A hyperspace model to decipher the genetic architecture of developmental processes: allometry meets ontogeny.
To better utilize limited resources for their survival and reproduction, all organisms undergo developmental changes in both body size and shape during ontogeny. The genetic analysis of size change with increasing age, i.e., growth, has received considerable attention in quantitative developmental genetic studies, but the genetic architecture of ontogenetic changes in body shape and its associated allometry have been poorly understood partly due to the lack of analytical tools. In this article, we attempt to construct a multivariate statistical framework for studying the genetic regulation of ontogenetic growth and shape. We have integrated biologically meaningful mathematical functions of growth curves and developmental allometry into the estimation process of genetic mapping aimed at identifying individual quantitative trait loci (QTL) for phenotypic variation. This model defined with high dimensions can characterize the ontogenetic patterns of genetic effects of QTL over the lifetime of an organism and assess the interplay between genetic actions/interactions and phenotypic integration. The closed forms for the residual covariance matrix and its determinant and inverse were derived to overcome the computational complexity typical of our high-dimensional model. We used a worked example to validate the utility of this model. The implications of this model for genetic research of evo-devo are discussed.
Wu
Rongling
R
Department of Statistics, University of Florida, Gainesville, Florida 32611, USA. rwu@stat.ufl.edu
Hou
Wei
W
D000465:Algorithms; D005075:Biological Evolution; D002874:Chromosome Mapping; D032461:Chromosomes, Plant; D004843:Epistasis, Genetic; D008040:Genetic Linkage; D006128:Growth / Q000235:genetics*; D008957:Models, Genetic; D010641:Phenotype; D032107:Populus / Q000235:genetics / Q000254:growth & development; D040641:Quantitative Trait Loci