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基于双基因座模型生成的家系数据的分离分析结论。

Conclusions of segregation analysis for family data generated under two-locus models.

作者信息

Dizier M H, Bonaïti-Pellié C, Clerget-Darpoux F

机构信息

Unité de Recherche d'Epidémiologie Génétique, INSERM Unité 155, Paris, France.

出版信息

Am J Hum Genet. 1993 Dec;53(6):1338-46.

Abstract

Susceptibility to a disease may involve the interactive effect of two genes. What conclusions will be drawn by segregation analysis in such a case? To answer this question, we considered a set of two-locus models and the corresponding exact distribution for 300 families. We investigated the conclusions and parameter estimations obtained for this sample, by comparing the likelihood expectations of the unified model and of more restricted models. In many cases, segregation analysis leads to the conclusion of a major gene effect, with or without a polygenic component--usually without a polygenic component in multiplicative models (i.e., where two genes have a multiplicative effect) and with such a component in nonmultiplicative models. For all the models considered, existence of a major gene effect is supported by transmission probability tests; there is evidence for transmission and agreement with the hypothesis of Mendelian transmission. Accordingly, there is no means of detecting that the effect of a major gene, with or without a polygenic component, does not correspond to the correct model. In addition, the parameter estimates for the major gene do not correspond to the characteristics of either of the two genes of the true model. This may substantially affect further linkage analysis.

摘要

对某种疾病的易感性可能涉及两个基因的相互作用。在这种情况下,分离分析会得出什么结论呢?为了回答这个问题,我们考虑了一组双基因座模型以及300个家庭的相应精确分布。我们通过比较统一模型和更受限模型的似然期望,研究了从这个样本中得出的结论和参数估计。在许多情况下,分离分析得出存在主基因效应的结论,有或没有多基因成分——在乘法模型中(即两个基因具有乘法效应)通常没有多基因成分,而在非乘法模型中有这样的成分。对于所有考虑的模型,主基因效应的存在都得到了传递概率检验的支持;有证据表明存在传递且与孟德尔传递假说相符。因此,没有办法检测出有或没有多基因成分的主基因效应并不符合正确模型。此外,主基因的参数估计与真实模型的两个基因的特征都不相符。这可能会对进一步的连锁分析产生重大影响。

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