QTL mapping under selective genotyping

Abstract

The selective genotyping approach has been known as a cost-saving strategy to reduce genotyping work and can still maintain efficiency in QTL mapping. Statistical QTL mapping methods developed for analyzing the data from selective genotyping can either consider or ignore the ungenotyped individuals in their models for QTL detection. We propose a statistical method based on the normal mixture model for selective genotyping when both genotyped and ungenotyped individuals are considered in the model for QTL analysis. The proposed method is developed on the basis of multiple-QTL model and has a simple estimation procedure similar to that for complete genotyping. As a result, the proposed method has the ability to provide better resolution, analyze epistasis and tackle multiple-QTL problem in QTL mapping under selective genotyping.?