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Originally published as Genetics Published Articles Ahead of Print on June 18, 2006.
Genetics, Vol. 173, 2091-2101, August 2006, Copyright © 2006
doi:10.1534/genetics.106.057331
Performance of Marker-Based Relatedness Estimators in Natural Populations of Outbred Vertebrates
Katalin Csilléry*,1,
Toby Johnson*,
Dario Beraldi*,
Tim Clutton-Brock
,
Dave Coltman
,
Bengt Hansson
,
Goran Spong and
Josephine M. Pemberton*
* Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom, Department of Zoology, University of Cambridge, Cambridge, CB2 3EJ, United Kingdom, Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada and Department of Animal Ecology, Lund University, 22362 Lund, Sweden
1 Corresponding author: Institute of Evolutionary Biology, School of Biological Sciences, The King's Buildings, Ashworth Laboratories, University of Edinburgh, W. Mains Rd., Edinburgh, EH9 3JT, United Kingdom.
E-mail: k.m.csillery{at}sms.ed.ac.uk
Knowledge of relatedness between pairs of individuals plays an important role in many research areas including evolutionary biology, quantitative genetics, and conservation. Pairwise relatedness estimation methods based on genetic data from highly variable molecular markers are now used extensively as a substitute for pedigrees. Although the sampling variance of the estimators has been intensively studied for the most common simple genetic relationships, such as unrelated, half- and full-sib, or parent–offspring, little attention has been paid to the average performance of the estimators, by which we mean the performance across all pairs of individuals in a sample. Here we apply two measures to quantify the average performance: first, misclassification rates between pairs of genetic relationships and, second, the proportion of variance explained in the pairwise relatedness estimates by the true population relatedness composition (i.e., the frequencies of different relationships in the population). Using simulated data derived from exceptionally good quality marker and pedigree data from five long-term projects of natural populations, we demonstrate that the average performance depends mainly on the population relatedness composition and may be improved by the marker data quality only within the limits of the population relatedness composition. Our five examples of vertebrate breeding systems suggest that due to the remarkably low variance in relatedness across the population, marker-based estimates may often have low power to address research questions of interest.
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