Lentil is a staple in many diets around the world and growing in popularity as a quick‐cooking, nutritious, plant‐based source of protein in the human diet. Lentil varieties are usually grown close to where they were bred. Future climate change scenarios will result in increased temperatures and shifts in lentil crop production areas, necessitating expanded breeding efforts. We show how we can use a daylength and temperature model to identify varieties most likely to succeed in these new environments, expand genetic diversity, and give plant breeders additional knowledge and tools to help mitigate these changes for lentil producers.

Understanding the genomic relationship between wild and cultivated genomes would facilitate access to the untapped variability found in crop wild relatives. We developed genome assemblies of a cultivated lentil (Lens culinaris) as well as a wild relative (L. ervoides). Comparative analyses revealed large-scale structural rearrangements and additional repetitive DNA in the cultivated genome, resulting in regions of reduced recombination, segregation distortion and permanent heterozygosity in the offspring of a cross between the two species. These novel findings provide plant breeders with better insight into how best to approach accessing the novel variability available in wild relatives.

Genomic selection (GS) is a marker-based selection initially suggested for livestock breeding and is being encouraged for crop breeding. Several statistical models are used to implement GS; however, none have been tested for use in lentil (Lens culinaris Medik.) breeding. This study was conducted to compare the accuracy of different GS models and prediction scenarios based on empirical data and to make recommendations for designing genomic selection strategies for lentil breeding. We evaluated nine single-trait (ST) models, two multiple-trait (MT) models, and a model that incorporates genotype × environment interaction (GEI) using populations from a lentil diversity panel and two recombinant inbred lines (RILs). The lines in all populations were phenotyped for five phenological traits and genotyped using a custom exome capture assay. Within-population, across-population, and across-environment genomic predictions were made. Prediction accuracy varied among the evaluated models, populations, prediction scenarios, and traits. Single-trait models showed similar accuracy in the absence of large effect quantitative trait loci (QTL) but BayesB outperformed all models when there were QTL with relatively large effects. Models that accounted for GEI and MT-GS models increased prediction accuracy for a low heritability trait by up to 66 and 14%, respectively. Moderate to high accuracies were obtained for within-population (range of .36-.85) and across-environment (range of .19-.89) predictions but across-population prediction accuracy was very low. Results suggest that GS can be implemented in lentil breeding to make predictions within populations and across environments, but across-population prediction should not be considered when the population size is small.

Breeding efforts have been important in addressing the challenges of wheat production in western Canada. We studied the effect of breeding on grain yield and other important traits of 100 wheat cultivars released in Canada from 1885 to 2012. The cultivars were grown in seven environments during 2011 to 2013. Grain yield was positively correlated with days to maturity and kernel weight but negatively correlated with plant height, lodging, and grain protein content. Results indicate that grain yield increased at a rate of 0.28% year–1 in 62 cultivars of Canada western red spring (CWRS) class, 1.2% year–1 in 9 cultivars of Canada prairie spring (CPS) class, but not in 14 studied cultivars of Canada western amber durum (CWAD) class due to breeding efforts. Grain protein content exhibited an increasing trend in cultivars of CWRS (0.05% year–1) and CPS (0.79% year–1) classes, and a decreasing trend in those of CWAD (0.23% year–1). Days to maturity decreased in CWRS (0.02% year‐1) and CWAD (0.09% year‐1) classes but remained unchanged in CPS class. Plant height exhibited a gradual decline in cultivars of CWRS (0.16% year–1) and CWAD class (0.44% year–1), but an increase in those of CPS class (0.50% year–1). Test weights showed an increasing trend in CWRS (0.04% year–1) and CPS (0.17% year–1) classes but not in CWAD class. Grain weight also increased over time in CWRS (0.06% year–1) and in CPS (0.41% year–1), but not in CWAD class. These results suggest that breeding efforts have improved yield, quality and other attributes in wheat cultivars of different Canadian wheat classes over the last 100 years.

No abstract