title: The genetic analysis of age-dependent traits: modeling the character process.
abstract: The extension of classical quantitative genetics to deal with function-valued characters (also called infinite-dimensional characters) such as growth curves, mortality curves, and reaction norms, was begun by Kirkpatrick and co-workers. In this theory, the analogs of variance components for single traits are covariance functions for function-valued traits. In the approach presented here, we employ a variety of parametric models for covariance functions that have a number of desirable properties: the functions (1) are positive definite, (2) can be estimated using procedures like those currently used for single traits, (3) have a small number of parameters, and (4) allow simple hypotheses to be easily tested. The methods are illustrated using data from a large experiment that examined the effects of spontaneous mutations on age-specific mortality rates in Drosophila melanogaster. Our methods are shown to work better than a standard multivariate analysis, which assumes the character value at each age is a distinct character. Advantages over existing methods that model covariance functions as a series of orthogonal polynomials are discussed.
authors.affiliation: Department of Ecology, Evolution and Behavior, University of Minnesota, Sait Paul, Minnesota 11508, USA. pletcher@demogr.mpg.de
authors.forename: S D
authors.initials: SD
authors.lastname: Pletcher
authors.forename: C J
authors.initials: CJ
authors.lastname: Geyer
mesh_terms: D000375:Aging / Q000235:genetics*; D000818:Animals; D003198:Computer Simulation; D004331:Drosophila melanogaster / Q000235:genetics / Q000254:growth & development; D005260:Female; D006128:Growth / Q000235:genetics; D008136:Longevity / Q000235:genetics; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D009154:Mutation; D011336:Probability