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    Genetic diversity and population structure of soybean lines adapted to sub-Saharan Africa using Single Nucleotide Polymorphism (SNP) markers

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    Journal Article (625.6Kb)
    Date
    2021
    Author
    Chander, S.
    Garcia-Oliveira, A.L.
    Gedil, M.
    Shah, T.
    Otusanya, G.O.
    Asiedu, R.
    Chigeza, G.
    Type
    Journal Article
    Review Status
    Peer Review
    Target Audience
    Scientists
    Metadata
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    Abstract/Description
    Soybean productivity in sub-Saharan Africa (SSA) is less than half of the global average yield. To plug the productivity gap, further improvement in grain yield must be attained by enhancing the genetic potential of new cultivars that depends on the genetic diversity of the parents. Hence, our aim was to assess genetic diversity and population structure of elite soybean genotypes, mainly released cultivars and advanced selections in SSA. In this study, a set of 165 lines was genotyped with high-throughput single nucleotide polymorphism (SNP) markers covering the complete genome of soybean. The genetic diversity (0.414) was high considering the bi-allelic nature of SNP markers. The polymorphic information content (PIC) varied from 0.079 to 0.375, with an average of 0.324 and about 49% of the markers had a PIC value above 0.350. Cluster analysis grouped all the genotypes into three major clusters. The model-based STRUCTURE and discriminant analysis of principal components (DAPC) exhibited high consistency in the allocation of lines in subpopulations or groups. Nonetheless, they presented some discrepancy and identified the presence of six and five subpopulations or groups, respectively. Principal coordinate analysis revealed more consistency with subgroups suggested by DAPC analysis. Our results clearly revealed the broad genetic base of TGx (Tropical Glycine max) lines that soybean breeders may select parents for crossing, testing and selection of future cultivars with desirable traits for SSA.
    Acknowledgements
    We are grateful to Rodomiro Ortiz (Swedish University of Agricultural Sciences, Sweden) for enriching the revised manuscript. The authors appreciate and acknowledge Peter Oyelakin, Sunday Ojo, Ademola Ajayi, and Ilesanmi Yinka for their support in IITA soybean screenhouse and DNA extraction. We are also thankful to the four anonymous reviewers for discussions and their pertinent suggestions on the manuscript.
    https://dx.doi.org/10.3390/agronomy11030604
    Multi standard citation
    Permanent link to this item
    https://hdl.handle.net/20.500.12478/7158
    IITA Authors ORCID
    Garcia-Oliveira ALhttps://orcid.org/0000-0001-8561-4172
    Melaku Gedilhttps://orcid.org/0000-0002-6258-6014
    Trushar Shahhttps://orcid.org/0000-0002-0091-7981
    Robert Asieduhttps://orcid.org/0000-0001-8943-2376
    Godfree Chigezahttps://orcid.org/0000-0002-9235-0694
    Digital Object Identifier (DOI)
    https://dx.doi.org/10.3390/agronomy11030604
    Research Themes
    Biometrics; Biotech and Plant Breeding; Plant Production and Health
    IITA Subjects
    Agronomy; Food Security; Genetic Improvement; Grain Legumes; Plant Breeding; Plant Genetic Resources; Plant Production; Soybean
    Agrovoc Terms
    Genetic Diversity; Population Structure; Single Nucleotide Polymorphism; Genetic Markers; Soybeans; Subsaharan Africa
    Regions
    Africa; Central Africa; East Africa; Southern Africa; West Africa
    Countries
    Benin (Dahomey); Burundi; Cameroon; Cote d’Ivoire (Ivory Coast); Ethiopia; Ghana; Kenya; Malawi; Mozambique; Nigeria; Sierra Leone; Togo; Uganda; Zambia
    Hubs
    Southern Africa Hub; Headquarters and Western Africa Hub
    Journals
    Agronomy
    Collections
    • Journal and Journal Articles4835
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