Vieland V J, Mérette C, Goodman D, Rouillard E
Department of Preventive Medicine and Environmental Health, University of Iowa College of Medicine, Iowa City 52242-1008, USA.
Genet Epidemiol. 1995;12(6):819-24. doi: 10.1002/gepi.1370120648.
We took as our working hypothesis the premise that there could be a single locus of major effect underlying a subset of cases in the simulated Problem 2 data set, and took as our primary goal the task of mapping that locus. Treating the disease as dichotomous and using discriminant function analysis, we were able to separate affected individuals into two disease categories: Disease Type I (DT-I) cases, whose disease was by hypothesis caused by the major locus; and Disease Type II (DT-II) cases, whose disease was by hypothesis produced by other causes. Segregation analysis showed evidence of simple recessive inheritance among the DT-I individuals. Linkage analysis under the best-fitting recessive model gave clear evidence of linkage to D1G2. In the generating model, this marker is linked to a major gene for disease with recombination fraction theta = 0, and the mode of inheritance at that locus is recessive (when the trait is considered as a dichotomy). We conclude that when the true model is complex, focussing on subtypes of disease that show evidence of simple Mendelian inheritance may be a useful first step in determining the underlying model and mapping major genes.
在模拟的问题2数据集中,可能存在一个对部分病例起主要作用的单一基因座,并将定位该基因座作为主要目标。将疾病视为二分变量并使用判别函数分析,我们能够将受影响个体分为两种疾病类别:疾病I型(DT-I)病例,根据假设其疾病由主要基因座引起;以及疾病II型(DT-II)病例,根据假设其疾病由其他原因导致。分离分析显示DT-I个体中存在简单隐性遗传的证据。在最佳拟合隐性模型下的连锁分析给出了与D1G2连锁的明确证据。在生成模型中,该标记与疾病的一个主要基因相连,重组率θ = 0,并且该基因座的遗传模式为隐性(当性状被视为二分变量时)。我们得出结论,当真实模型复杂时,关注显示简单孟德尔遗传证据的疾病亚型可能是确定潜在模型和定位主要基因的有用的第一步。