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GoFCards:一个用于人类功能获得性变异的综合数据库和分析平台。

GoFCards: an integrated database and analytic platform for gain of function variants in humans.

作者信息

Zhao Wenjing, Tao Youfu, Xiong Jiayi, Liu Lei, Wang Zhongqing, Shao Chuhan, Shang Ling, Hu Yue, Xu Yishu, Su Yingluo, Yu Jiahui, Feng Tianyi, Xie Junyi, Xu Huijuan, Zhang Zijun, Peng Jiayi, Wu Jianbin, Zhang Yuchang, Zhu Shaobo, Xia Kun, Tang Beisha, Zhao Guihu, Li Jinchen, Li Bin

机构信息

National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital & Center for Medical Genetics, School of Life Sciences, Central South University, No. 87 Xiangya Road, Furong District, Changsha, Hunan 410008, China.

Department of Medical Genetics, NHC Key Laboratory of Healthy Birth and Birth Defect Prevention in Western China, The First People's Hospital of Yunnan Province, No. 157 Jinbi Road, Xishan District, Kunming, Yunnan 650000, China.

出版信息

Nucleic Acids Res. 2025 Jan 6;53(D1):D976-D988. doi: 10.1093/nar/gkae1079.

Abstract

Gain-of-function (GOF) variants, which introduce new or amplify protein functions, are essential for understanding disease mechanisms. Despite advances in genomics and functional research, identifying and analyzing pathogenic GOF variants remains challenging owing to fragmented data and database limitations, underscoring the difficulty in accessing critical genetic information. To address this challenge, we manually reviewed the literature, pinpointing 3089 single-nucleotide variants and 72 insertions and deletions in 579 genes associated with 1299 diseases from 2069 studies, and integrated these with the 3.5 million predicted GOF variants. Our approach is complemented by a proprietary scoring system that prioritizes GOF variants on the basis of the evidence supporting their GOF effects and provides predictive scores for variants that lack existing documentation. We then developed a database named GoFCards for general geneticists and clinicians to easily obtain GOF variants in humans (http://www.genemed.tech/gofcards). This database also contains data from >150 sources and offers comprehensive variant-level and gene-level annotations, with the aim of providing users with convenient access to detailed and relevant genetic information. Furthermore, GoFCards empowers users with limited bioinformatic skills to analyze and annotate genetic data, and prioritize GOF variants. GoFCards offers an efficient platform for interpreting GOF variants and thereby advancing genetic research.

摘要

功能获得性(GOF)变异可引入新的蛋白质功能或增强现有蛋白质功能,对于理解疾病机制至关重要。尽管基因组学和功能研究取得了进展,但由于数据碎片化和数据库的局限性,识别和分析致病性GOF变异仍然具有挑战性,这凸显了获取关键遗传信息的困难。为应对这一挑战,我们人工查阅了文献,从2069项研究中找出了与1299种疾病相关的579个基因中的3089个单核苷酸变异以及72个插入和缺失,并将这些与350万个预测的GOF变异整合在一起。我们的方法辅以一个专有评分系统,该系统根据支持GOF效应的证据对GOF变异进行优先级排序,并为缺乏现有文献记录的变异提供预测分数。然后,我们开发了一个名为GoFCards的数据库,供普通遗传学家和临床医生轻松获取人类中的GOF变异(http://www.genemed.tech/gofcards)。该数据库还包含来自150多个来源的数据,并提供全面的变异水平和基因水平注释,旨在为用户提供方便的途径来获取详细和相关的遗传信息。此外,GoFCards使生物信息学技能有限的用户能够分析和注释遗传数据,并对GOF变异进行优先级排序。GoFCards为解释GOF变异从而推进遗传研究提供了一个高效的平台。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f340/11701611/e157dda90aef/gkae1079figgra1.jpg

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