scBiopsy-seq: a platform for temporal single-cell RNA-seq analysis

preprint OA: closed
📄 Open PDF Full text JSON View at publisher
Full text 1,576 characters · extracted from oa-doi-fallback · click to expand
Abstract The development of temporal single-cell RNA-seq (scRNA-seq) assay enabled us to systemically investigate the effects of various types of perturbations in a time course with single-cell resolution. However, the existing temporal scRNA-seq technologies have certain limitations in reliability, detection efficacy and detection diversity. In the current study, we develop scBiopsy-seq assay, which combines a synergistic electroosmosis-electrophoresis extraction method for efficient RNA extraction and digital microfluidics with contamination-isolated hydrophobic interface for high-performance sample processing. scBiopsy-seq extracts the cytoplasm at well-controlled volume to detect >10K genes per extraction with 90% successful rate. Functional enrichment analysis revealed that the genes robustly detected by scBiopsy-seq were associated to diverse biological processes, demonstrating its superb diversity of detection. scBiopsy-seq can perform the sequential extraction of the cytoplasm from the same cell multiple times, which allows us to associate the cell phenotypic responses with its transcriptional dynamics. We employed scBiopsy-seq to analyze the temporal response to a BRD4 degrader induced transcriptional suppression, which identified the key roles of fatty acid beta oxidation in this biological process. scBiopsy-seq with similar data quality as scRNA-seq will dramatically expand the application of temporal scRNA-seq towards a broader spectrum of cell biology research. Competing Interest Statement The authors have declared no competing interest.

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00