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PPARγ agonists induce biased signaling in human adipocytes

GSE266107 Homo sapiens (human) RNA-seq (gene expression) 58 samples Submitted 2025/10/26 Platform GPL24676Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 58 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
58 samples: 10 conditions, mostly with about 8 replicates eachGroups 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)
Biased signaling and ligand bias, often referred to as functional selectivity or selective nuclear receptor modulation, have been reported for many nuclear receptor partial agonists over the past 20 years. However, whether differences in nuclear receptor signaling produced by partial and full agonists results from less intense partial agonist modulation, off-target effects, or biased signaling remains unclear.
Read the full summary ↓
To determine whether biased signaling can occur through nuclear receptors we compare the transcriptional effects of two full agonists (which also favor different coactivator peptides) in human adipocytes. We also test the signaling effects of a partial agonist relative to full agonists. Furthermore, whether biased coactivator peptide recruitment translates to biased signaling in cells has not been determined. In a step towards this goal, we show that these same full agonists induce biased recruitment of 100-300 residue regions of coactivators containing all their nuclear receptor binding motifs. Together these data support the idea that nuclear receptor agonists can induce biased signaling through differences in coactivator recruitment.
This dataset
Open GSE266107 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 GSE266107_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 PRJNA1105894 and SRA study SRP504621. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 conditions, mostly with about 8 replicates each
Adipoctye,GW1929,24hr,Replicate,24hr, ×8 Adipoctye,Rosiglitazone,24hr,Replicate,24hr, ×8 Adipoctye,MRL24,24hr,Replicate,24hr, ×8 Adipoctye,DMSO,24hr,Replicate,24hr, ×8 T0070907 ×5 DMSO ×5 GW1929 ×4 T0070907 pretreated GW1929 ×4 +2 more

Supports a case/control comparison: 8 samples read as cases, 13 as controls.

How we read this: 10 replicated groups read from 58 sample titles; they account for 58 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

+ 18 more — browse all 58 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.