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Originally published as Genetics Published Articles Ahead of Print on October 18, 2007.

Genetics, Vol. 177, 1859-1870, November 2007, Copyright © 2007
doi:10.1534/genetics.107.077321

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A Semiparametric Approach for Composite Functional Mapping of Dynamic Quantitative Traits

Runqing Yang*, Huijiang Gao{dagger}, Xin Wang*, Ji Zhang*, Zhao-Bang Zeng{ddagger} and Rongling Wu§,1

* School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai 200240, People's Republic of China, {dagger} College of Animal Science and Technology, Northeast Agriculture University, Harbin 150030, People's Republic of China, {ddagger} Bioinformatics Research Center, Departments of Statistics and Genetics, North Carolina State University, Raleigh, North Carolina 27695 and § Department of Statistics, University of Florida, Gainesville, Florida 32611

1 Corresponding author: Department of Statistics, University of Florida, Gainesville, FL 32611.
E-mail: rwu{at}stat.ufl.edu

Functional mapping has emerged as a powerful tool for mapping quantitative trait loci (QTL) that control developmental patterns of complex dynamic traits. Original functional mapping has been constructed within the context of simple interval mapping, without consideration of separate multiple linked QTL for a dynamic trait. In this article, we present a statistical framework for mapping QTL that affect dynamic traits by capitalizing on the strengths of functional mapping and composite interval mapping. Within this so-called composite functional-mapping framework, functional mapping models the time-dependent genetic effects of a QTL tested within a marker interval using a biologically meaningful parametric function, whereas composite interval mapping models the time-dependent genetic effects of the markers outside the test interval to control the genome background using a flexible nonparametric approach based on Legendre polynomials. Such a semiparametric framework was formulated by a maximum-likelihood model and implemented with the EM algorithm, allowing for the estimation and the test of the mathematical parameters that define the QTL effects and the regression coefficients of the Legendre polynomials that describe the marker effects. Simulation studies were performed to investigate the statistical behavior of composite functional mapping and compare its advantage in separating multiple linked QTL as compared to functional mapping. We used the new mapping approach to analyze a genetic mapping example in rice, leading to the identification of multiple QTL, some of which are linked on the same chromosome, that control the developmental trajectory of leaf age.






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Copyright © 2007 by the Genetics Society of America.