Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA.
Department of Biology, Stanford University, Stanford, CA, USA.
Mol Biol Evol. 2021 Sep 27;38(10):4588-4602. doi: 10.1093/molbev/msab162.
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.
突变对适合度的影响可能因环境和遗传背景而异，但对于导致这种差异的因素知之甚少。为了量化基因组范围内突变适合度效应的相关性，我们提出了一个新的概念，称为群体间的适合度效应联合分布（DFE）。然后，我们提出了一个新的统计量 w 来衡量群体间的 DFE 相关性。通过模拟，我们表明从联合等位基因频率谱推断 DFE 相关性在统计学上是精确和稳健的。利用种群基因组数据，我们推断了人类、黑腹果蝇和野生番茄种群的 DFE 相关性。在这些物种中，我们发现联合 DFE 的整体相关性与遗传分化呈负相关。在人类和黑腹果蝇中，有害突变的 DFE 相关性低于耐受突变，表明复杂的联合 DFE。总之，DFE 相关性可以可靠地推断出来，这为种群分化的遗传学提供了广泛的见解。
