Genome‐wide Association Analysis for Drought Tolerance and Associated Traits in Common Bean

Hoyos‐Villegas, Valerio; Song, Qijian; Kelly, James D.

doi:10.3835/plantgenome2015.12.0122

Cited by 69 publications

(75 citation statements)

References 105 publications

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“…The known bruchid-resistant lines developed by CIAT, namely, resistant to Zabrotes (RAZ) and marker-assisted Zabrotes (MAZ) lines, were genotypes from both gene pools. Understanding the genetic basis and population structure of complex traits such as insect resistance assists in the selection of desirable genotypes (Hoyos-Villegas et al, 2017). Various studies have been conducted to analyze the genetic diversity and population structure of P. vulgaris, using different types of markers (Freyre et al, 1998;Papa and Gepts, 2003;Durán et al, 2005;González et al, 2005;Blair et al, 2010a;McClean et al, 2012;Mercati et al, 2013;Cichy et al, 2015a;Rodriguez et al, 2016;Raatz et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…More recently, different GWAS studies have been conducted for the identification of genomic regions associated with different traits, including agronomic performance (Kamfwa et al, 2015a;Moghaddam et al, 2016), cooking time , drought tolerance (Hoyos-Villegas et al, 2017), symbiotic N 2 fixation (Kamfwa et al, 2015b) (Morini et al, 2016;Zuiderveen et al, 2016;Choudhary et al, 2018) in the common bean, but limited attention has been paid to bruchid resistance. Bean bruchid (Zabrotes subfasciatus) resistance was mapped on a gene cluster on linkage group B4 for an arcelin, phytohemagglutinin, and a-amylase inhibitor (APA) locus in biparental populations (Osborn et al, 1986;Blair et al, 2010bBlair et al, , 2010c.…”

Section: Population Structure and Genome-wide Association Analysis Ofmentioning

confidence: 99%

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Population Structure and Genome‐Wide Association Analysis of Bruchid Resistance in Ethiopian Common Bean Genotypes

et al. 2019

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The common bean (Phaseolus vulgaris L.) is among the most important grain legume crops in Africa. However, the common bean grain is heavily damaged by the Mexican bean weevil (Zabrotes subfasciatus Boheman). This study was conducted to determine the population structure and genome‐wide marker–trait associations of bruchid resistance in the common bean. The phenotypic diversity and population structure of 297 genotypes were analyzed, using the Illumina BARCBean6K_3 SNP BeadChip. The genotypes consisted of landraces, released varieties, breeding lines, and Mexican bean weevil resistant lines. A population structure analysis based on a Bayesian genotype clustering approach classified the 297 genotypes into two subpopulations, namely, Middle American and Andean. Similar population patterns were also observed using principal component analysis. The genome‐wide association study analysis identified 24 single‐nucleotide polymorphisms (SNPs) on nine chromosomes, with a significant (P < 0.05) association with the percentages of adult emergence and seed weight loss. The SNPs located on Pv4 and Pv7 were significantly (P < 0.001) associated with the two traits. Other significant SNPs were identified on other chromosomes of the common bean, but none of them was above the cutoff point (1.00 × 10−4). Therefore, further verification of the SNPs that have a significant marker–trait association at P < 0.05 will be vital, and accessions with these SNPs may be useful as parental materials.

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Section: Discussionmentioning

confidence: 99%

Section: Population Structure and Genome-wide Association Analysis Ofmentioning

confidence: 99%

Population Structure and Genome‐Wide Association Analysis of Bruchid Resistance in Ethiopian Common Bean Genotypes

et al. 2019

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“…In common bean, 19 WRKY genes, 11 downregulated and eight upregulated, responded to drought stress (Wu et al, 2017) and eight significant marker-trait associations under drought stress were noted on chromosome 9 and 11 (Hoyos-Villegas et al, 2017). …”

Section: Synthesismentioning

confidence: 99%

Using Biotechnology-Led Approaches to Uplift Cereal and Food Legume Yields in Dryland Environments

Dwivedi¹,

Siddique

Farooq

et al. 2018

Front. Plant Sci.

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Drought and heat in dryland agriculture challenge the enhancement of crop productivity and threaten global food security. This review is centered on harnessing genetic variation through biotechnology-led approaches to select for increased productivity and stress tolerance that will enhance crop adaptation in dryland environments. Peer-reviewed literature, mostly from the last decade and involving experiments with at least two seasons’ data, form the basis of this review. It begins by highlighting the adverse impact of the increasing intensity and duration of drought and heat stress due to global warming on crop productivity and its impact on food and nutritional security in dryland environments. This is followed by (1) an overview of the physiological and molecular basis of plant adaptation to elevated CO2 (eCO2), drought, and heat stress; (2) the critical role of high-throughput phenotyping platforms to study phenomes and genomes to increase breeding efficiency; (3) opportunities to enhance stress tolerance and productivity in food crops (cereals and grain legumes) by deploying biotechnology-led approaches [pyramiding quantitative trait loci (QTL), genomic selection, marker-assisted recurrent selection, epigenetic variation, genome editing, and transgene) and inducing flowering independent of environmental clues to match the length of growing season; (4) opportunities to increase productivity in C3 crops by harnessing novel variations (genes and network) in crops’ (C3, C4) germplasm pools associated with increased photosynthesis; and (5) the adoption, impact, risk assessment, and enabling policy environments to scale up the adoption of seed-technology to enhance food and nutritional security. This synthesis of technological innovations and insights in seed-based technology offers crop genetic enhancers further opportunities to increase crop productivity in dryland environments.

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“…Various candidate genes or quantitative trait loci responsible for traits of interest have been identi ed using GWAS technology in different crops. For instance, in common bean several studies have reported identi cation of genomic regions and candidate genes associated with different traits for bruchid resistance [11], agronomic traits [12], drought tolerance [13], anthracnose and angular leaf spot diseases [14] and symbiotic nitrogen xation [15]. However, these studies have been conducted for different traits with different common bean cultivars in different geographical regions.…”

Section: Introductionmentioning

confidence: 99%

Genome-wide Identification of Powdery Mildew Resistance in Common Bean

Binagwa

Traore

Egnin

et al. 2020

Preprint

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Background Genome-wide association studies (GWAS) was utilized to detect genetic variations related to the powdery mildew (PM) resistance and several agronomic traits in common bean. However, its application in common bean and the PM interactions to identify genes and their location in the common bean genome has not been fully addressed. Results Genome-wide association studies (GWAS) through marker-trait association are useful molecular tools for identification of disease resistance and other agronomic traits. SNP genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to resistance to PM disease in a panel of 206 genotypes grown under field conditions for two consecutive years. Significant SNPs identified on chromosome 4 and 10 were repeatable, confirming the reliability of the phenotypic data scored from the genotypes grown in two locations within two years. A cluster of resistance genes was revealed on the chromosome 4 of common bean genome among which CNL and TNL like resistance genes were identified. Furthermore, two resistance genes Phavu_010G1320001g and Phavu_010G136800g were also identified on pv10; further sequence analysis showed that these genes were homologs to the Arabidopsis disease resistance protein (RLM1A-like) and the putative disease resistance protein (At4g11170.1), respectively. Two LRR receptor-like kinases (RLK) were also identified on pv11 in samples collected in 2018 only. Many genes encoding auxin-responsive protein, TIFY10A protein, growth-regulating factor 5-like, ubiquitin-like protein, cell wall protein RBR3-like protein related to PM resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed and may generate several layers of defense barriers or inducible reactions. Conclusion Our results provide new insights into common bean and PM interactions, and revealed putative resistance genes as well as their location on common bean genome that could be used for marker-assisted selection, functional genomic study approaches to confirm the role of these putative genes; hence, developing common bean resistance lines to the PM disease.

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Genome‐wide Association Analysis for Drought Tolerance and Associated Traits in Common Bean

Cited by 69 publications

References 105 publications

Population Structure and Genome‐Wide Association Analysis of Bruchid Resistance in Ethiopian Common Bean Genotypes

Population Structure and Genome‐Wide Association Analysis of Bruchid Resistance in Ethiopian Common Bean Genotypes

Using Biotechnology-Led Approaches to Uplift Cereal and Food Legume Yields in Dryland Environments

Genome-wide Identification of Powdery Mildew Resistance in Common Bean

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