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Temporal dynamics and functional annotation of transcriptome rhythmicity in HEK293T cells

GSE315903 Homo sapiens (human) RNA-seq (gene expression) 39 samples Submitted 2026/03/04 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 39 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
39 samples: 13 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.
Paper
Temporal dynamics and functional annotation of transcriptome rhythmicity in HEK293T cellsPloS one · 2026
Summary (written by the submitters)
HEK293T cells are a widely used experimental model in cell biology. However, the presence and robustness of intrinsic circadian rhythmicity in HEK293T cells remain controversial. To address this issue, we synchronized HEK293T cells with dexamethasone and initiated sample collection 24 hours after synchronization. Cells were harvested every 4 hours over a 48-hour period, followed by transcriptomic (RNA-seq) analysis.
Published in
Temporal dynamics and functional annotation of transcriptome rhythmicity in HEK293T cells
Sun Y, Dong H, Ge F et al. · PloS one 2026 · PMID 41746989 · doi:10.1371/journal.pone.0343991
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 GSE315903_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 PRJNA1399905 and SRA study SRP660623. Searching any of these in the dataset finder brings you back here.

Study design
13 conditions, mostly in triplicate
HEK 293T, 2WTCT0, ×3 HEK 293T, 2WTCT4, ×3 HEK 293T, 2WTCT8, ×3 HEK 293T, 2WTCT12, ×3 HEK 293T, 2WTCT16, ×3 HEK 293T, 2WTCT20, ×3 HEK 293T, 2WTCT24, ×3 HEK 293T, 2WTCT28, ×3 +5 more

Supports a between-group comparison across 39 samples.

How we read this: 13 replicated groups read from 39 sample titles; they account for 39 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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