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A 24-hour light-dark time-series bulk RNA-seq dataset of the mouse lacrimal gland

GSE333177 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/06/22 Platform GPL23479
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples: 8 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)
The lacrimal gland is a major exocrine organ responsible for tear secretion and is essential for maintaining ocular surface homeostasis. However, time-resolved transcriptomic resources for this tissue remain limited. Here, we generated a bulk RNA-seq time-series dataset from extraorbital lacrimal glands of male C57BL/6J mice maintained under a controlled 12:12 light-dark schedule.
Read the full summary ↓
Tissue samples were collected at 3-h intervals across a 24-h cycle, yielding eight time points with three biological replicates per time point. Libraries were prepared from total RNA and sequenced as 150-bp paired-end reads. This dataset provides a reusable temporal transcriptomic resource for downstream studies of lacrimal gland biology, ocular surface physiology, and gene-expression dynamics under defined light-dark conditions.
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 GSE333177_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 PRJNA1309031 and SRA study SRP613517. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in triplicate
Mouse extraorbital lacrimal gland ZT0 ×3 Mouse extraorbital lacrimal gland ZT3 ×3 Mouse extraorbital lacrimal gland ZT6 ×3 Mouse extraorbital lacrimal gland ZT9 ×3 Mouse extraorbital lacrimal gland ZT12 ×3 Mouse extraorbital lacrimal gland ZT15 ×3 Mouse extraorbital lacrimal gland ZT18 ×3 Mouse extraorbital lacrimal gland ZT21 ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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
Datasets on a similar topic

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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.