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A multi-omics characterization of the human lumbar spinal cord and motor cortex reveals non-overlapping molecular signatures in ALS [snRNA-Seq; snATAC-Seq]

GSE330130 Homo sapiens (human) Single-nucleus RNA-seq 87 samples Submitted 2026/07/24 Platform GPL34281
At a glance

Single-nucleus RNA-seq · human · 87 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism
Homo sapiens (human)
Samples
87 samples: 87 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.
Summary (written by the submitters)
Amyotrophic lateral sclerosis (ALS) is a debilitating neurodegenerative disease characterized by the loss of upper and lower motor neurons in the motor cortex (MTC) and spinal cord (SC), respectively, leading to muscle atrophy and ultimately respiratory failure. While motor neurons (MNs) are the selectively vulnerable cell type, their interactions with glia contribute to the progression of ALS pathology.
Read the full summary ↓
However, it remains unclear whether the molecular alterations underlying MN and glial dysfunction in ALS are the same in the MTC and lumbar SC (LSC). To address this, we constructed spatially-resolved gene expression maps of the MTC and LSC by combining spatial and single-nucleus transcriptomic profiles from a cohort of non-neurological controls and ALS patients clinically stratified by site of symptom onset. In the ventral horn of the LSC, we see a decrease in genes associated with MNs and synaptic signaling in ALS patients. We also identify region-specific alterations in endothelial- and glial-related functions. Notably, the severity of these MN deficits and endothelial-related functions is influenced by the site of symptom onset, whereas alterations in glial function largely are not. In the MTC, we observe layer-specific increases in synaptic signaling in ALS patients. Comparing the molecular and cellular changes within the LSC and MTC in ALS indicates that they are predominantly non-overlapping, and have different molecular signatures.
This dataset
Open GSE330130 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE330130_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1462802 and SRA study SRP698107. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
87 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 87 sample titles: 87 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

+ 47 more — browse all 87 samples with per-sample file links →

Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag 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.