Evidence map›Paper›PMID 42131894›Full record

ArticleJournal of microscopy2026

RNA-based CLEM (RCLEM) bridging RNA localisation and ultrastructural mapping in 3D.

Daan Verhaege, Lore Van Acker, Camille Wagner, Yentl Van den Berghe, Jérémy Verbeke, Martin Guilliams, Anna Kremer, Lien Van Hoecke, Roosmarijn E Vandenbroucke

Abstract read
In one paragraph

Article in Journal of microscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Daan VerhaegeVIB-UGent Center for Inflammation Research, VIB, Ghent, Belgium.
Lore Van AckerVIB-UGent Center for Inflammation Research, VIB, Ghent, Belgium.
Camille WagnerVIB-UGent Center for Inflammation Research, VIB, Ghent, Belgium.
Yentl Van den BergheVIB-UGent Center for Inflammation Research, VIB, Ghent, Belgium.ORCID 0000-0002-4893-6225
Jérémy VerbekeVIB-UGent Center for Inflammation Research, VIB, Ghent, Belgium.
Martin GuilliamsVIB-UGent Center for Inflammation Research, VIB, Ghent, Belgium.
Anna KremerVIB-UGent Center for Inflammation Research, VIB, Ghent, Belgium.ORCID 0000-0002-4613-1060
Lien Van HoeckeVIB-UGent Center for Inflammation Research, VIB, Ghent, Belgium.
Roosmarijn E VandenbrouckeVIB-UGent Center for Inflammation Research, VIB, Ghent, Belgium.

Funding

Research Foundation-Flanders (FWO) 1123625NResearch Foundation-Flanders (FWO) 1268823NResearch Foundation-Flanders (FWO) 3F017119Research Foundation-Flanders (FWO) 3G055121VIB Techwatch
6 · The paper itself

Abstract

Spatial transcriptomics and in situ hybridisation techniques have become essential for contextualising single-cell RNA sequencing (scRNA-seq) data by mapping cell type- and state-specific mRNA expression within intact tissues. Beyond validating scRNA-seq predictions, these spatial methods provide critical insight into the localisation of specific cell types and their spatial relationships with neighbouring cells. However, current approaches rely on light microscopy (LM), which, despite advances, lacks the resolution needed to resolve detailed cell morphology or subcellular RNA localisation in situ. While correlative imaging methods can enhance spatial context, RNA detection remains limited by the optical constraints of LM. To overcome these challenges, we developed a three-dimensional RNA-based correlated light and electron microscopy (RCLEM) workflow. This method integrates RNA labelling with serial block-face scanning electron microscopy (SBF-SEM), allowing high-resolution 3D visualisation of RNA molecules within their ultrastructural environment. We optimised the RNA labelling protocol for thick, whole-mount tissues by fine-tuning detergent conditions to preserve ultrastructure while maintaining probe accessibility. This RCLEM approach offers several advantages over protein-based correlative methods, including robust detection with nucleotide probes and independence from antibody optimisation or fixation-sensitive epitopes. Applied to choroid plexus (ChP) and liver tissue, this workflow enabled precise 3D correlation between mRNA expression and EM features, supporting detailed morphological characterisation of rare scRNA-seq-defined cell subtypes. This protocol is broadly applicable to other complex tissues and provides a powerful platform for integrative, high-resolution spatial transcriptomic analyses that bridge gene expression with ultrastructure. LAY DESCRIPTION: To overcome the resolution limits of current spatial transcriptomics, we developed a 3D RNA-based correlated light and electron microscopy (RCLEM) workflow. By integrating RNA labelling with scanning electron microscopy, this method enables high-resolution 3D visualisation of mRNA within its ultrastructural environment in thick tissues. Validated in choroid plexus and liver, our antibody-independent RCLEM approach provides a broadly applicable platform bridging gene expression and precise cellular morphology for advanced spatial analyses.

Indexed as

Imaging, Three-DimensionalMicroscopy, Electron, ScanningRNAAnimalsLiverMiceRNA, MessengerSingle-Cell AnalysisSingle-Cell Gene Expression AnalysisSpatial TranscriptomicsRNARNA, MessengerCLEM workflowhigh‐resolution confocal imagingRCLEMSBF‐SEM

Identifiers

PMID42131894
PMCPMC13280170

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.