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Leveraging deep single-soma RNA sequencing to explore the neural basis of human somatosensation

GSE249746 Homo sapiens (human) RNA-seq (gene expression) 1136 samples Submitted 2024/07/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 1136 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
Homo sapiens (human)
Samples
1136 samples: 122 × N2-RL5 vs 96 × N3-RT11 vs 92 × N2-RT12 vs 90 × N3-RL2Groups 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
Leveraging deep single-soma RNA sequencing to explore the neural basis of human somatosensationNature neuroscience · 2024
Summary (written by the submitters)
The versatility of somatosensation arises from heterogeneous dorsal root ganglion (DRG) neurons. However, soma transcriptomes of individual human (h)DRG neurons-critical information to decipher their functions-are lacking due to technical difficulties. In this study, we isolated somata from individual hDRG neurons and conducted deep RNA sequencing (RNA-seq) to detect, on average, over 9,000 unique genes per neuron, and we identified 16 neuronal types.
Read the full summary ↓
These results were corroborated and validated by spatial transcriptomics and RNAscope in situ hybridization. Cross-species analyses revealed divergence among potential pain-sensing neurons and the likely existence of human-specific neuronal types. Molecular-profile-informed microneurography recordings revealed temperature-sensing properties across human sensory afferent types. In summary, by employing single-soma deep RNA-seq and spatial transcriptomics, we generated an hDRG neuron atlas, which provides insights into human somatosensory physiology and serves as a foundation for translational work.
Published in
Leveraging deep single-soma RNA sequencing to explore the neural basis of human somatosensation
Yu H, Nagi SS, Usoskin D et al. · Nature neuroscience 2024 · PMID 39496796 · doi:10.1038/s41593-024-01794-1
This dataset
Open GSE249746 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 GSE249746_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 PRJNA1050278 and SRA study SRP476700. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39496796) ↗
Study design
122 × N2-RL5 vs 96 × N3-RT11 vs 92 × N2-RT12 vs 90 × N3-RL2

Supports a between-group comparison across 400 samples.

How we read this: 4 replicated groups read from the first 400 of 1136 sample titles; they account for 400 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

+ 1096 more — browse all 1136 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.