High Genetic Diversity but Absence of Population Structure in Local Chickens of Sri Lanka Inferred by Microsatellite Markers

Amali Malshani Samaraweera; Ranga Liyanage; Mohamed Nawaz Ibrahim; Ally Mwai Okeyo; Jianlin Han; Pradeepa Silva

doi:10.3389/fgene.2021.723706

High Genetic Diversity but Absence of Population Structure in Local Chickens of Sri Lanka Inferred by Microsatellite Markers

Front Genet. 2021 Sep 28:12:723706. doi: 10.3389/fgene.2021.723706. eCollection 2021.

Authors

Amali Malshani Samaraweera¹, Ranga Liyanage², Mohamed Nawaz Ibrahim³, Ally Mwai Okeyo³, Jianlin Han^{3

4}, Pradeepa Silva⁵

Affiliations

¹ Department of Animal Science, Faculty of Animal Science and Export Agriculture, Uva Wellassa University, Badulla, Sri Lanka.
² Postgraduate Institute of Agriculture, University of Peradeniya, Peradeniya, Sri Lanka.
³ International Livestock Research Institute (ILRI), Nairobi, Kenya.
⁴ CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China.
⁵ Department of Animal Science, Faculty of Agriculture, University of Peradeniya, Peradeniya, Sri Lanka.

Abstract

Local chicken populations belonging to five villages in two geographically separated provinces of Sri Lanka were analyzed using 20 microsatellite markers to determine the genetic diversity of local chickens. Population genetic parameters were estimated separately for five populations based on geographic locations and for eight populations based on phenotypes, such as naked neck, long legged, crested or crown, frizzle feathered, Giriraj, commercial layer, crossbreds, and non-descript chicken. The analysis revealed that there was a high genetic diversity among local chickens with high number of unique alleles, mean number of alleles per locus (MNA), and total number of alleles per locus per population. A total of 185 microsatellite alleles were detected in 192 samples, indicating a high allelic diversity. The MNA ranged from 8.10 (non-descript village chicken) to 3.50 (Giriraj) among phenotypes and from 7.30 (Tabbowa) to 6.50 (Labunoruwa) among village populations. In phenotypic groups, positive inbreeding coefficient (F _IS) values indicated the existence of population substructure with evidence of inbreeding. In commercial layers, a high expected heterozygosity He = 0.640 ± 0.042) and a negative F _IS were observed. The positive F _IS and high He estimates observed in village populations were due to the heterogeneity of samples, owing to free mating facilitated by communal feeding patterns. Highly admixed nature of phenotypes was explained as a result of rearing many phenotypes by households (58%) and interactions of chickens among neighboring households (53%). A weak substructure was evident due to the mating system, which disregarded the phenotypes. Based on genetic distances, crown chickens had the highest distance to other phenotypes, while the highest similarity was observed between non-descript village chickens and naked neck birds. The finding confirms the genetic wealth conserved within the populations as a result of the breeding system commonly practiced by chicken owners. Thus, the existing local chicken populations should be considered as a harbor of gene pool, which can be readily utilized in developing locally adapted and improved chicken breeds in the future.

Keywords: genetic diversity; local chicken; microsatellite marker; population structure; tropical climate.