Joseph MinusPhD studentEmail: j.minus@qmul.ac.ukProfileProfileProject title: Integrating fossils and genomes to unravel the pattern of mammalian diversification throughtime. Summary: Phylogenetic methods using genomic data have been used with great success to construct and study the evolutionary relationships between extant mammal species. However, due to methodological constraints, morphological data has so far been underutilised and this has become a limiting factor when trying to estimate patterns of divergence and extinction in the evolutionary history of this group. The proposed project aims to use recent advances in Bayesian statistical methods to reconstruct a species-level mammal phylogeny by combining morphology (from extant and extinct species) and genomic data (from extant species) and use the reconstructed phylogeny to unravel patterns of mammal evolution through time. Morphological data will come mainly from CT scan data obtained from previous work and online databases, which will also be supplemented with new scans from museum specimens taken over the course of the project. Genomic data will be obtained from online databases. The advantage of the proposed methodology is that fossil species will be used as dated tips in the phylogenetic reconstruction, which, together with extensive phylogenomic sampling from extant mammals, would provide more information about early mammalian evolution compared to previous studies. This reconstructed phylogeny can then be used to estimate rates of evolution and divergence times in order to place key evolutionary events in their geological/environmental context, allowing us to address a number of important questions, such as the relationship of mammal diversification and extinction to palaeoclimate or to understand the genetic basis of morphological innovation in this group. This could in turn provide useful inferences for the current climate crisis and how it may affect patterns of diversity and evolution in modern mammals and other vertebrates. Supervisor Dr Mario Dos Reis Barros Research