Jishu Xu, Michaela Hörner, Elena Buena Atienza, Kalaivani Manibarathi, Maike Nagel, Stefan Hauser, Jakob Admard, Nicolas Casadei, Stephan Ossowski, Rebecca Schuele
{"title":"长读rna测序揭示了人源性皮质神经元的转录特异性调控。","authors":"Jishu Xu, Michaela Hörner, Elena Buena Atienza, Kalaivani Manibarathi, Maike Nagel, Stefan Hauser, Jakob Admard, Nicolas Casadei, Stephan Ossowski, Rebecca Schuele","doi":"10.1098/rsob.250200","DOIUrl":null,"url":null,"abstract":"<p><p>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 <i>APP</i>, <i>KIF2A</i> and <i>BSCL2</i>, 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.</p>","PeriodicalId":19629,"journal":{"name":"Open Biology","volume":"15 7","pages":"250200"},"PeriodicalIF":3.6000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12308531/pdf/","citationCount":"0","resultStr":"{\"title\":\"Long-read RNA-sequencing reveals transcript-specific regulation in human-derived cortical neurons.\",\"authors\":\"Jishu Xu, Michaela Hörner, Elena Buena Atienza, Kalaivani Manibarathi, Maike Nagel, Stefan Hauser, Jakob Admard, Nicolas Casadei, Stephan Ossowski, Rebecca Schuele\",\"doi\":\"10.1098/rsob.250200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 <i>APP</i>, <i>KIF2A</i> and <i>BSCL2</i>, 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.</p>\",\"PeriodicalId\":19629,\"journal\":{\"name\":\"Open Biology\",\"volume\":\"15 7\",\"pages\":\"250200\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12308531/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Open Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1098/rsob.250200\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/30 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1098/rsob.250200","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/30 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Long-read RNA-sequencing reveals transcript-specific regulation in human-derived cortical neurons.
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 APP, KIF2A and BSCL2, 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.
期刊介绍:
Open Biology is an online journal that welcomes original, high impact research in cell and developmental biology, molecular and structural biology, biochemistry, neuroscience, immunology, microbiology and genetics.