應用分數檢定統計量於選擇性基因型試驗之數量性狀基因座定位研究

Abstract

生物上許多重要的經濟、生理、或與生化有關的性狀均為數量性狀。這些控制數量性狀的基因稱為數量性狀基因座 (Quantitative trait loci)，其定位與研究一直是作物和動物在遺傳育種上的重要課題。利用分子遺傳標誌資料，數量性狀基因座定位 (QTL mapping)方法可幫助我們了解QTL在染色體上的位置及其作用大小。選擇性基因型鑑定 (Selective genotyping)是一種只針對樣本族群之外表型極大與極小的部分個體進行基因型鑑定的方法，它除了降低遺傳鑑定的成本外，一般認為也可以增進定位數量性狀基因座的效率。本篇文章中，利用 Lee et al. (2013) 針對選擇性基因型鑑定所提出的兩種模式 (事後檢定模式與目前所行的模式)，分別推導其分數檢定統計量(score test statistics)作為另一種定位QTL的統計量，並研究其在選擇性基因型鑑定方法下的顯著性門檻值。結果發現，在單一QTL存在的假設情況下，兩種分數檢定統計量表現的一樣好。未來研究中，我們期待將單一QTL假設推廣至多個QTL存在的情況，進行選擇性基因型鑑定之數量性狀基因座定位研究。

The detection of quantitative trait loci (QTL) that govern many biologically and economically important traits is an important task in plant and animal breeding. Using genetic marker data, QTL mapping technique has been known to be an efficient tool to detect QTL location and estimate the QTL effect. In QTL mapping, selective genotyping, which genotypes only the individuals from high and low phenotypic values, is one of the most common strategies that can reduce the cost of marker genotyping and at the same time increase efficiency in QTL detection. In this thesis, with the posterior model of selective genotyping proposed by Lee et al. (2013), we derived score test statistic for the model and applied it to QTL detection. Moreover, we compare this score test statistics with that of the currently used model, and the threshold values of the score test statistics under selective genotyping are also investigated. As the result, we found out that the two score test statistics for the posterior model and currently used model perform equally well under single-QTL model. In the future, we intend to extend the single-QTL posterior model to multiple-QTL model for QTL detection under selective genotyping.