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Spatiotemporal Proteomic and Transcriptomic Landscape of DAT+ Dopaminergic Neurons Development and Function

GSE285556 Mus musculus (mouse) RNA-seq (gene expression) 27 samples Submitted 2025/04/16 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 27 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
27 samples: 27 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
Spatiotemporal proteomic and transcriptomic landscape of DAT+ dopaminergic neurons development and functioniScience · 2025
Summary (written by the submitters)
Dopaminergic (DA) neurons marked by the dopamine transporter (DAT) have multiple physiological functions and are involved in the regulation of mental and neurological diseases, prompting in-depth studies into their development and functions. This research explores the spatiotemporal proteomic and transcriptomic changes in DAT+ DA neurons within key brain regions involved in DA signaling—the nucleus accumbens (NAc), substantia nigra (SNc), and ventral tegmental area (VTA).
Read the full summary ↓
Utilizing cutting-edge multi-omics techniques, such as ultrasensitive trace sample proteomics and SMART_x0002_seq2 for transcriptomics, we examine the DA neuronal system at critical postnatal milestones: postnatal day 7 (P7), postnatal day 30 (P30), and postnatal day 60 (P60). The study reveals unique molecular profiles within DA neuron populations, showcasing their varied functional roles and developmental progression. Immunofluorescence mapping illustrates these molecular distributions, validating the quantitative data and highlighting the dynamic molecular structure of DA neurons. Our findings notably highlight a marked increase over time in Aldh1a1 expression, an essential enzyme for retinoic acid production, suggesting its evolving role in neuronal development and specific functions. This comprehensive analysis offers a profound molecular perspective on DAT+ DA neuron development, enhancing our understanding of their functional diversity and potential relevance in DA-related diseases.
Published in
Spatiotemporal proteomic and transcriptomic landscape of DAT+ dopaminergic neurons development and function
Zhao H, Chen P, Gao X et al. · iScience 2025 · PMID 40201125 · doi:10.1016/j.isci.2025.112115
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 GSE285556_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 PRJNA1204355 and SRA study SRP554531. Searching any of these in the dataset finder brings you back here.

Study design
27 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 27 sample titles: 27 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
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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.