Towards unbiased parentage assignment: combining genetic, behavioural and spatial data in a Bayesian framework

• Published in: Molecular ecology Vol. 15; no. 12; pp. 3715 - 3730
• Main Authors: HADFIELD, J.D, RICHARDSON, D.S, BURKE, T
• Format: Journal Article
• Language: English
• Published: Oxford, UK Oxford, UK : Blackwell Publishing Ltd 01.10.2006; Blackwell Publishing Ltd
• Subjects: Acrocephalus sechellensis; Animals; Bayes Theorem; Bayesian analysis; Computer Simulation; Ecology; Evolutionary biology; Genetics, Population; maternity; MCMC; microsatellite; Molecular biology; parentage analysis; paternity; Pedigree; Population genetics; Sexual Behavior, Animal; Seychelles warbler; Songbirds - genetics; Songbirds - physiology
• ISSN: 0962-1083; 1365-294X
• DOI: 10.1111/j.1365-294X.2006.03050.x

Inferring the parentage of a sample of individuals is often a prerequisite for many types of analysis in molecular ecology, evolutionary biology and quantitative genetics. In all but a few cases, the method of parentage assignment is divorced from the methods used to estimate the parameters of primary interest, such as mate choice or heritability. Here we present a Bayesian approach that simultaneously estimates the parentage of a sample of individuals and a wide range of population-level parameters in which we are interested. We show that joint estimation of parentage and population-level parameters increases the power of parentage assignment, reduces bias in parameter estimation, and accurately evaluates uncertainty in both. We illustrate the method by analysing a number of simulated test data sets, and through a re-analysis of parentage in the Seychelles warbler, Acrocephalus sechellensis. A combination of behavioural, spatial and genetic data are used in the analyses and, importantly, the method does not require strong prior information about the relationship between nongenetic data and parentage.