Department of Neurobiology and Behavior
Mudd hall, 215 Tower Rd, Ithaca, NY
The ‘omics revolution in evolutionary biology and related fields has opened new doors to a broader and more precise understanding of the fundamental processes that govern the natural history on earth. Generating billions of copies of DNA fragments from across entire genomes has become accessible for pretty much every organism. These data reveal the blueprints for natural variation and also carry the historical signatures of millions of years of evolution.
I am interested in using genome scale data for two main reasons. The first one is to perform population genomic and phylogenomic analyses that can uncover the evolutionary relation of closely related species or population that are currently on potentially different evolutionary trajectories because of variation in the selection landscape. Genomic data can reveal whether geographically disperse populations are still exchanging genes, whether population sizes have varied thereby constraining the effects from random genetic drift on population specific allele frequencies. In a population genomic scan in two behaviourally divergent but morphologically and ecologically cryptic Gryllus species we uncovered a strong role for ancestral gene flow and showed how despite the long history of homogenizing effects from gene exchange among divergent populations genes associated with song and preference behaviour showed strong signatures of selection (in review). In my current work on Hawaiian sword-tail crickets I can use the extensive biogeographic information available for the volcanic islands of the Hawaiian archipelago to generate hypotheses based on the arrival and dispersal of early cricket population, shedding rare lights on the evolutionary trajectory from small groups of founders to present day populations (see also Research).
The second reason is to integrate quantitative genetic insights and the variability in genetic divergence across the genome. Each genomic region is, in the broadest sense, associated with a different biological function (or lack thereof). Therefore, selection, drift, and gene flow are expected to affect different genomic regions differently. To understand the evolution of a group of species, we must thus examine the evolutionary history of different genomic regions separately. Ultimately, coupling the insights into the genetic and genomic architecture (e.g. the loci underlying variation in song behaviour in crickets and the variation in recombination rates across their genomes) with those from genomic scans in diverse population can make strong headway into charting past and predicting future evolutionary trajectories.