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Genome-Wide Association Study of Multi-Traits in Common Bean (Phaseolus Vulgaris L.)

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Abstract Background: Micronutrient deficiencies caused by lack of Iron (Fe), Zinc (Zn) and Vitamin A have negative effects on human health worldwide. Even though common bean meets Fe and Zn deficiencies based on recommended dietary allowances, the cooking time remains an important challenge. Understanding the genome organization, the loci and genes localization controlling multiple traits is crucial for developing enhanced micronutrient content and improved common bean with short cooking time. Results: In this study, GWAS method was used to determine SNPs associated with four traits studied, including water uptake, cooking time, Fe and Zn concentration level, using ~5,000 SNPs for a panel of 206 genotypes. By the analysis of population structure, 206 common bean genotypes were formed in three groups, the Mesoamerican gene pool, the Andean gene pool, and the admixture gene pool using the Bayesian method. With the significance levels between p = 2.94 x 10-08 to p = 8.33 x 10-03 and phenotypic variation of 8.26% to 18.19%, total of 10 SNPs was found to be significantly associated with traits on chromosomes Pv03, Pv04 and Pv10. Among of these SNPs, four SNPs were associated with water uptake, another four SNPs with the cooking time, one SNP with Zn concentration and one of less significant SNP associated with Fe concentration. Within the range or nearby the peak of significant SNP, putative loci encoding pectin degradation, cell structure and cellular exchange/transport were identified, suggesting these loci may play important roles in modulating expression of traits.Conclusion: The resultant data in this study contributed on deciphering the molecular mechanisms associated with water uptake, cooking time and micronutrient contents in common bean. The investigation of association between phenotypic and genotypic data has showed that GWAS approach is a powerful tool to dissect genetic architecture of complex traits and cooperate molecular breeding for advanced genotypes with enhanced micronutrients and short cooking time.
Title: Genome-Wide Association Study of Multi-Traits in Common Bean (Phaseolus Vulgaris L.)
Description:
Abstract Background: Micronutrient deficiencies caused by lack of Iron (Fe), Zinc (Zn) and Vitamin A have negative effects on human health worldwide.
Even though common bean meets Fe and Zn deficiencies based on recommended dietary allowances, the cooking time remains an important challenge.
Understanding the genome organization, the loci and genes localization controlling multiple traits is crucial for developing enhanced micronutrient content and improved common bean with short cooking time.
Results: In this study, GWAS method was used to determine SNPs associated with four traits studied, including water uptake, cooking time, Fe and Zn concentration level, using ~5,000 SNPs for a panel of 206 genotypes.
By the analysis of population structure, 206 common bean genotypes were formed in three groups, the Mesoamerican gene pool, the Andean gene pool, and the admixture gene pool using the Bayesian method.
With the significance levels between p = 2.
94 x 10-08 to p = 8.
33 x 10-03 and phenotypic variation of 8.
26% to 18.
19%, total of 10 SNPs was found to be significantly associated with traits on chromosomes Pv03, Pv04 and Pv10.
Among of these SNPs, four SNPs were associated with water uptake, another four SNPs with the cooking time, one SNP with Zn concentration and one of less significant SNP associated with Fe concentration.
Within the range or nearby the peak of significant SNP, putative loci encoding pectin degradation, cell structure and cellular exchange/transport were identified, suggesting these loci may play important roles in modulating expression of traits.
Conclusion: The resultant data in this study contributed on deciphering the molecular mechanisms associated with water uptake, cooking time and micronutrient contents in common bean.
The investigation of association between phenotypic and genotypic data has showed that GWAS approach is a powerful tool to dissect genetic architecture of complex traits and cooperate molecular breeding for advanced genotypes with enhanced micronutrients and short cooking time.

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