Andrew Sharo

Computational Biologist | NSF Postdoctoral Research Fellow Paleogenomics Group, UC Santa Cruz

I am a biologist interested in three main areas:

1. Wild animal welfare. Although rarely studied outside the ecology of fear, many wild animals have the capacity to experience positive and negative mental states. This capacity possibly evolved to improve decision making, driving individuals away from harmful stimuli and toward fitness-enhancing behaviors. Measuring welfare in wild animals has the potential to explain behavior, predict population trends, and aid in conservation efforts. Additionally, given the unfathomable number of wild vertebrates (at least 10^13 individuals) and invertebrates (at least 10^18 individuals), determining which animals have a capacity for welfare has important philosophical implications.

2. Conservation genetics. I have a longstanding interest in using DNA sequencing to give context to the population changes experienced by threatened species in the Anthropocene. As an NSF Postdoctoral Research Fellow in Beth Shapiro’s Paleogenomics Group, and in collaboration with Carlos Garza at NOAA, I compared modern and historical DNA in steelhead trout to quantify introgression from domesticated hatchery trout. Additionally, I have sequenced several genomes of the extinct heath hen, to better understand their demise and the unique adaptive variants they possessed. Both of these projects relied on museum specimens, an unparalleled resource. 

3.    Methods for computational biology. As a PhD student in Steven Brenner’s group at UC Berkeley, I worked to improve the diagnostic rate for rare genetic diseases in collaboration with clinicians at UCSF. I developed a novel structural variant impact predictor, StrVCTVRE, that helps clinical researchers prioritize germline structural variants likely to cause disease. When clinical labs find novel pathogenic variants, they catalog them in variant databases, such as ClinVar. In a separate project, I developed novel methods to assess whether these variant databases have improved over time, and how misclassification varies by ancestry.

To learn more about my current and past projects, see my research  and outreach pages.