Inferring Genome-Wide Correlations of Mutation Fitness Effects Between Populations

Overview

Journal Mol Biol Evol

Publisher Oxford University Press

Specialty Biology

Date 2021 May 27

PMID 34043790

Citations 20

Authors

Xin Huang

Alyssa Lyn Fortier

Alec J Coffman

Travis J Struck

Megan N Irby

Jennifer E James

Jose E Leon-Burguete

Aaron P Ragsdale

Ryan N Gutenkunst

Affiliations

Soon will be listed here.

Abstract

The effect of a mutation on fitness may differ between populations depending on environmental and genetic context, but little is known about the factors that underlie such differences. To quantify genome-wide correlations in mutation fitness effects, we developed a novel concept called a joint distribution of fitness effects (DFE) between populations. We then proposed a new statistic w to measure the DFE correlation between populations. Using simulation, we showed that inferring the DFE correlation from the joint allele frequency spectrum is statistically precise and robust. Using population genomic data, we inferred DFE correlations of populations in humans, Drosophila melanogaster, and wild tomatoes. In these species, we found that the overall correlation of the joint DFE was inversely related to genetic differentiation. In humans and D. melanogaster, deleterious mutations had a lower DFE correlation than tolerated mutations, indicating a complex joint DFE. Altogether, the DFE correlation can be reliably inferred, and it offers extensive insight into the genetics of population divergence.

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