Center for Novel Target and Therapeutic Intervention, Institute of Life Sciences, Chongqing Medical University, Chongqing 400016, China.
Nucleic Acids Res. 2023 Jan 6;51(D1):D1094-D1101. doi: 10.1093/nar/gkac872.
Genetically modified organisms (GMOs) can be generated to model human genetic disease or plant disease resistance, and they have contributed to the exploration and understanding of gene function, physiology, disease onset and drug target discovery. Here, PertOrg (http://www.inbirg.com/pertorg/) was introduced to provide multilevel alterations in GMOs. Raw data of 58 707 transcriptome profiles and associated information, such as phenotypic alterations, were collected and curated from studies involving in vivo genetic perturbation (e.g. knockdown, knockout and overexpression) in eight model organisms, including mouse, rat and zebrafish. The transcriptome profiles from before and after perturbation were organized into 10 116 comparison datasets, including 122 single-cell RNA-seq datasets. The raw data were checked and analysed using widely accepted and standardized pipelines to identify differentially expressed genes (DEGs) in perturbed organisms. As a result, 8 644 148 DEGs were identified and deposited as signatures of gene perturbations. Downstream functional enrichment analysis, cell type analysis and phenotypic alterations were also provided when available. Multiple search methods and analytical tools were created and implemented. Furthermore, case studies were presented to demonstrate how users can utilize the database. PertOrg 1.0 will be a valuable resource aiding in the exploration of gene functions, biological processes and disease models.
转基因生物(GMO)可用于模拟人类遗传疾病或植物抗病性,它们有助于探索和理解基因功能、生理学、疾病发病机制和药物靶点发现。这里介绍了 PertOrg(http://www.inbirg.com/pertorg/),它可以对 GMO 进行多层次的改变。从涉及八种模式生物(包括小鼠、大鼠和斑马鱼)体内遗传扰动(如敲低、敲除和过表达)的研究中收集并整理了 58707 个转录组谱和相关信息(如表型改变)的原始数据。扰动前后的转录组谱被组织成 10116 个比较数据集,包括 122 个单细胞 RNA-seq 数据集。使用广泛接受和标准化的流程检查和分析原始数据,以识别扰动生物体中的差异表达基因(DEGs)。结果鉴定并存储了 8644148 个 DEGs,作为基因扰动的特征。在可用时,还提供了下游功能富集分析、细胞类型分析和表型改变。创建和实施了多种搜索方法和分析工具。此外,还提供了案例研究,以展示用户如何利用该数据库。PertOrg 1.0 将是一个有价值的资源,有助于探索基因功能、生物过程和疾病模型。