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Genome-Wide Association Mapping and Genomic Prediction Analyses Reveal the Genetic Architecture of Grain Yield and Flowering Time Under Drought and Heat Stress Conditions in Maize.
Yuan, Yibing; Cairns, Jill E; Babu, Raman; Gowda, Manje; Makumbi, Dan; Magorokosho, Cosmos; Zhang, Ao; Liu, Yubo; Wang, Nan; Hao, Zhuanfang; San Vicente, Felix; Olsen, Michael S; Prasanna, Boddupalli M; Lu, Yanli; Zhang, Xuecai.
Afiliação
  • Yuan Y; Maize Research Institute, Sichuan Agricultural University, Wenjiang, China.
  • Cairns JE; Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, Chengdu, China.
  • Babu R; International Maize and Wheat Improvement Center, Texcoco, Mexico.
  • Gowda M; International Maize and Wheat Improvement Center, Harare, Zimbabwe.
  • Makumbi D; International Maize and Wheat Improvement Center, Texcoco, Mexico.
  • Magorokosho C; International Maize and Wheat Improvement Center, Nairobi, Kenya.
  • Zhang A; International Maize and Wheat Improvement Center, Nairobi, Kenya.
  • Liu Y; International Maize and Wheat Improvement Center, Harare, Zimbabwe.
  • Wang N; College of Bioscience and Biotechnology, Shenyang Agricultural University, Shenyang, China.
  • Hao Z; College of Bioscience and Biotechnology, Shenyang Agricultural University, Shenyang, China.
  • San Vicente F; International Maize and Wheat Improvement Center, Texcoco, Mexico.
  • Olsen MS; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
  • Prasanna BM; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
  • Lu Y; International Maize and Wheat Improvement Center, Texcoco, Mexico.
  • Zhang X; International Maize and Wheat Improvement Center, Nairobi, Kenya.
Front Plant Sci ; 9: 1919, 2018.
Article em En | MEDLINE | ID: mdl-30761177
ABSTRACT
Drought stress (DS) is a major constraint to maize yield production. Heat stress (HS) alone and in combination with DS are likely to become the increasing constraints. Association mapping and genomic prediction (GP) analyses were conducted in a collection of 300 tropical and subtropical maize inbred lines to reveal the genetic architecture of grain yield and flowering time under well-watered (WW), DS, HS, and combined DS and HS conditions. Out of the 381,165 genotyping-by-sequencing SNPs, 1549 SNPs were significantly associated with all the 12 trait-environment combinations, the average PVE (phenotypic variation explained) by these SNPs was 4.33%, and 541 of them had a PVE value greater than 5%. These significant associations were clustered into 446 genomic regions with a window size of 20 Mb per region, and 673 candidate genes containing the significantly associated SNPs were identified. In addition, 33 hotspots were identified for 12 trait-environment combinations and most were located on chromosomes 1 and 8. Compared with single SNP-based association mapping, the haplotype-based associated mapping detected fewer number of significant associations and candidate genes with higher PVE values. All the 688 candidate genes were enriched into 15 gene ontology terms, and 46 candidate genes showed significant differential expression under the WW and DS conditions. Association mapping results identified few overlapped significant markers and candidate genes for the same traits evaluated under different managements, indicating the genetic divergence between the individual stress tolerance and the combined drought and HS tolerance. The GP accuracies obtained from the marker-trait associated SNPs were relatively higher than those obtained from the genome-wide SNPs for most of the target traits. The genetic architecture information of the grain yield and flowering time revealed in this study, and the genomic regions identified for the different trait-environment combinations are useful in accelerating the efforts on rapid development of the stress-tolerant maize germplasm through marker-assisted selection and/or genomic selection.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Plant Sci Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Plant Sci Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China