Genomic Selection, Quantitative Trait Loci and Genome-Wide Association Mapping for Spring Bread Wheat (Triticum aestivum L.) Improvement

Molecular breeding involves the use of molecular markers to identify and characterize genes that control quantitative traits. Two of the most commonly used methods to dissect complex traits in plants are linkage analysis and association mapping. These methods are used to identify markers associated with quantitative trait loci (QTL) that underlie trait variation, which are used for marker assisted selection (MAS). Marker assisted selection has been successful to improve traits controlled by moderate to large effect QTL; however, it has limited application for traits controlled by many QTL with small effects. Genomic selection (GS) is suggested to overcome the limitation of MAS and improve genetic gain of quantitative traits. GS is a type of MAS that estimates the effects of genome-wide markers to calculate genomic estimated breeding values (GEBVs) for individuals without phenotypic records. In recent years, GS is gaining momentum in crop breeding programs but there is limited empirical evidence for practical application. The objectives of this study were to: i) evaluate the performance of various statistical approaches and models to predict agronomic and end-use quality traits using empirical data in spring bread wheat, ii) determine the effects of training population (TP) size, marker density, and population structure on genomic prediction accuracy, iii) examine GS prediction accuracy when modelling genotype-by-environment interaction (G × E) using different approaches, iv) detect marker-trait associations for agronomic and end-use quality traits in spring bread wheat, v) evaluate the effects of TP composition, cross-validation technique, and genetic relationship between the TP and SC on GS accuracy, and vi) compare genomic and phenotypic prediction accuracy. Six studies were conducted to meet these objectives using two populations of 231 and 304 spring bread wheat lines that were genotyped with the wheat 90K SNP array and phenotyped for nine agronomic and end-use quality traits. The main finding across these studies is that GS can accurately predict GEBVs for wheat traits and can be used to make predictions in different environments; thus, GS should be applied in wheat breeding programs. Each study provides specific insights into some of the advantages and limitations of different GS approaches, and gives recommendations for the application of GS in future breeding programs. Specific recommendations include using the GS model BayesB (especially for large effect QTL) for genomic prediction in a single environment, across-year genomic prediction using the reaction norm model, using a large TP size for making accurate genomic predictions, and not making across-population genomic predictions except for highly related population

Understanding photothermal interactions will help expand production range and increase genetic diversity of lentil (Lens culinaris Medik.)

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.This research was conducted as part of the ‘Application of Genomics to Innovation in the Lentil Economy (AGILE)' project funded by Genome Canada and managed by Genome Prairie. We are grateful for the matching financial support from the Saskatchewan Pulse Growers, Western Grains Research Foundation, the Government of Saskatchewan, and the University of Saskatchewan. We acknowledge the support from our international partners: University of Basilicata (UNIBAS) in Italy; Institute for Sustainable Agriculture (IAS) in Spain; Center for Agriculture Research in the Dry Areas (ICARDA) in Morocco, India and Bangladesh; Local Initiatives for Biodiversity, Research and Development (LI-BIRD) in Nepal; and United States Department of Agriculture (USDA CRIS Project 5348-21000-017-00D) in the USA, for conducting field experiments in their respective countries

CDC Covert durum wheat

CDC Covert durum wheat is adapted to the durum production area of the Canadian prairies. This conventional height durum wheat cultivar combines high grain yield with acceptable time to maturity, disease resistance, test weight and end-use suitability. CDC Covert is resistant to prevalent races of leaf and stem rust, has excellent common bunt resistance, and demonstrated end-use quality suitable for the Canada Western Amber Durum (CWAD) class.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author