Agriculturae Conspectus Scientificus, Vol 86, No 2 (2021)

Genetic Diversity and Gene Flow among Three Chicken Populations in Nigeria Using Microsatellite Markers

Ibrahim Oyedamola BAKARE, Babatunde Moses ILORI, Mathew WHETO, Lawrence Tokunbo EGBEYALE, Adeyinka Julius SANDA, Olajide OLOWOFESO

Pages: 173-181

Summary


To understand the level of genetic diversity among and within three improved locally adapted chicken populations in Nigeria, six microsatellite markers were used with 100 genomic DNA from Shika Brown (SB = 34), FUNAAB Alpha (FA = 33), and Noiler (NL = 33). The allelic and genotypic profiles of each representative from each population were determined through polymerase chain reaction amplification of the repeat region. Genetic diversity, genetic distance, level of inbreeding, polymorphism information content, and combined exclusion probabilities of markers (CPE/CPF) were analyzed using Microsoft Excel microsatellite toolkit, GenAlex, Microsatellite Analyser, FSTAT, and Poptree2. 416 alleles with 18.99% rare and 81.01% fixed alleles were observed across populations. The mean number of alleles was 23.111 ± 0.43, mean effective number of alleles was 16.975 ± 0.75, the expected heterozygosity was 0.940 ± 0.00, observed heterozygosity was 0.396 ± 0.02, mean PIC value was 0.937, and mean gene flow rate was 10.874 ± 0.817. The mean FIS was 0.579 ± 0.037 and the global FST was 0.023 ± 0.002. Nei’s genetic distance revealed that Shika Brown and the Noiler chicken populations were related (0.6985). The combined exclusion probability (CPE) across markers and populations was 0.999 (excluding a parent) and CPF was 1.000 (excluding both parents). The PIC/marker values across populations were greater than the minimum value of 0.5. High FIS and low FST value indicated a high inbreeding level within and low degree of genetic differentiation among the chicken populations. In conclusion, the microsatellite markers used are highly polymorphic and suitable for parentage analysis, control inbreeding, and could be used as baseline genetic information in conservation programs.


Keywords


chicken, microsatellite markers, genetic diversity, combined probability of exclusion

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