Genetics Research

Research Papers

Mapping interacting QTL for count phenotypes using hierarchical Poisson and binomial models: an application to reproductive traits in mice

JUN LIa1, RICHARD REYNOLDSa1, DANIEL POMPa3, DAVID B. ALLISONa1a2 and NENGJUN YIa1a2 c1

a1 Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL 35294, USA

a2 Clinical Nutrition Research Center, University of Alabama at Birmingham, Birmingham, AL 35294, USA

a3 Departments of Genetics, Nutrition, Cell and Molecular Physiology, University of North Carolina, Chapel Hill, NC 27599, USA

Summary

We proposed hierarchical Poisson and binomial models for mapping multiple interacting quantitative trait loci (QTLs) for count traits in experimental crosses. We applied our methods to two counted reproductive traits, live fetuses (LF) and dead fetuses (DF) at 17 days gestation, in an F2 female mouse population. We treated observed number of corpora lutea (ovulation rate) as the baseline and the total trials in our Poisson and binomial models, respectively. We detected more than 10 QTLs for LF and DF, most having epistatic and pleiotropic effects. The epistatic effects were larger, involved more QTLs, and explained a larger proportion of phenotypic variance than the main effects. Our analyses revealed a complex network of multiple interacting QTLs for the reproductive traits, and increase our understanding of the genetic architecture of reproductive characters. The proposed statistical models and methods provide valuable tools for detecting multiple interacting QTLs for complex count phenotypes.

(Received September 28 2009)

(Revised December 20 2009)

(Online publication March 04 2010)

Correspondence:

c1 Corresponding author: Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. Email: nyi@ms.soph.uab.edu

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