A statistical framework for genetic association studies of power curves in bird flight

Min Lin, Wei Zhao, Rongling Wu

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maxium likelihood context, implemented with the EM algorithm for estimating tthe population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameter of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution.

Original languageEnglish (US)
Pages (from-to)164-174
Number of pages11
JournalBiological Procedures Online
Volume8
Issue number1
DOIs
StatePublished - Oct 24 2006

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)

Fingerprint Dive into the research topics of 'A statistical framework for genetic association studies of power curves in bird flight'. Together they form a unique fingerprint.

Cite this