BBB seminar: David A. Liberles

David A. Liberles
Computational Biology Unit, Bergen Centre for Computational Science, University of Bergen

As genomes evolve through drift and under divergent selective pressure, gene content, sequence, expression, and function change. A resource, The Adaptive Evolution Database (TAED) has been created to describe this change, indexed phylogenetically. The initial characterization of genomic data in the database is gene sequence evolution, with statistical measures like the ratio of nonsynonymous to synonymous nucleotide substitution rates (Ka/Ks) as a measure of selective pressure. A subset of genes under positive selective pressure (potentially with changed functions) is being characterized in more detail. One example, myostatin, a negative regulator of skeletal muscle appears to have been under strong positive selective pressure early in the divergence of ruminant artiodactyls and this will be described in more detail.

Further, a simple physical framework has been established to characterize the evolution of protein models that fold and bind after gene duplication events. Initially, this framework has been used to model duplicate gene retention rates through subfunctionalization. The model is currently being extended to characterize the fold distribution in genomes using principles from physical chemistry and population genetics. Ultimately, we hope to tie this together into a greater understanding of how genes and genomes evolve and what this means for organismal phenotypes.