An evolutionary framework for measuring epigenomic information and estimating cell-type-specific fitness consequences

Gulko, B., Siepel, A. (December 2018) An evolutionary framework for measuring epigenomic information and estimating cell-type-specific fitness consequences. Nat Genet, 51 (2). pp. 335-342. ISSN 1061-4036

URL: https://www.ncbi.nlm.nih.gov/pubmed/30559490
DOI: 10.1038/s41588-018-0300-z

Abstract

Here we ask the question "How much information do epigenomic datasets provide about human genomic function?" We consider nine epigenomic features across 115 cell types and measure information about function as a reduction in entropy under a probabilistic evolutionary model fitted to human and nonhuman primate genomes. Several epigenomic features yield more information in combination than they do individually. We find that the entropy in human genetic variation predominantly reflects a balance between mutation and neutral drift. Our cell-type-specific FitCons scores reveal relationships among cell types and suggest that around 8% of nucleotide sites are constrained by natural selection.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > epigenetics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > epigenetics
CSHL Authors:
Communities: CSHL labs > Siepel lab
Depositing User: Matthew Dunn
Date: 17 December 2018
Date Deposited: 20 Dec 2018 19:48
Last Modified: 25 Feb 2019 19:50
Related URLs:
URI: http://repository.cshl.edu/id/eprint/37501

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