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Inference of Evolutionary Forces Acting on Human Biological Pathways
Author(s) -
Joséphine T. Daub,
Isabelle Dupanloup,
Marc RobinsonRechavi,
Laurent Excoffier
Publication year - 2015
Publication title -
genome biology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.702
H-Index - 74
ISSN - 1759-6653
DOI - 10.1093/gbe/evv083
Subject(s) - biology , natural selection , gene , selection (genetic algorithm) , evolutionary biology , inference , negative selection , nonsynonymous substitution , genetics , trait , statistical hypothesis testing , computational biology , outlier , null hypothesis , artificial intelligence , genome , computer science , statistics , mathematics , programming language
Because natural selection is likely to act on multiple genes underlying a given phenotypic trait, we study here the potential effect of ongoing and past selection on the genetic diversity of human biological pathways. We first show that genes included in gene sets are generally under stronger selective constraints than other genes and that their evolutionary response is correlated. We then introduce a new procedure to detect selection at the pathway level based on a decomposition of the classical McDonald-Kreitman test extended to multiple genes. This new test, called 2DNS, detects outlier gene sets and takes into account past demographic effects and evolutionary constraints specific to gene sets. Selective forces acting on gene sets can be easily identified by a mere visual inspection of the position of the gene sets relative to their two-dimensional null distribution. We thus find several outlier gene sets that show signals of positive, balancing, or purifying selection but also others showing an ancient relaxation of selective constraints. The principle of the 2DNS test can also be applied to other genomic contrasts. For instance, the comparison of patterns of polymorphisms private to African and non-African populations reveals that most pathways show a higher proportion of nonsynonymous mutations in non-Africans than in Africans, potentially due to different demographic histories and selective pressures.

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