{"title":"Population structuring of selected mungbean landraces of the Odisha State of India via DNA marker-based genetic diversity analysis","authors":"Ram Chandra Jena , Khusbu Agarwal , Tarini Shankar Ghosh , Pradeep Kumar Chand","doi":"10.1016/j.aggene.2016.11.007","DOIUrl":null,"url":null,"abstract":"<div><p>Ever-increasing demands of mungbean consumption, wide eco-geographical variations and inadequate achievements through conventional breeding necessitate comprehensive assessment of genetic variability coupled with population patterning. In the present work 30 mungbean landraces of the Odisha State of India representing four different geographical regions (populations) along with some Indian genotypes were used for elucidation of genetic diversity and population structure analysis using 52 SCoT (gene-targeted) and 45 RAPD (arbitrary) markers. SCoT markers proved to be more effective than RAPD in ascertaining genetic diversity at genotype level (% polymorphism, Rp, PIC, EMR, MI, GI and I) and population level (Na, Ne, H, I, Ht and Hs). Unique bands (23 RAPD and 47 SCoT) were generated which enabled identification of 16 and 25 genotypes respectively. Genetic diversity parameters of East Odisha revealed high genetic variability compared to other populations. AMOVA revealed ><!--> <!-->95% variation within the populations which is further supported by high gene flow and low level of genetic differentiation. UPGMA dendrogram and population structure grouped genotypes into 8 major clusters irrespective of their geographical affiliations. However, genotypes belonging to certain clusters exhibited significant geographical and morphological preferences using the cumulative strategy. The study illustrated the importance of combined marker analysis, which uses complementary information from two distinct and analogous markers and in the process, offers accurate and reliable results. Further, the applicability of in silico analysis in performing a high resolution patterning of genetic divergence and population structure was demonstrated.</p></div>","PeriodicalId":37751,"journal":{"name":"Agri Gene","volume":"3 ","pages":"Pages 67-86"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.aggene.2016.11.007","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agri Gene","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352215116300514","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 4
Abstract
Ever-increasing demands of mungbean consumption, wide eco-geographical variations and inadequate achievements through conventional breeding necessitate comprehensive assessment of genetic variability coupled with population patterning. In the present work 30 mungbean landraces of the Odisha State of India representing four different geographical regions (populations) along with some Indian genotypes were used for elucidation of genetic diversity and population structure analysis using 52 SCoT (gene-targeted) and 45 RAPD (arbitrary) markers. SCoT markers proved to be more effective than RAPD in ascertaining genetic diversity at genotype level (% polymorphism, Rp, PIC, EMR, MI, GI and I) and population level (Na, Ne, H, I, Ht and Hs). Unique bands (23 RAPD and 47 SCoT) were generated which enabled identification of 16 and 25 genotypes respectively. Genetic diversity parameters of East Odisha revealed high genetic variability compared to other populations. AMOVA revealed > 95% variation within the populations which is further supported by high gene flow and low level of genetic differentiation. UPGMA dendrogram and population structure grouped genotypes into 8 major clusters irrespective of their geographical affiliations. However, genotypes belonging to certain clusters exhibited significant geographical and morphological preferences using the cumulative strategy. The study illustrated the importance of combined marker analysis, which uses complementary information from two distinct and analogous markers and in the process, offers accurate and reliable results. Further, the applicability of in silico analysis in performing a high resolution patterning of genetic divergence and population structure was demonstrated.
Agri GeneAgricultural and Biological Sciences-Agricultural and Biological Sciences (miscellaneous)
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Agri Gene publishes papers that focus on the regulation, expression, function and evolution of genes in crop plants, farm animals, and agriculturally important insects and microorganisms. Agri Gene strives to be a diverse journal and topics in multiple fields will be considered for publication so long as their main focus is on agriculturally important organisms (plants, animals, insects, or microorganisms). Although not limited to the following, some examples of potential topics include: Gene discovery and characterization. Genetic markers to guide traditional breeding. Genetic effects of transposable elements. Evolutionary genetics, molecular evolution, population genetics, and phylogenetics. Profiling of gene expression and genetic variation. Biotechnology and crop or livestock improvement. Genetic improvement of biological control microorganisms. Genetic control of secondary metabolic pathways and metabolic enzymes of crop pathogens. Transcription analysis of beneficial or pest insect developmental stages Agri Gene encourages submission of novel manuscripts that present a reasonable level of analysis, functional relevance and/or mechanistic insight. Agri Gene also welcomes papers that have predominantly a descriptive component but improve the essential basis of knowledge for subsequent functional studies, or which provide important confirmation of recently published discoveries provided that the information is new.