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一种利用侧翼标记在品系杂交中定位数量性状位点的简单回归方法。

A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.

作者信息

Haley C S, Knott S A

机构信息

AFRC Institute of Animal Physiology and Genetics Research, Edinburgh Research Station, Roslin, Midlothian EH25 9PS, Edinburgh, U.K.

出版信息

Heredity (Edinb). 1992 Oct;69(4):315-24. doi: 10.1038/hdy.1992.131.

Abstract

The use of flanking marker methods has proved to be a powerful tool for the mapping of quantitative trait loci (QTL) in the segregating generations derived from crosses between inbred lines. Methods to analyse these data, based on maximum-likelihood, have been developed and provide good estimates of QTL effects in some situations. Maximum-likelihood methods are, however, relatively complex and can be computationally slow. In this paper we develop methods for mapping QTL based on multiple regression which can be applied using any general statistical package. We use the example of mapping in an F(2) population and show that these regression methods produce very similar results to those obtained using maximum likelihood. The relative simplicity of the regression methods means that models with more than a single QTL can be explored and we give examples of two lined loci and of two interacting loci. Other models, for example with more than two QTL, with environmental fixed effects, with between family variance or for threshold traits, could be fitted in a similar way. The ease, speed of application and generality of regression methods for flanking marker analysis, and the good estimates they obtain, suggest that they should provide the method of choice for the analysis of QTL mapping data from inbred line crosses.

摘要

侧翼标记方法已被证明是在近交系杂交产生的分离世代中定位数量性状基因座(QTL)的有力工具。基于最大似然法分析这些数据的方法已经得到发展,并且在某些情况下能很好地估计QTL效应。然而,最大似然法相对复杂,计算速度可能较慢。在本文中,我们开发了基于多元回归的QTL定位方法,这些方法可以使用任何通用统计软件包来应用。我们以F(2)群体中的定位为例,表明这些回归方法产生的结果与使用最大似然法得到的结果非常相似。回归方法相对简单,这意味着可以探索具有多个QTL的模型,我们给出了两个连锁基因座和两个互作基因座的例子。其他模型,例如具有多个以上QTL、具有环境固定效应、具有家系间方差或用于阈性状的模型,也可以以类似方式拟合。侧翼标记分析的回归方法应用简便、速度快且具有通用性,并且能得到良好的估计,这表明它们应该成为分析近交系杂交QTL定位数据的首选方法。

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