CIS Computing & Information Services

Evolutionary Gene Networks

Evolutionary Gene Networks unravel the genetic mechanisms that enable parasites to thrive

Visualizations of several gene networks, showing differences in connectedness and topology. Credit: Ian Misner/URI

March, 2011

The Lane Lab (Department of Biological Sciences, University of Rhode Island) focuses on genome evolution and reduction in parasites. Parasitic organisms have independently evolved in every major lineage of life on Earth, but despite both the medical, economic and agricultural impacts of parasites, very little is known about the process by which a species adopts a parasitic life style.

By combining their own data with publicly available genomes, the Lane Lab has amassed a comparative dataset of nearly 30 genomes to investigate changes specific to a parasitic lifestyle, but these analyses are computationally intensive. In an effort to streamline massive comparative genomic analysis, the Lane Lab utilizes Evolutionary Gene Networks (EGNs) to compute pair-wise comparisons on a genome scale. EGNs offer a powerful visual and analysis tool to understanding genome evolution. Yet, a typical run of the EGN pipeline took up to 8 days on the Lane Lab's Mac Pro workstation. With help from the CCV User Services Group, this runtime was reduced to less than a day by scaling up the computationally-intensive all-to-all BLASTN component of the pipeline using the mpiBLAST package on Oscar.