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Transcriptional characterization of cocaine withdrawal versus extinction within nucleus accumbens

GSE264129 Rattus norvegicus (rat) RNA-seq (gene expression) 84 samples Submitted 2025/01/13 Platform GPL25947
At a glance

RNA-seq (gene expression) · rat · 84 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
Rattus norvegicus (rat)
Samples
84 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.
Summary (written by the submitters)
Neurobiological alterations seen in addiction amplify during abstinence and compromise relapse prevention. Cocaine use disorder (CUD) exemplifies this phenomenon in which reward regions such as nucleus accumbens (NAc) undergo withdrawal-associated modifications. While genome-wide transcriptional changes in NAc are linked to specific addiction phases, these have not been examined in a context- and NAc-subregion-specific manner during withdrawal vs.
Read the full summary ↓
extinction. We used cocaine self-administration in rats combined with RNA-sequencing of NAc core and shell to transcriptionally profile withdrawal in the home-cage, in the previous drug context, or after extinction. As expected, home-cage withdrawal maintained drug seeking, whereas extinction reduced it. Conversely, withdrawal involving the drug context increased seeking. Bioinformatic analyses revealed specific gene expression patterns and networks associated with these states. Comparing NAc datasets of CUD patients highlighted conserved transcriptomic signatures with rats experiencing withdrawal in the drug context. Together, this work reveals fundamental mechanisms that can be targeted to attenuate relapse.
This dataset
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.

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 GSE264129_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1101032 and SRA study SRP502115. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 84 more — browse all 84 samples with per-sample file links →

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