Quantifying Selection Acting on a Complex Trait Using Allele Frequency Time Series Data
Quantifying Selection Acting on a Complex Trait Using Allele Frequency Time Series Data
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DOI：
10.1093/molbev/msr289
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发表时间：
2012-04-01
影响因子：
10.7
通讯作者：
Mustonen, Ville
中科院分区：
文献类型：
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作者：
Illingworth, Christopher J. R.;Parts, Leopold;Mustonen, Ville
当选择作用于一个遗传多样性很大的群体时，有益的等位基因的频率会增加。这一事实可以用来定位数量性状基因座，方法是对连续时间点的群体DNA进行测序，并观察等位基因频率的变化。在这里，我们提出了一种群体遗传学方法来分析来自这样的实验的等位基因频率的时间序列数据。该方法从一系列提出的进化场景开始，测量每个场景与观察到的频率变化的一致性。利用进化理论来建立等位基因频率的运动方程，然后推导出在每种情况下观察到测序数据的可能性。通过对这些可能性的比较，我们可以深入了解正在研究的系统的普遍动态。我们通过量化实验中的选择效应来说明这种方法，在实验中，两个表型不同的酵母菌株首先杂交，然后在热胁迫下繁殖(部分L，Cubillos FA，Warringer J，等人)。[14名合著者]。2011年。通过对被选择的群体进行测序来揭示特征的遗传结构。基因组Res)。从这些数据中，我们发现大约6%的多态位点在热应激条件下非中性进化，要么是因为它们与有益的(驱动)等位基因连锁，要么是因为它们本身就是驱动基因。我们进一步确定了包含一个或多个候选驱动等位基因的44个基因组区域，量化了它们的明显选择优势，获得了区域内重组率的估计，并表明驱动因素的动态表现出强烈的选择特征，超出了相加模型。我们的方法适用于研究一系列系统在不同进化压力下的适应。
When selection is acting on a large genetically diverse population, beneficial alleles increase in frequency. This fact can be used to map quantitative trait loci by sequencing the pooled DNA from the population at consecutive time points and observing allele frequency changes. Here, we present a population genetic method to analyze time series data of allele frequencies from such an experiment. Beginning with a range of proposed evolutionary scenarios, the method measures the consistency of each with the observed frequency changes. Evolutionary theory is utilized to formulate equations of motion for the allele frequencies, following which likelihoods for having observed the sequencing data under each scenario are derived. Comparison of these likelihoods gives an insight into the prevailing dynamics of the system under study. We illustrate the method by quantifying selective effects from an experiment, in which two phenotypically different yeast strains were first crossed and then propagated under heat stress (Parts L, Cubillos FA, Warringer J, et al. [14 co-authors]. 2011. Revealing the genetic structure of a trait by sequencing a population under selection. Genome Res). From these data, we discover that about 6% of polymorphic sites evolve nonneutrally under heat stress conditions, either because of their linkage to beneficial (driver) alleles or because they are drivers themselves. We further identify 44 genomic regions containing one or more candidate driver alleles, quantify their apparent selective advantage, obtain estimates of recombination rates within the regions, and show that the dynamics of the drivers display a strong signature of selection going beyond additive models. Our approach is applicable to study adaptation in a range of systems under different evolutionary pressures.