint Genome Institute, Walnut Creek, CA 94598,, School of Natural Sciences, University of California, Merced, CA 95343,
- Lawrence Berkeley National Laboratory, Berkeley, CA 94720,, US Department of Energy Joint Genome Institute, Walnut Creek, CA 94598,
- Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA 92093,, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093,
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037,, Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA 92037
Accurate enhancer identification is critical for understanding the spatiotemporal transcriptional regulation during development as well as the functional impact of disease-related noncoding genetic variants. Computational methods have been developed to predict the genomic locations of active enhancers based on histone modifications, but the accuracy and resolution of these methods remain limited. Here, we present an algorithm, regulator y element prediction based on tissue-specific local epigenetic marks (REPTILE), which integrates histone modification and whole-genome cytosine DNA methylation profiles to identify the precise location of enhancers. We tested the ability of REPTILE to identify enhancers previously validated in reporter assays. Compared with existing methods, REPTILE shows consistently superior performance across diverse cell and tissue types, and the enhancer locations are significantly more refined. We show that, by incorporating base-resolution methylation data, REPTILE greatly improves upon current methods for annotation of enhancers across a variety of cell and tissue types.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC); National Institutes of Health (NIH); Gordon and Betty Moore Foundation
- Grant/Contract Number:
- AC02-05CH11231; U54 HG006997; K12 GM068524; GBMF3034; R01 MH094670; U01 MH105985; GC1R-06673-B
- OSTI ID:
- 1343636
- Alternate ID(s):
- OSTI ID: 1393127
- Journal Information:
- Proceedings of the National Academy of Sciences of the United States of America, Journal Name: Proceedings of the National Academy of Sciences of the United States of America Vol. 114 Journal Issue: 9; ISSN 0027-8424
- Publisher:
- Proceedings of the National Academy of SciencesCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
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