Blanc J(1), Kremling KAG(2)(3), Buckler E(2)(4)(5), Josephs EB(6)(7). Author information:
(1)Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
(2)Plant Breeding and Genetics Section, School of Integrative Plant Science,
Cornell University, Ithaca, NY 14853, USA.
(3)Inari Agriculture, Cambridge, MA 02139, USA.
(4)Institute for Genomic Diversity, Cornell University, Ithaca, NY 14853, USA.
(5)United States Department of Agriculture-Agricultural Research Service, Robert
W. Holley Center for Agriculture and Health, Ithaca, NY 14853, USA.
(6)Department of Plant Biology, Michigan State University, East Lansing, MI
(7)Ecology, Evolution, and Behavior Program, Michigan State University, East
Lansing, MI 48824, USA.
Gene expression links genotypes to phenotypes, so identifying genes whose expression is shaped by selection will be important for understanding the traits and processes underlying local adaptation. However, detecting local adaptation for gene expression will require distinguishing between divergence due to selection and divergence due to genetic drift. Here, we adapt a QST-FST framework to detect local adaptation for transcriptome-wide gene expression levels in a population of diverse maize genotypes. We compare the number and types of selected genes across a wide range of maize populations and tissues, as well as selection on cold-response genes, drought-response genes, and coexpression clusters. We identify a number of genes whose expression levels are consistent with local adaptation and show that genes involved in stress response show enrichment for selection. Due to its history of intense selective breeding and domestication, maize evolution has long been of interest to researchers, and our study provides insight into the genes and processes important for in local adaptation of maize.
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