RESUMO
The present study aimed to detect the marker-trait association of a selected diverse panel of 127 mungbean genotypes against mungbean yellow mosaic India virus (MYMIV). Virus-specific primers pairs viz., AC-abut/AV-abut and BC-abut/BV-abut confirmed the involvement of MYMIV in yellow mosaic disease development and the same was validated through restriction digestion analysis. 256 genome-wide microsatellite markers were screened on a test panel in which 93 polymorphic markers were used in association studies. Population structure analysis led to formation of six distinct subpopulations. 1097 alleles were detected among 127 test genotypes whereas number of alleles ranged 2-22 and PIC values ranged 0.27-0.92%, indicating ample amount of variation at genome level. 15 microsatellite markers were detected as associated with MYMIV resistance, among them three microsatellites explained 11-14% phenotypic variation. The specific regions close to CEDG293, DMB-SSR008 and DMB-SSR059 associated with MYMIV resistance were detected, located on linkage group 2, 4 and 9 and may prove useful in marker-assisted mungbean improvement programme for enhancing MYMIV resistance.
RESUMO
In the present study, a diverse panel of 96 accessions of lentil germplasm was used to study flowering time over environments and to identify simple sequence repeat markers associated with flowering time through association mapping. The study showed high broad sense heritability estimate (h 2 bs=0.93) for flowering time in lentil. Screening of 534 SSR markers resulted in an identification of 75 SSR polymorphic markers (13.9%) across studied genotypes. These markers amplified 266 loci and generated 697 alleles ranging from two to 16 alleles per locus. Model-based cluster analysis used for the determination of population structure resulted in the identification of two distinct subpopulations. Distribution of flowering time was ranged from 40 to 70 days in subpopulation I and from 54 to 69 days in subpopulation II and did not skew either late or early flowering time within a subpopulation. No admixture was observed within the subpopulations. Use of the most accepted maximum likelihood model (P3D mixed linear model with optimum compression) of MTA analysis showed significant association of 26 SSR markers with flowering time at <0.05 probability. The percent of phenotypic explained by each associated marker with flowering time ranged from 2.1 to 21.8% and identified QTLs for flowering time explaining high phenotypic variation across the environments (10.7-21.8%) or in a particular environment (10.2-21.4%). In the present study, 13 EST-SSR showed significant association with flowering time and explained large phenotypic variation (2.3-21.8%) compared to genomic SSR markers (2.1-10.2%). Hence, these markers can be used as functional markers in the lentil breeding program to develop short duration cultivars.
