High-throughput profiling of chemical-induced gene expression across 93,644 perturbations
- Nat Methods. 2025 Aug 18. doi: 10.1038/s41592-025-02781-5.
- 1. School of Basic Medical Sciences, State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
- 2. Iomics Biosciences Inc., Beijing, China.
- 3. Chinese Institutes for Medical Research, Beijing, China.
- 4. School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
- 5. Department of Biology, University of California, San Diego, La Jolla, CA, USA.
- 6. School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
- 7. State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China.
- 8. School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China. [email protected].
- 9. Yibin Vocational College of Medicine and Health, Yibin, China. [email protected].
- 10. Iomics Biosciences Inc., Beijing, China. [email protected].
- 11. School of Basic Medical Sciences, State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, China. [email protected].
- # Contributed equally.
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/ .
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