Academic Journal
Massively Parallel Profiling of Single-Cell RNA Dynamics Using Well-TEMP-seq.
| Τίτλος: | Massively Parallel Profiling of Single-Cell RNA Dynamics Using Well-TEMP-seq. |
|---|---|
| Συγγραφείς: | Wang D; MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Fujian Key Laboratory of Chemical Biology, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China.; These authors contributed equally to this work., Lv Q; School of Life Sciences, Xiamen University, Xiamen, China.; These authors contributed equally to this work., Lin S; MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Fujian Key Laboratory of Chemical Biology, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China. |
| Πηγή: | Current protocols [Curr Protoc] 2026 Sep; Vol. 6 (9), pp. e70458. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: John Wiley & Sons Country of Publication: United States NLM ID: 101773894 Publication Model: Print Cited Medium: Internet ISSN: 2691-1299 (Electronic) Linking ISSN: 26911299 NLM ISO Abbreviation: Curr Protoc Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Hoboken, NJ : John Wiley & Sons, [2021]- |
| Ιατρικοί όροι (MeSH): | Single-Cell Analysis*/methods , Sequence Analysis, RNA*/methods , RNA*/genetics , High-Throughput Nucleotide Sequencing*/methods , Gene Expression Profiling*/methods, Single-Cell Gene Expression Analysis ; Animals ; Humans |
| Περίληψη: | Single-cell RNA sequencing (scRNA-seq) reveals the transcriptional heterogeneity of cells, revolutionizing our understanding of cellular processes. However, the static snapshots obtained from scRNA-seq fail to reveal the time-resolved dynamics of transcription, which impedes critical insights into various biological processes, such as cellular differentiation, embryonic development, disease progression, and responses to external stimuli. Here, we describe Well-TEMP-seq, a protocol for massively parallel profiling of the temporal dynamics of single-cell gene expression. Well-TEMP-seq combines metabolic RNA labeling with a microwell-based scRNA-seq method, Well-paired-seq, to distinguish newly transcribed RNAs marked by T-to-C substitutions from pre-existing RNAs in each of thousands of single cells. Well-TEMP-seq is high-throughput, cost-effective, accurate, and provides a low cell loss rate and high single cell/bead pairing efficiency. More importantly, Well-TEMP-seq can be easily set up in other labs, and the loading of cells and beads can be easily accomplished by an optical microscope and a pipette. We believe that Well-TEMP-seq will be widely adopted and help researchers perform transformative research to unveil the dynamics of single-cell gene expression in diverse biological processes. © 2026 Wiley Periodicals LLC. Basic Protocol 1: Well-paired-seq chip fabrication Basic Protocol 2: Well-TEMP-seq sample processing Basic Protocol 3: Bioinformatics analysis. (© 2026 Wiley Periodicals LLC.) |
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| Grant Information: | 2025J09060 Natural Science Foundation of Fujian Province of China |
| Contributed Indexing: | Keywords: 4‐thiouridine; gene expression dynamics; metabolic RNA labeling; microwell; single‐cell RNA sequencing |
| Substance Nomenclature: | 63231-63-0 (RNA) |
| Entry Date(s): | Date Created: 20260831 Date Completed: 20260831 Latest Revision: 20260902 |
| Update Code: | 20260902 |
| PubMed Central ID: | PMC13528962 |
| DOI: | 10.1002/cpz1.70458 |
| PMID: | 42671929 |
| Βάση Δεδομένων: | MEDLINE |
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