Abstract
AbstractStatic gene expression programs have been extensively characterized in stem cells and mature human cells. However, the dynamics of RNA isoform changes upon cell-state-transitions during cell differentiation, the determinants and functional consequences have largely remained unclear. Here, we established an improved model for human neurogenesis in vitro that is amenable for systems-wide analyses of gene expression. Our multi-omics analysis reveals that the pronounced alterations in cell morphology correlate strongly with widespread changes in RNA isoform expression. Our approach identifies thousands of new RNA isoforms that are expressed at distinct differentiation stages. RNA isoforms mainly arise from exon skipping and the alternative usage of transcription start and polyadenylation sites during human neurogenesis. The transcript isoform changes can remodel the identity and functions of protein isoforms. Finally, our study identifies a set of RNA binding proteins as a potential determinant of differentiation stage-specific global isoform changes. This work supports the view of regulated isoform changes that underlie state-transitions during neurogenesis.
Funder
Max Planck Society
Studienstiftung des Deutschen Volkes
Federation of European Biochemical Societies
Volkswagen Foundation
Deutsche Forschungsgemeinschaft
Fulbright Program
Publisher
Springer Science and Business Media LLC
Reference127 articles.
1. Abcam Neural Markers Guide. https://docs.abcam.com/pdf/neuroscience/neural-markers-guide-web.pdf [DATASET]
2. Abascal F, Acosta R, Addleman NJ, Adrian J, Afzal V, Ai R, Aken B, Akiyama JA, Jammal OA, Amrhein H et al (2020) Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 583:699–710
3. Abugessaisa I, Noguchi S, Hasegawa A, Kondo A, Kawaji H, Carninci P, Kasukawa T (2019) refTSS: a reference data set for human and mouse transcription start sites. J Mol Biol 431:2407–2422. [DATASET]
4. Afgan, Nekrutenko E, Grüning BA A, Blankenberg D, Goecks J, Schatz MC, Ostrovsky AE, Mahmoud A, Lonie AJ, Syme A et al (2022) The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update. Nucleic Acids Res 50:gkac247
5. Anders S, Reyes A, Huber W (2012) Detecting differential usage of exons from RNA-seq data. Genome Res 22:2008–2017