H. Harrison, P. Saenz-Agudelo, S. Planes, G. Jones, M. Berumen
Molecular Ecology, 22, pp. 1158-1170, (2013)
Parentage studies and family reconstructions have become increasingly
popular for investigating a range of evolutionary, ecological and
behavioural processes in natural populations. However, a number of
different assignment methods have emerged in common use and the accuracy
of each may differ in relation to the number of loci examined, allelic
diversity, incomplete sampling of all candidate parents and the presence
of genotyping errors. Here, we examine how these factors affect the
accuracy of three popular parentage inference methods (colony, famoz
and an exclusion-Bayes’ theorem approach by Christie (Molecular Ecology
Resources, 2010a, 10, 115) to resolve true parent–offspring pairs using
simulated data. Our findings demonstrate that accuracy increases with
the number and diversity of loci. These were clearly the most important
factors in obtaining accurate assignments explaining 75–90% of variance
in overall accuracy across 60 simulated scenarios. Furthermore, the
proportion of candidate parents sampled had a small but significant
impact on the susceptibility of each method to either false-positive or
false-negative assignments. Within the range of values simulated, colony
outperformed FaMoz, which outperformed the exclusion-Bayes’ theorem
method. However, with 20 or more highly polymorphic loci, all methods
could be applied with confidence. Our results show that for parentage
inference in natural populations, careful consideration of the number
and quality of markers will increase the accuracy of assignments and
mitigate the effects of incomplete sampling of parental populations.