Fine-Scale Mapping Of QTL Using Pedigree Transmission Disequilibrium Test

Threshold traits and quantitative traits are important in livestock production, and mapping the quantitative trait loci (QTL) to increase the breeding efficiency is a long term object for geneticists and breeders. The great development in genomics makes it possible to unveil the genetic basis of threshold and quantitative traits at molecular level. Although linkage analysis has been proved a successful method for QTL mapping in farm animals, it usually maps QTL on a region of 10-20cM. This resolution is too poor to be used to identify QTL. Therefore, exploring new approach on QTL fine mapping is important and a precondition for QTL positional cloning.TDT (transmission disequilibrium test) has received great attention recently in human genetics due to its simplicity and powerfulness. But TDT only deals with data from independent nuclear families and information will be lost for extended pedigree which incorporates information not only from parents and siblings but also from other relatives. Meanwhile, it is difficult to apply TDT in farm animals. In this study, pedigree transmission disequilibrium test (PTDT) is proposed for QTL mapping of threshold traits, at the same time, quantitative traits can be transformed into threshold traits using three transforming methods and analyzed by PTDT. Therefore, PTDT can be an unified framework for QTL fine mapping.The power and type I error of PTDT under different QTL effect level (10%, 30%, 50%) and prevalence level of status 1 animals (0.1, 0.2, 0.4) are investigated by Monte Carlo simulation. It is shown that PTDT is a robust and valid approach for mapping QTL of threshold traits. Moreover, PTDT is powerful for marker with multiple alleles and multiple tightly linked markers, too.From the results of simulation on quantitative traits, following conclusions can be derived. (1) As PTDT does in threshold traits, PTDT is valid not only for different QTL effect level, but also for maker with multiple alleles and multiple tightly linked markers. (2) Under an appropriate selection ratio s (in this study, s is 0.2, 0.4, 0.6, 0.8, respectively), the power of PTDT can be improved and the genotying individuals can be decreased using selective genotyping design. However, the power of PTDT is related with population size and population structure, an appropriate selection ratio can be defined by simulation based on the existing data. (3) Among the three transforming methods, mixed-family selection is the best, full-sib selection has same power to mixed-family selection in many parameter combinations, and Estimated Breeding Value (EBV) selection is inferior to them.It is also shown that the power of PTDT can be improved through increasing the number of extended pedigree and offspring per dam. Compared with increasing the number of extended pedigree, increasing the number of offspring per dam is more effective.