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从黑腹果蝇群体基因组数据中检测硬选择和软选择的漂变。

Detection of hard and soft selective sweeps from Drosophila melanogaster population genomic data.

机构信息

Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California, United States of America.

Department of Human Genetics, University of California, Los Angeles, California, United States of America.

出版信息

PLoS Genet. 2021 Feb 26;17(2):e1009373. doi: 10.1371/journal.pgen.1009373. eCollection 2021 Feb.

Abstract

Whether hard sweeps or soft sweeps dominate adaptation has been a matter of much debate. Recently, we developed haplotype homozygosity statistics that (i) can detect both hard and soft sweeps with similar power and (ii) can classify the detected sweeps as hard or soft. The application of our method to population genomic data from a natural population of Drosophila melanogaster (DGRP) allowed us to rediscover three known cases of adaptation at the loci Ace, Cyp6g1, and CHKov1 known to be driven by soft sweeps, and detected additional candidate loci for recent and strong sweeps. Surprisingly, all of the top 50 candidates showed patterns much more consistent with soft rather than hard sweeps. Recently, Harris et al. 2018 criticized this work, suggesting that all the candidate loci detected by our haplotype statistics, including the positive controls, are unlikely to be sweeps at all and that instead these haplotype patterns can be more easily explained by complex neutral demographic models. They also claim that these neutral non-sweeps are likely to be hard instead of soft sweeps. Here, we reanalyze the DGRP data using a range of complex admixture demographic models and reconfirm our original published results suggesting that the majority of recent and strong sweeps in D. melanogaster are first likely to be true sweeps, and second, that they do appear to be soft. Furthermore, we discuss ways to take this work forward given that most demographic models employed in such analyses are necessarily too simple to capture the full demographic complexity, while more realistic models are unlikely to be inferred correctly because they require a large number of free parameters.

摘要

硬选择还是软选择主导适应一直是一个争论不休的问题。最近,我们开发了单倍型纯合性统计方法,(i)可以用相似的能力检测到硬选择和软选择,(ii)可以将检测到的选择分类为硬选择或软选择。该方法应用于来自黑腹果蝇(DGRP)自然种群的群体基因组数据,使我们能够重新发现三个已知的适应案例,即在 Ace、Cyp6g1 和 CHKov1 位点上的适应,这些位点已知是由软选择驱动的,并且检测到了其他最近和强选择的候选位点。令人惊讶的是,前 50 个候选者中的所有候选者的模式与软选择而不是硬选择更为一致。最近,Harris 等人。2018 年对此工作提出了批评,他们认为我们单倍型统计方法检测到的所有候选位点,包括阳性对照,都不太可能是选择,而这些单倍型模式更有可能是由复杂的中性种群动态模型更容易解释。他们还声称,这些中性的非选择更可能是硬选择而不是软选择。在这里,我们使用一系列复杂的混合种群动态模型重新分析 DGRP 数据,并重新确认我们的原始研究结果,表明黑腹果蝇中的大多数近期和强选择更可能是真正的选择,其次,它们确实似乎是软选择。此外,我们还讨论了如何在大多数用于此类分析的种群动态模型都必然过于简单而无法捕捉到全部种群动态复杂性的情况下推进这项工作,而更现实的模型不太可能被正确推断,因为它们需要大量的自由参数。

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