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Transcriptomic analysis of 30dpp ovaries and 35dpp testes exposed to the cocktails of pharmaceuticals ibuprofen (IBU), 2hydroxyIBU (2hIBU), diclofenac (DCF) and 17a ethinyl-estradiol (EE2) in mice

GSE235586 Mus musculus (mouse) RNA-seq (gene expression) 54 samples Submitted 2024/09/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 54 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
54 samples: 54 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)
The endocrine disrupting pharmaceuticals, non-steroidal anti-inflammatory drugs (NSAIDs) and 17α-ethinyl-estradiol (EE2), are among the most relevant molecules found in aquatic ecosystems, surface and drinking water due to their incomplete removal by wastewater treatment plants. Exposure to therapeutic doses has a negative impact on gonadal development and fertility in rodent models; however, the effects of their chronic exposure at lower doses are not known.
Read the full summary ↓
In this study, we investigated the impact of chronic exposure to a mixture containing ibuprofen, 2hydroxy-ibuprofen, diclofenac, and EE2 at two environmentally relevant doses (added to the drinking water from fetal life, 8.5 dpc, until puberty) on the reproductive tract in F1 exposed mice and their F2 offspring. In F1 animals, exposure delayed male puberty and accelerated female puberty. In post-pubertal F1 testes and ovaries, differentiation/maturation of the different gonad cell types was altered, and some of these modifications were observed also in the non-exposed F2 generation. Transcriptomic analysis of post-pubertal testes and ovaries of F1 (exposed) and F2 animals revealed significant changes in gene expression profiles and enriched pathways, particularly the inflammasome, metabolism and extracellular matrix pathways, compared with controls (non-exposed). This suggested that exposure to these drug cocktails has an inter-generational impact (Int. J. Mol. Sci. 2023, 24, 5890. /doi: 10.3390/ijms24065890)
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 GSE235586_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 PRJNA986506 and SRA study SRP445381. Searching any of these in the dataset finder brings you back here.

Study design
54 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 54 sample titles: 54 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

+ 14 more — browse all 54 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.