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Detecting adaptive differentiation in structured populations with genomic data and common gardens

Emily B. Josephs, Jeremy J. Berg, Jeffrey Ross-Ibarra, Graham Coop
doi: https://doi.org/10.1101/368506
Emily B. Josephs
*Department of Evolution and Ecology, University of California, Davis, CA, USA
†Center for Population Biology, University of California, Davis, CA, USA
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  • For correspondence: emjo@ucdavis.edu
Jeremy J. Berg
‡Department of Biological Sciences, Columbia University, NY, USA
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Jeffrey Ross-Ibarra
§Department of Plant Sciences, University of California, Davis, CA, USA
†Center for Population Biology, University of California, Davis, CA, USA
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Graham Coop
*Department of Evolution and Ecology, University of California, Davis, CA, USA
†Center for Population Biology, University of California, Davis, CA, USA
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Abstract

Adaptation in quantitative traits often occurs through subtle shifts in allele frequencies at many loci, a process called polygenic adaptation. While a number of methods have been developed to detect polygenic adaptation in human populations, we lack clear strategies for doing so in many other systems. In particular, there is an opportunity to develop new methods that leverage datasets with genomic data and common garden trait measurements to systematically detect the quantitative traits important for adaptation. Here, we develop methods that do just this, using principal components of the relatedness matrix to detect excess divergence consistent with polygenic adaptation and using a conditional test to control for confounding effects due to population structure. We apply these methods to inbred maize lines from the USDA germplasm pool and maize landraces from Europe. Ultimately, these methods can be applied to additional domesticated and wild species to give us a broader picture of the specific traits that contribute to adaptation and the overall importance of polygenic adaptation in shaping quantitative trait variation.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted July 13, 2018.
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Detecting adaptive differentiation in structured populations with genomic data and common gardens
Emily B. Josephs, Jeremy J. Berg, Jeffrey Ross-Ibarra, Graham Coop
bioRxiv 368506; doi: https://doi.org/10.1101/368506
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Detecting adaptive differentiation in structured populations with genomic data and common gardens
Emily B. Josephs, Jeremy J. Berg, Jeffrey Ross-Ibarra, Graham Coop
bioRxiv 368506; doi: https://doi.org/10.1101/368506

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