Genome‐wide association mapping of agronomic traits and grain characteristics in spring wheat under conventional and organic management systems

Abstract

Previous genome‐wide association studies in Canadian spring wheat (Triticum aestivum L.) cultivars were based on consensus linkage maps of small population sizes. Here, we used a panel of 192 spring wheat cultivars widely used in western Canada to (a) explore the allelic variation and effects of six known genes and (b) identify genomic regions associated with eight agronomic traits and grain characteristics using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 map. The panel was evaluated for heading, maturity, plant height, lodging, grain yield, grain protein content, test weight, and kernel weight under four conventionally (high N) and three organically (low N) managed environments and genotyped with the wheat 90K single‐nucleotide polymorphism (SNP) array of which 23,342 SNPs were polymorphic. Using gene‐specific functional markers, the proportion of homozygous genotypes with favorable alleles was low for Fhb1 (7–8%), Rht‐D1 (14%), and Rht‐B1 (18%); moderate for Lr34/Yr18 (28–39%); and high for Glu‐A1 (78%) and Glu‐D1 (85%). We identified a total of 172 SNPs located at 94 genomic regions across 19 chromosomes of which 82 regions were associated with a single trait and 12 regions coincided with two to three traits. Twenty‐seven of the 94 regions (28%) were common between the conventional and organic managements systems; the remaining were management specific. Two of the identified regions on chromosome 5A (586.5–588.6 Mb) and 5B (575.8 Mb) coincided with the vernalization response Vrn‐A1 and Vrn‐B1 genes, respectively. The IWGSC RefSeq v2.0 physical positions presented here would serve as the basis for easily comparing independent discovery studies in the future.

Identification of Fusarium head blight sources of resistance and associated QTLs in historical and modern Canadian spring wheat

“…The historical and modern Canadian spring wheat varieties and lines used in the present study have been previously used for GWAS to map QTLs associated with agronomic traits and grain characteristics ( Semagn et al., 2022b ) and resistance to stripe rust, leaf rust, leaf spot, and common bunt ( Iqbal et al., 2022 ). Using the IWGSC RefSeq v2.0 physical information and the overall mean phenotype data of four conventionally and three organically managed environments, we uncovered a total of 108 QTLs associated with days to heading (9), days to maturity (12), plant height (15), lodging tolerance (12), thousand kernel weight (13), test weight (13), grain yield (16), and grain protein content (18).…”

“…Most meta-QTLs were physically located within a short interval, which requires further refinement using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq ( Zhu et al., 2021a ) physical map. In previous studies, we have used the IWGSC physical positions of the Wheat 90K iSelect array ( Wang et al., 2014 ) to characterize QTLs associated with agronomic traits and grain characteristics ( Semagn et al., 2022b ) and reaction to leaf rust, stripe rust, common bunt, and leaf spot ( Iqbal et al., 2023 ) in a historical and modern Canadian spring wheat association mapping panel.…”

Identification of Disease Resistance Parents and Genome-Wide Association Mapping of Resistance in Spring Wheat

“…The analyses were done using the imputed SNP genotype data, the kinship matrix to account for relatedness, the first three PCs from principal components as covariates to account for population structure, and the disease severity scores (BLUEs) computed per environment and combined across all environments. The threshold for declaring significant marker-trait association was set to p < 3.1 × 10 −4 or Log 10 (1/p) value ≥ 3.5, which is the same as the threshold used in a previous study [ 88 ]. Genome-wide p values were visualized in Manhattan plots using SNPevg [ 89 ].…”

Identification of Spring Wheat with Superior Agronomic Performance under Contrasting Nitrogen Managements Using Linear Phenotypic Selection Indices

“…The present study was conducted on 196 cultivars consisting of 176 historical and modern spring wheat cultivars registered in western Canada between 1905 and 2018, and 20 unregistered advanced breeding lines ( Table S1 ), which all, hereinafter, are referred to as cultivars. Of the 196 cultivars, 192 represented eight of the wheat classes in western Canada, originating from 14 breeding programs (institutions), and having been used in previous studies for molecular diversity and population structure analysis using the wheat 90K iSelect array [ 68 ], genome-wide association mapping [ 27 ], and as one of the populations in genomic selection [ 30 , 69 ]. The germplasm was evaluated for days to maturity, plant height, grain yield, and GPC at five conventionally (2017–2021) and at four organically (2018–2021) managed environments at the Crop Research Facility of the University of Alberta South Campus, Edmonton, Alberta, Canada.…”

“…The five breeding methods employed to develop cultivars for organic agriculture are the following: (i) indirect selection under conventional management, (ii) direct selection under organic management in all generations, (iii) selection under conventional management in early generations, followed by selection under organic management in advanced generations, (iv) marker-assisted selection (MAS), and (iv) genomic selection [ 4 , 14 , 15 ]. The University of Alberta Wheat Program, Edmonton, AB, has studied the pros and cons of these methods in diverse spring wheat lines and cultivars evaluated under both conventional and organic management systems, including comparing yield components [ 16 , 17 , 18 ], the performance of sole crop with mixtures [ 19 , 20 ], weed and nutrient competitive abilities [ 8 , 9 , 21 ], breadmaking quality [ 22 ], mapping genes and quantitative trait loci (QTL) associated with agronomic traits [ 23 , 24 , 25 , 26 , 27 , 28 , 29 ], and comparing the prediction accuracies of different genomic selection models [ 30 , 31 ]. Recently, we reported the physical positions of 44 QTLs associated with heading, flowering, and maturity [ 26 ] and 152 QTLs associated with nine agronomic and end-use quality traits in four recombinant inbred line (RIL) populations, which were evaluated under conventional and organic management systems [ 25 ].…”