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Scalable single-cell total RNA sequencing unifies coding and non-coding transcriptomics

GSE315939 Homo sapiens Expression profiling by high throughput sequencing 5 samples Submitted 2026/01/12 Platform GPL34281
Summary
Current single-cell RNA atlases largely capture polyadenylated transcripts while missing critical regulatory layers from non-coding RNA. To address this, we developed TotalX - a generalizable framework that adapts Smart-seq total RNA profiling for use in droplet-based platforms, and captures a broad complement of coding and non-coding RNAsusing a unified pipeline. Applying this approach to developing human brain, we generate a dataset mapping diverse RNA biotypes across all neuronal and non-neuronal lineages, revealingbiotype-specific expression programs with cell-type and temporal specificity. Tracking miRNA dynamics in Cajal–Retzius neurons, transient and early-born neurons in the cortex, we show the enrichment and target anti-correlation of MIR137, associated with schizophrenia and intellectual disability, suggesting tight regulatory control. We apply TotalX to human peripheral blood mononuclear cells and identify transcriptional modules combining coding and non-coding RNAs and tRNA dynamics. Additionally, we analyze dengue-infected hepatocytes and capture non-adenylated viral transcripts that distinguish infection states. This expanded coverage helps with understanding cellular identity and gene regulation at atlas scale
Published in
Scalable single-cell total RNA sequencing unifies coding and noncoding transcriptomics
Isakova A, Liu DD, Cvijović I et al. · Nature biotechnology 2026 · PMID 41917462 · doi:10.1038/s41587-026-03068-6
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Direct links to NCBI, no account and no request form: the whole study as GSE315939_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 5 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1399985 and SRA study SRP660685. Searching any of these in the dataset finder brings you back here.

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