Omics · study · 2026
Integrated single-nucleus RNA-seq dataset of mouse brain from a multi-factorial benchmarking study
Listed in NCBI GEO
Single-nucleus RNA sequencing (snRNA-seq) is pivotal for dissecting cellular heterogeneity in the brain, yet the individual and interactive effects of technical variables on cell composition and gene expression remain poorly quantified.
Description
Here we present the first multi-factorial benchmarking study of snRNA-seq technical confounders in the adult mouse brain, by performing a systematic evaluation of tissue harvest methods (post-mortem vs. in vivo) and nuclear fixation (methanol-fixed vs. fresh), using the identical sequencing platforms (SeekOne Digital Droplet).
We find that standard post-mortem harvest induces a rapid, selective loss of metabolically active glutamatergic neuron subpopulations, which obscures transcripts related to advanced cognitive functions while preserving overall cellular proportions. While methanol fixation minimally alters cell-type composition, it introduces cell-type-specific gene expression shifts that preferentially stabilize structural and core functional transcripts.
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We validated these technical artifacts to provide a systematic map of confounders, identifying glutamatergic neurons as uniquely vulnerable to workflow-induced bias. Our study offers a robust experimental and analytical framework to separate technical noise from true biological signal. These findings establish that precise reporting and control of workflow variables are prerequisites for building reproducible, integrative brain cell atlases and ensuring accurate biological discovery in single-cell transcriptomics.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE327nnn/GSE327236 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE327236 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA1450007 ncbi.nlm.nih.gov/bioproject/PRJNA1450007 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Mus musculus
- From keywords
- Life Sciences
- Inferred from text
- RNA sequencing 75% · Sequencing 75% · Single-cell RNA sequencing 65%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE327236 | 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[modality].local:modality:single-cell-rna-seq | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[organism].NCBITaxon:10090 | 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 |