Screening for epistatic selection signatures: A simulation study.

ABSTRACT: Detecting combinations of alleles that diverged between subpopulations via selection signature statistics can contribute to decipher the phenomenon of epistasis. This research focused on the simulation of genomic data from subpopulations under divergent epistatic selection (ES). We used D'IS2 and FST statistics in pairs of loci to scan the whole-genome. The results showed the ability to identify loci under additive-by-additive ES (ESaa) by reporting large statistical departures between subpopulations with a high level of divergence, while it did not show the same advantage in the other types of ES. Despite this, limitations such as the difficulty to distinguish between the quasi-complete fixation of one locus by ESaa from other events were observed. However, D'IS2 can detect loci under ESa

SUBMITTER: Id-Lahoucine S 

PROVIDER: S-EPMC6355851 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature