Gene's 'selective signature' aids detection of natural selection in microbial evolution

Scientists at MIT have come up with a mathematical approach for analyzing a protein simultaneously in a set of ecologically distinct species to identify occurrences of natural selection in an organism’s evolution.

The new method determines the “selective signature” of a gene, that is, the pattern of fast or slow evolution of that gene across a group of species, and uses that signature to infer gene function or to map changes to ecological shifts.

By reversing the usual order of inquiry—studying an organism, then trying to identify which genes are involved in a particular function—the scientists hope to hasten the understanding of microbial evolution by taking advantage of the nearly 2,500 microbes already sequenced.

“By comparing across species, we looked for changes in genes that reflect natural selection and then asked, ‘How does this gene relate to the ecology of the species it occurs in?’” said Eric Alm, the Doherty Assistant Professor of Ocean Utilization in the Department of Civil and Environmental Engineering. “The selective signature method also allows us to focus on a single species and better understand the selective pressures on it.”

“Our hope is that other researchers will take this tool and apply it to sets of related species with fully sequenced genomes to understand the genetic basis of that ecological divergence,” said graduate student B. Jesse Shapiro, who co-authored with Alm a paper published in the February issue of PLoS Genetics.

Their work also suggests that evolution occurs on functional modules—genes that may not sit together on the genome, but that encode proteins that perform similar functions.

“When we see similar results across all the genes in a pathway, it suggests the genomic landscape may be organized into functional modules even at the level of natural selection,” said Alm. “If that’s true, it may be easier than expected to understand the complex evolutionary pressures on a cell.”