Multiple-merger coalescents - suitable models for gene genealogies in real populations?

多重合并聚结——真实人群中基因谱系的合适模型？

• 批准号: 284099193
• 负责人: Dr. Fabian Freund
• 金额: --
• 依托单位: Fachgebiet Nutzpflanzenbiodiversität und Züchtungsinformatik (350b)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2015
• 资助国家: 德国
• 起止时间: 2014-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/284099193?language=en
• 关键词: Multiple; merger; coalescents; suitable; models

To assess which evolutionary forces have acted on a real population, one can compare the observed genetic diversity in a sample with its distribution under one or several theoretical models for possible evolutionary histories of the population. Such models include a model of the sample's genealogy. For a single selectively neutral genetic locus without recombination, the standard genealogy model is Kingman's n-coalescent if the sample of size n is taken form a randomly mating population with fixed size, much higher than the sample size. Kingman's n-coalescent is a random bifurcating tree with n leaves. This genealogy model can be extended e.g. to account for population size fluctuations in the past or for population subdivision while still being a bifurcating tree. However, theoretical models for populations with properties like reproduction sweepstakes or rapid selection will lead to multifurcating random trees as genealogies of a sample called multiple-merger n-coalescents.The main goal of this project is to assess whether samples from real populations which have properties where theoretical models predict multiple-merger n-coalescents genealogies are actually fitting better to these models than to extended Kingman's n-coalescents based on the observed genetic diversity. Several statistical methods have been proposed to distinguish between multiple-merger n-coalescents and the (extended) Kingman's n-coalescent (gene tree maximum likelihood, approximate Bayesian computation (ABC), approximate likelihood and an approach using a minimum-distance statistic, the latter three based on the site frequency spectrum of the sample). Further aims of this project are to refine and extend the ABC inference method and to investigate whether using statistics based on other genetic information than the site frequency spectrum can improve inference capacity. The inference capacity of the available inference methods will be compared via simulation for different genealogy model comparisons to identify the best method for a given comparison of different n-coalescents as genealogy models. To assess the main goal, first populations that might be linked to multiple-merger genealogies are identified. For these, specific multiple-merger n-coalescents and (extended) Kingman's n-coalescents (biologically reasonable alternative models) are used as potential genealogy models. For these models, inference for the best model is performed following the inference protocol established before. The inference results are then discussed in the light of known properties of the populations.

为了评估哪些进化力量作用于一个真实的种群，人们可以将样本中观察到的遗传多样性与其在一个或几个理论模型下的分布进行比较，以了解种群可能的进化历史。这样的模型包括样本系谱的模型。对于一个没有重组的选择性中性基因座，如果样本量为n，且样本量远大于样本量，则标准的系谱模型是金曼的n-聚结模型。金曼的n-合并树是一个随机分叉树n叶。这个谱系模型可以扩展，例如，考虑到过去的人口规模波动或人口细分，同时仍然是一个分叉树。然而，在这方面，具有繁殖抽奖或快速选择等性质的种群的理论模型将导致多叉随机树作为称为多合并n-聚结的样本的系谱。该项目的主要目标是评估来自真实的种群的样本是否具有理论模型预测多合并n-聚结系谱的性质，实际上更适合这些模型，而不是扩展的金曼的n-聚结。基于观察到的遗传多样性的聚结。已经提出了几种统计方法来区分多合并的n-聚结和（扩展的）金曼的n-聚结（基因树最大似然，近似贝叶斯计算（ABC），近似似然和使用最小距离统计的方法，后三个基于站点频谱的样本）。本项目的进一步目标是改进和扩展ABC推理方法，并调查是否使用基于其他遗传信息的统计数据，而不是站点频谱，可以提高推理能力。将通过针对不同谱系模型比较的模拟来比较可用推断方法的推断能力，以识别针对作为谱系模型的不同n-聚结剂的给定比较的最佳方法。为了评估主要目标，首先确定可能与多重合并系谱有关的人群。对于这些，特定的多合并n-聚结和（扩展）金曼的n-聚结（生物合理的替代模型）被用作潜在的系谱模型。对于这些模型，按照之前建立的推理协议执行对最佳模型的推理。然后，根据已知的性质的人口的推断结果进行了讨论。