structure analysis
Recently Published Documents





2022 ◽  
Vol 12 ◽  
Versha Rohilla ◽  
Rajesh Kumar Yadav ◽  
Atman Poonia ◽  
Ravika Sheoran ◽  
Gita Kumari ◽  

Mung bean [Vigna radiata (L.) Wilczek] is an important short-duration grain legume widely known for its nutritional, soil ameliorative, and cropping system intensification properties. This study aims at evaluating genetic diversity among mung bean genotypes and detecting genomic regions associated with various yield attributing traits and yellow mosaic disease (YMD) resistance by association mapping. A panel of 80 cultivars and advanced breeding lines was evaluated for 10 yield-related and YMD resistance traits during kharif (monsoon) and summer seasons of 2018–2019 and 2019–2020. A total of 164 genome-wide simple sequence repeat (SSR) markers were initially screened, out of which 89 were found polymorphic which generated 317 polymorphic alleles with an average of 3.56 alleles per SSR locus. The number of alleles at each locus varied from 2 to 7. The population genetic structure analysis grouped different genotypes in three major clusters and three genetically distinct subpopulations (SPs) (i.e., SP-1, SP-2, and SP-3) with one admixture subpopulation (SP-4). Both cluster and population genetic structure analysis categorized the advanced mung bean genotypes in a single group/SP and the released varieties in other groups/SPs, suggesting that the studied genotypes may have common ancestral history at some level. The population genetic structure was also in agreement with the genetic diversity analysis. The estimate of the average degree of linkage disequilibrium (LD) present at the genome level in 80 mung bean genotypes unveiled significant LD blocks. Over the four seasons, 10 marker-trait associations were observed significant for YMD and four seed yield (SY)-related traits viz., days to flowering, days to maturity, plant height, and number of pods per plant using the mixed linear model (MLM) method. These associations may be useful for marker-assisted mung bean yield improvement programs and YMD resistance.

2022 ◽  
Shusaku Ukai ◽  
Norihito Fukui ◽  
Takahisa Ikeue ◽  
Hiroshi Shinokubo

2022 ◽  
Umakanta Ngangkham ◽  
Akoijam Ratankumar Singh ◽  
Bhuvaneswari S ◽  
Konsam Sarika ◽  

Abstract North- Eastern parts of India fall under the Eastern Himalayan region and it is a diversity hotspot of many crops, including maize. Maize is an important traditional cereal crop grown in hill ecology of the region mainly for food, fodder and feed. To tap the potentiality of maize genetic resources in crop improvement programmes, assessment of genetic diversity is a basic requirement. Hence, in the present study, assessment of genetic diversity in thirty early generation maize inbreds developed from different germplasm of NE India was taken up using genome wide distributed fifty two microsatellite markers. The marker analysis revealed a large variation with a total of 189 alleles with an average of 3.63 alleles per marker locus. The allele size ranged from 50 bp ( phi 036 ) to 295 bp ( p 101049 ) which revealed a high level of genetic diversity among the loci. The PIC value ranged from 0.17 ( umc 1622 ) to 0.76 ( umc 1153 ) with an average value of 0.49. The value of expected Heterozygosity (H Exp ) ranged from 0.19 to 0.80 with an average of 0.57, whereas the Observed Heterozygosity (H Obs ) ranged from 0 to 0.89 with a mean of 0.14.The genetic dissimilarity between the genotype pairs ranged from 0.40 to 0.64 with a mean value of 0.57. Cluster analysis resolved the inbreds into three distinct sub-clusters. Similarly, population structure analysis also classified the inbred lines into three-subpopulations. Marker-trait associations showed a total of twelve SSR markers significantly associated with seven agronomic traits. From the present study, wide genetic variability was found among the maize inbreds with high potential to contribute new beneficial and unique alleles in genetic enhancement program of maize in India and particularly, in NE region.

Sign in / Sign up

Export Citation Format

Share Document