CBGDA: a manually curated resource for gene–disease associations based on genome-wide CRISPR

Author:

Du Qingsong1ORCID,Zhang Zhiyu1,Yang Wanyi1,Zhou Xunyu1,Zhou Nan2ORCID,Wu Chuanfang1,Bao Jinku1

Affiliation:

1. Key Laboratory of the State Ministry of Education for Bio-Resources and Ecologic Environment, College of Life Sciences, Sichuan University , 29 Wangjiang Rd, Chengdu 610064, China

2. Research Center, The Affiliated Brain Hospital, Guangzhou Medical University , 36 Mingxin Rd, Guangzhou 510000, China

Abstract

Abstract The field of understanding the association between genes and diseases is rapidly expanding, making it challenging for researchers to keep up with the influx of new publications and genetic datasets. Fortunately, there are now several regularly updated databases available that focus on cataloging gene–disease relationships. The development of the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 system has revolutionized the field of gene editing, providing a highly efficient, accurate, and reliable method for exploring gene–disease associations. However, currently, there is no resource specifically dedicated to collecting and integrating the latest experimentally supported gene–disease association data derived from genome-wide CRISPR screening. To address this gap, we have developed the CRISPR-Based Gene–Disease Associations (CBGDA) database, which includes over 200 manually curated gene–disease association data derived from genome-wide CRISPR screening studies. Through CBGDA, users can explore gene–disease association data derived from genome-wide CRISPR screening, gaining insights into the expression patterns of genes in different diseases, associated chemical data, and variant information. This provides a novel perspective on understanding the associations between genes and diseases. What is more, CBGDA integrates data from several other databases and resources, enhancing its comprehensiveness and utility. In summary, CBGDA offers a fresh perspective and comprehensive insights into the research on gene–disease associations. It fills the gap by providing a dedicated resource for accessing up-to-date, experimentally supported gene–disease association data derived from genome-wide CRISPR screening. Database URL: http://cbgda.zhounan.org/main

Funder

National Nature Science Foundation of China

Publisher

Oxford University Press (OUP)

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