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Combined single-cell profiling of expression and DNA methylation reveals splicing regulation and heterogeneity

  • Background: Alternative splicing is a key mechanism in eukaryotic cells to increase the effective number of functionally distinct gene products. Using bulk RNA sequencing, splicing variation has been studied both across human tissues and in genetically diverse individuals. This has identified disease-relevant splicing events, as well as associations between splicing and genomic variations, including sequence composition and conservation. However, variability in splicing between single cells from the same tissue and its determinants remain poorly understood. Results: We applied parallel DNA methylation and transcriptome sequencing to differentiating human induced pluripotent stem cells to characterize splicing variation (exon skipping) and its determinants. Our results shows that splicing rates in single cells can be accurately predicted based on sequence composition and other genomic features. We also identified a moderate but significant contribution from DNA methylation to splicing variation across cells. By combining sequence information and DNA methylation, we derived an accurate model (AUC=0.85) for predicting different splicing modes of individual cassette exons. These explain conventional inclusion and exclusion patterns, but also more subtle modes of cell-to-cell variation in splicing. Finally, we identified and characterized associations between DNA methylation and splicing changes during cell differentiation. Conclusions: Our study yields new insights into alternative splicing at the single-cell level and reveals a previously underappreciated component of DNA methylation variation on splicing.

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Metadaten
Author:Stephanie M. LinkerORCiDGND, Lara UrbanORCiD, Stephen ClarkORCiD, Mariya ChhatriwalaORCiD, Shradha Amatya, Davis J. McCarthyORCiD, Ingo EbersbergerORCiDGND, Ludovic VallierORCiD, Wolf ReikORCiD, Oliver StegleORCiDGND, Marc Jan BonderORCiD
URN:urn:nbn:de:hebis:30:3-858507
URL:https://www.biorxiv.org/content/10.1101/328138v1
DOI:https://doi.org/10.1101/328138
Parent Title (English):bioRxiv
Publisher:bioRxiv
Document Type:Preprint
Language:English
Date of Publication (online):2018/05/22
Date of first Publication:2018/05/22
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2024/07/16
Issue:32813 Version 1
Edition:Version 1
Page Number:28
Institutes:Biowissenschaften / Biowissenschaften
Angeschlossene und kooperierende Institutionen / Senckenbergische Naturforschende Gesellschaft
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International