GEO series

Spatially tuneable multi-omics sequencing using light-driven combinatorial barcoding of molecules in tissues / RNA_LCM

GSE260698 Mus musculus (mouse) RNA-seq (gene expression) 2 samples Submitted 2026/06/03 Platform GPL21626

At a glance

RNA-seq (gene expression) · mouse · 2 samples

What it is: RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism: Mus musculus (mouse)
Samples: 2 samples
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: Spatially tunable multiomic sequencing using light-driven combinatorial barcoding of molecules in tissuesProceedings of the National Academy of Sciences of the United States of America · 2026

Summary (written by the submitters)

Mapping the molecular identities and functions of cells alongside their spatial tissue context is key to understanding the complex interplay within and between their tissue neighbourhoods. A wide range of methods enable spatial profiling of regions, some down to the level of individual cells, in their anatomical context, via different barcoding schemes that encode either the location or the identity of target molecules.

Read the full summary ↓

However, all these technologies face a trade-off between spatial resolution, depth of profiling, and scalability. Here, we present Barcoding by Activated Linkage of Indexes (BALI), a method that uses light to write combinatorial spatial molecular barcodes directly onto target molecules in situ, enabling multi-omics profiling by next generation sequencing. A unique feature of BALI is that the user can define the number, size, and shape of the spatial locations to be interrogated, with the potential to profile millions of distinct regions down to subcellular scale. As a proof of concept, we used BALI to capture the transcriptome, chromatin accessibility, or both, from distinct areas of the mouse brain in single tissue sections, demonstrating strong concordance with publicly available datasets. BALI therefore combines high spatial resolution, high throughput, histological adaptability, and workflow accessibility to enable powerful spatial multi-omics profiling.

Published in

Spatially tunable multiomic sequencing using light-driven combinatorial barcoding of molecules in tissues

Battistoni G, Torres-Garcia S, Sia CY et al. · Proceedings of the National Academy of Sciences of the United States of America 2026 · PMID 42150070 · doi:10.1073/pnas.2527896123

This dataset

Open GSE260698 in finder → Find more mouse 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 GSE260698_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1082721. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42150070) ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

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Search all mouse RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.