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Two-trait-locus linkage analysis: a powerful strategy for mapping complex genetic traits.

机译:两性基因座连锁分析:一种用于绘制复杂遗传性状的有力策略。

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摘要

Recent advances in molecular biology have provided geneticists with ever-increasing numbers of highly polymorphic genetic markers that have made possible linkage mapping of loci responsible for many human diseases. However, nearly all diseases mapped to date follow clear Mendelian, single-locus segregation patterns. In contrast, many common familial diseases such as diabetes, psoriasis, several forms of cancer, and schizophrenia are familial and appear to have a genetic component but do not exhibit simple Mendelian transmission. More complex models are required to explain the genetics of these important diseases. In this paper, we explore two-trait-locus, two-marker-locus linkage analysis in which two trait loci are mapped simultaneously to separate genetic markers. We compare the utility of this approach to standard one-trait-locus, one-marker-locus linkage analysis with and without allowance for heterogeneity. We also compare the utility of the two-trait-locus, two-marker-locus analysis to two-trait-locus, one-marker-locus linkage analysis. For common diseases, pedigrees are often bilineal, with disease genes entering via two or more unrelated pedigree members. Since such pedigrees often are avoided in linkage studies, we also investigate the relative information content of unilineal and bilineal pedigrees. For the dominant-or-recessive and threshold models that we consider, we find that two-trait-locus, two-marker-locus linkage analysis can provide substantially more linkage information, as measured by expected maximum lod score, than standard one-trait-locus, one-marker-locus methods, even allowing for heterogeneity, while, for a dominant-or-dominant generating model, one-locus models that allow for heterogeneity extract essentially as much information as the two-trait-locus methods. For these three models, we also find that bilineal pedigrees provide sufficient linkage information to warrant their inclusion in such studies. We also discuss strategies for assessing the significance of the two linkages assumed in two-trait-locus, two-marker-locus models.
机译:分子生物学的最新进展为遗传学家提供了越来越多的高度多态性遗传标记,这使得负责许多人类疾病的基因座的连锁作图成为可能。但是,迄今为止,几乎所有疾病都遵循明确的孟德尔式单基因座隔离模式。相反,许多常见的家族性疾病,例如糖尿病,牛皮癣,多种形式的癌症和精神分裂症,都是家族性的,似乎具有遗传成分,但不表现出简单的孟德尔传播。需要更复杂的模型来解释这些重要疾病的遗传学。在本文中,我们探索了两个性状基因座,两个标记物基因座连锁分析,其中两个性状基因座同时定位到单独的遗传标记上。我们将这种方法的效用与标准的单性状基因座,单标记物基因座连锁分析(有无异质性)进行了比较。我们还比较了两性状,两标记位点分析与两性状,一标记位点连锁分析的效用。对于常见疾病,家谱通常是双线性的,疾病基因通过两个或多个不相关的家谱成员进入。由于在联系研究中通常避免使用这种谱系,因此我们还研究了单谱系和双谱系的相对信息内容。对于我们考虑的显性或隐性和阈值模型,我们发现与预期的最大lod得分相比,两性状位点,两标记性位点连锁分析可以提供比标准单性状更多的连锁信息。 -场所,单标记场所方法,甚至允许异质性,而对于显性或显性生成模型,允许异质性的一场所模型提取的信息基本上与两性状-场所方法相同。对于这三个模型,我们还发现,双系谱系提供了足够的关联信息,以确保将其纳入此类研究。我们还讨论了评估两个性状基因座,两个标记基因座模型中假设的两个关联的重要性的策略。

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