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Stable predictive markers for Phytophthora sojae avirulence genes that impair infection of soybean uncovered by whole genome sequencing of 31 isolates

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Title
Stable predictive markers for Phytophthora sojae avirulence genes that impair infection of soybean uncovered by whole genome sequencing of 31 isolates
Published in
BMC Biology, July 2018
DOI 10.1186/s12915-018-0549-9
Pubmed ID
Authors

Geneviève Arsenault-Labrecque, Humira Sonah, Amandine Lebreton, Caroline Labbé, Geneviève Marchand, Allen Xue, François Belzile, Brian J. Knaus, Niklaus J. Grünwald, Richard R. Bélanger

Abstract

The interaction between oomycete plant pathogen Phytophthora sojae and soybean is characterized by the presence of avirulence (Avr) genes in P. sojae, which encode for effectors that trigger immune responses and resistance in soybean via corresponding resistance genes (Rps). A recent survey highlighted a rapid diversification of P. sojae Avr genes in soybean fields and the need to deploy new Rps genes. However, the full genetic diversity of P. sojae isolates remains complex and dynamic and is mostly characterized on the basis of phenotypic associations with differential soybean lines. We sequenced the genomes of 31 isolates of P. sojae, representing a large spectrum of the pathotypes found in soybean fields, and compared all the genetic variations associated with seven Avr genes (1a, 1b, 1c, 1d, 1k, 3a, 6) and how the derived haplotypes matched reported phenotypes in 217 interactions. We discovered new variants, copy number variations and some discrepancies with the virulence of previously described isolates with Avr genes, notably with Avr1b and Avr1c. In addition, genomic signatures revealed 11.5% potentially erroneous phenotypes. When these interactions were re-phenotyped, and the Avr genes re-sequenced over time and analyzed for expression, our results showed that genomic signatures alone accurately predicted 99.5% of the interactions. This comprehensive genomic analysis of seven Avr genes of P. sojae in a population of 31 isolates highlights that genomic signatures can be used as accurate predictors of phenotypes for compatibility with Rps genes in soybean. Our findings also show that spontaneous mutations, often speculated as a source of aberrant phenotypes, did not occur within the confines of our experiments and further suggest that epigenesis or gene silencing do not account alone for previous discordance between genotypes and phenotypes. Furthermore, on the basis of newly identified virulence patterns within Avr1c, our results offer an explanation why Rps1c has failed more rapidly in the field than the reported information on virulence pathotypes.

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The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 21%
Student > Master 6 15%
Student > Bachelor 5 13%
Professor 2 5%
Student > Ph. D. Student 2 5%
Other 3 8%
Unknown 13 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 41%
Biochemistry, Genetics and Molecular Biology 2 5%
Nursing and Health Professions 1 3%
Environmental Science 1 3%
Immunology and Microbiology 1 3%
Other 3 8%
Unknown 15 38%