Xu Jishu, Hörner Michaela, Atienza Elena Buena, Manibarathi Kalaivani, Nagel Maike, Hauser Stefan, Admard Jakob, Casadei Nicolas, Ossowski Stephan, Schuele Rebecca
Centre for Neurology and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, Germany.
Open Biol. 2025 Jul;15(7):250200. doi: 10.1098/rsob.250200. Epub 2025 Jul 30.
Long-read RNA sequencing has transformed transcriptome analysis by enabling comprehensive mapping of full-length transcripts, providing an unprecedented resolution of transcript diversity, alternative splicing and transcript-specific regulation. In this study, we employed nanopore long-read RNA sequencing to profile the transcriptomes of three cell types commonly used to model brain disorders, human fibroblasts, induced pluripotent stem cells and stem cell-derived cortical neurons, identifying extensive transcript diversity with 15 072 transcripts in stem cell-derived cortical neurons, 13 048 in fibroblasts and 12 759 in induced pluripotent stem cells. Our analyses uncovered 35 519 differential transcript expression events and 5135 differential transcript usage events, underscoring the complexity of transcriptomic regulation across these cell types. Importantly, by integrating differential transcript expression and usage analyses, we gained deeper insights into transcript dynamics that are not captured by gene-level expression analysis alone. Differential transcript usage analysis highlighted transcript-specific changes in disease-relevant genes such as , and , associated with Alzheimer's disease, neuronal migration disorders and degenerative axonopathies, respectively. This added resolution emphasizes the significance of transcript-level variations that often remain hidden in traditional differential gene expression analyses. Overall, our work provides a framework for understanding transcript diversity in both pluripotent and specialized cell types, which can be used to investigate transcriptomic changes in disease states in future work. Additionally, this study underscores the utility of differential transcript usage analysis in advancing our understanding of neurodevelopmental and neurodegenerative diseases, paving the way for identifying transcript-specific therapeutic targets.
长读长RNA测序通过实现全长转录本的全面映射，为转录组分析带来了变革，提供了前所未有的转录本多样性、可变剪接和转录本特异性调控分辨率。在本研究中，我们采用纳米孔长读长RNA测序对三种常用于模拟脑部疾病的细胞类型（人类成纤维细胞、诱导多能干细胞和干细胞衍生的皮质神经元）的转录组进行分析，在干细胞衍生的皮质神经元中鉴定出15072个转录本、在成纤维细胞中鉴定出13048个转录本、在诱导多能干细胞中鉴定出12759个转录本，发现了广泛的转录本多样性。我们的分析揭示了35519个差异转录本表达事件和5135个差异转录本使用事件，突显了这些细胞类型间转录组调控的复杂性。重要的是，通过整合差异转录本表达和使用分析，我们对转录本动态有了更深入的了解，而这是仅通过基因水平表达分析无法获得的。差异转录本使用分析突出了与疾病相关基因（如分别与阿尔茨海默病、神经元迁移障碍和退行性轴索病相关的 、 和 ）中的转录本特异性变化。这种额外的分辨率强调了转录本水平变异的重要性，这些变异在传统的差异基因表达分析中常常被隐藏。总体而言，我们的工作为理解多能和特化细胞类型中的转录本多样性提供了一个框架，可用于在未来的研究中调查疾病状态下的转录组变化。此外，本研究强调了差异转录本使用分析在推进我们对神经发育和神经退行性疾病理解方面的效用，为识别转录本特异性治疗靶点铺平了道路。
