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The SoyaGen Project: Putting Genomics to Work for Soybean Breeders.

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.

Belzile F, Jean M, Torkamaneh D, Tardivel A, Lemay MA, Boudhrioua C, Arsenault-Labrecque G, Dussault-Benoit C, Lebreton A, de Ronne M, Tremblay V, Labbé C, O'Donoughue L, St-Amour VB, Copley T, Fortier E, Ste-Croix DT, Mimee B, Cober E, Rajcan I, Warkentin T, Gagnon É, Legay S, Auclair J, Bélanger R.

Front Plant Sci. 2022 Apr 26;13:887553. doi: 10.3389/fpls.2022.887553.

Abstract

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 sojaeHeterodera glycinesSclerotinia 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.

 

See https://pubmed.ncbi.nlm.nih.gov/35557742/

 

FIGURE 5

Genome-wide association mapping of resistance to Phytophthora sojae in a soybean population of 357 plant introductions (PIs). Reproduced with permission from de Ronne et al. (2021)

 

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