People

Diego F. Salazar-Tortosa has been a Postdoctoral Researcher in the Enard Lab since 2019. He received his PhD in Systems and Fundamental Biology at the University of Granada. In his dissertation, he studied the response of pine trees (Pinus genus) to climate change using several complementary approaches: 1) Experimental studies to understand the physiological basis of differential environmental tolerance; 2) The integration of species distribution models and evolutionary (i.e. phylogenetic and phylgeographic) history to predict habitat suitability under climatic change; and 3) A comparative evolutionary approach to study the role of dispersal to cope with aridity and environmental heterogeneity. He is interested in organismal evolution along with its influence on the differentiation of complex traits and the response to the environment. In the Enard Lab, Diego is focusing on human population genetics and its implications for human health. He is developing new methods to detect selection that overcome limitations of previous approaches. He is using Mixture Density Networks to assess the probability of adaptation while accounting for genomic factors that confound the search for selection. He will apply this approach to statistics previously developed to detect selection, along with new ones developed in the Enard Lab that are able to detect older events of selection. He is also interested in applying these approaches to genetic association studies, which can benefit from considering genomic confounding factors. His list of publications can be found here.

Elise Lauterbur is a Postdoctoral Fellow in the Enard Lab. Her work centers around bridging molecular ecology and evolution, including developing novel field and computational methods. She obtained her PhD in 2019 in Ecology and Evolution from Stony Brook University where she was advised by Dr. Liliana Dávalos and Dr. Patricia Wright. There, she studied the physiology and genetics of cyanide adaptation in bamboo-specialized mammals, the properties of the coalescent in populations with small and declining effective population sizes, and adaptation via gene duplication. In the Enard Lab, she is focusing on two projects: (1) Developing a deep learning method using a convolutional neural network (CNN) to detect ancient and partial selective sweeps. Current detection methods lack power to detect old, incomplete sweeps, causing identification bias toward recent selection events. This CNN will allow better analysis of ancient signals of incomplete sweeps; and (2) Building a model of how pathogen pressure varies with environment. Infectious disease prevalence is controlled by complex interactions of host, pathogen, and environment, but broad patterns are hard to confirm. We are sequencing North American Myotis bats across habitats and correlating levels of genomic disease adaptation (using VIPs and BIPs) with local environmental conditions. In addition, in her teaching and mentoring, she endeavors to make learning a collaborative experience that supports and benefits from students of diverse backgrounds. For more about Elise, please see lauterbur.weebly.com.

Chenlu Di is a PhD student in the Enard Lab. She is interested in how viruses influence the evolution of their hosts. In example, the long-term impacts of past viral infections on the genetic diversity of host populations. She earned her bachelor’s degree from Zhejiang University where she worked on constructing the reverse genetic system of plant viruses. She is currently exploring the relationship between adaptation and human diseases.