Identification of QTLs for Resistance to Sclerotinia sclerotiorum in Carioca Common Bean by the Moving Away Method

Identification of QTLs for Resistance to Sclerotinia sclerotiorum in Carioca Common Bean by the Moving Away Method

The aim of this study was to use multiple DNA markers for detection of QTLs related to resistance to white mold in an F2 population of common bean evaluated by the straw test method. The DNA from 186 F2 plants and from the parents was extracted for genotypic evaluation using SSR, AFLP, and SRAP mark...

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Bibliographic Details
Published in:ISRN molecular biology Vol. 2014; pp. 828102 - 7
Main Authors: Lara, Letícia A. de C., Santos, João B. dos, Veloso, Juliana S., Balestre, Marcio, Alves, Filipe C., Leite, Monik E.
Format: Journal Article
Language:English
Published: United States Hindawi Publishing Corporation 2014
Hindawi Limited
Subjects:
Beans
Crop diseases
Genomes
Genomics
Phaseolus vulgaris
Random variables
Sclerotinia sclerotiorum
Brazil
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Summary:The aim of this study was to use multiple DNA markers for detection of QTLs related to resistance to white mold in an F2 population of common bean evaluated by the straw test method. The DNA from 186 F2 plants and from the parents was extracted for genotypic evaluation using SSR, AFLP, and SRAP markers. For phenotypic analysis, 186 F2:4 progenies and ten lines were evaluated, in a 14 × 14 triple lattice experimental design. The adjusted mean values of the F2:4 progenies were used for identification of QTLs by Bayesian shrinkage analysis. Significant differences were observed among the progenies for reaction to white mold. In identification of QTLs, 17 markers identified QTLs for resistance—13 SSRs and 4 AFLPs. The moving away method under the Bayesian approach proved to be efficient in the identification of QTLs when a genetic map is not used due to the low density of markers. The ME1 and BM211 markers are near the QTLs, with the effect of increasing resistance to white mold, and they have high heritability. They are thus promising for marker-assisted selection.
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Academic Editors: R. Kiyama, A. J. Molenaar, and T. Tozaki
ISSN:2090-7907
2090-7907
DOI:10.1155/2014/828102