Departamento de Biología Funcional, Facultad de Biología, Universidad de Oviedo, Oviedo, Spain.
Centro de Investigación Mariña, Departamento de Bioquímica, Genética e Inmunología, Edificio CC Experimentais, Campus de Vigo, Universidade de Vigo, Vigo, Spain.
Mol Biol Evol. 2020 Dec 16;37(12):3642-3653. doi: 10.1093/molbev/msaa169.
Inferring changes in effective population size (Ne) in the recent past is of special interest for conservation of endangered species and for human history research. Current methods for estimating the very recent historical Ne are unable to detect complex demographic trajectories involving multiple episodes of bottlenecks, drops, and expansions. We develop a theoretical and computational framework to infer the demographic history of a population within the past 100 generations from the observed spectrum of linkage disequilibrium (LD) of pairs of loci over a wide range of recombination rates in a sample of contemporary individuals. The cumulative contributions of all of the previous generations to the observed LD are included in our model, and a genetic algorithm is used to search for the sequence of historical Ne values that best explains the observed LD spectrum. The method can be applied from large samples to samples of fewer than ten individuals using a variety of genotyping and DNA sequencing data: haploid, diploid with phased or unphased genotypes and pseudohaploid data from low-coverage sequencing. The method was tested by computer simulation for sensitivity to genotyping errors, temporal heterogeneity of samples, population admixture, and structural division into subpopulations, showing high tolerance to deviations from the assumptions of the model. Computer simulations also show that the proposed method outperforms other leading approaches when the inference concerns recent timeframes. Analysis of data from a variety of human and animal populations gave results in agreement with previous estimations by other methods or with records of historical events.
推断近期有效种群大小 (Ne) 的变化对于濒危物种的保护和人类历史研究具有特殊意义。目前用于估计非常近期历史 Ne 的方法无法检测到涉及多个瓶颈、下降和扩张阶段的复杂人口轨迹。我们开发了一个理论和计算框架,从当代个体样本中广泛的重组率范围内观察到的成对位点的连锁不平衡 (LD) 频谱推断种群在过去 100 代内的人口历史。我们的模型包括所有以前世代对观察到的 LD 的累积贡献,并且遗传算法用于搜索最能解释观察到的 LD 频谱的历史 Ne 值序列。该方法可以应用于从大样本到少于十个个体的样本,使用各种基因分型和 DNA 测序数据:来自低覆盖率测序的单体型、具有相位或非相位基因型的二倍体和拟单体型数据。该方法通过计算机模拟针对基因分型错误、样本时间异质性、种群混合和结构划分为亚群的敏感性进行了测试,对模型假设的偏差具有很高的容忍度。计算机模拟还表明,当推断涉及近期时间框架时,该方法优于其他领先方法。对来自各种人类和动物种群的数据的分析结果与其他方法的先前估计或历史事件的记录一致。