Accurate estimation of the timing of selective events in human evolutionary history facilitates the understanding of human adaptations. The main goal ofthis project is to extend an existing phylogenetic- dating approach to estimate the time to the most recent common ancestor of a selected allele, as a proxy for the onset of selective pressures. The new method to estimate the onset of selective pressures will use a Hidden Markov Model to estimate, for each chromosome, the genomic region that hitchhiked along with the selected allele and the number of mutations that have accumulated since the tMRCA. Given an estimate of the mutation rate, the number of mutations across chromosomes provides an estimate ofthe tMRCA. Additionally, the project will evaluate the accuracy and precision of existing methods in estimating the age of the selected allele under various demographic models. Finally, the new method will be applied to population genetic data currently being generated for loci that have been predicted to have been subject to positive selection in one or more human populations. Adaptations to different environments are likely to play an important role in variation in disease prevalence among ethnic groups. Thus, an accurate characterization of local adaptation in humans is of fundamental importance to understanding disease susceptibility, as well as other phenotypes. Currently, it is thought that many local adaptations result from the dispersal of anatomically modern humans from East Africa. If so, patterns of polymorphism from non-African individuals should show the signature of adaptations dating to 40-100 Kya. To date, however, scans of polymorphism data from a limited number of populations have yielded conflicting results as to both the chronology and geography of local adaptations. I propose to develop and evaluate methods to estimate the timing of adaptation, thereby helping to interpret large-scale analysis of the signature of selection based on polymorphism data. My overall career goal is to become an independent researcher in a research institution. I am interested in distinuishing past selective events from other demographic forces that have influenced variation in the genome and understanding how those events have shaped the phenotypic diversity seen in populations today. The training proposed here provides an opportunity to develop a broader range of quantitative skills in theoretical population genetics. My graduate work focused on learning experimental techniques to study population genetics and molecular evolution. As a postdoctoral researcher at University of Chicago, I will have the unparalleled opportunity to develop a stronger background in statistical theoretical population genetics, under the guidance of Molly Przeworski and Jonathan Pritchard. With this training I will be able to develop cutting-edge methods for population genetics analysis and apply those methods to large amounts of sequence and genotype data: Sixth Briefly explain activities other than research and relate them to the proposed research training. During the first year of funding, I plan to supplement my postdoctoral research training with graduate courses in the Department of Statistics. The courses will help provide me with the necessary tools for rigorous statistical analysis of human population genetic data. Drs. Molly Przeworski and Jonathan Pritchard are leaders in human population genetics. They are particularly known for developing novel methods and applying them large-scale data sets to answer outstanding questions in human population genetics. Thus, they are the ideal mentors for the types of projects that I hope to execute during my post-doctoral training. Both of their groups interact on a daily basis which provides for stimulating environment for population genetics research. My postdoctoral experience will provide an opportunity for me to become a competitive population genetics researcher. I will strengthen my computational and quantitative expertise during my postdoctoral training. The research outlined in this proposal, combined with the faculty and resources at University of Chicago, is the perfect opportunity for me to expand my suite of research skills. Additionally, the collaborations that I establish while at University of Chicago will last well into my career as an independent researcher.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Postdoctoral Individual National Research Service Award (F32)
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Special Emphasis Panel (ZRG1-F08-F (20))
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Bender, Michael T
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Stanford University
Schools of Medicine
United States
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Kelley, Joanna L; Yee, Muh-Ching; Brown, Anthony P et al. (2016) The Genome of the Self-Fertilizing Mangrove Rivulus Fish, Kryptolebias marmoratus: A Model for Studying Phenotypic Plasticity and Adaptations to Extreme Environments. Genome Biol Evol 8:2145-54
Kelley, Joanna L; Peyton, Justin T; Fiston-Lavier, Anna-Sophie et al. (2014) Compact genome of the Antarctic midge is likely an adaptation to an extreme environment. Nat Commun 5:4611
Ma, Xin; Kelley, Joanna L; Eilertson, Kirsten et al. (2013) Population genomic analysis reveals a rich speciation and demographic history of orang-utans (Pongo pygmaeus and Pongo abelii). PLoS One 8:e77175
Kelley, Joanna L; Passow, Courtney N; Plath, Martin et al. (2012) Genomic resources for a model in adaptation and speciation research: characterization of the Poecilia mexicana transcriptome. BMC Genomics 13:652
Kelley, Joanna L (2012) Systematic underestimation of the age of selected alleles. Front Genet 3:165
Kelley, Joanna L; Yee, Muh-Ching; Lee, Clarence et al. (2012) The possibility of de novo assembly of the genome and population genomics of the mangrove rivulus, Kryptolebias marmoratus. Integr Comp Biol 52:737-42
Hernandez, Ryan D; Kelley, Joanna L; Elyashiv, Eyal et al. (2011) Classic selective sweeps were rare in recent human evolution. Science 331:920-4