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

IF 16.6 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Nucleic Acids Research Pub Date : 2025-01-06 DOI:10.1093/nar/gkae1079
Wenjing Zhao, Youfu Tao, Jiayi Xiong, Lei Liu, Zhongqing Wang, Chuhan Shao, Ling Shang, Yue Hu, Yishu Xu, Yingluo Su, Jiahui Yu, Tianyi Feng, Junyi Xie, Huijuan Xu, Zijun Zhang, Jiayi Peng, Jianbin Wu, Yuchang Zhang, Shaobo Zhu, Kun Xia, Beisha Tang, Guihu Zhao, Jinchen Li, Bin Li
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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.

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GoFCards:人类功能增益变异综合数据库和分析平台。
功能增益(GOF)变异引入了新的蛋白质功能或扩大了蛋白质功能,对于了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,但由于数据零散和数据库的局限性,识别和分析致病性 GOF 变体仍具有挑战性,这凸显了获取关键遗传信息的难度。为了应对这一挑战,我们对文献进行了人工审查,从 2069 项研究中精确定位了与 1299 种疾病相关的 579 个基因中的 3089 个单核苷酸变异和 72 个插入和缺失,并将这些变异与 350 万个预测的 GOF 变异进行了整合。我们的方法得到了一个专有评分系统的补充,该系统根据支持 GOF 变异效应的证据对 GOF 变异进行优先排序,并为缺乏现有文献的变异提供预测评分。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,并提供全面的变体级和基因级注释,目的是让用户方便地获取详细的相关遗传信息。此外,GoFCards 使生物信息技能有限的用户也能分析和注释基因数据,并对 GOF 变异进行优先排序。GoFCards 为解释 GOF 变异提供了一个高效的平台,从而推动了基因研究的发展。
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来源期刊
Nucleic Acids Research
Nucleic Acids Research 生物-生化与分子生物学
CiteScore
27.10
自引率
4.70%
发文量
1057
审稿时长
2 months
期刊介绍: Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.
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