Begum Tina, Ghosh Tapash Chandra
Bioinformatics Centre, Bose Institute, Kolkata, West Bengal, India.
Bioinformatics Centre, Bose Institute, Kolkata, West Bengal, India
Genome Biol Evol. 2014 Oct 5;6(10):2741-53. doi: 10.1093/gbe/evu220.
To date, numerous studies have been attempted to determine the extent of variation in evolutionary rates between human disease and nondisease (ND) genes. In our present study, we have considered human autosomal monogenic (Mendelian) disease genes, which were classified into two groups according to the number of phenotypic defects, that is, specific disease (SPD) gene (one gene: one defect) and shared disease (SHD) gene (one gene: multiple defects). Here, we have compared the evolutionary rates of these two groups of genes, that is, SPD genes and SHD genes with respect to ND genes. We observed that the average evolutionary rates are slow in SHD group, intermediate in SPD group, and fast in ND group. Group-to-group evolutionary rate differences remain statistically significant regardless of their gene expression levels and number of defects. We demonstrated that disease genes are under strong selective constraint if they emerge through edgetic perturbation or drug-induced perturbation of the interactome network, show tissue-restricted expression, and are involved in transmembrane transport. Among all the factors, our regression analyses interestingly suggest the independent effects of 1) drug-induced perturbation and 2) the interaction term of expression breadth and transmembrane transport on protein evolutionary rates. We reasoned that the drug-induced network disruption is a combination of several edgetic perturbations and, thus, has more severe effect on gene phenotypes.
迄今为止,已有众多研究试图确定人类疾病基因与非疾病(ND)基因之间进化速率的差异程度。在我们目前的研究中,我们考虑了人类常染色体单基因(孟德尔)疾病基因,这些基因根据表型缺陷的数量分为两组,即特定疾病(SPD)基因(一个基因:一种缺陷)和共享疾病(SHD)基因(一个基因:多种缺陷)。在这里,我们比较了这两组基因,即SPD基因和SHD基因相对于ND基因的进化速率。我们观察到,SHD组的平均进化速率较慢,SPD组的居中,而ND组的较快。无论基因表达水平和缺陷数量如何,组间进化速率差异在统计学上仍然显著。我们证明,如果疾病基因通过相互作用组网络的边缘扰动或药物诱导的扰动出现,表现出组织限制性表达,并参与跨膜运输,那么它们就会受到强烈的选择约束。在所有因素中,我们的回归分析有趣地表明了1)药物诱导的扰动和2)表达广度与跨膜运输的相互作用项对蛋白质进化速率的独立影响。我们推断,药物诱导的网络破坏是几种边缘扰动的组合,因此对基因表型有更严重的影响。