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Assessment of genetic diversity in Vigna unguiculata L. (Walp) accessions using inter-simple sequence repeat (ISSR) and start codon targeted (SCoT) polymorphic markers

Overview of attention for article published in BMC Genomic Data, November 2017
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Title
Assessment of genetic diversity in Vigna unguiculata L. (Walp) accessions using inter-simple sequence repeat (ISSR) and start codon targeted (SCoT) polymorphic markers
Published in
BMC Genomic Data, November 2017
DOI 10.1186/s12863-017-0567-6
Pubmed ID
Authors

David Okeh Igwe, Celestine Azubike Afiukwa, Benjamin Ewa Ubi, Kenneth Idika Ogbu, Omena Bernard Ojuederie, George Nkem Ude

Abstract

Assessment of genetic diversity of Vigna unguiculata (L.) Walp (cowpea) accessions using informative molecular markers is imperative for their genetic improvement and conservation. Use of efficacious molecular markers to obtain the required knowledge of the genetic diversity within the local and regional germplasm collections can enhance the overall effectiveness of cowpea improvement programs, hence, the comparative assessment of Inter-simple sequence repeat (ISSR) and Start codon targeted (SCoT) markers in genetic diversity of V. unguiculata accessions from different regions in Nigeria. Comparative analysis of the genetic diversity of eighteen accessions from different locations in Nigeria was investigated using ISSR and SCoT markers. DNA extraction was done using Zymogen Kit according to its manufacturer's instructions followed by amplifications with ISSR and SCoT and agarose gel electrophoresis. The reproducible bands were scored for analyses of dendrograms, principal component analysis, genetic diversity, allele frequency, polymorphic information content, and population structure. Both ISSR and SCoT markers resolved the accessions into five major clusters based on dendrogram and principal component analyses. Alleles of 32 and 52 were obtained with ISSR and SCoT, respectively. Numbers of alleles, gene diversity and polymorphic information content detected with ISSR were 9.4000, 0.7358 and 0.7192, while SCoT yielded 11.1667, 0.8158 and 0.8009, respectively. Polymorphic loci were 70 and 80 in ISSR and SCoT, respectively. Both markers produced high polymorphism (94.44-100%). The ranges of effective number of alleles (Ne) were 1.2887 ± 0.1797-1.7831 ± 0.2944 and 1.7416 ± 0.0776-1.9181 ± 0.2426 in ISSR and SCoT, respectively. The Nei's genetic diversity (H) ranged from 0.2112 ± 0.0600-0.4335 ± 0.1371 and 0.4111 ± 0.0226-0.4778 ± 0.1168 in ISSR and SCoT, respectively. Shannon's information index (I) from ISSR and SCoT were 0.3583 ± 0.0639-0.6237 ± 0.1759 and 0.5911 ± 0.0233-0.6706 ± 0.1604. Total gene diversity (Ht), gene diversity within population (Hs), coefficient of gene differentiation (Gst) and level of gene flow (Nm) revealed by ISSR were 0.4498, 0.3203, 0.2878 and 1.2371 respectively, while SCoT had 0.4808, 0.4522, 0.0594 and 7.9245. Both markers showed highest genetic diversity in accessions from Ebonyi. Our study demonstrated that SCoT markers were more efficient than ISSR for genetic diversity studies in V. unguiculata and can be integrated in the exploration of their genetic diversity for improvement and germplasm utilization.

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Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 15%
Student > Master 8 15%
Lecturer 4 8%
Student > Doctoral Student 3 6%
Unspecified 2 4%
Other 7 13%
Unknown 21 40%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 36%
Biochemistry, Genetics and Molecular Biology 4 8%
Unspecified 2 4%
Arts and Humanities 1 2%
Environmental Science 1 2%
Other 0 0%
Unknown 26 49%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 November 2017.
All research outputs
#20,663,600
of 25,382,440 outputs
Outputs from BMC Genomic Data
#861
of 1,204 outputs
Outputs of similar age
#333,513
of 438,959 outputs
Outputs of similar age from BMC Genomic Data
#18
of 28 outputs
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