Paper on network dynamics and protein evolution published

By | July 5, 2016

Congratulations to Brian Mannakee on his paper that just came out in PLoS Genetics. In it, we use dynamical systems biology models to predict rates of protein domain evolution. The success of these predictions suggests that natural selection is acting to preserve network dynamics in the face of perturbations from mutations. Although the models are imperfect, we think this work shows the power of systems biology models for quantitatively predicting evolutionary processes.


Paper on triallelic population genomics published

By | March 30, 2016

Triallelic figureCongratulations to Aaron Ragsdale on his paper that was just accepted for publication in Genetics. In it, we develop a novel diffusion model for trialleic sites, which required some non-trivial applied mathematics. We then apply the model to mutually nonsynonymous codons in Drosophila, to infer the correlation between selection coefficients for mutations at the same protein site. Remarkably, our inferred correlation agrees quantitatively with direct biochemical experiments in bacteria and yeast, suggesting that the correlation we measure is a fundamental property of protein evolution.

Two papers on African Pygmies published

By | January 21, 2016

PygmyTogetherCongratulations to Benson Hsieh on his two papers that were recently accepted for publication in Genome Research. Both result from our close collaboration with Michael Hammer, Benon’s PhD co-supervisor.

In the first paper, we infer a complex demographic model for Central African Pygmies and neighboring farmers. We then use that model as the basis for whole-genome neutral simulations that account for recombination and mutation rate heterogeneity. Those simulations then act as a null model for scanning the genome for evidence of natural selection.

In the second paper, we use a similar null-model approach to test for evidence of archaic admixture into the ancestors of contemporary pygmies. We show not only that such admixture occurred, but that it likely occurred several times.