Bayesian implementation of the multispecies-coalescent-with-introgression (MSci) model for analysis of population genomic data

不同物种的基因组包含有关物种进化史的丰富信息。通过比较不同物种或同一物种不同个体的DNA序列，我们可以弄清楚这些物种是如何相关的，当它们彼此背离时，是否以及何时存在跨物种杂交。然而，为了从我们的基因组中提取这些信息，强大的统计模型和高效的计算算法是必要的。多物种融合与导入(MSCI)模型为基因组序列数据的比较分析提供了一个自然的框架，考虑了遗传物质代代相传时生物繁殖的随机波动、基因突变的随机积累以及可能的跨物种杂交事件。我们将在我们的贝叶斯马尔科夫链蒙特卡罗模拟程序中实现MSCI模型，以便它可以用于估计物种的系统发育和物种分化时间、祖先种群规模以及杂交的时间和速度。这些参数将为物种起源提供重要的见解。我们将应用我们最新开发的方法来分析由我们的合作者产生的赫利柯斯蝴蝶、马达加斯加鼠狐猴和蜥蜴的基因组数据集。

Genomes from different species contain rich information about the evolutionary history of the species. By comparing DNA sequences from different species or different individuals of the same species we can work out how the species are related, when they diverged from each other, whether and when there was cross-species hybridisation. Nevertheless, to extract this information from our genomes, powerful statistical models and efficient computational algorithms are necessary. The multispecies-coalescent-with-introgression (MSci) model provides a natural framework for comparative analysis of genomic sequence data, accommodating the random fluctuations of biological reproduction when genetic materials are passed over generations, random accumulations of genetic mutations as well as possible cross-species hybridisation events. We will implement the MSci model in our Bayesian Markov chain Monte Carlo simulation program, so that it can be used to estimate species phylogenies and species divergence times, ancestral population sizes, and the time and rate of hybridisation. Those parameters will provide important insights into the origin of species. We will apply our newly developed methods to analyse genomic datasets from Heliconius butterflies, Malagasy mouse lemurs, and lizards, generated by our collaborators.