Affordable Access

deepdyve-link
Publisher Website

Base-Biased Evolution of Disease-Associated Mutations in the Human Genome.

Authors
  • Xue, Cheng1
  • Chen, Hua2
  • Yu, Fuli3
  • 1 Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas.
  • 2 Center for Computational Genomics, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China. , (China)
  • 3 Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas. [email protected]
Type
Published Article
Journal
Human Mutation
Publisher
Wiley (John Wiley & Sons)
Publication Date
Nov 01, 2016
Volume
37
Issue
11
Pages
1209–1214
Identifiers
DOI: 10.1002/humu.23065
PMID: 27507420
Source
Medline
Keywords
License
Unknown

Abstract

Understanding the evolution of disease-associated mutations is fundamental to analyze pathogenetics of diseases. Mutation, recombination (by GC-biased gene conversion, gBGC), and selection have been known to shape the evolution of disease-associated mutations, but how these evolutionary forces work together is still an open question. In this study, we analyzed several human large-scale datasets (1000 Genomes, ESP6500, ExAC and ClinVar), and found that base-biased mutagenesis generates more GC→AT than AT→GC mutations, while gBGC promotes the fixation of AT→GC mutations to balance the impact of base-biased mutation on genome. Due to this effect of gBGC, purifying selection removes more deleterious AT→GC mutations than GC→AT from population, but many high-frequency (fixed and nearly fixed) deleterious AT→GC mutations are remained possibly due to high genetic load. As a special subset, disease-associated mutations follow this evolutionary rule, in which disease-associated GC→AT mutations are more enriched in rare mutations compared with AT→GC, while disease-associated AT→GC are more enriched in mutations with high frequency. Thus, we presented a base-biased evolutionary framework that explains the base-biased generation and accumulation of disease-associated mutations in human populations.

Report this publication

Statistics

Seen <100 times