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Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches
Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches
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Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches
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Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches
Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches

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Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches
Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches
Journal Article

Linked candidate genes of different functions for white mold resistance in common bean (Phaseolus vulgaris L) are identified by multiple QTL mapping approaches

2023
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Overview
White mold (WM) is a major disease in common bean ( Phaseolus vulgaris L.), and its complex quantitative genetic control limits the development of WM resistant cultivars. WM2.2, one of the nine meta-QTL with a major effect on WM tolerance, explains up to 35% of the phenotypic variation and was previously mapped to a large genomic interval on Pv02. Our objective was to narrow the interval of this QTL using combined approach of classic QTL mapping and QTL-based bulk segregant analysis (BSA), and confirming those results with Khufu de novo QTL-seq. The phenotypic and genotypic data from two RIL populations, ‘Raven’/I9365-31 (R31) and ‘AN–37’/PS02–029C–20 (Z0726-9), were used to select resistant and susceptible lines to generate subpopulations for bulk DNA sequencing. The QTL physical interval was determined by considering overlapping interval of the identified QTL or peak region in both populations by three independent QTL mapping analyses. Our findings revealed that meta-QTL WM2.2 consists of three regions, WM2.2a (4.27-5.76 Mb; euchromatic), WM 2.2b (12.19 to 17.61 Mb; heterochromatic), and WM2.2c (23.01-25.74 Mb; heterochromatic) found in both populations. Gene models encoding for gibberellin 2-oxidase 8, pentatricopeptide repeat, and heat-shock proteins are the likely candidate genes associated with WM2.2a resistance. A TIR-NBS-LRR class of disease resistance protein (Phvul.002G09200) and LRR domain containing family proteins are potential candidate genes associated with WM2.2b resistance. Nine gene models encoding disease resistance protein [pathogenesis-related thaumatin superfamily protein and disease resistance-responsive (dirigent-like protein) family protein etc] found within the WM2.2c QTL interval are putative candidate genes. WM2.2a region is most likely associated with avoidance mechanisms while WM2.2b and WM2.2c regions trigger physiological resistance based on putative candidate genes.