*Jatinder.sangha2@agr.gc.ca

Improving grain yield (GY) and grain protein concentration (GPC) under variable climates are currently two important objectives of wheat breeding programs. Variability in environmental conditions can affect the reliability of these traits leading to uncertainty to growers and the industry. Marker trait associations (MTAs) are desirable to improve the selection procedure in wheat breeding for complex traits which are difficult to predict and phenotype.

We created 30 multi-environment datasets for grain yield and grain protein analysis using a set of 198 doubled haploid (DH) lines, derived from a Carberry/AC Cadillac cross, that were grown for six years (2014-2019) under rainfed and irrigated field environments. Approximately 11K polymorphic markers with from the 90K iSelect SNP array were deployed in a genome wide association study (GWAS) for high threshold MTA detection. A total of 71 MTAs were identified to be significantly associated to GY and GPC in different environments, of which 22 overlapped MTAs detected in both irrigated and rainfed environments.

The phenotypic variance explanation of each combined GY and GPC MTA was estimated using ridge-regression best linear unbiased prediction (rrBLUP), of which 19 MTAs had the same favourable/unfavourable alleles for GY and GPC. Gene identifications of 70 out of 71 combined MTAs were found in the NCBI and 54 in the EnsemblPlants databases, of which 55 genes had characterized functional annotations, including disease resistance, spike characteristics, zinc finger related domains, kinases, root traits and others.

Best linear unbiased estimate (BLUE) analysis used to detect DH lines having an ideal combination of favourable/unfavourable alleles differentiated the two parents, three high GY lines and three low GY lines with variation in physiological traits such as carbon isotope discrimination, stomatal conductance, and stomatal numbers.

Further research on the genetic basis of these SNP markers with GY, GPC, and various physiological traits is required to understand the benefits of this study to wheat breeders for improving wheat cultivars for variable environments.