Groh Jeffrey, Coop Graham
Department of Evolution and Ecology, and Center for Population Biology, University of California, Davis, CA 95616.
bioRxiv. 2023 May 26:2023.05.25.542345. doi: 10.1101/2023.05.25.542345.
Genomic evidence supports an important role for selection in shaping patterns of introgression along the genome, but frameworks for understanding the dynamics underlying these patterns within hybrid populations have been lacking. Here, we develop methods based on the Wavelet Transform to understand the spatial genomic scale of local ancestry variation and its association with recombination rates. We present theory and use simulations to show how wavelet-based decompositions of ancestry variance along the genome and the correlation between ancestry and recombination reflect the joint effects of recombination, genetic drift, and genome-wide selection against introgressed alleles. Due to the clock-like effect of recombination in hybrids breaking up parental haplotypes, drift and selection produce predictable patterns of local ancestry variation at varying spatial genomic scales through time. Using wavelet approaches to identify the genomic scale of variance in ancestry and its correlates, we show that these methods can detect temporally localized effects of drift and selection. We apply these methods to previously published datasets from hybrid populations of swordtail fish () and baboons (), and to inferred Neanderthal introgression in modern humans. Across systems, we find that upwards of 20% of the variation in local ancestry at the broadest genomic scales can be attributed to systematic selection against introgressed alleles, consistent with strong selection acting on early-generation hybrids. We also see signals of selection at fine genomic scales and much longer time scales. However, we show that our ability to confidently infer selection at fine scales is likely limited by inherent biases in current methods for estimating local ancestry from genomic similarity. Wavelet approaches will become widely applicable as genomic data from systems with introgression become increasingly available, and can help shed light on generalities of the genomic consequences of interspecific hybridization.
基因组证据支持选择在塑造全基因组渐渗模式中发挥重要作用,但一直缺乏理解杂交种群中这些模式背后动态机制的框架。在此,我们开发了基于小波变换的方法,以了解本地祖先变异的空间基因组尺度及其与重组率的关联。我们提出理论并通过模拟展示了沿基因组的祖先方差的小波分解以及祖先与重组之间的相关性如何反映重组、遗传漂变和针对渐渗等位基因的全基因组选择的联合效应。由于杂种中重组的时钟样效应会打破亲本单倍型,随着时间推移,漂变和选择在不同的空间基因组尺度上产生可预测的本地祖先变异模式。使用小波方法来识别祖先方差及其相关因素的基因组尺度,我们表明这些方法可以检测到漂变和选择的时间局部效应。我们将这些方法应用于先前发表的剑尾鱼()和狒狒()杂交种群的数据集,以及现代人类中推断的尼安德特人渐渗情况。在各个系统中,我们发现,在最宽泛的基因组尺度上,超过20%的本地祖先变异可归因于针对渐渗等位基因的系统选择,这与对早期杂种的强烈选择作用一致。我们还在精细的基因组尺度和更长的时间尺度上看到了选择信号。然而,我们表明,我们在精细尺度上可靠推断选择的能力可能受到当前从基因组相似性估计本地祖先方法中固有偏差的限制。随着来自具有渐渗的系统的基因组数据越来越多,小波方法将变得广泛适用,并有助于揭示种间杂交基因组后果的一般性。