Kiambi, D. K.Newbury, H. J.Ford-Lloyd, B. V.Dawson, I.2024-03-152017-01-192024-03-152017-01-191684–5315https://repo.pacuniversity.ac.ke/handle/123456789/1033.2ARTICLEMolecular markers have been used extensively in studying genetic diversity, genetic relationships and germplasm management. However, the understanding of between and within population genetic variation and how it is partitioned on the basis of geographic origin is crucial as this helps to improve sampling efficiency. The objective of this study was therefore to assess the intra-specific diversity in Oryza longistaminata and how the variation is partitioned within and between different geographic locations, using molecular markers. AFLP analysis generated 176 bands that revealed high levels of polymorphism (95.6%) and diversity within and between populations. The mean Nei’s genetic diversity for all the 176 loci in the 48 populations was 0.302 and diversity for populations within countries ranged from 0.1161 to 0.2126. Partitioning of between and within population diversity revealed that the mean allelic diversity at each polymorphic locus was HT = 0.3445. The within population diversity was (HS = 0.1755) and the between population diversity was (DST = 0.1688). Results of AMOVA revealed significant differences (p<0.05) in genetic variation among populations within different countries of the region. Genetic parameters estimated from AFLP data indicated that there are high levels of genetic diversity in the wild populations of O. longistaminata studied and that this diversity is higher within than between populations. Hierarchical partitioning also revealed that most of this diversity is found between populations within countries than among countries. Regional collection and conservation strategies therefore need to consider country differences while national strategies should consider population differences within countries.enMolecular markers,AFLP,Oryza longistaminatapopulationsgenetic diversityContrasting genetic diversity among Oryza longistaminata (A. Chev et Roehr) populations from different geographic origins using AFLPArticle