RoCK and ROI: single-cell transcriptomics with multiplexed enrichment of selected transcripts and region-specific sequencing

Single-cell profiling technologies allow exploring molecular mechanisms that drive development, health, and disease. However, current methods still fall short of profiling single cell transcriptomes comprehensively, with one major challenge being high non-detection rates of specific transcripts and transcript regions. Such information is often crucial to understanding the biology of cells. Here, we introduce RoCK and ROI (Robust Capture of Key transcripts and Regions Of Interest), a scRNA-seq workflow encompassing two techniques. RoCKseq uses targeted capture to enrich for key transcripts, thereby supporting the detection and identification of cell types and complex phenotypes in scRNA-seq experiments. ROIseq directs a subset of reads to a specific region of interest via selective priming. Importantly, RoCK and ROI enables retrieval of specific sequence information without compromising overall single cell transcriptome information. We validate RoCK and ROI across diverse biological systems highlighting the versatility and showing the power of the method to retrieve critical transcriptomic features.

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Publication Details

Journal
Nature Communications
Published
2025-12-10
DOI
https://doi.org/10.1038/s41467-025-66248-z
Citations
2
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
1.61
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RoCK and ROI: single-cell transcriptomics with multiplexed enrichment of selected transcripts and region-specific sequencing

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Nature Communications
Single-cell and spatial transcriptomics
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RoCK and ROI: single-cell transcriptomics with multiplexed enrichment of selected transcripts and region-specific sequencing

Konrad Basler, Izaskun Mallona, Michael David Brügger, Erich Brunner, Mark D. Robinson, Claudia Dorothea Baldus, Lorenz Bastian, Tomáš Valenta, Quentin Szabo, Malwine Barz, Andreas E. Moor, Kristina Handler, Hassan Fazilaty, Fiona Kerlin, Giulia Moro, Robert P. Zinzen, Joël Maillard
article en
2 citations

Abstract

Single-cell profiling technologies allow exploring molecular mechanisms that drive development, health, and disease. However, current methods still fall short of profiling single cell transcriptomes comprehensively, with one major challenge being high non-detection rates of specific transcripts and transcript regions. Such information is often crucial to understanding the biology of cells. Here, we introduce RoCK and ROI (Robust Capture of Key transcripts and Regions Of Interest), a scRNA-seq workflow encompassing two techniques. RoCKseq uses targeted capture to enrich for key transcripts, thereby supporting the detection and identification of cell types and complex phenotypes in scRNA-seq experiments. ROIseq directs a subset of reads to a specific region of interest via selective priming. Importantly, RoCK and ROI enables retrieval of specific sequence information without compromising overall single cell transcriptome information. We validate RoCK and ROI across diverse biological systems highlighting the versatility and showing the power of the method to retrieve critical transcriptomic features.

Nature CommunicationsVol. 16(1)
SIB Swiss Institute of Bioinformatics (CH), University of Zurich (CH), Max Delbrück Center (DE), ETH Zurich (CH), University Hospital Schleswig-Holstein (DE), Life Science Zurich (CH), Czech Academy of Sciences, Institute of Molecular Genetics (CZ), Clinical Research Center Kiel (DE), Freie Universität Berlin (DE), University of Lübeck (DE)
Openalex Percentile: Top 14%
Single-cell and spatial transcriptomics
1.61
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