Integration of Maximum Likelihood Paternity Analysis with Quantitative Genetics

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9707722 Meagher Paternity analysis and quantitative genetic analysis both have proven to be effective tools for studying the evolutionary dynamics of contemporary populations. A large number of recent studies have incorporated these methodologies on one level or another. One of the ongoing problems in applying quantitative genetic approaches, however, lies in obtaining precise estimates of quantitative genetic parameters, such as additive genetic variation and genetic correlations. Such estimates have been obtained for a limited number of species, primarily short-lived organisms that can be readily bred under controlled conditions and with crossing designs over two or more generations. A short-cut often used for long-lived organisms is to make measurements on field-collected progeny, typically grouped into maternal sibships. Because investigators do not usually know whether individuals within maternal sibships are related as half-sibs (different fathers) or full-sibs (the same father), such maternal sibships provide estimates that are confounded with maternal and dominance effects to an unmeasured and unknown degree. These estimates are thus only gross approximations to additive genetic variance values. Statistical advances in genetic-marker based paternity analysis over the past decade have made it feasible to determine the underlying paternal sibship structure of field-collected progeny in considerable detail. The goal of this project is to integrate maximum likelihood methods for paternity analysis with maximum likelihood estimation of quantitative genetic parameters. In this way, more complete information about genealogical relationships within field-collected progeny can be brought to bear, and evolutionary studies of natural populations substantively enhanced.