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Effects of norepinephrine(NE) and dexamethasone(DEX) exposure on signaling pathways in ciliary body cells

GSE335628 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2026/06/23 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 14 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
14 samples: 5 conditions, mostly in triplicateGroups 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)
Aqueous humor production by the ciliary body is regulated in part by hormonal cues, including norepinephrine (NE) and dexamethasone (DEX), and its circadian variation is thought to reflect rhythmic changes in these signals. However, the transcriptional programs and molecular pathways through which NE and DEX influence human non-pigmented ciliary epithelial cells remain incompletely defined.
Read the full summary ↓
In this study, we performed RNA-seq analysis of human non-pigmented ciliary epithelial cells exposed to NE or DEX for 1 or 2 hours, with vehicle-treated cells as controls, to identify stimulus-responsive genes and pathways associated with ciliary body function and aqueous humor production.
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 GSE335628_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 PRJNA1479024 and SRA study SRP710093. Searching any of these in the dataset finder brings you back here.

Study design
5 conditions, mostly in triplicate
Human, NEpiC, DEX, 1h ×3 Human, NEpiC, NE, 1h ×3 Human, NEpiC, DMSO, 1h ×3 Human, NEpiC, DEX, 2h ×3 Human, NEpiC, DMSO, 2h ×2

Supports a between-group comparison across 14 samples.

How we read this: 5 replicated groups read from 14 sample titles; they account for 14 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
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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.