Functional mapping for quantitative trait loci governing growth rates: a parametric model.
Are there-specific quantitative trait loci (QTL) governing growth rates in biology? This is emerging as an exciting but challenging question for contemporary developmental biology, evolutionary biology, and plant and animal breeding. In this article, we present a new statistical model for mapping QTL underlying age-specific growth rates. This model is based on the mechanistic relationship between growth rates and ages established by a variety of mathematical functions. A maximum likelihood approach, implemented with the EM algorithm, is developed to provide the estimates of QTL position, growth parameters characterized by QTL effects, and residual variances and covariances. Based on our model, a number of biologically important hypotheses can be formulated concerning the genetic basis of growth. We use forest trees as an example to demonstrate the power of our model, in which a QTL for stem growth diameter growth rates is successfully mapped to a linkage group constructed from polymorphic markers. The implications of the new model are discussed.
Wu
Rongling
R
Department of Statistics, University of Florida, Gainesville, Florida 32611, USA. rwu@stat.ufl.edu
Ma
Chang-Xing
CX
Zhao
Wei
W
Casella
George
G
D000367:Age Factors; D002678:Chimera / Q000235:genetics / Q000254:growth & development; D002874:Chromosome Mapping / Q000379:methods* / Q000706:statistics & numerical data*; D032461:Chromosomes, Plant / Q000235:genetics*; D003198:Computer Simulation; D017343:Genes, Plant / Q000235:genetics; D008040:Genetic Linkage / Q000235:genetics; D005838:Genotype; D016013:Likelihood Functions; D008957:Models, Genetic; D015233:Models, Statistical; D032107:Populus / Q000235:genetics* / Q000254:growth & development*; D040641:Quantitative Trait Loci / Q000235:genetics*