Evolutionary Signatures amongst Disease Genes Permit Novel Methods for Gene Prioritization and Construction of Informative Gene-Based Networks

Priedigkeit, N and Wolfe, N and Clark, NL (2015) Evolutionary Signatures amongst Disease Genes Permit Novel Methods for Gene Prioritization and Construction of Informative Gene-Based Networks. PLoS Genetics, 11 (2). 1 - 17. ISSN 1553-7390

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Abstract

Genes involved in the same function tend to have similar evolutionary histories, in that their rates of evolution covary over time. This coevolutionary signature, termed Evolutionary Rate Covariation (ERC), is calculated using only gene sequences from a set of closely related species and has demonstrated potential as a computational tool for inferring functional relationships between genes. To further define applications of ERC, we first established that roughly 55% of genetic diseases posses an ERC signature between their contributing genes. At a false discovery rate of 5% we report 40 such diseases including cancers, developmental disorders and mitochondrial diseases. Given these coevolutionary signatures between disease genes, we then assessed ERC's ability to prioritize known disease genes out of a list of unrelated candidates. We found that in the presence of an ERC signature, the true disease gene is effectively prioritized to the top 6% of candidates on average. We then apply this strategy to a melanoma-associated region on chromosome 1 and identify MCL1 as a potential causative gene. Furthermore, to gain global insight into disease mechanisms, we used ERC to predict molecular connections between 310 nominally distinct diseases. The resulting “disease map” network associates several diseases with related pathogenic mechanisms and unveils many novel relationships between clinically distinct diseases, such as between Hirschsprung's disease and melanoma. Taken together, these results demonstrate the utility of molecular evolution as a gene discovery platform and show that evolutionary signatures can be used to build informative gene-based networks.

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Details

Item Type:	Article
Status:	Published
Creators/Authors:	Creators Email Pitt Username ORCID Priedigkeit, N priedigkeit.nolan@medstudent.pitt.edu NMP50 Wolfe, N Clark, NL nclark@pitt.edu NCLARK
Contributors:	Contribution Contributors Name Email Pitt Username ORCID Editor Akey, Joshua M. UNSPECIFIED UNSPECIFIED UNSPECIFIED
Date:	1 January 2015
Date Type:	Publication
Journal or Publication Title:	PLoS Genetics
Volume:	11
Number:	2
Page Range:	1 - 17
DOI or Unique Handle:	10.1371/journal.pgen.1004967
Schools and Programs:	School of Medicine > Computational and Systems Biology School of Medicine > Pharmacology and Chemical Biology
Refereed:	Yes
ISSN:	1553-7390
Other ID:	NLM PMC4334549
PubMed Central ID:	PMC4334549
PubMed ID:	25679399
Date Deposited:	12 May 2015 18:13
Last Modified:	03 Apr 2021 09:55
URI:	http://d-scholarship.pitt.edu/id/eprint/24095

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