Application of genomic assisted breeding for improvement of barley cultivars
Pauli, William Duke.
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The use of genome-wide association studies (GWAS) to detect quantitative trait loci (QTL) controlling complex traits has become a popular approach for studying key traits in crop plants. The goal of this research was to identify regions of the barley (Hordeum vulgare L.) genome that impact both agronomic and malting quality traits. By identifying these regions of the genome and their associated diagnostic markers, we gain an understanding of the genetic architecture of the traits as well as develop informative markers that can be utilized for marker-assisted selection. We used the data generated by the Barley Coordinated Agricultural Program to identify marker-trait associations impacting agronomic performance using a Q+K mixed linear model accounting for population structure and relatedness among lines. This data was also used to develop a genotyping platform specific to the Montana State University (MSU) Barley Breeding Program. This genotyping platform was used to genotype 650 advance generation lines from eleven bi-parental families to investigate the genetic basis of malting quality traits and the regions of the barley genome impacting them. We detected 41 significant marker-trait associations for the agronomic traits we studied with 31 of those being previously detected in bi-parental mapping studies. We detected 54 significant marker-trait associations for the malting quality traits with 24 of those being previously reported. The combined results from both studies indicate that major genes impacting key traits in barley are still segregating in US germplasm as well as in the MSU germplasm. This demonstrates that there is useful standing genetic variation that can be utilized for superior barley cultivar development and further genetic gain. Furthermore, by identifying the beneficial alleles, and their associated markers, we can form a "catalog" of major genes and QTL impacting agronomic and malting quality traits which can be used for marker-assisted selection. This work also demonstrates the feasibility and utility of conducting GWAS in narrow germplasm arrays like those found in regional breeding programs and serves as a paradigm for other cereal breeding programs. Together, these studies show how genomic data can be leveraged for varietal improvement in regional plant breeding programs.