Exploring the Genetic Divergence in Mungbean (Vigna radiata L.) Germplasm Using Multiple Molecular Marker Systems

Tabasum, Aqsa; Hameed, Amjad; Asghar, Muhammad

doi:10.1007/s12033-020-00270-y

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…Cluster analysis of the seven mung beans based on the genetic similarity coefficients grouped them into three main clusters. This compares to the findings on other mung bean genotypes [12]. The improved varieties fell in the same clusters with the landraces, which indicates that they are genetically related.…”

Section: Discussioncontrasting

confidence: 41%

“…Development of many DNA markers has enabled germplasm characterization of the duplicated accessions, population structures, and genetic relationships and establishes distribution of variation between individuals and accessions. Marker choices that have been used in genetic diversity studies include RAPD [12], eSSR [13], SRAP [14], ISSR [15], STMS [16], and AFLP [17]. Microsatellites have proven to be a highly attractive genetic marker since they are highly reproducible, polymorphic, multi-allelic, co-dominant, and therefore considered for this study [18].…”

Section: Introductionmentioning

confidence: 99%

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Genetic and phenotypic diversity of selected Kenyan mung bean (Vigna radiata L. Wilckzek) genotypes

Mwangi

Okoth

Kariuki

et al. 2021

Journal of Genetic Engineering and Biotechnology

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Background Mung bean is a pulse crop principally grown in the tropic and subtropic parts of the world for its nutrient-rich seeds. Seven mung beans accessions from Eastern Kenya were evaluated using thirteen phenotypic traits. In addition, 10 SSR markers were used to determine their genetic diversity and population structure. This aimed at enhancing germplasm utilization for subsequent mung bean breeding programs. Results Analysis of variance for most of the phenology traits showed significant variation, with the yield traits recording the highest. The first three principal components (PC) explained 83.4% of the overall phenotypic variation, with the highest (PC1) being due to variation of majority of the traits studied such as pod length, plant height, and seeds per pod. The dendogram revealed that the improved genotypes had common ancestry with the local landraces. The seven mung beans were also genotyped using 10 microsatellite markers, eight of which showed clear and consistent amplification profiles with scorable polymorphisms in all the studied genotypes. Genetic diversity, allele number, and polymorphic information content (PIC) were determined using powermarker (version 3.25) and phylogenetic tree constructed using DARWIN version 6.0.12. Analysis of molecular variance (AMOVA) was calculated using GenALEx version 6.5. A total of 23 alleles were detected from the seven genotypes on all the chromosomes studied with an average of 2.875 across the loci. The PIC values ranged from 0.1224 (CEDG056) to 0.5918 (CEDG092) with a mean of 0.3724. Among the markers, CEDG092 was highly informative while the rest were reasonably informative except CEDG056, which was less informative. Gene diversity ranged from 0.1836 (CEDG050) to 0.5102 (CDED088) with an average of 0.3534. The Jaccards dissimilarity matrix indicated that genotypes VC614850 and N26 had the highest level of dissimilarity while VC637245 and N26 had lowest dissimilarity index. The phylogenetic tree grouped the genotypes into three clusters as revealed by population structure analysis (K = 3), with cluster III having one unique genotype (VC6137B) only. AMOVA indicated that the highest variation (99%) was between individual genotype. In addition, marker traits association analysis revealed 18 significant associations (P < 0.05). Conclusion These findings indicate sufficient variation among the studied genotypes that can be considered for germplasm breeding programs.

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Section: Discussioncontrasting

confidence: 41%

Section: Introductionmentioning

confidence: 99%

Genetic and phenotypic diversity of selected Kenyan mung bean (Vigna radiata L. Wilckzek) genotypes

Mwangi

Okoth

Kariuki

et al. 2021

Journal of Genetic Engineering and Biotechnology

View full text Add to dashboard Cite

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“…In recent year use of SSR marker in diversity as well as marker assisted breeding (MAB) programme in Mungbean have tremendously increased [2,8]. In the present investigation, we aimed to develop a rapid protocol for molecular marker analysis in mungbean.…”

Section: Resultsmentioning

confidence: 99%

Rapid Method for Genomic DNA Isolation of Mungbean [Vignar adiata (L.) Wilczek]

Kumawat¹,

Parsad²,

Sahni

2023

CJAST

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The most significant pulse crop in India is the mungbean [Vignar adiata (L.) Wilczek], which constitutes almost 16% of the national pulse area. For biotechnological interventions, it is prerequisite to develop a rapid and cost-effective method for genomic DNA isolation suitable for PCR. In present investigation,modified CTAB method was used to extract the genomic DNA from the leaf tissues of mungbesn. By crushing the leaves of several mungbean genotypes in a pre-heated CTAB extraction buffer, genomic DNA was extracted. Further, SSR markers were used to assess the efficiency of the extracted DNA.The SSR marker-based PCR amplification findings showed that the DNA extracted using this approach was of good quality and suitable for SSR analysis.

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Applicability of Start Codon Targeted (SCoT) markers for the assessment of genetic diversity in bread wheat germplasm

Altaf,

Nadeem,

Ali

et al. 2024

Genet Resour Crop Evol

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Research endeavors focused on examining genetic diversity play a pivotal role in advancing agricultural practices, as they furnish valuable insights for breeding programs and the preservation of germplasm. Wheat holds significant global importance as a cereal crop, serving as a primary source of sustenance for almost one-third of the global human population. In the current study, a total of 80 bread wheat genotypes were characterized using the start codon targeted (SCoT) marker system. A set of 14 polymorphic primers yielded a cumulative count of 399 bands with an average of 28.05 bands per primer. The range of diversity markers, such as polymorphism information content (0.26–0.59), effective numbers of alleles (1.27–1.59), Shannon’s information index (0.30–0.51), and gene diversity (0.18–0.34), provided evidence of elevated genetic differences within the examined germplasm. According to the findings of the molecular variance analysis, greater genetic variations are found within populations (92%). The model-based structural approach partitioned the 80 bread wheat genotypes into two distinct populations (Population A and B). The diversity indices based on the structures of the populations revealed that population A had greater diversity compared to population B. Both the principal coordinate analysis and the neighbor-joining analysis also differentiated the 80 different bread wheat genotypes based on their respective collection points. The present crop diversity offers great opportunities for enhancing crop quality and increasing tolerance to environmental challenges, both of which will lead to a reduction in the problem of food insecurity.

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Exploring the Genetic Divergence in Mungbean (Vigna radiata L.) Germplasm Using Multiple Molecular Marker Systems

Cited by 5 publications

References 30 publications

Genetic and phenotypic diversity of selected Kenyan mung bean (Vigna radiata L. Wilckzek) genotypes

Genetic and phenotypic diversity of selected Kenyan mung bean (Vigna radiata L. Wilckzek) genotypes

Rapid Method for Genomic DNA Isolation of Mungbean [Vignar adiata (L.) Wilczek]

Applicability of Start Codon Targeted (SCoT) markers for the assessment of genetic diversity in bread wheat germplasm

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