Yang Bing, Zhang Man, Shi Yanmei, Zheng Bing-Qi, Shi Chuanping, Lu Daning, Yang Zhi-Zhi, Dong Yi-Ming, Zhu Liwen, Ma Xingyu, Zhang Jingyuan, He Jiehua, Zhang Yin, Hu Kaishun, Lin Haoming, Liao Jian-You, Yin Dong
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yan Jiang West Road, Guangzhou, Guangdong, 510120, China.
HBP Surgery Department, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yan Jiang West Road, Guangzhou, Guangdong, 510120, China.
Nucleic Acids Res. 2025 Jan 6;53(D1):D1120-D1131. doi: 10.1093/nar/gkae777.
Perturb-Seq combines CRISPR (clustered regularly interspaced short palindromic repeats)-based genetic screens with single-cell RNA sequencing readouts for high-content phenotypic screens. Despite the rapid accumulation of Perturb-Seq datasets, there remains a lack of a user-friendly platform for their efficient reuse. Here, we developed PerturbDB (http://research.gzsys.org.cn/perturbdb), a platform to help users unveil gene functions using Perturb-Seq datasets. PerturbDB hosts 66 Perturb-Seq datasets, which encompass 4 518 521 single-cell transcriptomes derived from the knockdown of 10 194 genes across 19 different cell lines. All datasets were uniformly processed using the Mixscape algorithm. Genes were clustered by their perturbed transcriptomic phenotypes derived from Perturb-Seq data, resulting in 421 gene clusters, 157 of which were stable across different cellular contexts. Through integrating chemically perturbed transcriptomes with Perturb-Seq data, we identified 552 potential inhibitors targeting 1409 genes, including an mammalian target of rapamycin (mTOR) signaling inhibitor, retinol, which was experimentally verified. Moreover, we developed a 'Cancer' module to facilitate the understanding of the regulatory role of genes in cancer using Perturb-Seq data. An interactive web interface has also been developed, enabling users to visualize, analyze and download all the comprehensive datasets available in PerturbDB. PerturbDB will greatly drive gene functional studies and enhance our understanding of the regulatory roles of genes in diseases such as cancer.
Perturb-Seq将基于CRISPR（成簇规律间隔短回文重复序列）的基因筛选与用于高内涵表型筛选的单细胞RNA测序读数相结合。尽管Perturb-Seq数据集迅速积累，但仍缺乏一个便于用户高效复用这些数据集的平台。在此，我们开发了PerturbDB（http://research.gzsys.org.cn/perturbdb），这是一个帮助用户利用Perturb-Seq数据集揭示基因功能的平台。PerturbDB包含66个Perturb-Seq数据集，涵盖了来自19种不同细胞系中10194个基因敲低产生的4518521个单细胞转录组。所有数据集均使用Mixscape算法进行统一处理。根据Perturb-Seq数据得出的转录组表型对基因进行聚类，得到421个基因簇，其中157个在不同细胞环境中是稳定的。通过将化学扰动的转录组与Perturb-Seq数据整合，我们鉴定出了552种针对1409个基因的潜在抑制剂，其中包括一种经实验验证的哺乳动物雷帕霉素靶蛋白（mTOR）信号抑制剂视黄醇。此外，我们还开发了一个“癌症”模块，以促进利用Perturb-Seq数据理解基因在癌症中的调控作用。我们还开发了一个交互式网页界面，使用户能够可视化、分析和下载PerturbDB中所有的综合数据集。PerturbDB将极大地推动基因功能研究，并增进我们对基因在癌症等疾病中的调控作用的理解。
