ArticleNucleic acids research2026
sc-rDSeq: a robust and cost-effective full-length total RNA sequencing method for single cells reveals multilayered heterogeneity in drug-resistant lung cancer cells.
Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- sc-rDSeq: Droplet-based single-cell full-length total RNA-seq method.Biology methods & protocols · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
sc-rDSeq is a scalable, full-length total RNA droplet-based technology that captures both polyadenylated and nonpolyadenylated RNAs, including histone RNAs, small and long non-coding RNAs, and enhancer RNAs. It achieves a 10-fold increase in UMIs per cell compared to conventional scRNAseq like 10× Chromium and inDrops, while remaining simple and cost-efficient. Applied to lung cancer cells, sc-rDSeq uncovered hidden heterogeneity, divergent signaling pathways, and non-polyA RNA variations undetectable by 3' end-based methods. Following EGFR inhibitor treatment, cell cycle arrest was detected through non-polyA histone messenger RNA expression, revealing seven distinct subpopulations of cells with upregulation of different persister-related programs, like migration, sterol synthesis and matrix formation. Additionally, by leveraging single-cell expression variability and pseudo-bulk analyses, sc-rDSeq unveiled alternative splicing events and single nucleotide variations that distinguished the drug resistant subsets. sc-rDSeq therefore opens the way for in-depth personalized medicine applications through massive-scale and multifaceted analysis of different RNA species, splicing events, and sequence variations.
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Registered trials
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