Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose–response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment.

毒理学基因组学测量分子特征，如转录本、蛋白质、代谢物和表观基因组修饰，以了解和预测环境和药物暴露的毒理学影响。由于基因表达谱的创新可以提供大规模的机制和定量信息，转录组学已成为当代毒理学研究中不可或缺的工具。这些数据可用于通过使用转录组生物标志物、网络推理分析、模式匹配方法和人工智能来预测毒理学危害。此外，即使在无法预测特定危害的情况下，高通量剂量反应模型等新兴方法也可以利用毒理学数据来保护人类健康。最后，单细胞转录组学和多组学提供了对毒理学机制的详细见解。在这里，我们回顾了毒物基因组学诞生以来在将转录组学应用于毒理学测试方面取得的进展，并重点介绍了正在改变风险评估的进展。