I am interested in understanding the evolution of gene regulatory elements involved with the origins of behavioral diversity and its adaptive value. I use both empirical and computational methods that allow me to study regulatory evolution from single-gene to the genome-wide level. More specifically, I have used traditional PCR based techniques to identify genetic variants that differ between species, populations and individuals. However, my interests are focused on genes known to be involved with aspects of social cognition (i.e. vasopressin receptor Avpr1a which regulates pairbonding space use and sexual fidelity). More recently, I've also became interested in the use of bioinformatic tools to identify gene regulatory elements across the genome of Prairie voles using ChIP-seq data from the ventral pallidum. Next-generation sequencing methods have been also useful to me for exploring divergence at the level of natural populations of prairie voles. I have also been able to use transcriptomic data from the brain to understand species differences in gene expression between promiscuous and monogamous voles.

Now, as a postdoc in the Wray lab at Duke University. I am using ATAC-seq data sets from primate (including humans) brains, fibroblasts and adipocytes to identify putatively regulatory elements that have evolved by positive selection using branch-specific methods. One of the most interesting challenges that I have found with my approach so far, is how to identify good neutral proxy to compare different models of evolution in the background and foreground. For this reason, I am developing bioinformatic strategies and pipelines to sample neutrally-evolving alignments across primate genomes, while producing summary statistics to validate the results.

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