Assessment of the Genetic Diversity and Population Structure of Local Chickens of Five Gabonese Ecotypes Using 28 of the 30 Microsatellite Markers Recommended by the FAO
DOI:
https://doi.org/10.3923/ijps.2024.109.121Keywords:
Gabon, Gallus gallus domesticus, genetic diversity, Indigenous chicken, introgression, population structureAbstract
Background and Objective: The management of livestock biodiversity has become an important issue for the international scientific community. For this purpose, we assessed genetic variation in local chicken (Gallus gallus) populations from five regions of Gabon. Materials and Methods: A total of 28 microsatellite markers were used to genotype 194 individuals, including one commercial line (Isa Brown) that was assessed for possible introgression into local gene pools. A total of 292 alleles were revealed in the whole population with an average of 10.429 alleles per locus. Results: The observed heterozygosity rate was 0.484, 0.472, 0.495, 0.483 and 0.495 for Franceville, Libreville, Makokou, Mouila and Oyem, respectively. These values are below the expected heterozygosity for each locality (p<0.05). This resulted in a positive inbreeding coefficient in the local chicken populations and a negative coefficient in the commercial chickens. Wright's F-statistics (Fit = 0.216; Fis = 0.110; Fst = 0.123) suggesting moderate differentiation of individuals. Analysis of molecular variance revealed that 83% of the total genetic diversity was attributed to within-population variation and the remaining 5 and 12% were attributed to differentiation between regions and individuals, respectively. The pairwise genetic distances of the populations were very small (0.008≤GD≤0.017) between local populations and very large (0.833≤GD≤0.884) when comparing the local populations to the commercial chicken population. The analysis of the structure of the whole population revealed three genetic entities. These results showed that the study population has a satisfactory genetic diversity and a low level of introgression of exotic genes into the identified local gene pool. Conclusion: This genetic diversity constitutes an important basis for the implementation of conservation and genetic improvement programmes for local chickens in Gabon.
References
Fadlaoui, A., 2006. Modélisation bioéconomique de la conservation des ressources génétiques animales. Ph.D. Thesis, Université Catholique de Louvain
FAO, 2011. Draft guidelines on molecular genetic characterization of animal genetic resources. Rome Comm. Genet. Food Agric. Sixth Sess. 61-63. https://openknowledge.fao.org/items/b7a00762-aa91-4991-9221-2d7ee5029dd9
Tadano, R., M. Sekino, M. Nishibori and M. Tsudzuki, 2007. Microsatellite marker analysis for the genetic relationships among Japanese long-tailed chicken breeds. Poult. Sci., 86: 460-469.
FAO, 2005. Interactions of Gender, Agricultural Biodiversity and Local Knowledge in the Service of Food Security [In French]. Food and Agriculture Organization, Rome, Italy, Pages: 190.
Zanetti, E., 2009. Genetic, phenotypic and proteomic characterisation of local chicken breeds. Ph.D. Thesis, University of Padua.
FAO, 2007. The state of the world's animal genetic resources for food and agriculture. Food and Agriculture Organization, Rome, Italy, Pages: 511.
FAO., 2007. Global plan of action for animal genetic resources and the Interlaken declaration. Proceeding of the International Technical Conference on Animal Genetic Resources for Food and Agriculture Interlaken, September 3-7, 2007 Food and Agriculture Organization of the United Nations 1-37.
Mboumba, S., G.D. Maganga, M.A. Ndzighe and T.C. Keambou, 2020. Morphobiometric characterization of the local chicken from two regions of Gabon. J. Interdiscip. Res. Sci., 1: 26-34.
Habimana, R., T.O. Okeno, K. Ngeno, S. Mboumba and P. Assami et al., 2020. Genetic diversity and population structure of indigenous chicken in Rwanda using microsatellite markers. PLOS ONE, Vol. 15.
Keambou, T.C., B.A. Hako, S. Ommeh, C. Bembide and E.P. Ngono et al., 2014. Genetic diversity of the Cameroon indigenous chicken ecotypes. Int. J. Poult. Sci., 13: 279-291.
Smith, L.M. and L.A. Burgoyne, 2004. Collecting, archiving and processing DNA from wildlife samples using FTA databasing paper. BMC Ecol., 4: 4-4.
FAO, 2011. Draft guidelines on molecular genetic characterization of animal genetic resources. Commission on Genetic Resources for Food and Agriculture, Thirteenth Regular Session, Rome, Italy. http://www.fao.org/docrep/meeting/022/am652e.pdf.
Guo, X. and R.C. Elston, 1999. Linkage information content of polymorphic genetic markers. Hum. Heredity, 49: 112-118.
Liu, K. and S.V. Muse, 2005. PowerMarker: An integrated analysis environment for genetic marker analysis. Bioinformatics, 21: 2128-2129.
Google, 2024. Google Earth Pro 7.3.6.9796. https://earth.google.com/web/search/Gabon
Peakall, R. and P.E. Smouse, 2012. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics, 28: 2537-2539.
Nei, M., 1972. Genetic distance between populations. Am. Naturalist, 106: 283-292.
Yeh, F.C., R.C. Yang, T.B.J. Boyle, Z. Ye, J.M. Xiyan, R. Yang and T.J. Boyle, 2000. PopGene32, Microsoft Windows-based freeware for population genetic analysis. Version 1.32. Molecular Biology and Biotechnology Centre, University of Alberta, Edmonton, Canada. https://www.scienceopen.com/document?vid=2d45ad78-b140-4b66-b80f-2c9f513ec997.
Perrier, X. and J.P. Jacquemoud-Collet, 2006. DARwin software. Genetic Improvement of Vegetatively Propagated Crops. http://darwin.cirad.fr/Home.php.
Pritchard, J.K., M. Stephens and P. Donnelly, 2000. Inference of population structure using multilocus genotype data. Genetics, 155: 945-959.
Evanno, G., S. Regnaut and J. Goudet, 2005. Detecting the number of clusters of individuals using the software structure: A simulation study. Mol. Ecol., 14: 2611-2620.
Earl, D.A. and B.M. vonHoldt, 2012. Structure harvester: A website and program for visualizing structure output and implementing the Evanno method. Conservation Genet. Resour., 4: 359-361.
Kaya, M. and M.A. Yildiz, 2008. Genetic diversity among Turkish native chickens, denizli and gerze, estimated by microsatellite markers. Biochem. Genet., 46: 480-491.
Yacouba, Z., H. Isidore, K. Michel, G.B. Isidore and T. Boureima et al., 2022. Genetic diversity and population structure of local chicken ecotypes in Burkina Faso using microsatellite markers. Genes, Vol. 13.
Fotsa, J.C., D.P. Kamdem, A. Bordas, M. Tixier-Boichard and X. Rognon, 2011. Assessment of the genetic diversity of Cameroon indigenous chickens by the use of microsatellites. Livest. Res. Rural Dev., Vol. 23.
Bodzsar, N., H. Eding, T. Revay, A. Hidas and S. Weigend, 2009. Genetic diversity of Hungarian indigenous chicken breeds based on microsatellite markers. Anim. Genet., 40: 516-523.
Dana, N., 2011. Breeding programs for indigenous chicken in Ethiopia: Analysis of diversity in production systems and chicken populations. Ph.D. Thesis, Wageningen University, The Netherlands.
Clementino, C.S., F.J.V. Barbosa, A.M.F. Carvalho, R.A.R. Costa-Filho and G.R. Silva et al., 2010. Microsatellite DNA Loci for population studies in Brazilian chicken ecotypes. Int. J. Poult. Sci., 9: 1100-1106.
Li, Y.C., A.B. Korol, T. Fahima, A. Beiles and E. Nevo, 2002. Microsatellites: Genomic distribution, putative functions and mutational mechanisms: A review. Mol. Ecol., 11: 2453-2465.
Putman, A.I. and I. Carbone, 2014. Challenges in analysis and interpretation of microsatellite data for population genetic studies. Ecol. Evol., 4: 4399-4428.
Cheng, H.W., 2010. Breeding of tomorrow's chickens to improve well-being. Poult. Sci., 89: 805-813.
Loukou N.E., C.V. Yapi-Gnaoré, T. Gnénékita, Y. Coulibaly and X. Rognon et al., 2009. Evaluation de la diversité des poulets traditionnels de deux zones agroecologiques de Cote d'Ivoire a l'aide de marqueurs microsatellites. J. Anim. Plant Sci., 5: 425-436.
Jordana, J., P. Alexandrino, A. Beja-Pereira, I. Bessa and J. Cañon et al., 2004. Genetic structure of eighteen local south European beef cattle breeds by comparative F-statistics analysis. J. Anim. Breed. Genet., 120: 73-87.
Mohammadabadi, M.R., M. Nikbakhti, H.R. Mirzaee, A. Shandi, D.A. Saghi, M.N. Romanov and I.G. Moiseyeva, 2010. Genetic variability in three native Iranian chicken populations of the Khorasan province based on microsatellite markers. Russ. J. Genet., 46: 505-509.
Holsinger, K.E. and B.S. Weir, 2009. Genetics in geographically structured populations: Defining, estimating and interpreting FST. Nat. Rev. Genet., 10: 639-650.
Ozdemir, D. and M. Cassandro, 2018. Assessment of the population structure and genetic diversity of Denizli chicken subpopulations using SSR markers. Ital. J. Anim. Sci., 17: 312-320.
Muchadeyi, F.C., H. Eding, C.B.A. Wollny, E. Groeneveld and S.M. Makuza et al., 2007. Absence of population substructuring in Zimbabwe chicken ecotypes inferred using microsatellite analysis. Anim. Genet., 38: 332-339.
van Marle-K-sterI, E., C.A. HeferI, L.H. NelII and M.A.M. Groenen, 2008. Genetic diversity and population structure of locally adapted South African chicken lines: Implications for conservation. S. Afr. J. Anim. Sci., vol.38.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 The Author(s)

This work is licensed under a Creative Commons Attribution 4.0 International License.
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.