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Nat Genet. 2019 Feb;51(2):335-342. doi: 10.1038/s41588-018-0300-z. Epub 2018 Dec 17.

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

Author information

1
Graduate Field of Computer Science, Cornell University, Ithaca, NY, USA.
2
Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
3
Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. asiepel@cshl.edu.

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.

PMID:
30559490
DOI:
10.1038/s41588-018-0300-z

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