GoFCards: an integrated database and analytic platform for gain of function variants in humans
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.
Authors
- Wenjing Zhao (ORCID: https://orcid.org/0000-0002-8374-1087)
- Zhongqing Wang (ORCID: https://orcid.org/0000-0002-5330-7538)
- Yuhang Su (ORCID: https://orcid.org/0000-0002-7990-1332)
- Lei Liu (ORCID: https://orcid.org/0000-0002-5095-7244)
- Zijun Zhang (ORCID: https://orcid.org/0000-0002-4292-4709)
- Junyi Xie (ORCID: https://orcid.org/0000-0003-2474-9262)
- Kun Xia (ORCID: https://orcid.org/0000-0001-8090-6002)
- Jinchen Li (ORCID: https://orcid.org/0009-0002-3893-8128)
- Ling Shang (ORCID: https://orcid.org/0000-0003-2072-6848)
- Jiayi Xiong
- Yongsheng Tao (ORCID: https://orcid.org/0000-0001-5840-2254)
- Beisha Tang (ORCID: https://orcid.org/0000-0003-2120-1576)
- Bin Li (ORCID: https://orcid.org/0000-0002-8442-0154)
- Yi Zhang (ORCID: https://orcid.org/0000-0003-2729-5374)
- XU Hui-juan
- Guihu Zhao (ORCID: https://orcid.org/0000-0003-4033-1843)
- Yue Hu (ORCID: https://orcid.org/0000-0002-9240-6483)
- Jiahui Yu
- Yishu Xu (ORCID: https://orcid.org/0009-0002-6633-5711)
- Tao Feng (ORCID: https://orcid.org/0000-0002-4238-4589)
- Jianbin Wu (ORCID: https://orcid.org/0000-0003-3063-0743)
- Jiayi Peng
- Chuhan Shao (ORCID: https://orcid.org/0000-0003-3489-3815)
- Shaobo Zhu
Institutions
- Kunming University of Science and Technology (CN)
- Central South University (CN)
- First People's Hospital of Yunnan Province (CN)
- National Clinical Research (US)
- First Affiliated Hospital of University of South China (CN)
- Xiangya Hospital Central South University (CN)
- Laboratoire de Génétique Médicale (FR)
- University of South China (CN)
Publication Details
- Journal
- Nucleic Acids Research
- Published
- 2024-11-23
- DOI
- https://doi.org/10.1093/nar/gkae1079
- Citations
- 5
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 2.75
Funders
- National Natural Science Foundation of China
- Central South University
- Natural Science Foundation of Hunan Province
- National Key Research and Development Program of China