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Theor Appl Genet ; 128(1): 73-91, 2015 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-25367378

RESUMO

KEY MESSAGE: Using genome-wide association studies, 39 SNP markers likely tagging 21 different loci for carbon isotope ratio (δ (13) C) were identified in soybean. Water deficit stress is a major factor limiting soybean [Glycine max (L.) Merr.] yield. Soybean genotypes with improved water use efficiency (WUE) may be used to develop cultivars with increased yield under drought. A collection of 373 diverse soybean genotypes was grown in four environments (2 years and two locations) and characterized for carbon isotope ratio (δ(13)C) as a surrogate measure of WUE. Population structure was assessed based on 12,347 single nucleotide polymorphisms (SNPs), and genome-wide association studies (GWAS) were conducted to identify SNPs associated with δ(13)C. Across all four environments, δ(13)C ranged from a minimum of -30.55‰ to a maximum of -27.74‰. Although δ(13)C values were significantly different between the two locations in both years, results were consistent among genotypes across years and locations. Diversity analysis indicated that eight subpopulations could contain all individuals and revealed that within-subpopulation diversity, rather than among-subpopulation diversity, explained most (80%) of the diversity among the 373 genotypes. A total of 39 SNPs that showed a significant association with δ(13)C in at least two environments or for the average across all environments were identified by GWAS. Fifteen of these SNPs were located within a gene. The 39 SNPs likely tagged 21 different loci and demonstrated that markers for δ(13)C can be identified in soybean using GWAS. Further research is necessary to confirm the marker associations identified and to evaluate their usefulness for selecting genotypes with increased WUE.


Assuntos
Isótopos de Carbono/análise , Genótipo , Glycine max/genética , Polimorfismo de Nucleotídeo Único , Secas , Estudos de Associação Genética , Genética Populacional , Desequilíbrio de Ligação , Modelos Genéticos , Estresse Fisiológico
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