Study of Mungbean Yellow Mosaic Virus (Mymv) Resistance in Mungbean (Vigna radiata L. Wilczek) and Urdbean (Vigna mungo L. Hepper) Employing Nbs-Lrr and in-Silico Based Markers
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Date
2017-11
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University of Agricultural Science, Dharwad
Abstract
The present investigation was carried out at the Institute of Agriculture Biotechnology (IABT), Dharwad, during 2015- 16 with an objective to study the mungbean yellow mosaic virus (MYMV) resistance in urdbean and mungbean employing NBS-LRR and in-silico based markers. 107 and 13 genotypes of mungbean and urdbean were screened for MYMV disease at GPB botanical garden in summer 2015. Genetic variability, correlation and molecular diversity were studied. Sixteen genotypes of mungbean were found to be resistance to MYMV. Among the urdbean genotypes only three genotypes, viz., UTTARA, IPU-02-43 and DU3 exhibited moderate resistance reaction to MYMV. Markers MTB 99, RGA1-TG, VuRS02F16V and SI-INV were specific to MYMV. The molecular diversity analysis revealed that markers used in the study distinguished the mungbean and urdbean genotypes by forming separate clusters. High GCV, PCV, higher heritability and high genetic advance over the mean were recorded for number of branches, number of bunches, number of pods per plant and total seed yield indicated the presence of additive gene action. So these traits can be improved through simple direct selection. The total seed yield exhibited highly significant and positive correlation with pods per plant, pod length, seeds per pod and hundred seed weight at both phenotypic and genotypic level among urdbean genotypes which indicates indirect selection of these traits will improve the seed yield.
The mungbean genotypes viz., HUM1, SML 134, HUM 12 and urdbean genotypes, viz., IPU-02-43, UTTARA which showed resistance to MYMV can be utilized as parents in developing disease resistant varieties. The four putative markers identified can be used to differentiate the resistant and susceptible genotypes among mungbean genotypes and they could also be further validated using mapping populations.