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Updated: Apr 4, 2026

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Identification of Circular RNAs using RNA Sequencing
Published on: November 14, 2019
12.9K
Tabula Sapiens reveals the non-coding RNA landscape across 22 human organs and tissues
Jaeyoon Lee1, Madhav Mantri1, Kavita Murthy1
1Department of Bioengineering, Stanford University; Stanford, CA 94305, USA.
Biorxiv : the Preprint Server for Biology
|April 3, 2026
Summary
This study maps the non-coding transcriptome across 22 human organs, revealing cell type-specific expression and subcellular localization of non-coding RNAs. These findings highlight their crucial roles in cellular processes.
Area of Science:
- Genomics
- Molecular Biology
- Cell Biology
Background:
- Non-coding RNAs (ncRNAs) are crucial for cellular processes, but their expression is underexplored in single-cell studies.
- Current single-cell transcriptomics often targets polyadenylated RNA, overlooking non-coding and non-polyadenylated transcripts.
Purpose of the Study:
- To comprehensively profile the non-coding transcriptome across diverse human tissues at single-cell resolution.
- To investigate cell type specificity, subcellular localization, and dynamic expression patterns of ncRNAs.
Main Methods:
- Single-cell and single-nucleus total RNA sequencing of 22 human organs and tissues.
- Simultaneous profiling of polyadenylated and non-polyadenylated RNA transcripts.
- Comparative analysis of protein-coding and non-coding gene expression patterns.
Main Results:
- A higher proportion of non-coding genes exhibit cell type-specific expression compared to protein-coding genes.
- Identified cell type-dependent nuclear and cytoplasmic enrichment of specific non-coding RNAs.
- Revealed cell type-specific tRNA repertoires and dynamic ncRNA expression during the cell cycle and senescence.
Conclusions:
- This study provides a valuable resource for exploring the non-coding RNA landscape in human cells and tissues.
- The findings underscore the significant and diverse roles of ncRNAs in cellular function and regulation.
- The data enables joint analysis of coding and non-coding transcriptomes at single-cell and subcellular levels.
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