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Development of Targeting Induced Local Lesions IN Genomes TILLING Populations in Small Grain Crops by Ethyl Methanesulfonate Mutagenesis
Published on: July 16, 2019
Tracing post-domestication historical events and screening pre-breeding germplasm from large gene pools in wheat in
Demissew Sertse1, Aramde Fetene2, Jen Leon3
1Department of Plant Science, University of Manitoba, Winnipeg, MB, Canada. demis.desta@umanitoba.ca.
Abstract:
Wheat, particularly common wheat (Triticum aestivum L.), is a major crop accounting for 25% of the world cereal production and thriving in diverse ecogeographic regions. Its adaptation to diverse environments arises from its three distinct genomes adapted to different environments and post-domestication anthropogenic interventions. In search of key genomic regions revealing historic events and breeding significance to common wheat, we performed genome scan and genome-environment association (GEA) analyses using high-marker density genotype datasets. Whole-genome scans revealed highly differentiated regions on chromosomes 2A, 3B, and 4A. In-depth analyses corroborated our previous prediction of the 4A differentiated region signifying the separation between Spelt/Macha and other wheat types. Individual chromosome scans captured key introgressions, including one from T. timopheevii and one from Thinopyrum ponticum on 2B and 3D, respectively, as well as known genes such as Vrn-A1 on 5A. GEA highlighted loci linked to latitude-induced environmental variations, influencing traits such as photoperiodism and responses to abiotic stress. Variation at the Vrn-A1 locus on 5A assigned accessions to two haplotypes (6% and 94%). Further analysis on Vrn-A1 coding gene revealed four subgroups of the major haplotype, while the minor haplotype remained undifferentiated. Analyses at differentiated loci mostly dichotomized the population, illustrating the possibility of isolating pre-breeding materials with desirable traits from large gene pools in the absence of phenotype data. Given the current availability of broad genetic data, the genome-scan-GEA hybrid can be an efficient and cost-effective approach for pinpointing environmentally resilient pre-breeding germplasm from vast gene pools, including gene banks regardless of trait characterization.
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