The SoyaGen Project: Putting Genomics to Work for Soybean Breeders

Frontiers in Plant Science

Elroy Cober¹  Dave T. Ste-Croix²  Benjamin Mimee²  Tanya Copley³  Louise O’Donoughue³  Eric Fortier³  Aurélie Tardivel³  Vincent-Thomas Boucher St-Amour³  Istvan Rajcan⁴  Tom Warkentin⁵  Richard Bélanger⁶  Davoud Torkamaneh⁶  Amandine Lebreton⁶  Martine Jean⁶  Vanessa Tremblay⁶  Chloe Dussault-Benoit⁶  Marc-André Lemay⁶  Chiheb Boudhrioua⁶  Geneviève Arsenault-Labrecque⁶  Caroline Labbé⁶  François Belzile⁶  Maxime de Ronne⁶  Sylvain Legay⁷  Éric Gagnon⁸  Jérôme Auclair⁹ 

[1] Agriculture and Agri-Food Canada, Ottawa, ON, Canada;Agriculture and Agri-Food Canada, St-Jean-sur-Richelieu, QC, Canada;Centre de Recherche sur les Grains (CEROM), Saint-Mathieu-de-Beloeil, QC, Canada;Department of Plant Agriculture, University of Guelph, Guelph, ON, Canada;Department of Plant Sciences, University of Saskatchewan, Saskatoon, SK, Canada;Département de Phytologie, Université Laval, Quebec City, QC, Canada;Semences Prograin Inc., Saint-Césaire, QC, Canada;Sevita Genetics, Inkerman, ON, Canada;Sollio Agriculture, Saint-Hyacinthe, QC, Canada;

关键词: translational genomics;    genetic diversity;    marker-trait associations;    haplotypes;    genomic prediction;   

DOI  :  10.3389/fpls.2022.887553

来源: DOAJ

【 摘 要 】

The SoyaGen project was a collaborative endeavor involving Canadian soybean researchers and breeders from academia and the private sector as well as international collaborators. Its aims were to develop genomics-derived solutions to real-world challenges faced by breeders. Based on the needs expressed by the stakeholders, the research efforts were focused on maximizing realized yield through optimization of maturity and improved disease resistance. The main deliverables related to molecular breeding in soybean will be reviewed here. These include: (1) SNP datasets capturing the genetic diversity within cultivated soybean (both within a worldwide collection of > 1,000 soybean accessions and a subset of 102 short-season accessions (MG0 and earlier) directly relevant to this group); (2) SNP markers for selecting favorable alleles at key maturity genes as well as loci associated with increased resistance to key pathogens and pests (Phytophthora sojae, Heterodera glycines, Sclerotinia sclerotiorum); (3) diagnostic tools to facilitate the identification and mapping of specific pathotypes of P. sojae; and (4) a genomic prediction approach to identify the most promising combinations of parents. As a result of this fruitful collaboration, breeders have gained new tools and approaches to implement molecular, genomics-informed breeding strategies. We believe these tools and approaches are broadly applicable to soybean breeding efforts around the world.

【 授权许可】

Unknown