GEO series

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus [snRNA-seq]

GSE264624 Homo sapiens (human) Spatial transcriptomics 26 samples Submitted 2024/04/27 Platform GPL24676

At a glance

Spatial transcriptomics · human · 26 samples

What it is: Spatial transcriptomicsGene activity measured with its position in a tissue section.
Organism: Homo sapiens (human)
Samples: 26 samples: 26 samples, each with a distinct title — no replicated groupsGroups 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: An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampusNature neuroscience · 2025

Summary (written by the submitters)

The hippocampus contains many unique cell types, which serve the structure’s specialized functions, including learning, memory and cognition. These cells have distinct spatial topography, morphology, physiology, and connectivity, highlighting the need for transcriptome-wide profiling strategies that retain cytoarchitectural organization.

Read the full summary ↓

Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus across ten adult neurotypical donors. We defined molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization and transfer learning, we integrated these data to define gene expression patterns within the snRNA-seq data and probe their expression in the SRT data. Using this approach, we leveraged existing rodent datasets that feature information on circuit connectivity and neural activity induction to make predictions about axonal projection targets and likelihood of ensemble recruitment in spatially-defined cellular populations of the human hippocampus. Finally, we integrated genome-wide association studies with transcriptomic data to identify enrichment of genetic components for neurodevelopmental, neuropsychiatric, and neurodegenerative disorders across cell types, spatial domains, and gene expression patterns of the human hippocampus. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

Published in

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus

Thompson JR, Nelson ED, Tippani M et al. · Nature neuroscience 2025 · PMID 40739059 · doi:10.1038/s41593-025-02022-0

This dataset

Open GSE264624 in finder → Find more human 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 GSE264624_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 PRJNA1103675. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40739059) ↗

Study design

26 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 26 sample titles: 26 distinct titles with little repetition. 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

GSM8224155 1c_scp
GSM8224156 2c_scp
GSM8224157 10c_scp
GSM8224158 11c_scp
GSM8224159 12c_scp
GSM8224160 13c_scp
GSM8224161 14c_scp
GSM8224162 15c_scp
GSM8224163 16c_scp
GSM8224164 17c_scp
GSM8224165 18c_scp
GSM8224166 19c_scp
GSM8224167 20c_scp
GSM8224168 21c_scp
GSM8224169 22c_scp
GSM8224170 23c_scp
GSM8224171 24c_scp
GSM8224172 25c_scp
GSM8224173 26c_scp
GSM8224174 27c_scp
GSM8224175 32c_scp
GSM8224176 33c_scp
GSM8224177 36c_scp
GSM8224178 37c_scp
GSM8224179 38c_scp
GSM8224180 39c_scp

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