Exponential mapping of quantitative trait loci governing allometric relationships in organisms

Chang Xing Ma, George Casella, Ramon C. Littell, André I. Khuri, Rongling Wu

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Allometric scaling relationships or quarter-power rules, as a universal biological law, can be viewed as having some genetic component, and the particular genes (or quantitative trait loci, QTL) underlying these allometric relationships can be mapped using molecular markers. We develop a mathematical and statistical model for mapping allometric QTL on the basis of nonlinear power functions using Taylor's approximation theory. Simulation studies indicate that the QTL position and effect can be estimated using our model, but the estimation precision can be improved from the higher- over lower-order approximation when the sample size used and gene effects are small. The application of our approach in a real example from forest trees leads to successful detection of a QTL governing the allometric relationship between 3rd-year stem height and 3rd-year stem biomass. It is expected that our model will have broad implications for genetic, evolutionary, biomedical and breeding research.

Original languageEnglish (US)
Pages (from-to)313-324
Number of pages12
JournalJournal of Mathematical Biology
Volume47
Issue number4
DOIs
StatePublished - Oct 1 2003

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Agricultural and Biological Sciences (miscellaneous)
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Exponential mapping of quantitative trait loci governing allometric relationships in organisms'. Together they form a unique fingerprint.

Cite this