A Simple Regression-Based Method to Map Quantitative Trait Loci Underlying Function-Valued Phenotypes

Genetics. 2014 Aug;197(4):1409-16. doi: 10.1534/genetics.114.166306. Epub 2014 Jun 14.

Abstract

Most statistical methods for quantitative trait loci (QTL) mapping focus on a single phenotype. However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including function-valued phenotypes, such as growth measured over time. While methods exist for QTL mapping with function-valued phenotypes, they are generally computationally intensive and focus on single-QTL models. We propose two simple, fast methods that maintain high power and precision and are amenable to extensions with multiple-QTL models using a penalized likelihood approach. After identifying multiple QTL by these approaches, we can view the function-valued QTL effects to provide a deeper understanding of the underlying processes. Our methods have been implemented as a package for R, funqtl.

Keywords: QTL; function-valued trait; growth curves; model selection.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Arabidopsis / genetics
  • Chromosome Mapping / methods*
  • Computer Simulation
  • Likelihood Functions
  • Models, Genetic
  • Phenotype*
  • Quantitative Trait Loci*
  • Regression Analysis