Adapting Biosystems

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A major goal of my research is to understand the processes that generate diversity in the number of lineages. This is a primary challenge in the field of macroevolution, where I got my start in research; we are only beginning to be able to explain why some branches of the Tree of Life are so much more diverse than others. I have previously identified some fundamental regularities in the processes that shape biodiversity across disparate groups of organisms and across disparate time scales; in my research group, we are looking to understand the evolutionary and ecological mechanisms that might explain these regularities. I have also identified some fundamental limits to how much scientists can learn about the processes that generate biodiversity from molecular data alone and have shown that in some cases, researchers may have been pushing these limits. In the next phase of my research, I aim to extend our previous insights and quantify hard bounds on what information we can extract from molecular datasets regarding several other evolutionary phenomena that are of broad interest to researchers. This work will help us determine exactly what we can hope to learn (and exactly what we cannot), to develop novel strategies for making the most of available data, and to identify inferences for which will require additional types of data. These results are also relevant to the study of disease dynamics. The fact that for rapidly evolving pathogens, such SARS-CoV2, genetic diversity accumulates on the time-scale of epidemics, means we can potentially estimate epidemiological parameters such as R0 using molecular phylogenies. As the tools used to study viral lineage diversity are very similar to those used to study organismal diversity, I am extending our macroevolutionary work to quantify the information content of viral phylogenies. This will provide a better measure of our confidence in epidemiological inferences. Alongside this work, I am developing novel approaches for better integrating molecular data with more conventional case count data so that these different types of information can reciprocally inform one another. I also plan to use macroevolutionary tools to reconstruct the diversification of B-cell (antibody) sequences. Working with immunologists, I am developing new statistical techniques for measuring the evolution of an individuals B-cell repertoire as well as precisely defining what we can and cannot learn from purely sequence-based approaches.