Empirical Evaluation of Genetic Clustering Methods Using Multilocus Genotypes From 20 Chicken Breeds

We tested the utility of genetic cluster analysis in ascertaining population structure of a large data set for which population structure was previously known. Each of 600 individuals representing 20 distinct chicken breeds was genotyped for 27 microsatellite loci, and individual multilocus genotype...

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Bibliographic Details
Published in:Genetics (Austin) 2001-10, Vol.159 (2), p.699-713
Main Authors: Rosenberg, Noah A, Burke, Terry, Elo, Kari, Feldman, Marcus W, Freidlin, Paul J, Groenen, Martien A. M, Hillel, Jossi, Maki-Tanila, Asko, Tixier-Boichard, Michele, Vignal, Alain, Wimmers, Klaus, Weigend, Steffen
Format: Article
Language:English
Subjects:
Algorithms
Animal Breeding and Genetics
Animal Breeding and Genomics
Animal populations
Animals
Chickens - genetics
Fokkerij en Genetica
Fokkerij en Genomica
Genes
Genetic Markers
Genetics
Genotype
Heterozygote
Leerstoelgroep Fokkerij en genetica
Life Sciences
Multigene Family
Poultry
Species Specificity
WIAS
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Summary:We tested the utility of genetic cluster analysis in ascertaining population structure of a large data set for which population structure was previously known. Each of 600 individuals representing 20 distinct chicken breeds was genotyped for 27 microsatellite loci, and individual multilocus genotypes were used to infer genetic clusters. Individuals from each breed were inferred to belong mostly to the same cluster. The clustering success rate, measuring the fraction of individuals that were properly inferred to belong to their correct breeds, was consistently approximately 98%. When markers of highest expected heterozygosity were used, genotypes that included at least 8-10 highly variable markers from among the 27 markers genotyped also achieved >95% clustering success. When 12-15 highly variable markers and only 15-20 of the 30 individuals per breed were used, clustering success was at least 90%. We suggest that in species for which population structure is of interest, databases of multilocus genotypes at highly variable markers should be compiled. These genotypes could then be used as training samples for genetic cluster analysis and to facilitate assignments of individuals of unknown origin to populations. The clustering algorithm has potential applications in defining the within-species genetic units that are useful in problems of conservation.
ISSN:0016-6731
1943-2631
1943-2631
DOI:10.1093/genetics/159.2.699