Literature DB >> 35522263

Genetic mapping and genomic prediction of sclerotinia stem rot resistance to rapeseed/canola (Brassica napus L.) at seedling stage.

Jayanta Roy1, Luis E Del Río Mendoza2, Nonoy Bandillo1, Phillip E McClean1,3, Mukhlesur Rahman4.   

Abstract

KEY MESSAGE: GWAS detected ninety-eight significant SNPs associated with Sclerotinia sclerotiorum resistance. Six statistical models resulted in medium to high predictive ability, depending on trait, indicating potential of genomic prediction for disease resistance breeding. The lack of complete host resistance and a complex resistance inheritance nature between rapeseed/canola and Sclerotinia sclerotiorum often limits the development of functional molecular markers that enable breeding for sclerotinia stem rot (SSR) resistance. However, genomics-assisted selection has the potential to accelerate the breeding for SSR resistance. Therefore, genome-wide association (GWA) mapping and genomic prediction (GP) were performed using a diverse panel of 337 rapeseed/canola genotypes. Three-week-old seedlings were screened using the petiole inoculation technique (PIT). Days to wilt (DW) up to 2 weeks and lesion phenotypes (LP) at 3, 4, and 7 days post-inoculation (dpi) were recorded. A strong correlation (r = - 0.90) between DW and LP_4dpi implied that a single time point scoring at four days could be used as a proxy trait. GWA analyses using single-locus (SL) and multi-locus (ML) models identified a total of 41, and 208 significantly associated SNPs, respectively. Out of these, ninety-eight SNPs were identified by a combination of the SL model and any of the ML models, at least two ML models, or two traits. These SNPs explained 1.25-12.22% of the phenotypic variance and considered as significant, could be associated with SSR resistance. Eighty-three candidate genes with a function in disease resistance were associated with the significant SNPs. Six GP models resulted in moderate to high (0.42-0.67) predictive ability depending on SSR resistance traits. The resistant genotypes and significant SNPs will serve as valuable resources for future SSR resistance breeding. Our results also highlight the potential of genomic selection to improve rapeseed/canola breeding for SSR resistance.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Year:  2022        PMID: 35522263     DOI: 10.1007/s00122-022-04104-0

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  53 in total

1.  Haploview: analysis and visualization of LD and haplotype maps.

Authors:  J C Barrett; B Fry; J Maller; M J Daly
Journal:  Bioinformatics       Date:  2004-08-05       Impact factor: 6.937

2.  The impact of genetic architecture on genome-wide evaluation methods.

Authors:  Hans D Daetwyler; Ricardo Pong-Wong; Beatriz Villanueva; John A Woolliams
Journal:  Genetics       Date:  2010-04-20       Impact factor: 4.562

3.  Sclerotinia sclerotiorum (Lib.) de Bary: biology and molecular traits of a cosmopolitan pathogen.

Authors:  Melvin D Bolton; Bart P H J Thomma; Berlin D Nelson
Journal:  Mol Plant Pathol       Date:  2006-01-01       Impact factor: 5.663

4.  TASSEL: software for association mapping of complex traits in diverse samples.

Authors:  Peter J Bradbury; Zhiwu Zhang; Dallas E Kroon; Terry M Casstevens; Yogesh Ramdoss; Edward S Buckler
Journal:  Bioinformatics       Date:  2007-06-22       Impact factor: 6.937

5.  Response of Canola Cultivars to Sclerotinia sclerotiorum in Controlled and Field Environments.

Authors:  C A Bradley; R A Henson; P M Porter; D G LeGare; L E Del Río; S D Khot
Journal:  Plant Dis       Date:  2006-02       Impact factor: 4.438

6.  A One-Penny Imputed Genome from Next-Generation Reference Panels.

Authors:  Brian L Browning; Ying Zhou; Sharon R Browning
Journal:  Am J Hum Genet       Date:  2018-08-09       Impact factor: 11.025

Review 7.  Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

Authors:  José Crossa; Paulino Pérez-Rodríguez; Jaime Cuevas; Osval Montesinos-López; Diego Jarquín; Gustavo de Los Campos; Juan Burgueño; Juan M González-Camacho; Sergio Pérez-Elizalde; Yoseph Beyene; Susanne Dreisigacker; Ravi Singh; Xuecai Zhang; Manje Gowda; Manish Roorkiwal; Jessica Rutkoski; Rajeev K Varshney
Journal:  Trends Plant Sci       Date:  2017-09-28       Impact factor: 18.313

Review 8.  Bandwagons I, too, have known.

Authors:  Rex Bernardo
Journal:  Theor Appl Genet       Date:  2016-09-28       Impact factor: 5.699

9.  Plant genetics. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome.

Authors:  Boulos Chalhoub; France Denoeud; Shengyi Liu; Isobel A P Parkin; Haibao Tang; Xiyin Wang; Julien Chiquet; Harry Belcram; Chaobo Tong; Birgit Samans; Margot Corréa; Corinne Da Silva; Jérémy Just; Cyril Falentin; Chu Shin Koh; Isabelle Le Clainche; Maria Bernard; Pascal Bento; Benjamin Noel; Karine Labadie; Adriana Alberti; Mathieu Charles; Dominique Arnaud; Hui Guo; Christian Daviaud; Salman Alamery; Kamel Jabbari; Meixia Zhao; Patrick P Edger; Houda Chelaifa; David Tack; Gilles Lassalle; Imen Mestiri; Nicolas Schnel; Marie-Christine Le Paslier; Guangyi Fan; Victor Renault; Philippe E Bayer; Agnieszka A Golicz; Sahana Manoli; Tae-Ho Lee; Vinh Ha Dinh Thi; Smahane Chalabi; Qiong Hu; Chuchuan Fan; Reece Tollenaere; Yunhai Lu; Christophe Battail; Jinxiong Shen; Christine H D Sidebottom; Xinfa Wang; Aurélie Canaguier; Aurélie Chauveau; Aurélie Bérard; Gwenaëlle Deniot; Mei Guan; Zhongsong Liu; Fengming Sun; Yong Pyo Lim; Eric Lyons; Christopher D Town; Ian Bancroft; Xiaowu Wang; Jinling Meng; Jianxin Ma; J Chris Pires; Graham J King; Dominique Brunel; Régine Delourme; Michel Renard; Jean-Marc Aury; Keith L Adams; Jacqueline Batley; Rod J Snowdon; Jorg Tost; David Edwards; Yongming Zhou; Wei Hua; Andrew G Sharpe; Andrew H Paterson; Chunyun Guan; Patrick Wincker
Journal:  Science       Date:  2014-08-21       Impact factor: 47.728

10.  Transcriptome analysis of the plant pathogen Sclerotinia sclerotiorum interaction with resistant and susceptible canola (Brassica napus) lines.

Authors:  Kishore Chittem; William R Yajima; Rubella S Goswami; Luis E Del Río Mendoza
Journal:  PLoS One       Date:  2020-03-11       Impact factor: 3.240

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