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Genome-wide association studies for yield-related traits in soft red winter wheat grown in Virginia.
Ward, Brian P; Brown-Guedira, Gina; Kolb, Frederic L; Van Sanford, David A; Tyagi, Priyanka; Sneller, Clay H; Griffey, Carl A.
Afiliação
  • Ward BP; Department Of Crop and Soil Environmental Sciences, Virginia Tech, Blacksburg, Virginia, United States of America.
  • Brown-Guedira G; Eastern Regional Small Grains Genotyping Laboratory, USDA-ARS, Raleigh, North Carolina, United States of America.
  • Kolb FL; Department of Crop Sciences, University of Illinois, Urbana, Illinois, United States of America.
  • Van Sanford DA; Department of Plant and Soil Sciences, University of Kentucky, Lexington, Kentucky, United States of America.
  • Tyagi P; Department of Crop and Soil Sciences, North Carolina State University, Raleigh, North Carolina, United States of America.
  • Sneller CH; Ohio Agricultural Research and Development Center, The Ohio State University, Wooster, Ohio, United States of America.
  • Griffey CA; Department Of Crop and Soil Environmental Sciences, Virginia Tech, Blacksburg, Virginia, United States of America.
PLoS One ; 14(2): e0208217, 2019.
Article em En | MEDLINE | ID: mdl-30794545
Grain yield is a trait of paramount importance in the breeding of all cereals. In wheat (Triticum aestivum L.), yield has steadily increased since the Green Revolution, though the current rate of increase is not forecasted to keep pace with demand due to growing world population and increasing affluence. While several genome-wide association studies (GWAS) on yield and related component traits have been performed in wheat, the previous lack of a reference genome has made comparisons between studies difficult. In this study, a GWAS for yield and yield-related traits was carried out on a population of 322 soft red winter wheat lines across a total of four rain-fed environments in the state of Virginia using single-nucleotide polymorphism (SNP) marker data generated by a genotyping-by-sequencing (GBS) protocol. Two separate mixed linear models were used to identify significant marker-trait associations (MTAs). The first was a single-locus model utilizing a leave-one-chromosome-out approach to estimating kinship. The second was a sub-setting kinship estimation multi-locus method (FarmCPU). The single-locus model identified nine significant MTAs for various yield-related traits, while the FarmCPU model identified 74 significant MTAs. The availability of the wheat reference genome allowed for the description of MTAs in terms of both genetic and physical positions, and enabled more extensive post-GWAS characterization of significant MTAs. The results indicate a number of promising candidate genes contributing to grain yield, including an ortholog of the rice aberrant panicle organization (APO1) protein and a gibberellin oxidase protein (GA2ox-A1) affecting the trait grains per square meter, an ortholog of the Arabidopsis thaliana mother of flowering time and terminal flowering 1 (MFT) gene affecting the trait seeds per square meter, and a B2 heat stress response protein affecting the trait seeds per head.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Triticum / Característica Quantitativa Herdável / Estudo de Associação Genômica Ampla Tipo de estudo: Prognostic_studies / Risk_factors_studies País/Região como assunto: America do norte Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Triticum / Característica Quantitativa Herdável / Estudo de Associação Genômica Ampla Tipo de estudo: Prognostic_studies / Risk_factors_studies País/Região como assunto: America do norte Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos