1. ¹Department of Statistics, University of Florida, Gainesville, FL, USA
2. ²The Key Laboratory of Forest Genetics and Gene Engineering, Nanjing Forestry University, Nanjing, Jiangsu, People's Republic of China
3. ³UF Genetics Institute, University of Florida, Gainesville, FL, USA

Correspondence: Professor R Wu, Department of Statistics, University of Florida, Gainesville, FL 32611, USA. E-mail: rwu@stat.ufl.edu

Received 10 March 2008; Revised 25 April 2008; Accepted 30 April 2008; Published online 9 July 2008.

Abstract

Functional mapping has emerged as a next-generation statistical tool for mapping quantitative trait loci (QTL) that affect complex dynamic traits. In this article, we incorporated the idea of nonlinear mixed-effect (NLME) models into the mixture-based framework of functional mapping, aimed to generalize the spectrum of applications for functional mapping. NLME-based functional mapping, implemented with the linearization algorithm based on the first-order Taylor expansion, can provide reasonable estimates of QTL genotypic-specific curve parameters (fixed effect) and the between-individual variation of these parameters (random effect). Results from simulation studies suggest that the NLME-based model is more general than traditional functional mapping. The new model can be useful for the identification of the ontogenetic patterns of QTL genetic effects during time course.