Integrating traits into polymorphism-aware trees to better model speciation

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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.