Literature DB >> 34964282

Mapping of partial resistance to Phytophthora sojae in soybean PIs using whole-genome sequencing reveals a major QTL.

Maxime de Ronne1, Parthasarathy Santhanam1, Benjamin Cinget1, Caroline Labbé1, Amandine Lebreton1, Heng Ye2, Tri D Vuong2, Haifei Hu3, Babu Valliyodan2,4, David Edwards3, Henry T Nguyen2, François Belzile1,5, Richard Bélanger1.   

Abstract

In the last decade, more than 70 quantitative trait loci (QTL) related to soybean [Glycine max (L.) Merr.] partial resistance (PR) against Phytophthora sojae have been identified by genome-wide association studies (GWAS). However, most of them have either a minor effect on the resistance level or are specific to a single phenotypic variable or one isolate, thereby limiting their use in breeding programs. In this study, we have used an analytical approach combining (a) the phenotypic characterization of a diverse panel of 357 soybean accessions for resistance to P. sojae captured through a single variable, corrected dry weight; (b) a new hydroponic assay allowing the inoculation of a combination of P. sojae isolates covering the spectrum of commercially relevant Rps genes; and (c) exhaustive genotyping through whole-genome resequencing (WGS). This led to the identification of a novel P. sojae resistance QTL with a relatively major effect compared with the previously reported QTL. The QTL interval, spanning ∼500 kb on chromosome (Chr) 15, does not colocalize with previously reported QTL for P. sojae resistance. Plants carrying the favorable allele at this QTL were 60% more resistant. Eight genes were found to reside in the linkage disequilibrium (LD) block containing the peak single-nucleotide polymorphism (SNP) including Glyma.15G217100, which encodes a major latex protein (MLP)-like protein, with a functional annotation related to pathogen resistance. Expression analysis of Glyma.15G217100 indicated that it was nearly eight times more highly expressed in a group of plant introductions (PIs) carrying the resistant (R) allele compared with those carrying the susceptible (S) allele within a short period after inoculation. These results offer new and valuable options to develop improved soybean cultivars with broad resistance to P. sojae through marker-assisted selection.
© 2021 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.

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Year:  2021        PMID: 34964282     DOI: 10.1002/tpg2.20184

Source DB:  PubMed          Journal:  Plant Genome        ISSN: 1940-3372            Impact factor:   4.089


  4 in total

Review 1.  Breeding for disease resistance in soybean: a global perspective.

Authors:  Feng Lin; Sushil Satish Chhapekar; Caio Canella Vieira; Marcos Paulo Da Silva; Alejandro Rojas; Dongho Lee; Nianxi Liu; Esteban Mariano Pardo; Yi-Chen Lee; Zhimin Dong; Jose Baldin Pinheiro; Leonardo Daniel Ploper; John Rupe; Pengyin Chen; Dechun Wang; Henry T Nguyen
Journal:  Theor Appl Genet       Date:  2022-07-05       Impact factor: 5.699

2.  Identification of Candidate Genes for a Major Quantitative Disease Resistance Locus From Soybean PI 427105B for Resistance to Phytophthora sojae.

Authors:  Stephanie Karhoff; Christian Vargas-Garcia; Sungwoo Lee; M A Rouf Mian; Michelle A Graham; Anne E Dorrance; Leah K McHale
Journal:  Front Plant Sci       Date:  2022-06-14       Impact factor: 6.627

Review 3.  The SoyaGen Project: Putting Genomics to Work for Soybean Breeders.

Authors:  François Belzile; Martine Jean; Davoud Torkamaneh; Aurélie Tardivel; Marc-André Lemay; Chiheb Boudhrioua; Geneviève Arsenault-Labrecque; Chloe Dussault-Benoit; Amandine Lebreton; Maxime de Ronne; Vanessa Tremblay; Caroline Labbé; Louise O'Donoughue; Vincent-Thomas Boucher St-Amour; Tanya Copley; Eric Fortier; Dave T Ste-Croix; Benjamin Mimee; Elroy Cober; Istvan Rajcan; Tom Warkentin; Éric Gagnon; Sylvain Legay; Jérôme Auclair; Richard Bélanger
Journal:  Front Plant Sci       Date:  2022-04-26       Impact factor: 6.627

4.  Genome-Wide Association Study of Partial Resistance to P. sojae in Wild Soybeans from Heilongjiang Province, China.

Authors:  Wei Li; Miao Liu; Yong-Cai Lai; Jian-Xin Liu; Chao Fan; Guang Yang; Ling Wang; Wen-Wei Liang; Shu-Feng Di; De-Yue Yu; Ying-Dong Bi
Journal:  Curr Issues Mol Biol       Date:  2022-07-17       Impact factor: 2.976

  4 in total

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