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Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models

Pokhilko, Alexandra, Handel, Adam, Curion, Fabiola, Volpato, Viola, Whiteley, Emma, Bostrand, Sunniva, Newey, Sarah, Akerman, Colin, Webber, Caleb ORCID:, Clark, Michael, Bowden, Rory and Cader, M. Zameel 2022. Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models. Genome Research 31 , pp. 1069-1081. 10.1101/gr.273961.120

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Single-cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but it is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ∼1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell type identification, developmental trajectories, and gene regulatory networks. This allowed us to resolve differences among neuronal populations, which were generated in two different laboratories using the same differentiation protocol. ScCapture-seq improved TF-gene regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to improve scRNA-seq resolution.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Advanced Research Computing @ Cardiff (ARCCA)
MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Additional Information: This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at
Publisher: Cold Spring Harbor Laboratory Press
ISSN: 1088-9051
Date of First Compliant Deposit: 14 April 2021
Date of Acceptance: 23 March 2021
Last Modified: 19 Jul 2024 15:27

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