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    Population structure and genetic diversity of rice (Oryza sativa L.) germplasm from the Democratic Republic of Congo (DRC) using DArTseq-Derived Single Nucleotide Polymorphism (SNP)

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    Journal Article (2.453Mb)
    Date
    2023-07-19
    Author
    Kimwemwe, P.K.
    Bukomarhe, C.B.
    Mamati, E.G.
    Githiri, S.M.
    Civava, R.M.
    Mignouna, J.
    Kimani, W.
    Fofana, M.
    Type
    Journal Article
    Review Status
    Peer Review
    Target Audience
    Scientists
    Metadata
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    Abstract/Description
    Understanding the genetic diversity and population structure of rice is crucial for breeding programs, conservation efforts, and the development of sustainable agricultural practices. This study aimed to assess the genetic diversity and population structure of 94 rice (Oryza sativa L.) genotypes from the Democratic Republic of Congo using a set of 8389 high-quality DArTseq-based single nucleotide polymorphism (SNP) markers. The average polymorphic information content (PIC) of the markers was 0.25. About 42.4% of the SNPs had a PIC value between 0.25 and 0.5, which were moderately informative. The ADMIXTURE program was used for structure analysis, which revealed five sub-populations (K = 5), with admixtures. In principal component analysis (PCA), the first three principal components accounted for 36.3% of the total variation. Analysis of molecular variance revealed significant variation between sub-populations (36.09%) and within genotypes (34.04%). The low overall number of migrants (Nm = 0.23) and high fixation index (Fst = 0.52) indicated limited gene flow and significant differentiation between the sub-populations. Observed heterozygosity (Ho = 0.08) was lower than expected heterozygosity (He = 0.14) because of the high inbreeding (Fis = 0.52) nature of rice. A high average Euclidean genetic distance (0.87) revealed the existence of genetic diversity among the 94 genotypes. The significant genetic diversity among the evaluated rice genotypes can be further explored to obtain potentially desirable genes for rice improvement.
    Acknowledgements
    The authors thank the training manager of IITA under the PICAGL project (2019–2022) for administrative support. We are also grateful to the INERA staff, especially the rice breeding program for their help in providing the collection of rice genotypes.
    https://doi.org/10.3390/agronomy13071906
    Multi standard citation
    Permanent link to this item
    https://hdl.handle.net/20.500.12478/8511
    IITA Authors ORCID
    Paul Kitenge Kimwemwehttps://orcid.org/0000-0002-1006-8207
    Bahati Bukomarhe Chancehttps://orcid.org/0000-0003-2711-4027
    Digital Object Identifier (DOI)
    https://doi.org/10.3390/agronomy13071906
    IITA Subjects
    Agronomy; Food Security; Genetic Improvement; Plant Breeding; Plant Genetic Resources; Plant Production
    Agrovoc Terms
    Agricultural Practices; Agronomy; Analysis; Breeding; Development; Gene Flow; Genes; Genotypes; Germplasm; Information; Oryza Sativa; Polymorphism; Population; Quality; Rice
    Regions
    Africa; Central Africa
    Countries
    Democratic Republic of the Congo
    Hubs
    Central Africa Hub
    Journals
    Agronomy
    Collections
    • Journal and Journal Articles5286
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