Genome-Wide Mapping of Gene–Phenotype Relationships in Experimentally Evolved Populations. (31st May 2018)

• Record Type: Journal Article
• Authors: Mueller, Laurence D; Phillips, Mark A; Barter, Thomas T; Greenspan, Zachary S; Rose, Michael R
• Editors: Barlow, Miriam
• Is Part Of: Molecular biology and evolution. Volume 35:Number 8(2018)
• Page Start: 2085
• Page End: 2095
• Publication Date: 2018-05-31
• Subjects: experimental evolution -- statistical learning -- computer simulation; Molecular biology -- Periodicals; Molecular evolution -- Periodicals; Evolution, Molecular -- Periodicals; Molecular Biology -- Periodicals; 572.8
• DOI: 10.1093/molbev/msy113
• Languages: English
• ISSNs: 0737-4038

Abstract

Abstract: Model organisms subjected to sustained experimental evolution often show levels of phenotypic differentiation that dramatically exceed the phenotypic differences observed in natural populations. Genome-wide sequencing of pooled populations then offers the opportunity to make inferences about the genes that are the cause of these phenotypic differences. We tested, through computer simulations, the efficacy of a statistical learning technique called the "fused lasso additive model" (FLAM). We focused on the ability of FLAM to distinguish between genes which are differentiated and directly affect a phenotype from differentiated genes which have no effect on the phenotype. FLAM can separate these two classes of genes even with relatively small samples (10 populations, in total). The efficacy of FLAM is improved with increased number of populations, reduced environmental phenotypic variation, and increased within-treatment among-replicate variation. FLAM was applied to SNP variation measured in both twenty-population and thirty-population studies of Drosophila subjected to selection for age-at-reproduction, to illustrate the application of the method.