title: A computing platform to map ecological metabolism by integrating functional mapping and the metabolic theory of ecology.
abstract: Whole-organism metabolic rate co-varies allometrically with body mass, and is also affected by temperature through different biochemical mechanisms. Here we implement a computational platform to map specific quantitative trait loci (QTLs) that govern the dependence of metabolic rate on size and temperature. The model was formulated within settings of genetic mapping or genome-wide association studies through a mapping population genotyped by a set of molecular markers throughout the genome and phenotyped for metabolic parameters over a range of temperature. The model, estimated by a maximum-likelihood approach, allows a genome-wide search for the underlying metabolic QTLs and the estimation of genotype-specific parameters that specify the metabolism of an organism. Our model provides a tool to detect pleiotropy and epistasis that cause the size- and temperature-dependent change of metabolic rate.
authors.forename: Qin
authors.initials: Q
authors.lastname: Yan
authors.forename: Xuli
authors.initials: X
authors.lastname: Zhu
authors.forename: Libo
authors.initials: L
authors.lastname: Jiang
authors.forename: Meixia
authors.initials: M
authors.lastname: Ye
authors.forename: Lidan
authors.initials: L
authors.lastname: Sun
authors.forename: John S
authors.initials: JS
authors.lastname: Terblanche
authors.forename: Rongling
authors.initials: R
authors.lastname: Wu
mesh_terms: D002874:Chromosome Mapping; D017753:Ecosystem; D055106:Genome-Wide Association Study; D005838:Genotype; D016013:Likelihood Functions; D040641:Quantitative Trait Loci
keywords: QTL; allometry; functional mapping; the metabolic theory of ecology