Lei Xiang, Yumei Wang, Wei Shao, Qingzhou Li, Xiankuo Yu, Mingming Wei, Yu Gui, Shengrong Li, Pan Qin, Chao Hu, Guochen Zhang, Xianwen Zhang, Jiawen Wang, Yingying Li, Jun An, Yan Luo, Yile Liao, Jinghong Deng, Xinran Tai, Richard Y. Xu, Lijun Huang, Dale Guo, Guanbin Zhang, Zhi Xie, Yun Deng, Junquan Xu, Dong Wang
{"title":"93,644次扰动中化学诱导基因表达的高通量分析。","authors":"Lei Xiang, Yumei Wang, Wei Shao, Qingzhou Li, Xiankuo Yu, Mingming Wei, Yu Gui, Shengrong Li, Pan Qin, Chao Hu, Guochen Zhang, Xianwen Zhang, Jiawen Wang, Yingying Li, Jun An, Yan Luo, Yile Liao, Jinghong Deng, Xinran Tai, Richard Y. Xu, Lijun Huang, Dale Guo, Guanbin Zhang, Zhi Xie, Yun Deng, Junquan Xu, Dong Wang","doi":"10.1038/s41592-025-02781-5","DOIUrl":null,"url":null,"abstract":"In this Resource, we present an extensive dataset of chemical-induced gene signatures (CIGS), encompassing expression patterns of 3,407 genes regulating key biological processes in 2 human cell lines exposed to 13,221 compounds across 93,664 perturbations. This dataset encompasses 319,045,108 gene expression events, generated through 2 high-throughput technologies: the previously documented high-throughput sequencing-based high-throughput screening (HTS2) and the newly developed highly multiplexed and parallel sequencing (HiMAP-seq). Our results show that HiMAP-seq is comparable to RNA sequencing, but can profile the expression of thousands of genes across thousands of samples in one single test by utilizing a pooled-sample strategy. We further illustrate CIGS’s utility in elucidating the mechanism of action of unannotated small molecules, like ligustroflavone and 2,4-dihydroxybenzaldehyde, and to identify perturbation-induced cell states, such as those resistant to ferroptosis. The full dataset is publicly accessible at https://cigs.iomicscloud.com/ . CIGS is a high-resolution dataset comprising chemical perturbation-induced 319,045,108 gene expression events.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"22 9","pages":"1954-1963"},"PeriodicalIF":32.1000,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High-throughput profiling of chemical-induced gene expression across 93,644 perturbations\",\"authors\":\"Lei Xiang, Yumei Wang, Wei Shao, Qingzhou Li, Xiankuo Yu, Mingming Wei, Yu Gui, Shengrong Li, Pan Qin, Chao Hu, Guochen Zhang, Xianwen Zhang, Jiawen Wang, Yingying Li, Jun An, Yan Luo, Yile Liao, Jinghong Deng, Xinran Tai, Richard Y. Xu, Lijun Huang, Dale Guo, Guanbin Zhang, Zhi Xie, Yun Deng, Junquan Xu, Dong Wang\",\"doi\":\"10.1038/s41592-025-02781-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this Resource, we present an extensive dataset of chemical-induced gene signatures (CIGS), encompassing expression patterns of 3,407 genes regulating key biological processes in 2 human cell lines exposed to 13,221 compounds across 93,664 perturbations. This dataset encompasses 319,045,108 gene expression events, generated through 2 high-throughput technologies: the previously documented high-throughput sequencing-based high-throughput screening (HTS2) and the newly developed highly multiplexed and parallel sequencing (HiMAP-seq). Our results show that HiMAP-seq is comparable to RNA sequencing, but can profile the expression of thousands of genes across thousands of samples in one single test by utilizing a pooled-sample strategy. We further illustrate CIGS’s utility in elucidating the mechanism of action of unannotated small molecules, like ligustroflavone and 2,4-dihydroxybenzaldehyde, and to identify perturbation-induced cell states, such as those resistant to ferroptosis. The full dataset is publicly accessible at https://cigs.iomicscloud.com/ . CIGS is a high-resolution dataset comprising chemical perturbation-induced 319,045,108 gene expression events.\",\"PeriodicalId\":18981,\"journal\":{\"name\":\"Nature Methods\",\"volume\":\"22 9\",\"pages\":\"1954-1963\"},\"PeriodicalIF\":32.1000,\"publicationDate\":\"2025-08-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Methods\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.nature.com/articles/s41592-025-02781-5\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Methods","FirstCategoryId":"99","ListUrlMain":"https://www.nature.com/articles/s41592-025-02781-5","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
High-throughput profiling of chemical-induced gene expression across 93,644 perturbations
In this Resource, we present an extensive dataset of chemical-induced gene signatures (CIGS), encompassing expression patterns of 3,407 genes regulating key biological processes in 2 human cell lines exposed to 13,221 compounds across 93,664 perturbations. This dataset encompasses 319,045,108 gene expression events, generated through 2 high-throughput technologies: the previously documented high-throughput sequencing-based high-throughput screening (HTS2) and the newly developed highly multiplexed and parallel sequencing (HiMAP-seq). Our results show that HiMAP-seq is comparable to RNA sequencing, but can profile the expression of thousands of genes across thousands of samples in one single test by utilizing a pooled-sample strategy. We further illustrate CIGS’s utility in elucidating the mechanism of action of unannotated small molecules, like ligustroflavone and 2,4-dihydroxybenzaldehyde, and to identify perturbation-induced cell states, such as those resistant to ferroptosis. The full dataset is publicly accessible at https://cigs.iomicscloud.com/ . CIGS is a high-resolution dataset comprising chemical perturbation-induced 319,045,108 gene expression events.
期刊介绍:
Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.