RT Journal Article SR Electronic T1 Inferring genome-wide correlations of mutation fitness effects between populations JF bioRxiv FD Cold Spring Harbor Laboratory SP 703918 DO 10.1101/703918 A1 Xin Huang A1 Alyssa Lyn Fortier A1 Alec J. Coffman A1 Travis J. Struck A1 Megan N. Irby A1 Jennifer E. James A1 José E. Léon-Burguete A1 Aaron P. Ragsdale A1 Ryan N. Gutenkunst YR 2021 UL http://biorxiv.org/content/early/2021/02/18/703918.abstract AB 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 specices, 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.Competing Interest StatementThe authors have declared no competing interest.