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ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Plant, Soil and Nutrition Research » Research » Publications at this Location » Publication #384472

Research Project: Improving Crop Efficiency Using Genomic Diversity and Computational Modeling

Location: Plant, Soil and Nutrition Research

Title: Local adaptation contributes to gene expression divergence in maize

item BLANC, JENNIFER - University Of Chicago
item KREMLING, KARL - Cornell University
item Buckler, Edward - Ed
item JOSEPHS, EMILY - Michigan State University

Submitted to: Genes, Genomes, Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/20/2020
Publication Date: 1/23/2021
Citation: Blanc, J., Kremling, K., Buckler IV, E.S., Josephs, E. 2021. Local adaptation contributes to gene expression divergence in maize. Genes, Genomes, Genetics. 11(2):jkab004.

Interpretive Summary: Across the globe maize has adapted to thousands of local environments in the last several thousand years. These include adaptations to wide range of rainfall, soil conditions, and temperatures, which will all be critical as the US maize crop needs to adapt to climate change. The problem is how to identify the genes involved in local adaptation and apply that knowledge to making more maize to farmer’s fields in the US. This research developed a novel approach for comparing how maize genes were expressed relative to how maize gene variants were distributed across these environments. This provided insight into which genes were contributing to adaptation. The main contribution of this study was methodological--a novel approach that could be applied to any crop to identify adaptation genes. In the case of maize, it provides insight into how larger-scale studies could tap diversity on adaptation from maize landraces across the Americas.

Technical Abstract: 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.