Schork N J, Thiel B, St Jean P
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio 44109, USA.
J Exp Zool. 1998;282(1-2):133-49.
Although all meiotic (or linkage) mapping strategies ultimately rely on Mendel's laws, the precise manner in which these laws are exploited in relevant statistical models determines the utility of each strategy for different traits and diseases. In this paper we review the motivation and principles behind each of the three most often used statistical strategies for mapping loci that influence complex, multifactorial traits and diseases (such as diabetes and hypertension), namely: pedigree-based parametric linkage, relative pair allele sharing analysis, and association or linkage disequilibrium analysis. It is our hope to show how Mendel's laws are exploited in each through use of two basic concepts: the short-term evolution of chromosomes, and kinship. Problems inherent in each strategy are described. We then consider how extensions, modifications, or novel derivatives of these three strategies might be fashioned that make better use of the concepts of kinship and short-term chromosome evolution. Two strategies receive emphasis: a haplotype sharing method, which considers the kinship of groups of individuals, and extended variance component models, which make use of genotype information in novel ways.
尽管所有减数分裂（或连锁）定位策略最终都依赖于孟德尔定律，但在相关统计模型中运用这些定律的精确方式决定了每种策略对不同性状和疾病的效用。在本文中，我们回顾了用于定位影响复杂多因素性状和疾病（如糖尿病和高血压）的基因座的三种最常用统计策略背后的动机和原理，即：基于家系的参数连锁分析、相对对等位基因共享分析以及关联或连锁不平衡分析。我们希望通过使用两个基本概念——染色体的短期进化和亲缘关系，展示孟德尔定律在每种策略中是如何运用的。描述了每种策略所固有的问题。然后，我们考虑如何构建这三种策略的扩展、修改或新的衍生方法，以便更好地利用亲缘关系和染色体短期进化的概念。重点介绍了两种策略：一种是考虑个体组亲缘关系的单倍型共享方法，另一种是采用新颖方式利用基因型信息的扩展方差成分模型。
