Preliminary Construction In Theoretical Framework Of QTL Mapping For Dynamic Trait

Dynamic trait are those phenotypic value changes with time and other quantifiable factors such as age, parities, physical status, performace level and eviornments etc.. In estimation of breeding value for the dynamic trait, the process with dynamic changes was described by a Legendre polynomial on time (test day) of certain order. On this opinion, the effect of dynamic trait loci could also be explained by inserting a legendre polynomial in each genetic factors, and so the mathematic model for mapping dynamic trait loci was constructed.The objective of this study is to propose a general theoretical framework for embedding a dynamic process in the statistical analysis of QTL mapping for dynamic trait. A maximum likelihood based method, implemented with EM algorithm, was induced to estimate QTL location and effects on dynamic process. The newly approach was demonstrated by Monte Carlo simulation and the effect of population size and test day density on detect power for the QTL with different heritbility and the factor combination in simulation study was designed by orthogonal table. It showed that the individual number and test-day density with almost same effect on QTL analysis and detection, and showed complementation with each other in same sample size. It would need less individual and test-day records with higher heritability in the detection for dynamic trait loci. But the power of detection would be sufficient with individuals above 300 and test-day density over 5% even if in lower heritability.That the detection power of regression analysis in different situation, i.e., individual number, test-day density and heritability, under equal residual variance was also studied and compared with maximum likelihood method. It showed similar detection ability as maximum likelihood method in each combination even regression analysis tended to be lower accuracy and lower precision on estimate of residual variance compared with maximum likelihood. And regression analysis performed significant advantage in computation process and computationspeed.Compared with previous separate analysis and multiple trait mapping, it considered the underlying law in changes of dynamic trait by incorporating a function about the changes of gene effect with dynamic process to QTL mapping model. And because of the reduction of parameter estimated, the detection would be more power and more precision. Especially it can be insured that with same geometric shape in both hand of the mapping or the equivalence infitted parameters by using Legendre polynomial to describe the effect of QTL on the processABSTRACTof dynamic trait.In view of the economical importance of dynamic traits and its extensive existence in features, the study for QTL mapping of these trait would be important in theoretical and practical for revealing its genetic law and increasing its improvement efficiency.