Integrating traits into polymorphism-aware trees to better model speciation

将性状整合到多态性感知树中以更好地模拟物种形成

• 批准号: 2884663
• 金额: --
• 依托单位: University of St Andrews
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2884663
• 关键词: Integrating; traits; into; polymorphism; aware

It is a compulsory requirement of the Research Council that a project abstract/description must be included. Efforts to understand the speciation history of taxa have been hampered by incongruity among phylogenetic trees from different genomic regions. Different biological processes can cause incongruence: horizontal gene transfer or hybridization, gene duplication and loss, and incomplete lineage sorting (ILS). ILS occurs when genes coalesce not in extant species, but in the ancestral populations that gave rise to them. As a result, some genes from a species may cluster with sequences from a sister species rather than their own. This project aims to see the "wood from the trees".Dr. Kosiol's group has developed an approached called Polymorphism-aware phylogenetic Models (PoMo), which is based on allele frequencies and so overcomes these limitations. Standard models treat substitutions as instantaneous events, but PoMo describes them as a process: substitutions start as mutations to new, low-frequency alleles, then experience a series of changes in allele frequency. The changes of allele frequencies are modelled by a continuous-time Markov chain based on DNA models (introduction of variation due to mutations) and the continuous Moran model (removal of variation due to genetic drift and natural selection). In this PhD project the approach will be extended to trait evolution.The project will develop the PoMo approach in a Bayesian framework with the following objectives:(i) Integrate trait evolution into the model, so the method can be used to study genotype and binary phenotype data in a unified analysis. We will use self-incompatibilities in plant as an application as these are well studied and can act as a proof of principal.(ii) Expand the approach from binary traits to multiple discrete states. Together with Dr. Welch's group, the student will work on applications to seabirds (order Procellariiformes) using traits such as flight and foraging.(iii) Tackle time-series data of gene expression (RNA-Seq) as continuous function-valued traits in the context of species trees.

研究理事会的强制性要求是必须包括项目摘要/描述。不同基因组区域的系统发育树之间的不一致性阻碍了对分类群物种形成历史的理解。不同的生物学过程可能导致不一致：水平基因转移或杂交，基因复制和丢失，以及不完全谱系分类（ILS）。当基因不是在现存物种中结合，而是在产生它们的祖先群体中结合时，ILS就会发生。因此，来自一个物种的一些基因可能与来自姐妹物种的序列而不是它们自己的序列聚类。这个项目的目的是看到“树木中的木材”。Kosiol博士的团队开发了一种称为多态性感知系统发育模型（PoMo）的方法，该方法基于等位基因频率，因此克服了这些限制。标准模型将替换视为瞬时事件，但PoMo将其描述为一个过程：替换开始为新的低频等位基因的突变，然后经历等位基因频率的一系列变化。等位基因频率的变化由基于DNA模型（由于突变而引入变异）和连续Moran模型（由于遗传漂变和自然选择而去除变异）的连续时间马尔可夫链建模。在这个博士项目中，该方法将扩展到性状进化。该项目将在贝叶斯框架中开发PoMo方法，其目标如下：（i）将性状进化集成到模型中，因此该方法可以用于在统一分析中研究基因型和二元表型数据。我们将使用植物中的自交不亲和性作为应用程序，因为这些都是很好的研究，可以作为一个证明的原则。(ii)将方法从二元性状扩展到多个离散状态。与韦尔奇博士的小组一起，学生将使用飞行和觅食等特征应用于海鸟（Procellariiformes）。(iii)将基因表达的时间序列数据（RNA-Seq）作为物种树背景下的连续函数值性状进行处理。