3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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.

          Related collections

          Most cited references42

          • Record: found
          • Abstract: found
          • Article: not found

          Inference of Population Structure Using Multilocus Genotype Data

          We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Application of phylogenetic networks in evolutionary studies.

              The evolutionary history of a set of taxa is usually represented by a phylogenetic tree, and this model has greatly facilitated the discussion and testing of hypotheses. However, it is well known that more complex evolutionary scenarios are poorly described by such models. Further, even when evolution proceeds in a tree-like manner, analysis of the data may not be best served by using methods that enforce a tree structure but rather by a richer visualization of the data to evaluate its properties, at least as an essential first step. Thus, phylogenetic networks should be employed when reticulate events such as hybridization, horizontal gene transfer, recombination, or gene duplication and loss are believed to be involved, and, even in the absence of such events, phylogenetic networks have a useful role to play. This article reviews the terminology used for phylogenetic networks and covers both split networks and reticulate networks, how they are defined, and how they can be interpreted. Additionally, the article outlines the beginnings of a comprehensive statistical framework for applying split network methods. We show how split networks can represent confidence sets of trees and introduce a conservative statistical test for whether the conflicting signal in a network is treelike. Finally, this article describes a new program, SplitsTree4, an interactive and comprehensive tool for inferring different types of phylogenetic networks from sequences, distances, and trees.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                28 September 2021
                2021
                : 12
                : 723706
                Affiliations
                [1] 1Department of Animal Science, Faculty of Animal Science and Export Agriculture, Uva Wellassa University , Badulla, Sri Lanka
                [2] 2Postgraduate Institute of Agriculture, University of Peradeniya , Peradeniya, Sri Lanka
                [3] 3International Livestock Research Institute (ILRI) , Nairobi, Kenya
                [4] 4CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS) , Beijing, China
                [5] 5Department of Animal Science, Faculty of Agriculture, University of Peradeniya , Peradeniya, Sri Lanka
                Author notes

                Edited by: Mohammed Ali Al Abri, Sultan Qaboos University, Oman

                Reviewed by: Giri Athrey, Texas A&M University, United States; Coralie Danchin, Institut de l’Elevage, France

                *Correspondence: Pradeepa Silva, pradeepas@ 123456pdn.ac.lk

                This article was submitted to Livestock Genomics, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2021.723706
                8505892
                34650594
                4b048344-67fc-4b92-af2c-60d2bdff5548
                Copyright © 2021 Samaraweera, Liyanage, Ibrahim, Okeyo, Han and Silva.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 11 June 2021
                : 25 August 2021
                Page count
                Figures: 10, Tables: 8, Equations: 0, References: 43, Pages: 13, Words: 8573
                Funding
                Funded by: Global Environment Facility, doi 10.13039/100011150;
                Categories
                Genetics
                Original Research

                Genetics
                local chicken,microsatellite marker,genetic diversity,population structure,tropical climate

                Comments

                Comment on this article