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A cost-effective and flexible workflow for high-resolution spatial transcriptomics in fixed tissue

GSE292893 Homo sapiens (human) Spatial transcriptomics 52 samples Submitted 2025/05/26 Platform GPL24676Platform GPL24247
At a glance

Spatial transcriptomics · human · 52 samples

What it is
Spatial transcriptomicsGene activity measured with its position in a tissue section.
Organism
Homo sapiens (human)
Samples
52 samples: 17 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
High-resolution spatial transcriptomics in fixed tissue using a cost-effective PCL-seq workflowGenome research · 2025
Summary (written by the submitters)
The spatial heterogeneity of gene expression has driven the development of diverse spatial transcriptomics technologies. Here, we introduce photocleavage and ligation sequencing (PCL-seq), a spatial indexing method based on a light-controlled DNA labeling strategy applied to tissue sections. PCL-seq employs photocleavable oligonucleotides and sequence adapters to construct transcriptional profiles of specific regions of interest (ROIs), designated via microscopically controlled photo-illumination.
Read the full summary ↓
In frozen mouse embryos, PCL-seq generates spatially aligned gene expression matrices and achieves high-quality data outputs, detecting approximately 170,000 unique molecular identifiers (UMIs) and 8,600 genes (irradiation diameter=100 µm). Moreover, PCL-seq is compatible with formalin-fixed and paraffin-embedded (FFPE) tissues, successfully identifying thousands of differentially enriched transcripts in the digits and vertebrae of FFPE mouse embryo sections. Additionally, PCL-seq achieves subcellular resolution, as demonstrated by differential expression profiling between nuclear and cytoplasmic compartments. These features establish PCL-seq as an accessible and versatile workflow for spatial transcriptomic analyses in both frozen and FFPE tissues at subcellular resolution.
Published in
High-resolution spatial transcriptomics in fixed tissue using a cost-effective PCL-seq workflow
Dong X, Hu M, Cui X et al. · Genome research 2025 · PMID 40764053 · doi:10.1101/gr.279906.124
This dataset
Open GSE292893 in finder → Find more RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE292893_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Spatial studies usually ship Space Ranger style folders (count matrix plus tissue images). Look for them among the supplementary files.

Also filed as BioProject PRJNA1241821 and SRA study SRP573011. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40764053) ↗
Study design
17 conditions, mostly in triplicate
Mouse embryo, PAX6 positive, ×4 Mouse embryo, PAX6 negative, ×4 Mouse embryo, digit target, ×4 HEK293 and NIH/3T3 cells, 293 target, 1/100, ×3 HEK293 and NIH/3T3 cells, 293 target, 1/1000, ×3 HEK293 and NIH/3T3 cells, 293 target, 1/10000, ×3 HEK293 and NIH/3T3 cells, 3T3 target, 1/100, ×3 HEK293 and NIH/3T3 cells, 3T3 target, 1/1000, ×3 +9 more

Supports a between-group comparison across 52 samples.

How we read this: 17 replicated groups read from 52 sample titles; they account for 52 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 12 more — browse all 52 samples with per-sample file links →

Datasets on a similar topic

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