000280257 001__ 280257
000280257 005__ 20250831001836.0
000280257 0247_ $$2doi$$a10.1098/rsob.250200
000280257 0247_ $$2pmid$$apmid:40735840
000280257 0247_ $$2pmc$$apmc:PMC12308531
000280257 0247_ $$2altmetric$$aaltmetric:180390225
000280257 037__ $$aDZNE-2025-00935
000280257 041__ $$aEnglish
000280257 082__ $$a570
000280257 1001_ $$0P:(DE-2719)9002275$$aXu, Jishu$$b0
000280257 245__ $$aLong-read RNA-sequencing reveals transcript-specific regulation in human-derived cortical neurons.
000280257 260__ $$aLondon$$bRoyal Society Publishing$$c2025
000280257 3367_ $$2DRIVER$$aarticle
000280257 3367_ $$2DataCite$$aOutput Types/Journal article
000280257 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1754894993_31917
000280257 3367_ $$2BibTeX$$aARTICLE
000280257 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000280257 3367_ $$00$$2EndNote$$aJournal Article
000280257 520__ $$aLong-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.
000280257 536__ $$0G:(DE-HGF)POF4-352$$a352 - Disease Mechanisms (POF4-352)$$cPOF4-352$$fPOF IV$$x0
000280257 588__ $$aDataset connected to CrossRef, PubMed, , Journals: pub.dzne.de
000280257 650_7 $$2Other$$aalternative splicing
000280257 650_7 $$2Other$$ahuman-derived cortical neurons
000280257 650_7 $$2Other$$ainduced pluripotent stem cells
000280257 650_7 $$2Other$$along-read RNA-sequencing
000280257 650_7 $$2Other$$atranscript usage
000280257 650_7 $$2Other$$atranscriptomics
000280257 650_2 $$2MeSH$$aHumans
000280257 650_2 $$2MeSH$$aNeurons: metabolism
000280257 650_2 $$2MeSH$$aNeurons: cytology
000280257 650_2 $$2MeSH$$aSequence Analysis, RNA: methods
000280257 650_2 $$2MeSH$$aTranscriptome
000280257 650_2 $$2MeSH$$aInduced Pluripotent Stem Cells: metabolism
000280257 650_2 $$2MeSH$$aInduced Pluripotent Stem Cells: cytology
000280257 650_2 $$2MeSH$$aGene Expression Profiling: methods
000280257 650_2 $$2MeSH$$aGene Expression Regulation
000280257 650_2 $$2MeSH$$aFibroblasts: metabolism
000280257 650_2 $$2MeSH$$aFibroblasts: cytology
000280257 650_2 $$2MeSH$$aCerebral Cortex: cytology
000280257 650_2 $$2MeSH$$aCerebral Cortex: metabolism
000280257 650_2 $$2MeSH$$aAlternative Splicing
000280257 7001_ $$00000-0001-5485-4990$$aHörner, Michaela$$b1
000280257 7001_ $$aAtienza, Elena Buena$$b2
000280257 7001_ $$0P:(DE-2719)9002385$$aManibarathi, Kalaivani$$b3
000280257 7001_ $$0P:(DE-2719)2812101$$aNagel, Maike$$b4
000280257 7001_ $$0P:(DE-2719)2810998$$aHauser, Stefan$$b5$$udzne
000280257 7001_ $$aAdmard, Jakob$$b6
000280257 7001_ $$aCasadei, Nicolas$$b7
000280257 7001_ $$aOssowski, Stephan$$b8
000280257 7001_ $$0P:(DE-2719)2812018$$aSchuele, Rebecca$$b9
000280257 773__ $$0PERI:(DE-600)2630944-0$$a10.1098/rsob.250200$$gVol. 15, no. 7, p. 250200$$n7$$p250200$$tOpen biology$$v15$$x2046-2441$$y2025
000280257 8564_ $$uhttps://pub.dzne.de/record/280257/files/DZNE-2025-00935.pdf$$yOpenAccess
000280257 8564_ $$uhttps://pub.dzne.de/record/280257/files/DZNE-2025-00935%20SUP.docx
000280257 8564_ $$uhttps://pub.dzne.de/record/280257/files/DZNE-2025-00935.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000280257 909CO $$ooai:pub.dzne.de:280257$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000280257 9101_ $$0I:(DE-588)1065079516$$6P:(DE-2719)9002385$$aDeutsches Zentrum für Neurodegenerative Erkrankungen$$b3$$kDZNE
000280257 9101_ $$0I:(DE-588)1065079516$$6P:(DE-2719)2812101$$aDeutsches Zentrum für Neurodegenerative Erkrankungen$$b4$$kDZNE
000280257 9101_ $$0I:(DE-588)1065079516$$6P:(DE-2719)2810998$$aDeutsches Zentrum für Neurodegenerative Erkrankungen$$b5$$kDZNE
000280257 9101_ $$0I:(DE-HGF)0$$6P:(DE-2719)2812018$$aExternal Institute$$b9$$kExtern
000280257 9131_ $$0G:(DE-HGF)POF4-352$$1G:(DE-HGF)POF4-350$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lNeurodegenerative Diseases$$vDisease Mechanisms$$x0
000280257 9141_ $$y2025
000280257 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-30
000280257 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-30
000280257 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2024-12-30
000280257 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2024-12-30
000280257 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000280257 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bOPEN BIOL : 2022$$d2024-12-30
000280257 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2021-03-15T10:46:58Z
000280257 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2021-03-15T10:46:58Z
000280257 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-30
000280257 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2024-12-30
000280257 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-30
000280257 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000280257 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Anonymous peer review$$d2021-03-15T10:46:58Z
000280257 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2024-12-30
000280257 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bOPEN BIOL : 2022$$d2024-12-30
000280257 915__ $$0StatID:(DE-HGF)0430$$2StatID$$aNational-Konsortium$$d2024-12-30$$wger
000280257 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-30
000280257 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-30
000280257 9201_ $$0I:(DE-2719)1210016$$kAG Hauser$$lAdvanced cellular models of neurodegeneration$$x0
000280257 980__ $$ajournal
000280257 980__ $$aVDB
000280257 980__ $$aUNRESTRICTED
000280257 980__ $$aI:(DE-2719)1210016
000280257 9801_ $$aFullTexts