Understanding human disease mutations through the use of interspecific genetic variation
Understanding human disease mutations through the use of interspecific genetic variation
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DOI：
10.1093/hmg/10.21.2319
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发表时间：
2001-10-02
影响因子：
3.5
通讯作者：
Kumar, S
中科院分区：
文献类型：
--
作者：
Miller, MP;Kumar, S
有关疾病患者基因替换突变的数据存在于各种在线资源中。此外，基因组测序项目和个体基因测序工作已导致不同后生动物物种中疾病基因同源物的鉴定。这两类信息的可用性提供了独特的机会，通过对比长期和短期分子进化模式来研究遗传疾病发展中的重要因素。因此，我们对七个疾病基因的与疾病相关的人类遗传变异进行了分析：囊性纤维化跨膜电导调节因子、葡萄糖-6-磷酸脱氢酶、神经细胞粘附分子L1、苯丙氨酸羟化酶、配对框6、X连锁视网膜劈裂基因和TSC2/马铃薯球蛋白。我们的分析表明，从进化的角度来看，疾病突变显示出明确的模式。在后生动物的长期历史中，最保守的氨基酸位置上导致疾病的人类替代突变过多。相比之下，人类多态性置换突变和沉默突变根据基因内氨基酸位点的保守水平随机分布在各个位点上。此外，引起疾病的氨基酸变化通常在物种之间观察不到。使用格兰瑟姆的化学差异矩阵，我们发现在疾病患者中观察到的氨基酸变化比在物种之间和未患病人类中发现的变化要彻底得多。总的来说，我们的结果证明了进化分析对于理解人类疾病突变模式的有用性，并强调了目前从各种模式生物基因组测序项目生成的序列数据的生物医学意义。
Data on replacement mutations in genes of disease patients exist in a variety of online resources. In addition, genome sequencing projects and individual gene sequencing efforts have led to the identification of disease gene homologs in diverse metazoan species. The availability of these two types of information provides unique opportunities to investigate factors that are important in the development of genetically based disease by contrasting long and short-term molecular evolutionary patterns. Therefore, we conducted an analysis of disease-associated human genetic variation for seven disease genes: the cystic fibrosis transmembrane conductance regulator, glucose-6-phosphate dehydrogenase, the neural cell adhesion molecule L1, phenylalanine hydroxylase, paired box 6, the X-linked retinoschisis gene and TSC2/tuberin. Our analyses indicate that disease mutations show definite patterns when examined from an evolutionary perspective. Human replacement mutations resulting in disease are overabundant at amino acid positions most conserved throughout the long-term history of metazoans. In contrast, human polymorphic replacement mutations and silent mutations are randomly distributed across sites with respect to the level of conservation of amino acid sites within genes. Furthermore, disease-causing amino acid changes are of types usually not observed among species. Using Grantham's chemical difference matrix, we find that amino acid changes observed in disease patients are far more radical than the variation found among species and in non-diseased humans. Overall, our results demonstrate the usefulness of evolutionary analyses for understanding patterns of human disease mutations and underscore the biomedical significance of sequence data currently being generated from various model organism genome sequencing projects.