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A haplotype method detects diverse scenarios of local adaptation from genomic sequence variation

机译:单倍型方法可从基因组序列变异中检测出多种多样的局部适应方案

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Identifying genomic targets of population-specific positive selection is a major goal in several areas of basic and applied biology. However, it is unclear how often such selection should act on new mutations versus standing genetic variation or recurrent mutation, and furthermore, favoured alleles may either become fixed or remain variable in the population. Very few population genetic statistics are sensitive to all of these modes of selection. Here, we introduce and evaluate the Comparative Haplotype Identity statistic (chi(MD)), which assesses whether pairwise haplotype sharing at a locus in one population is unusually large compared with another population, relative to genomewide trends. Using simulations that emulate human and Drosophila genetic variation, we find that chi(MD) is sensitive to a wide range of selection scenarios, and for some very challenging cases (e.g. partial soft sweeps), it outperforms other two-population statistics. We also find that, as with F-ST, our haplotype approach has the ability to detect surprisingly ancient selective sweeps. Particularly for the scenarios resembling human variation, we find that chi(MD) outperforms other frequency-and haplotype-based statistics for soft and/or partial selective sweeps. Applying chi(MD) and other between-population statistics to published population genomic data from D. melanogaster, we find both shared and unique genes and functional categories identified by each statistic. The broad utility and computational simplicity of chi(MD) will make it an especially valuable tool in the search for genes targeted by local adaptation.
机译:在特定的基础生物学和应用生物学领域,确定特定人群正选择的基因组目标是一个主要目标。但是,尚不清楚这种选择应该多久作用于新突变而不是遗传突变或复发突变,而且,所支持的等位基因可能在群体中变得固定或保持可变。很少有人口遗传统计学对所有这些选择模式敏感。在这里,我们介绍并评估比较单倍型同一性统计量(chi(MD)),该统计量评估相对于全基因组趋势,一个人群中一个基因座的成对单倍型共享是否比另一个人群异常大。通过使用模拟人类和果蝇遗传变异的模拟,我们发现chi(MD)对广泛的选择场景敏感,在某些非常具有挑战性的情况下(例如部分软扫除),它的表现优于其他两个种群的统计数据。我们还发现,与F-ST一样,我们的单倍型方法能够检测出令人惊讶的古老选择性扫描。特别是对于类似于人类变异的场景,我们发现chi(MD)优于其他基于频率和单倍型的软和/或部分选择性扫描的统计数据。将chi(MD)和其他种群之间的统计数据应用于已发布的D. melanogaster的种群基因组数据,我们发现共享的和独特的基因以及每种统计所确定的功能类别。 chi(MD)的广泛用途和计算简单性将使其成为寻找局部适应性靶向基因的特别有价值的工具。

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