An optimal parametric proportional hazards model for mapping heading time loci in rice

Usually, statistical methods for mapping quantitative trait loci (QTL) require that the phenotypes follow the normal distribution and therefore may not be appropriate to analyze survival traits of skewed distribution. As a result, parametric and semi-parametric models in survival analysis are incorporated into the framework of the interval mapping for survival trait loci. Through formulating the effects of the QTL genotype on the survival time with a Cox proportional hazards model, we construct a general parametric model for mapping survival trait loci, in which baseline hazard function is selectable for goodness of fit to the effects of QTL genotype on survival curve. Bayesian information criterion is used to choose the optimal baseline hazard function with maximum likelihood and parsimonious parameters. Heading time, defined by days from sowing to heading is a typical survival trait. In this study, we apply the mapping method to locate QTL for heading time in rice and conclude that among the six commonly used survival distributions, Gamma distribution is the optimal baseline hazard function and by which, four QTLs are identified.