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      Genetic diversity of Nile tilapia ( Oreochromis niloticus) populations in Ethiopia: insights from nuclear DNA microsatellites and implications for conservation

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          Abstract

          Background

          Nile tilapia, Oreochromis niloticus (Linnaeus, 1758) is among the economically most important freshwater fish species in East Africa, and a major source of protein for local consumption. Human induced translocations of non-native stocks for aquaculture and fisheries have been found as a potential threat to the genetic diversity and integrity of local populations. In the present study, we investigate the genetic structure of O. niloticus from 16 waterbodies across Ethiopia using 37 microsatellite loci with SSR-GBAS techniques.

          Results

          The samples are structured into three main clusters shaped either by biogeographic factors or stocking activities. High F ST values (Global F ST  = 0.438) between populations indicate a high level of genetic differentiation and may suggest long term isolation even within the same drainage systems. Natural populations of the Omo-Turkana system and the lakes in the Southern Main Ethiopian Rift showed the highest genetic variability while low variability was found in stocked populations of lakes Hora, Hashenge and Hayq.

          Conclusions

          The results presented herein, may provide an essential basis for the management and conservation of the unique genetic resources in northern East Africa, and advance our understanding of biodiversity, phylogeny, evolution and development towards phylogenetically more accurate taxonomic classifications.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12862-021-01829-2.

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          Most cited references62

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          Detecting the number of clusters of individuals using the software structure: a simulation study

          The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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            STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method

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              Estimation of average heterozygosity and genetic distance from a small number of individuals.

              M Nei (1978)
              The magnitudes of the systematic biases involved in sample heterozygosity and sample genetic distances are evaluated, and formulae for obtaining unbiased estimates of average heterozygosity and genetic distance are developed. It is also shown that the number of individuals to be used for estimating average heterozygosity can be very small if a large number of loci are studied and the average heterozygosity is low. The number of individuals to be used for estimating genetic distance can also be very small if the genetic distance is large and the average heterozygosity of the two species compared is low.
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                Author and article information

                Contributors
                bubuwiwi2008@gmail.com
                paul.meulenbroek@boku.ac.at
                Journal
                BMC Ecol Evol
                BMC Ecol Evol
                BMC Ecology and Evolution
                BioMed Central (London )
                2730-7182
                7 June 2021
                7 June 2021
                2021
                : 21
                : 113
                Affiliations
                [1 ]EIAR - National Fisheries and Other Aquatic Life Research Center, P.O. Box 64, Sebeta, Ethiopia
                [2 ]GRID grid.5173.0, ISNI 0000 0001 2298 5320, Institute for Integrative Nature Conservation Research, , University of Natural Resources and Life Sciences, Vienna, ; Gregor Mendel-Straße 33, 1180 Vienna, Austria
                [3 ]GRID grid.9983.b, ISNI 0000 0001 2181 4263, MARE-Marine and Environmental Sciences Centre, , Universidade de Lisboa, ; Lisbon, Portugal
                [4 ]GRID grid.5173.0, ISNI 0000 0001 2298 5320, Institute of Hydrobiology and Aquatic Ecosystem Management (IHG), , University of Natural Resources and Life Sciences, Vienna, ; Gregor-Mendel Straße 33, 1180 Vienna, Austria
                [5 ]WasserCluster Lunz – biologische Station, Lunz am See, Dr. Carl Kupelwieser Prom. 5, 3293 Lunz/See, Austria
                [6 ]GRID grid.5110.5, ISNI 0000000121539003, University of Graz, Institute of Biology, ; Universitätsplatz 2, 8010 Graz, Austria
                [7 ]National Environment Management Authority, P.O. Box 22255, Kampala, Uganda
                [8 ]GRID grid.7123.7, ISNI 0000 0001 1250 5688, Department of Zoological Sciences, , Addis Ababa University, ; 1000 Addis Ababa, Ethiopia
                Article
                1829
                10.1186/s12862-021-01829-2
                8183085
                34098870
                e3bd132a-fa4e-42ee-939a-d96f0c0e7d4c
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 15 March 2021
                : 9 May 2021
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                ethiopian rift valley,cichlid,genotyping,admixture,freshwater biodiversity,stocking

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