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基因中致病突变的分析

Analyses of Disease Causing Mutations in Gene.

作者信息

Jafar Hussain Hafiz Muhammad, Khan Ranjha, Li Chunyi, Aftab Ayesha, Muneer Iqra, Wahab Fazal, Wu Limin, Jiang Xiaohua, Xu Peng

机构信息

The First Affiliated Hospital of USTC, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, China.

Shenyang Dongfang Jinghua Hospital, Shenyang, Liaoning, China.

出版信息

Ann Clin Lab Sci. 2019 Nov;49(6):710-721.

Abstract

The (secreted LY6/urokinase type plasminogen activator receptor related protein-1) belongs to the gene family of urokinase, a type of plasminogen activator receptor (uPAR). Mutations in the have been reported to cause serious genetic problems of skin, Mal De Meleda, and malignancies. With the advancement of computational tools, it became possible to predict the potential impact of gene variants on the structure and function of protein. Therefore, in present study, we aimed to perform analyses of the disease causing mutations using online tools. In-total, 21 variants occurring in coding and non-coding regions of were found from public databases. In curated data, we have found 57.14% (12/21) missense, 23.81% (5/21) splice site, 9.52% (2/21) nonsense, 4.76% (1/21) deletion, and 4.76% (1/21) frameshift mutations. Moreover, heterogeneity in genotypes and phenotypes, along with 7 hotspot points in has been noted. analyses of the subjected variants have depicted a range of pathogenicity by combinatorial predictions of different tools from being lowly to highly pathogenic. Thus, the present study paves a platform to link computational analyses of mutations for important regulatory genes that can be undertaken for their phenotypes and their correlation with the disease status in case control studies.

摘要

分泌型LY6/尿激酶型纤溶酶原激活物受体相关蛋白-1(secreted LY6/urokinase type plasminogen activator receptor related protein-1)属于尿激酶基因家族,尿激酶是纤溶酶原激活物受体(uPAR)的一种。据报道,该基因的突变会导致严重的皮肤遗传问题、梅勒达病(Mal De Meleda)和恶性肿瘤。随着计算工具的发展,预测基因变异对蛋白质结构和功能的潜在影响成为可能。因此,在本研究中,我们旨在使用在线工具对导致疾病的该基因突变进行分析。总共从公共数据库中发现了21个发生在该基因编码区和非编码区的变异。在整理的数据中,我们发现错义突变占57.14%(12/21)、剪接位点突变占23.81%(5/21)、无义突变占9.52%(2/21)、缺失突变占4.76%(1/21)、移码突变占4.76%(1/21)。此外,还注意到该基因在基因型和表型上的异质性以及7个热点区域。对这些变异的分析通过不同工具的组合预测描绘了一系列从低致病性到高致病性的致病性情况。因此,本研究为连接重要调控基因突变的计算分析搭建了一个平台,在病例对照研究中可以针对这些突变的表型及其与疾病状态的相关性进行研究。

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