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Genetics-inspired data-driven approaches explain and predict crop performance fluctuations attributed to changing climatic conditions

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Molecular Plant 2022年第2期15卷 203-206页

作者： Xianran Li Tingting Guo Guihua Bai Zhiwu Zhang deven see Juliet Marshall Kimberly A.Garland-Campbell Jianming Yu USDA Agricultural Research ServiceWheat HealthGeneticsand Quality Research UnitPullmanWA 99164USA Department of Agronomy Iowa State UniversityAmesIA 50011USA USDA Agricultural Research ServiceHard Winter Wheat Genetics Research UnitManhattanKS 66506USA Department of Crop and Soil Sciences Washington State UniversityPullmanWA 99164USA Department of Plant Sciences University of Idaho Research and ExtensionIdaho FallsID 83402USA

Dear Editor,Genetics-focused approaches have been widely used to uncover major genetic variants associated with performance ***,manipulating,and editing genetic variants significantly improve crop ***,the genetic component explains a portion of performance variation,and the environ-mental component contributes to the remaining,often large,portion(Laidig et al.,2017;Bonecke et al.,2020;Li et al.,2021).To ensure superior and robust performance,elite varieties are extensively tested across multiple years and *** extensive performance records,coupled with climatic profiles,could be leveraged to understand climate's impact on agriculture through approaches parallel to quantitative genetics approaches(Figure 1A).

关键词： performance attributed Figure

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Association Analysis of SP-SNPs and Avirulence Genes in Puccinia striiformis f. sp. tritici, the Wheat Stripe Rust Pathogen

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American Journal of Plant Sciences 2016年第1期7卷 126-137页

作者： Chongjing Xia Meinan Wang Anmin Wan Derick A. Jiwan deven R. see Xianming Chen Department of Plant Pathology Washington State University Pullman USA United States Department of Agriculture Agricultural Research Service Wheat Health Genetics and Quality Research Unit Pullman USA

Puccinia striiformis f. sp. tritici (Pst) is one of the pathogenic fungi on wheat, caused stripe rust that is a great threat for wheat production all over the world. Intensive efforts have been made to study genetics of wheat resistance to this disease, but few on avirulence of the pathogen due mainly to the nature of obligate biotrophism and the lack of systems for studying its genetics and molecular manipulations. To overcome these limitations, a natural Pst population comprising 352 isolates representative of a diverse virulence spectrum was genotyped using 97 secreted protein-single nucleotide polymorphism (SP-SNP) markers to identify candidate avirulence genes using association analysis. Among avirulence genes corresponding to 19 resistance genes, significantly associated SP-SNP markers were detected for avirulence genes AvYr1, AvYr2, AvYr6, AvYr7, AvYr8, AvYr44, AvYrExp2, AvYrSP, and AvYrTye. These results indicate that association analysis can be used to identify markers for avirulence genes. This study has laid the foundation for developing more SP-SNPs for mapping avirulence genes using segregating populations that can be generated through sexual reproduction on alternate hosts of the pathogen.

关键词： Puccinia striiformis f. sp. tritici Wheat Stripe Rust Avirulence Genes Secreted Proteins Single Nucleotide Polymorphism Association Analysis

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