Transcriptional profiling of mouse projection neurons with VECTORseq
Existing techniques for transcriptional profiling of projection neurons could be applied to only one neuronal population per experiment. To increase throughput, we developed VECTORseq, which repurposes retrogradely infecting viruses to deliver multiplexable RNA barcodes, enabling projection anatomy...
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Veröffentlicht in: | STAR protocols 2022-09, Vol.3 (3), p.101625-101625, Article 101625 |
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Sprache: | eng |
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Zusammenfassung: | Existing techniques for transcriptional profiling of projection neurons could be applied to only one neuronal population per experiment. To increase throughput, we developed VECTORseq, which repurposes retrogradely infecting viruses to deliver multiplexable RNA barcodes, enabling projection anatomy to be read out in single-cell datasets. In this protocol, we describe the delivery of viral barcodes to mouse brain to label different projection neurons. We then detail single-cell or nuclei isolation for sequencing, followed by the analysis of single-cell sequencing data.
For complete details on the use and execution of this protocol, please refer to Cheung et al. (2021).
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•Using VECTORseq for multiplexed transcriptional profiling of projection neurons•Strategies are provided for single-cell and single-nucleus sequencing•Analytical approaches for identifying viral barcodes in sequencing datasets
Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
Existing techniques for transcriptional profiling of projection neurons could be applied to only one neuronal population per experiment. To increase throughput, we developed VECTORseq, which repurposes retrogradely infecting viruses to deliver multiplexable RNA barcodes, enabling projection anatomy to be read out in single-cell datasets. In this protocol, we describe the delivery of viral barcodes to mouse brain to label different projection neurons. We then detail single-cell or nuclei isolation for sequencing, followed by the analysis of single-cell sequencing data. |
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ISSN: | 2666-1667 2666-1667 |
DOI: | 10.1016/j.xpro.2022.101625 |