Acta Scientific Veterinary Sciences (ISSN: 2582-3183)

Research Article Volume 6 Issue 4

Microsatellites Diversity Analysis of Nigerian Chicken Genetic Resources in the Rising Climatic Change

Bolatito OA1-3*, Akpere L4, Ilori BM1,5, Hassan TB2, Ajayi DA2, Omitogun OG4, Okere AU2, Aladele SE2 and Adebambo AO1,5

1Centre of Excellence in Agricultural Development and Sustainable Environment, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria
2National Centre for Genetic Resources and Biotechnology, Moor Plantation, Ibadan, Oyo State, Nigeria
3Federal College of Animal Health and Production Technology, Moor Plantation, Ibadan, Oyo State. Nigeria
4Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria
5Department of Animal Breeding and Genetics, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria

*Corresponding Author: Bolatito OA, Centre of Excellence in Agricultural Development and Sustainable Environment, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria.

Received: February 26, 2024Published: March 06, 2024


Microsatellite diversity analysis is crucial for Nigerian chicken genetic resources (NCGR) in the rising climatic change which can help to identify genetic diversity within the population. The study described the microsatellites diversity of NCGR. Genomic Deoxyribonucleic Acid (DNA) was isolated from chicken blood samples using Invitrogen DNA extraction kit. Twenty FAO/ISAG microsatellite markers were used in multiplex Polymerase Chain Reaction to amplify 96 Nigerian chickens’ genomes. The fluorescent amplicons were analyzed through Capillary Electrophoresis using Hitachi ABI PRISM 3130 X 1 DNA Sequencer at the Laboratorio de Genetica Animal, EMBRAPA Suinos e Aves, Concordia-SC, Brazil. Genetic diversity and calculations of the variations among the NCGR were performed in GenALEx software 6.5. The microsatellites analysis of NCGR revealed selection against heterozygosity in the population with the exception of 7 markers that showed negative inbreeding levels. The mean number of alleles per locus of 4.279 with sizes ranging from 87 to 360 base pairs were detected. A relative average of 50% heterozygosity was obtained in the NCGR population. Mean fixation index (F) over all loci for the chicken strains of 0.134±0.037 indicates free interbreeding. The inbreeding co-efficient of FIS 0.145 across markers and population differentiations deviated from Hardy-Weinberg Equilibrium. The NCGR population subdivision of FST 0.132 over the loci indicated moderate differentiation. Migrant rate of 2.01 was obtained for each marker across the NCGR population. Pairwise FST by AMOVA of 0.175 indicates low to moderate differentiation among the chicken sub-populations while the NW and SB chickens are highly differentiated, FST 0.175. Developing appropriate management strategies will help to protect the microsatellite diverse but less differentiated Nigerian chicken genetic resources (NCGR) population against the rising climatic change and will further support their adaptation and productivity.

Keywords: Nigerian Chicken Genetic Resources; Climate Change; Microsatellite Markers; Within Populations, Inbreeding Reduction


  1. Magiri R., et al. “Impact of Climate Change on Animal Health, Emerging and Re-emerging Diseases in Africa”. In: W. Leal Filho et al. (eds.), African Handbook of Climate Change Adaptation (2021): 1835-1851.
  2. "Climate Change: Impacts, adaptation and vulnerability: Working Group II contribution to the Fourth Assessment Report of the IPCC Intergovernmental Panel on Climate Change; Geneva”. (2007): 976.
  3. Lowe AJ., et al. “Genetic resource impacts of habitat loss and degradation; reconciling empirical evidence and predicted theory for Neotropical trees”. Heredity 95 (2005): 255-273.
  4. Moura RF., et al. “The use of microsatellite markers in Neotropical studies of wild birds: a literature review”. Anais da Academia Brasileira de Ciências1 (2017): 145-154.
  5. “Chicken genetic resources used in smallholder production systems and opportunities for their development”. In: P. Sørensen (ed), FAO Smallholder Poultry Production, Rome, Italy (2010) 53.
  6. Wang MS., et al. “863 genomes reveal the origin and domestication of chicken”. Cell Research 30 (2010): 693-701.
  7. Lawler A. “Why did the chicken cross the world?”. Atria Books, New York (2014).
  8. “Africa sustainable livestock (ASL) 2050. Livestock and livelihoods spotlight-Nigeria cattle and poultry sectors”. FAO, Rome, Italy (2018): 1-12.
  9. Bolatito OA., et al. “Utilisation and Registration Assessment Status of Chicken Genetic Resources in Nigeria”. Asian Journal of Research in Animal and Veterinary Sciences3 (2022): 28-36.
  10. Olori VE. “An evaluation of two ecotypes of the Nigerian Indigenous chicken”. Master of Science Thesis, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria (1992).
  11. Nwosu CC., et al. “A biometrical study of the conformation of the native chickens”. Nigerian Journal of Animal Production 12 (1985): 141-146.
  12. Eshiett NO., et al. “Productivity of indigenous chicken under village management system”. A paper presented at 25th Annual Conference of Agricultural Society of Nigeria, Owerri, Imo State. Nigeria (1989).
  13. Ukwu H., et al. “Preliminary Assessment of Within-Ecotype Genetic Diversity at the Haemoglobin Locus in the Tiv Local Chickens in Makurdi, Nigeria”. International Journal of Livestock Research4 (2018): 22-29.
  14. Crawford R. “Poultry Breeding and Genetics”. Developments in Animal and Veterinary Sciences 22 (1990). Elsevier, Amsterdam.
  15. Bolatito OA., et al. “Fertility and hatchability potentials of Shikabrown® chickens and effect of body weight and age of chicken on egg quality traits in the Southwest, Nigeria”. Nigerian Journal of Animal Science2 (2017): 23-32.
  16. NACGRAB FMST. “The National Register for Chicken. National Committee for the Naming, Registration and Release of Crop Varieties and Livestock breeds”. National Centre for Genetic Resources and Biotechnology, Federal Ministry of Science and Technology (200)1-2.
  17. NACGRAB FMST. “The National Register for Chicken”. National Committee for the Naming, Registration and Release of Crop Varieties and Livestock breeds. National Centre for Genetic Resources and Biotechnology, Federal Ministry of Science and Technology (2018) 3-4.
  18. Primmer CR., et al. “Frequency of Microsatellites in the Avian Genome”. Nature Genetics 13 (2019): 391-393.
  19. Ellegren H. “Microsatellites: simple sequences with complex evolution”. National Revolution Genetics 5 (2004): 435-445.
  20. Carrano AV., et al. “Constructing chromosome-and region-specific cosmid maps of the human genome”. Genome2 (1989): 1059-1065.
  21. Padhi MK. “Importance of indigenous breeds of chicken for rural economy and their improvements for higher production performance”. Hindawi Publishing Corporation Scientifica (2016): 1-9.
  22. Olowofeso O. “Combined exclusion of probabilities of ten microsatellite markers used with Nigerian Chicken populations”. European International Journal of Science and Technology 4 (2016): 21-32.
  23. Carvalho DA., et al. “Diversity and Genetic Relationship of Free-Range Chickens from the Northeast Region of Brazil”. Animals 10 (2020): 1857-1870.
  24. Bianchi M., et al. “A microsatellites-based survey on the genetic structure of two Italian local chicken breeds”. Italian Journal of Animal Sciencee39 (2011): 205-211.
  25. Ohwojakpor O., et al. “Genetic diversity of chicken populations in south-south region of Nigeria using microsatellite markers”. Egyptian Journal of Poultry Science 2 (2012): 263-271.
  26. Tadelle D., et al. “Village chicken production systems in Ethiopia: 2. Use pattern and performance valuation and chicken products and socio-economic functions of chicken”. Livestock Resource for Rural Development, 15.1 (2003).
  27. Rudresh BH., et al. “Microsatellite based genetic diversity study in indigenous chicken ecotypes of Karnataka”. Veterinary World 8 (2015): 970-976.
  28. “Molecular characterization of animal genetic resources. FAO Animal Production and Health Guidelines”. No. 9. Rome. (2011): 85.
  29. Desjardins P., et al. “Nanodrop microvolume quantification of nucleic acid”. Journal of Visual Experimentation45 (2010): 2565.
  30. Applied Biosystems. “Genemapper Software version 4.1”. Microsatellite analysis getting started guide (2009): 1-71.
  31. Peakall R., et al. “GenAlEx 6.5: genetic analysis in excel. Population genetic software for teaching and research, an update”. Bioinformatics 28 (2012): 2537-2539.
  32. Nei M. “Genetic distance between populations”. The American Naturalist949 (1972): 283-292.
  33. Ponsuksili S., et al. “Genetic variability in chickens using polymorphic microsatellites markers”. Thailand Journal of Agricultural Science 29 (1996): 571-580.
  34. Van Marle-Koster E., et al. “Genetic diversity and population structure of locally adapted South African chicken lines: implication for conservation”. South African Journal of Animal Science4 (2008): 271-281.
  35. Davila SG., et al. “Evaluation of diversity between different Spanish chicken breeds, a tester line, and a White Leghorn population based on microsatellite markers”. Poultry Science 88 (2009): 2518-2525.
  36. Hillel J., et al. “Biodiversity of 52 chicken populations assessed by microsatellite typing of DNA pools”. Genetic Selection Evolution 35 (2003): 533-557.
  37. Zhang X., et al. “Genetic diversity of Chinese native chicken breeds based on protein polymorphism, randomly amplified polymorphic DNA, and microsatellite polymorphism”. Poultry Science81 (2002): 1463-1472.
  38. Fonteque GV., et al. “Genetic polymorphism of fifteen microsatellite loci in Brazilian (blue-egg Caipira) chickens”. Pesquisa Veterinaria Brasileira1 (2014): 98-102.
  39. Muchadeyi FC., et al. “Variation in village chicken production systems among agro-ecological zones of Zimbabwe”. Tropical Animal Health Production 39 (2007): 453-461.
  40. Groen AF., et al. “Microsatellite polymorphism in commercial broiler and layer lines”. In: Proceedings of the 5th World Congress on Genetics Applied to Livestock Production. University of Guelph, Guelph, ON, Canada 21 (1994): 94-97.
  41. Ajibike AB., et al. “Genetic diversity and population structure of Nigerian indigenous chickens inferred from microsatellite markers”. Agriclturae Conspectus Scientificus (Poljoprivredna Znansteva Smotra) 1 (2022): 61-67.
  42. Pryke SR., et al. “The relative role of male vs. female mate choice in maintaining assortative pairing among discrete colour morphs”. Journal of Evolutionary Biology 30 (2000): 1512-1521.
  43. Wright S. “The Interpretation of Population Structure by F-Statistics with Special Regard to Systems of Mating”. Evolution3 (1965): 395-420.
  44. Adebambo AO., et al. “Characterisation of Nigeria indigenous chicken ecotypes using microsatellite markers”. In: Proceedings of the 3rd Nigeria International Poultry Summit February 22-26, SI, Ola (2009): 84-91.
  45. Hassen H., et al. “Study on the genetic diversity of native chickens in Northwest Ethiopia using microsatellite markers”. African Journal of Biotechnology7 (2009): 1347-1353.
  46. Excoffer L., et al. “Analysis of molecular variance inferred from metric distances among DNA haplotypes: Application to human mitochondrial DNA restriction data”. Genetics 131 (1992): 479-491.
  47. Sami AF., et al. “Genetic variation analysis of Sinai chicken and Japanese quail populations using microsatellite DNA markers”. In: Proceedings of International Conference on Food and Agricultural Sciences, Singapore 55 (2013): 12-17.
  48. Khobondo JO., et al. “Genetic and nutrition development of indigenous chicken in Africa”. Livestock Research for Rural Development 7 (2015).
  49. Hartl DL. “A primer of population genetics, 2nd edition" Sunderland, Mass., Sinauer Associates, Inc. (1988): 305.


Citation: Bolatito OA., et al. “Microsatellites Diversity Analysis of Nigerian Chicken Genetic Resources in the Rising Climatic Change".Acta Scientific Veterinary Sciences 6.4 (2024): 03-15.


Copyright: © 2024 Bolatito OA., et al. 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.


Acceptance rate35%
Acceptance to publication20-30 days
Impact Factor1.008

Indexed In

News and Events

  • Certification for Review
    Acta Scientific certifies the Editors/reviewers for their review done towards the assigned articles of the respective journals.
  • Submission Timeline for Upcoming Issue
    The last date for submission of articles for regular Issues is June 25, 2024.
  • Publication Certificate
    Authors will be issued a "Publication Certificate" as a mark of appreciation for publishing their work.
  • Best Article of the Issue
    The Editors will elect one Best Article after each issue release. The authors of this article will be provided with a certificate of "Best Article of the Issue"
  • Welcoming Article Submission
    Acta Scientific delightfully welcomes active researchers for submission of articles towards the upcoming issue of respective journals.

Contact US