Skip to main content
http://Jaume%20Plensa's%20Mirall%20sculpture%20outside%20Allen%20Institute%20HQ%20in%20Seattle.

Morgan Wirthlin, Ph.D.

Scientist II

Bio:

Morgan Wirthlin is a Scientist II in the EvoGen team and Human Cell Types lab who joined the Allen Institute in 2022. She works to synthesize multi-omics datasets from a diversity of species, bringing a comparative evolutionary perspective to unlock the genomic bases of neural cell types and their resultant phenotypes. Previously, she completed a postdoctoral fellowship at Carnegie Mellon University’s Computational Biology Department and Neuroscience Institute. There, she helped to advance computational and experimental methods for connecting epigenomics to behavioral phenotypes, from bat vocal learning to manakin courtship dances. She received her B.A. in Biological Sciences (Evolution and Ecology) from the University of Chicago in 2009 and her Ph.D. in Behavioral Neuroscience from Oregon Health & Science University in 2016. In her dissertation work, she sought to identify the fundamental genomic and molecular properties that characterize brain circuits for vocal learning, the basis for birdsong and human speech. Her research seeks to understand the evolution of complex motor behaviors in a diversity of species through a synthesis of comparative genomics and experimental neurobiology, as well as developing new methods for exploring neurogenomics questions in naturalistic field settings.

Research Focus:

How are skilled, learned behaviors - such as the ability to speak and sing - encoded in our genes? The brain is comprised of a dazzling array of cell types all working in concert to produce behavior, governed by large-scale gene network interactions, the result of millions of years of evolutionary optimization. The falling costs of sequencing have led to an abundance of genomic data, holding great promise for unlocking the genetic basis for behavior. However, the development of effective strategies to decipher complex brain-gene network interactions has been lagging. I explore this problem by approaching computational genomics from the perspective of an evolutionary biologist. In my work, I have shown that one of the best resources we have for connecting genes to behavior is the rich diversity of emerging model species that share complex behavioral traits, such as the learned vocal behavior of songbirds, bats, and humans.
My Publications

Science Programs at Allen Institute