A computing platform to map ecological metabolism by integrating functional mapping and the metabolic theory of ecology

Qin Yan, Xuli Zhu, Libo Jiang, Meixia Ye, Lidan Sun, John S. Terblanche, Rongling Wu

Research output: Contribution to journalArticle

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 metabolismof an organism. Our model provides a tool to detect pleiotropy and epistasis that cause the size- and temperature-dependent change of metabolic rate.

Original languageEnglish (US)
Pages (from-to)137-144
Number of pages8
JournalBriefings in bioinformatics
Volume18
Issue number1
DOIs
StatePublished - Jan 1 2017

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Molecular Biology

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