Identification of candidate genes associated with CBB resistance in common bean HR45 (Phaseolus vulgaris L.) using cDNA-AFLP

2010 ◽  
Vol 38 (1) ◽  
pp. 75-81 ◽  
Author(s):  
Chun Shi ◽  
Sarita Chaudhary ◽  
Kangfu Yu ◽  
Soon J. Park ◽  
Alireza Navabi ◽  
...  
2012 ◽  
Vol 30 (3) ◽  
pp. 1265-1277 ◽  
Author(s):  
Matthew W. Blair ◽  
Andrea Lorena Herrera ◽  
Tito Alejandro Sandoval ◽  
Gina Viviana Caldas ◽  
Marizia Filleppi ◽  
...  

2019 ◽  
Author(s):  
Atena Oladzadabbasabadi ◽  
Sujan Mamidi ◽  
Phillip N. Miklas ◽  
Rian Lee ◽  
Phillip McClean

Abstract Background White mold (WM) is a major disease in common bean ( Phaseolus vulgaris L.), and its complex quantitative genetic control has limited the development of WM resistant cultivars. WM2.2 is one of the nine meta-QTL that has a major effect on WM tolerance. This QTL explains up to 35% of the phenotypic variation and was previously mapped to a large interval on Pv02. Our objective was to narrow the interval of this QTL using QTL-based bulk segregant analysis.Results The phenotypic and genotypic data from two RIL populations (R31 and Z0726-9), which possess different genetic backgrounds for white mold resistance, were used to select resistant and susceptible lines to generate subpopulations for bulk DNA sequencing, and reads were aligned against the sequence of the resistance parent. The QTL physical intervals for each RIL population were mapped by fixed SNPs in 10kb-2kb sliding windows. WM2.2 QTL was split into two regions WM2.2a (3.54-4.56 Mbp; euchromatic) and WM 2.2b (12.19 to 26.41 Mbp; heterochromatic) in populations R31 and Z0726-9, respectively. For each QTL interval, the possible functional contribution of significant non-synonymous and synonymous polymorphisms was investigated. Gene models encoding for pentatricopeptide repeat, gibberellin 2-oxidase, and heat-shock proteins are the likely candidate genes associated with WM2.2a resistance. A TIR-NBS-LRR class of disease resistance protein and a EF-TU receptor are potential candidate genes associated with WM2.2b resistance and most likely trigger a physiological resistance response to WM.Conclusion QTL-based pooled sequencing analysis revealed that the large genomic region associated with WM2.2 meta QTL consists of two major QTL each associated with a different WM resistance function. WM2.2a region is most likely associated with avoidance mechanisms while WM2.2b region triggers physiological resistance.


Plants ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1572
Author(s):  
Júlio Cesar F. Elias ◽  
Maria Celeste Gonçalves-Vidigal ◽  
Andrea Ariani ◽  
Giseli Valentini ◽  
Maria da Conceição Martiniano-Souza ◽  
...  

Abiotic stress is a limiting factor for common bean (Phaseolus vulgaris L.) production globally. The study of the genotypic, phenotypic, and bio-climatic variables in a broad set of accessions may assist the identification of genomic regions involved in the climatic adaptation of the common bean. We conducted a genotyping-by-sequencing analysis using 28,823 SNPs on 110 georeferenced common bean accessions from Brazil to discover associations between SNPs and bio-climatic indexes. The population structure analysis clustered the accessions into two groups corresponding to the Andean and Mesoamerican gene pools. Of the 19 bioclimatic variables, 17 exhibited a significant association with SNPs on chromosomes Pv01, Pv02, Pv03, Pv04, Pv06, Pv09, Pv10, and Pv11 of common bean. Ten candidate genes were associated with specific bio-climatic variables related to temperature and precipitation. The candidate genes associated with this significant Pv09 region encode a Platz transcription factor family protein previously reported to be an essential regulator of drought stress. The SNP markers and candidate genes associated with the bio-climatic variables should be validated in segregating populations for water stress, which could further be used for marker-assisted selection. As a result, bean breeding programs may be able to provide advances in obtaining drought-tolerant cultivars.


2021 ◽  
Author(s):  
Sofora Jan ◽  
Irshad Ahmad Rather ◽  
Parvaze Ahmad Sofi ◽  
Mohd Altaf Wani ◽  
Farooq Ahmad Sheikh ◽  
...  

2021 ◽  
Author(s):  
Rosa Cecilia Viscarra‐Torrico ◽  
Aga Pajak ◽  
Alvaro Soler Garzón ◽  
BaiLing Zhang ◽  
Sudhakar Pandurangan ◽  
...  

2021 ◽  
Vol 99 ◽  
pp. 103883
Author(s):  
Mayra Denise Herrera ◽  
Rosalía Reynoso-Camacho ◽  
Valentín Melero-Meraz ◽  
Salvador H. Guzmán-Maldonado ◽  
Jorge A. Acosta-Gallegos

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