A method for calculating probabilities of fitness consequences for point mutations across the human genome

Gulko, B., Hubisz, M. J., Gronau, I., Siepel, A. (March 2015) A method for calculating probabilities of fitness consequences for point mutations across the human genome. Nature Genetics, 47 (3). pp. 276-283. ISSN 1061-4036

URL: http://www.ncbi.nlm.nih.gov/pubmed/25599402
DOI: 10.1038/ng.3196

Abstract

We describe a new computational method for estimating the probability that a point mutation at each position in a genome will influence fitness. These 'fitness consequence' (fitCons) scores serve as evolution-based measures of potential genomic function. Our approach is to cluster genomic positions into groups exhibiting distinct 'fingerprints' on the basis of high-throughput functional genomic data, then to estimate a probability of fitness consequences for each group from associated patterns of genetic polymorphism and divergence. We have generated fitCons scores for three human cell types on the basis of public data from ENCODE. In comparison with conventional conservation scores, fitCons scores show considerably improved prediction power for cis regulatory elements. In addition, fitCons scores indicate that 4.2-7.5% of nucleotides in the human genome have influenced fitness since the human-chimpanzee divergence, and they suggest that recent evolutionary turnover has had limited impact on the functional content of the genome.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > computational biology
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > genomes
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > mutations
CSHL Authors:
Communities: CSHL labs > Siepel lab
Depositing User: Matt Covey
Date: March 2015
Date Deposited: 09 Feb 2015 20:26
Last Modified: 17 Apr 2015 14:13
PMCID: PMC4342276
Related URLs:
URI: https://repository.cshl.edu/id/eprint/31191

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