GEO series

To explore the functional consequences of ZBTB7A Overexpression in rodent OFC astrocytes in the context of a mild stressor

GSE174527 Mus musculus (mouse) RNA-seq (gene expression) 23 samples Submitted 2024/11/07 Platform GPL21103

At a glance

RNA-seq (gene expression) · mouse · 23 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: 23 samples: 23 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)

Major Depressive Disorder (MDD) arises from a complex interaction between genetics and environmental influences such as stress, which leads to persistent changes in frontolimbic gene expression and cellular function. Although relatively understudied in depression, the orbitofrontal cortex (OFC) exhibits significant changes in neuronal activity in MDD, as well as widespread gene expression changes, including consistent upregulation of inflammatory stress pathways.

Read the full summary ↓

Inflammation signaling in non-neuronal cell-types can disrupt normal neurotransmission, though the molecular mechanisms that regulate this interaction are not well understood. Our laboratory has implemented nuclei-sorting coupled with ATAC-seq in human postmortem OFC to characterize over 200 MDD-specific open chromatin regions (OCRs), which were detected exclusively in the non-neuronal cell population. From this dataset, we identified ZBTB7A, a chromatin remodeling protein with binding motifs significantly overrepresented in these MDD-specific OCRs. ZBTB7A has been shown to orchestrate chromatin accessibility for NF-kB target genes, however, its functional role in psychiatric disease has not yet been explored. In a series of studies utilizing astrocyte-specific viral manipulations, we found that overexpressing this chromatin remodeler in rodent OFC astrocytes was sufficient to induce aberrant expression of inflammatory genes, behavioral deficits, and neuronal hyperactivity in response to a mild stressor, compared to GFP-expressing mice. Together, these findings demonstrate a novel chromatin-based mechanism for increased inflammatory signaling in astrocytes that ultimately impairs neuroadaptive responses to stress with direct implications for OFC dysfunction in MDD pathology.

This dataset

Open GSE174527 in finder → Find more mouse 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 GSE174527_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 PRJNA730442 and SRA study SRP320066. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

23 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 23 sample titles: 23 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

GSM5318937 GC_S1.gz
GSM5318938 GC_S2.gz
GSM5318939 GC_S10.gz
GSM5318940 GC_S11.gz
GSM5318941 GC_S19.gz
GSM5318942 GS_S3.gz
GSM5318943 GS_S4.gz
GSM5318944 GS_S5.gz
GSM5318945 GS_S12.gz
GSM5318946 GS_S13.gz
GSM5318947 GS_S20.gz
GSM5318948 GS_S21.gz
GSM5318949 GS_S22.gz
GSM5318950 ZC_S6.gz
GSM5318951 ZC_S14.gz
GSM5318952 ZC_S15.gz
GSM5318953 ZC_S23.gz
GSM5318954 ZC_S24.gz
GSM5318955 ZS_S7.gz
GSM5318956 ZS_S9.gz
GSM5318957 ZS_S17.gz
GSM5318958 ZS_S25.gz
GSM5318959 ZS_S26.gz

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Search all mouse RNA-seq 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.