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Transcriptome data of Huh7 cells treated with glucose or fructose

GSE293320 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/03/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
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 transcriptome sequencing compared gene expression differences in Huh7 cells treated with glucose versus fructose. At the nutrient level, fructose treatment alone did not induce severe endoplasmic reticulum (ER) stress compared to glucose. However, upon KHK-C overexpression, fructose treatment led to significant ER stress. At the genetic level, glucose treatment did not trigger ER stress even with KHK-C overexpression, whereas fructose treatment under the same conditions resulted in pronounced ER stress.
Read the full summary ↓
Additionally, Aldob knockdown further exacerbated ER stress. In summary, our findings suggest that in Huh7 cells, KHK-C-mediated phosphorylation of fructose into fructose-1-phosphate (F1P) leads to intracellular F1P accumulation, which drives severe ER stress.
This dataset
Open GSE293320 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 GSE293320_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 PRJNA1244013 and SRA study SRP575163. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
GV ×3 GK ×3 GVS ×3 GKS ×3 FV ×3 FK ×3 FVS ×3 FKS ×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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