Multiple-merger coalescents - suitable models for gene genealogies in real 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种群可能进化历史的理论模型下的分布进行比较。这样的模型包括样本谱系的模型。对于没有重组的单个选择性中性基因座，如果从固定大小的随机交配群体中取n大小的样本，则标准的谱系模型为Kingman's n-coalescent。Kingman's n-coalescent是一个有n个叶子的随机分岔树。这种谱系模型可以扩展，例如，考虑过去的种群规模波动或种群细分，同时仍然是一个分岔树。然而，具有繁殖抽奖或快速选择等特性的种群的理论模型将导致多分叉随机树作为一个称为多合并n-聚结的样本的家谱。该项目的主要目标是评估来自真实种群的样本是否具有理论模型预测多重合并n- coalesies谱系的特性，实际上比基于观察到的遗传多样性扩展的Kingman n- coalesies更适合这些模型。已经提出了几种统计方法来区分多重合并n-聚结和（扩展的）Kingman 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，后三种方法基于样本的站点频谱）。本项目的进一步目标是改进和扩展ABC推断方法，并研究使用基于其他遗传信息而不是站点频谱的统计是否可以提高推断能力。通过对不同家谱模型比较的仿真，比较现有推理方法的推理能力，以确定不同n-聚结作为家谱模型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谱系有关的种群。对于这些，特定的多重合并n-聚结和（扩展的）Kingman的n-聚结（生物学上合理的替代模型）被用作潜在的谱系模型。对于这些模型，根据前面建立的推理协议进行最佳模型的推理。然后根据已知的总体性质讨论推断结果。

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.