Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments
The genetic improvement of economically important production traits of dry bean (Phaseolus vulgaris L.), for geographic regions where production is threatened by drought and high temperature stress, is challenging because of the complex genetic nature of these traits. Large scale SNP data sets for the two major gene pools of bean, Andean and Middle American, were developed by mapping multiple pools of genotype-by-sequencing reads and identifying over 200k SNPs for each gene pool against the most recent assembly of the P. vulgaris genome sequence. Moderately sized Bean Abiotic Stress Evaluation (BASE) panels, consisting of genotypes appropriate for production in Central America and Africa, were assembled. Phylogenetic analyses demonstrated the BASE populations represented broad genetic diversity for the appropriate races within the two gene pools. Joint mixed linear model genome-wide association studies with data from multiple locations discovered genetic factors associated with four production traits in both heat and drought stress environments using the BASE panels. Pleiotropic genetic factors were discovered using a multi-trait mixed model analysis. SNPs within or near candidate genes associated with hormone signaling, epigenetic regulation, and ROS detoxification under stress conditions were identified and can be used as genetic markers in dry bean breeding programs.
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Format: | Journal Article biblioteca |
Language: | English |
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Oxford University Press
2019-06
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Subjects: | phaseolus vulgaris, common beans, gene pools, andean, drought stress, abiotic stress, |
Online Access: | https://hdl.handle.net/10568/102152 https://doi.org/10.1534/g3.119.400072 |
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dig-cgspace-10568-1021522023-12-08T19:36:04Z Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments Oladzad, Atena Porch, Timothy G. Rosas, Juan Carlos Moghaddam, Samira Mafi Beaver, James S. Beebe, Stephen E. Burridge, Jimmy Jochua, Celestina Nhagupana Miguel, Magalhaes Amade Miklas, Phillip N. Raatz, Bodo White, Jeffrey W. Lynch, Jonathan P. McClean, Phillip E. phaseolus vulgaris common beans gene pools andean drought stress abiotic stress The genetic improvement of economically important production traits of dry bean (Phaseolus vulgaris L.), for geographic regions where production is threatened by drought and high temperature stress, is challenging because of the complex genetic nature of these traits. Large scale SNP data sets for the two major gene pools of bean, Andean and Middle American, were developed by mapping multiple pools of genotype-by-sequencing reads and identifying over 200k SNPs for each gene pool against the most recent assembly of the P. vulgaris genome sequence. Moderately sized Bean Abiotic Stress Evaluation (BASE) panels, consisting of genotypes appropriate for production in Central America and Africa, were assembled. Phylogenetic analyses demonstrated the BASE populations represented broad genetic diversity for the appropriate races within the two gene pools. Joint mixed linear model genome-wide association studies with data from multiple locations discovered genetic factors associated with four production traits in both heat and drought stress environments using the BASE panels. Pleiotropic genetic factors were discovered using a multi-trait mixed model analysis. SNPs within or near candidate genes associated with hormone signaling, epigenetic regulation, and ROS detoxification under stress conditions were identified and can be used as genetic markers in dry bean breeding programs. 2019-06 2019-07-10T19:40:07Z 2019-07-10T19:40:07Z Journal Article Oladzad, Atena; Porch, Timothy; Rosas, Juan Carlos; Moghaddam, Samira Mafi Beaver, James; Beebe, Steve E.; Burridge, Jimmy ; Jochua, Celestina Nhagupana; Miguel, Magalhaes Amade; Miklas, Phillip N.; Ratz, Bodo; White, Jeffery W.; Lynch, Jonathan & McClean, Phillip E. (2019). Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments. G3: Genes, Genomes, Genetics, 9(6): 1881-1892 2160-1836 https://hdl.handle.net/10568/102152 https://doi.org/10.1534/g3.119.400072 en CC-BY-4.0 Open Access 1881-1892 Oxford University Press G3: Genes, Genomes, Genetics |
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phaseolus vulgaris common beans gene pools andean drought stress abiotic stress phaseolus vulgaris common beans gene pools andean drought stress abiotic stress |
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phaseolus vulgaris common beans gene pools andean drought stress abiotic stress phaseolus vulgaris common beans gene pools andean drought stress abiotic stress Oladzad, Atena Porch, Timothy G. Rosas, Juan Carlos Moghaddam, Samira Mafi Beaver, James S. Beebe, Stephen E. Burridge, Jimmy Jochua, Celestina Nhagupana Miguel, Magalhaes Amade Miklas, Phillip N. Raatz, Bodo White, Jeffrey W. Lynch, Jonathan P. McClean, Phillip E. Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments |
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The genetic improvement of economically important production traits of dry bean (Phaseolus vulgaris L.), for geographic regions where production is threatened by drought and high temperature stress, is challenging because of the complex genetic nature of these traits. Large scale SNP data sets for the two major gene pools of bean, Andean and Middle American, were developed by mapping multiple pools of genotype-by-sequencing reads and identifying over 200k SNPs for each gene pool against the most recent assembly of the P. vulgaris genome sequence. Moderately sized Bean Abiotic Stress Evaluation (BASE) panels, consisting of genotypes appropriate for production in Central America and Africa, were assembled. Phylogenetic analyses demonstrated the BASE populations represented broad genetic diversity for the appropriate races within the two gene pools. Joint mixed linear model genome-wide association studies with data from multiple locations discovered genetic factors associated with four production traits in both heat and drought stress environments using the BASE panels. Pleiotropic genetic factors were discovered using a multi-trait mixed model analysis. SNPs within or near candidate genes associated with hormone signaling, epigenetic regulation, and ROS detoxification under stress conditions were identified and can be used as genetic markers in dry bean breeding programs. |
format |
Journal Article |
topic_facet |
phaseolus vulgaris common beans gene pools andean drought stress abiotic stress |
author |
Oladzad, Atena Porch, Timothy G. Rosas, Juan Carlos Moghaddam, Samira Mafi Beaver, James S. Beebe, Stephen E. Burridge, Jimmy Jochua, Celestina Nhagupana Miguel, Magalhaes Amade Miklas, Phillip N. Raatz, Bodo White, Jeffrey W. Lynch, Jonathan P. McClean, Phillip E. |
author_facet |
Oladzad, Atena Porch, Timothy G. Rosas, Juan Carlos Moghaddam, Samira Mafi Beaver, James S. Beebe, Stephen E. Burridge, Jimmy Jochua, Celestina Nhagupana Miguel, Magalhaes Amade Miklas, Phillip N. Raatz, Bodo White, Jeffrey W. Lynch, Jonathan P. McClean, Phillip E. |
author_sort |
Oladzad, Atena |
title |
Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments |
title_short |
Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments |
title_full |
Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments |
title_fullStr |
Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments |
title_full_unstemmed |
Single and Multi-trait GWAS Identify Genetic Factors Associated with Production Traits in Common Bean Under Abiotic Stress Environments |
title_sort |
single and multi-trait gwas identify genetic factors associated with production traits in common bean under abiotic stress environments |
publisher |
Oxford University Press |
publishDate |
2019-06 |
url |
https://hdl.handle.net/10568/102152 https://doi.org/10.1534/g3.119.400072 |
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