| dc.contributor.author | Kimwemwe, P.K. |
| dc.contributor.author | Bukomarhe, C.B. |
| dc.contributor.author | Mamati, E.G. |
| dc.contributor.author | Githiri, S.M. |
| dc.contributor.author | Civava, R.M. |
| dc.contributor.author | Mignouna, J. |
| dc.contributor.author | Kimani, W. |
| dc.contributor.author | Fofana, M. |
| dc.date.accessioned | 2024-08-21T14:30:57Z |
| dc.date.available | 2024-08-21T14:30:57Z |
| dc.date.issued | 2023-07-19 |
| dc.identifier.citation | Kimwemwe, P.K., Bukomarhe, C.B., Mamati, E.G., Githiri, S.M., Civava, R.M., Mignouna, J., ... & Fofana, M. (2023). 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). Agronomy, 13(7): 1906, 1-17. |
| dc.identifier.issn | 2073-4395 |
| dc.identifier.uri | https://hdl.handle.net/20.500.12478/8511 |
| dc.description.abstract | 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. |
| dc.description.sponsorship | World Bank |
| dc.format.extent | 1-17 |
| dc.language.iso | en |
| dc.subject | Agricultural Practices |
| dc.subject | Agronomy |
| dc.subject | Analysis |
| dc.subject | Breeding |
| dc.subject | Development |
| dc.subject | Gene Flow |
| dc.subject | Genes |
| dc.subject | Genotypes |
| dc.subject | Germplasm |
| dc.subject | Information |
| dc.subject | Oryza Sativa |
| dc.subject | Polymorphism |
| dc.subject | Population |
| dc.subject | Quality |
| dc.subject | Rice |
| dc.title | 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) |
| dc.type | Journal Article |
| cg.contributor.affiliation | Jomo Kenyatta University of Agriculture and Technology |
| cg.contributor.affiliation | International Institute of Tropical Agriculture |
| cg.contributor.affiliation | Institut National pour l’Etude et la Recherche Agronomiques, DRC |
| cg.contributor.affiliation | International Livestock Research Institute |
| cg.coverage.region | Africa |
| cg.coverage.region | Central Africa |
| cg.coverage.country | Democratic Republic of the Congo |
| cg.coverage.hub | Central Africa Hub |
| cg.isijournal | ISI Journal |
| cg.authorship.types | CGIAR and developing country institute |
| cg.iitasubject | Agronomy |
| cg.iitasubject | Food Security |
| cg.iitasubject | Genetic Improvement |
| cg.iitasubject | Plant Breeding |
| cg.iitasubject | Plant Genetic Resources |
| cg.iitasubject | Plant Production |
| cg.journal | Agronomy |
| cg.notes | Open Access Journal |
| cg.accessibilitystatus | Open Access |
| cg.reviewstatus | Peer Review |
| cg.usagerightslicense | Creative Commons Attribution 4.0 (CC BY 0.0) |
| cg.targetaudience | Scientists |
| cg.identifier.doi | https://doi.org/10.3390/agronomy13071906 |
| cg.iitaauthor.identifier | Paul Kitenge Kimwemwe: 0000-0002-1006-8207 |
| cg.iitaauthor.identifier | Bahati Bukomarhe Chance: 0000-0003-2711-4027 |
| cg.futureupdate.required | No |
| cg.identifier.issue | 7: 1906 |
| cg.identifier.volume | 13 |
| cg.contributor.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. |
