A genome-wide association study of malting quality across eight U.S. barley breeding programs

Abstract

We report malt quality QTLs relevant to breeding with greater precision than previous mapping studies. The distribution of favorable alleles suggests strategies for marker-assisted breeding and germplasm exchange. This study leverages the breeding data of 1,862 barley breeding lines evaluated in 97 field trials for genome-wide association study of malting quality traits in barley. The mapping panel consisted of six-row and two-row advanced breeding lines from eight breeding populations established at six public breeding programs across the United States. A total of 4,976 grain samples were subjected to micro-malting analysis and mapping of nine quality traits was conducted with 3,072 SNP markers distributed throughout the genome. Association mapping was performed for individual breeding populations and for combined six-row and two-row populations. Only 16% of the QTL we report here had been detected in prior bi-parental mapping studies. Comparison of the analyses of the combined two-row and six-row panels identified only two QTL regions that were common to both. In total, 108 and 107 significant marker-trait associations were identified in all six-row and all two-row breeding programs, respectively. A total of 102 and 65 marker-trait associations were specific to individual six-row and two-row breeding programs, respectively indicating that most marker-trait associations were breeding population specific. Combining datasets from different breeding program resulted in both the loss of some QTL that were apparent in the analyses of individual programs and the discovery of new QTL not identified in individual programs. This suggests that simply increasing sample size by pooling samples with different breeding history does not necessarily increase the power to detect associations. The genetic architecture of malting quality and the distribution of favorable alleles suggest strategies for marker-assisted selection and germplasm exchange.

Effects of Barley (Hordeum Vulgare L.) Variety and Growing Environment on Beer Flavor

“…Some of the associations accounted for a high percentage of phenotypic variation (e.g., 68% for soluble protein on chromosome 5H and 55% for toffee on chromosome 7H). Five of the QTL positions for malting quality traits detected in this study are in the same chromosomal regions as those recently summarized by Mohammadi et al (27), an indirect validation of the multitrait QTL strategy employed with this small population size.…”

“…Samples from the 2014 experiment were micromalted by the USDA Cereal Crop Research Unit (Madison, WI, U.S.A.) using the procedures described by Mohammadi et al (27). Samples (250 g each) of the parents from the 2014 trial, and of all entries from the 2015 trials, were micromalted by Rahr Malting Co. (Shakopee, MN, U.S.A.) using a Joe White Malting unit.…”

“…Therefore, an augmented design (27) was used in which sensory assessments were structured so that in each session there were, first, reference (Miller High Life), parent, (Golden Promise and Full Pint), and check (Rahr Pils) beers and, second, unreplicated parent, doubled haploid, and CDC Copeland beers. Each tasting session included Miller High Life, Golden Promise, Full Pint, Rahr Pils, and 11 unreplicated beers.…”

“…Nonetheless, certain barley varieties are acknowledged by some brewers to have notable flavor attributes. These attributes have been sufficient to ensure the continued production of specific varieties even when newer varieties have superior agronomic characteristics, malting performance, or both (27). Notable examples are Golden Promise, Klages, and Maris Otter.…”

Development and Genetic Characterization of an Advanced Backcross-Nested Association Mapping (AB-NAM) Population of Wild × Cultivated Barley

“…Marker-trait associations were deemed significant when they were above a 0.05 false discovery rate (FDR) threshold. To obtain estimates of allele substitution effect, marker effects were calculated by passing a single marker to the mixed.solve function in the rrBLUP R package (Endelman 2011;Mohammadi et al 2015). For protein, the frequency of detection of marker-trait associations was calculated across sampling subsets, and those associations observed ,5% of samples are not reported.…”