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

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NIAID Data Ecosystem2026-05-10 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP660685
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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 Overall design: HEK293T cells and DENV2 infected Huh7 cells were processed using TotalX method. We also compared TotalX implementations without as well as with two rounds of DASH in miRNA(+) configurations on HEK293T cells
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2026-01-12
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