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Functional mapping for genetic control of programmed cell death

¹ Department of Statistics, University of Florida, Gainesville, Florida
² Department of Statistics and Probability, Michigan State University, East Lansing, Michigan
³ College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, Zhejiang, China

"Naturally occurring" or "programmed" cell death (PCD) in which the cell uses specialized cellular machinery to kill itself is a ubiquitous phenomenon that occurs early in organ development. Such a cell suicide mechanism that enables metazoans to control cell number and eliminate cells threatening the organism’s survival has been thought to be under genetic control. In this report, we develop a novel statistical model for mapping specific genes or quantitative trait loci (QTL) that are responsible for the PCD process based on polymorphic molecular markers. This model incorporates the biological mechanisms of PCD that undergoes two different developmental stages, exponential growth and polynomial death. We derived a parametric approach to model the exponential growth and a nonparametric approach based on the Legendre function to model the polynomial death. A series of stationary and nonstationary models has been used to approximate the structure of the covariance matrix among cell numbers at a multitude of different times. The statistical behavior of our model is investigated through simulation studies and validated by a real example in rice.

quantitative trait loci; semiparametric model; mean-covariance structure model; EM-Simplex algorithm; order selection

This article has been cited by other articles:

				R. Yang, H. Gao, X. Wang, J. Zhang, Z.-B. Zeng, and R. Wu A Semiparametric Approach for Composite Functional Mapping of Dynamic Quantitative Traits Genetics, November 1, 2007; 177(3): 1859 - 1870. [Abstract] [Full Text] [PDF]