The soybean–Phytophthora sojae interaction operates on a gene‐for‐gene relationship, where the product of a resistance gene (Rps) in the host recognizes that of an avirulence gene (Avr) in the pathogen to generate an incompatible reaction. To exploit this form of resistance, one must match with precision the appropriate Rps gene with the corresponding Avr gene. Currently, this association is evaluated by phenotyping assays that are labour‐intensive and often imprecise. To circumvent this limitation, we sought to develop a molecular assay that would reveal the avirulence allele of the seven main Avr genes (Avr1a, Avr1b, Avr1c, Avr1d, Avr1k, Avr3a, and Avr6) in order to diagnose with precision the pathotypes of P. sojae isolates. For this purpose, we analysed the genomic regions of these Avr genes in 31 recently sequenced isolates with different virulence profiles and identified discriminant mutations between avirulence and virulence alleles. Specific primers were designed to generate amplicons of a distinct size, and polymerase chain reaction conditions were optimized in a final assay of two parallel runs. When tested on the 31 isolates of known virulence, the assay accurately revealed all avirulence alleles. The test was further assessed and compared to a phenotyping assay on 25 isolates of unknown virulence. The two assays matched in 97% (170/175) of the interactions studied. Interestingly, the sole cases of discrepancy were obtained with Avr3a, which suggests a possible imperfect interaction with Rps3a. This molecular assay offers a powerful and reliable tool to exploit and study with greater precision soybean resistance against P. sojae.

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.