PT - JOURNAL ARTICLE AU - Alyssa Lyn Fortier AU - Alec J. Coffman AU - Travis J. Struck AU - Megan N. Irby AU - Jose E. L. Burguete AU - Aaron P. Ragsdale AU - Ryan N. Gutenkunst TI - DFEnitely different: Genome-wide characterization of differences in mutation fitness effects between populations AID - 10.1101/703918 DP - 2019 Jan 01 TA - bioRxiv PG - 703918 4099 - http://biorxiv.org/content/early/2019/07/16/703918.short 4100 - http://biorxiv.org/content/early/2019/07/16/703918.full AB - The effect of a mutation on fitness may differ between populations, depending on environmental and genetic context. Experimental studies have shown that such differences exist, but little is known about the broad patterns of such differences or the factors that drive them. To quantify genome-wide patterns of differences in mutation fitness effects, we extended the concept of a distribution of fitness effects (DFE) to a joint DFE between populations. To infer the joint DFE, we fit parametric models that included demographic history to genomic data summarized by the joint allele frequency spectrum. Using simulations, we showed that our approach is statistically powerful and robust to many forms of model misspecification. We then applied our approach to populations of Drosophila melanogaster, wild tomatoes, and humans. We found that mutation fitness effects are overall least correlated between populations in tomatoes and most correlated in humans, corresponding to overall genetic differentiation. In D. melanogaster and tomatoes, mutations in genes involved in immunity and stress response showed the lowest correlation of fitness effects, consistent with environmental influence. In D. melanogaster and humans, deleterious mutations showed a lower correlation of fitness effects than tolerated mutations, hinting at the complexity of the joint DFE. Together, our results show that the joint DFE can be reliably inferred and that it offers extensive insight into the genetics of population divergence.