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

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

Noah A. Rosenberg^a, Terry Burke^b, Kari Elo^e, Marcus W. Feldman^a, Paul J. Freidlin^c, Martien A. M. Groenen^d, Jossi Hillel^c, Asko Mäki-Tanila^e, Michèle Tixier-Boichard^f, Alain Vignal^g, Klaus Wimmers^h, and Steffen Weigendⁱ
^a Department of Biological Sciences, Stanford University, Stanford, California 94305,
^b Department of Animal and Plant Sciences, Sheffield University, S10 2TN, United Kingdom,
^c Department of Genetics, The Hebrew University of Jerusalem, Faculty of Agriculture, Rehovot 76100, Israel,
^d Institute of Animal Sciences, Wageningen Agricultural University, 6700 AH Wageningen, The Netherlands,
^e Agricultural Research Centre, Institute of Animal Production, FIN-31600 Jokioinen, Finland,
^f Institut National de la Recherche Agronomique, Centre de Recherches de Jouy-en-Josas, 78 352 Jouy-en-Josas Cedex, France,
^g Institut National de la Recherche Agronomique, Centre INRA de Toulouse, 31326 Castanet Tolosan, France,
^h Institute of Animal Breeding Science, Rheinische Friedrich-Wilhelms-Universitat, D-53012 Bonn, Germany
ⁱ Institute for Animal Science and Animal Behaviour, Mariensee, 31535 Neustadt, Germany

Corresponding author: Noah A. Rosenberg, Program in Molecular and Computational Biology, University of Southern California, 1042 W. 36th Pl., DRB 155, Los Angeles, CA 90089-1113., noahr{at}usc.edu (E-mail)

Communicating editor: G. B. GOLDING

We tested the utility of genetic cluster analysis in ascertainingpopulation structure of a large data set for which populationstructure was previously known. Each of 600 individuals representing20 distinct chicken breeds was genotyped for 27 microsatelliteloci, and individual multilocus genotypes were used to infergenetic clusters. Individuals from each breed were inferredto belong mostly to the same cluster. The clustering successrate, measuring the fraction of individuals that were properlyinferred to belong to their correct breeds, was consistently $~$ 98%. When markers of highest expected heterozygosity were used,genotypes that included at least 8–10 highly variablemarkers from among the 27 markers genotyped also achieved >95%clustering success. When 12–15 highly variable markersand only 15–20 of the 30 individuals per breed were used,clustering success was at least 90%. We suggest that in speciesfor which population structure is of interest, databases ofmultilocus genotypes at highly variable markers should be compiled.These genotypes could then be used as training samples for geneticcluster analysis and to facilitate assignments of individualsof unknown origin to populations. The clustering algorithm haspotential applications in defining the within-species geneticunits that are useful in problems of conservation.

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