Omics · study · 2026
Hydrogel Microencapsulation Enables High-Sensitivity Mitochondrial RNA Profiling from Ultra-Low Input Samples
Listed in NCBI GEO
The 13 protein-coding genes encoded by the mitochondrial genome are essential markers for cellular energy metabolism and diverse physiological and pathological processes.
Description
However, conventional RNA-seq methods often suffer from poor sensitivity in detecting mitochondrial transcripts due to their low abundance, vulnerability to degradation, and loss during sample preparation. Here, we present a hydrogel-assisted RNA sequencing strategy that encapsulates individual RNA molecules within semi-permeable core-shell microgels (~80 μm in diameter), enabling ultra-low-input profiling, approximately equivalent to one RNA molecule per each of 1.2 million nanoliter-scale compartments.
This spatial confinement minimizes intermolecular interactions, preserves mitochondrial RNA integrity, and enhances both reverse transcription and Tn5 tagmentation efficiency of mitochondrial RNA molecules. Compared with conventional RNA-seq, our method significantly improves the detection of all 13 protein-coding mitochondrial genes, even with minimal RNA input (~1 ng) and low sequencing depth (~1 million reads). This strategy provides a robust, cost-effective, and scalable approach for accurate and reproducible profiling of mitochondrial transcripts, establishing a powerful tool for investigating mitochondrial function in low-input or precious samples, with broad implications for biomedical research and clinical diagnostics.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE299nnn/GSE299609 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE299609 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1275678 ncbi.nlm.nih.gov/bioproject/PRJNA1275678 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Homo sapiens
- From keywords
- Life Sciences
- Inferred from text
- RNA sequencing 75% · Sequencing 75%
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE299609 | 15 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[modality].local:modality:rna-seq | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:sequencing | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |