Predicting Trait Values and Evolutionary Change from DNA Sequences

By Zachary Gompert

Department of Biology, Utah State University 

How predictable is evolution? This question has been asked and answered in various ways. Studies of parallel and convergent evolution have shown species can predictably evolve similar phenotypes in response to similar environmental challenges, and this sometimes even involves the same genes or mutations. On the other hand, scientists have argued major external phenomena, such as cataclysmic meteor strikes and climate cycles, render long-term patterns of evolution unpredictable. Thus, evolution can be predictable to different degrees depending on the scale and specific features one is interested in.

The Gompert lab at Utah State University thinks a lot about predictability, both in terms of the predictability of evolution, and in terms of predicting phenotypes (i.e., trait values) from genetic/genomic data. In other words, we want to be able to predict traits from genes, and to predict how such traits and the underlying gene/allele frequencies change. And when we can't do these things, we want to understand why. Our work often relies on computationally intensive statistical modelling and simulations, which we use both to develop theory and to fit models. This requires access to large numbers of compute nodes, and in some cases large amounts of memory, substantial disk space and long-running jobs, all of which have been made possible by USU's partnership with the University of Utah CHPC.

Read more in the Spring 2018 newsletter.

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