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United States Department of Agriculture

Agricultural Research Service

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Research Project: Analysis of Clinal Variation in Maize: Implementation of an Experimental Framework for Studying Crop Adaptation

Location: Corn Insects and Crop Genetics Research

Project Number: 5030-21000-060-01-R
Project Type: Reimbursable Cooperative Agreement

Start Date: Apr 1, 2011
End Date: Mar 31, 2017

The proposed project has two general goals: first, to increase knowledge about the genetic architecture of response to artificial selection for adaptation; second, to characterize geoclimatic influences on tropical maize phenotypes, haplotypes, and ecology. The specific scientific aims of this project are 1) Evaluate Association-Selection Mapping as an experimental approach for characterizing the genetic architecture of adaptation, and 2) Identify geoclimatic responsive haplotypes limiting temperate adaptation and maize improvement.

Increasing the resiliency and sustainability of crop production requires approaches that harness genetic diversity to adapt plants to existing and future environmental challenges. Tropical maize possesses significantly greater genetic variation than U.S. maize and harbors favorable alleles for numerous traits that are absent from U.S. maize that will be important for adapting to climate change. The search for favorable alleles for maize productivity under abiotic stress and emerging pathogens will require meaningful phenotypic evaluation of tropical diversity in the temperate target environments where maize is produced. This proposal leverages contemporary conventional breeding techniques combined with technologies that utilize recent advances in genomic sequence information to develop new plant varieties. It addresses core issues related to access and use of novel genetic diversity and will directly facilitate crop improvement by increasing knowledge of adaptation and response to selection. The interdisciplinary team will conduct Association-Selection Mapping studies across 10 environments in North America, test ecogeographic consequences of photoperiod and temperature during artificial selection, and identify alleles that can mitigate the photoperiod-response problem faced by corn breeders.

Last Modified: 10/17/2017
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