GEO series

REP-1 depletion causes altered mitochondrial energy metabolism in CHM disease, shifting from glycolysis to lipid oxidation

GSE299462 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/05/20 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 12 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: 12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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: REP-1 deficiency induces aberrant mitochondrial metabolic rewiring from glycolysis to lipid oxidation in CHM diseaseCell death & disease · 2026

Summary (written by the submitters)

The persistent supply of glucose in the retina is essential for underpinning ATP production to meet the retinal cell’s energy requirements essential for the vision. Glucose transporters mainly mediate the glucose supply and diffusion thorough the retinal vasculature, choroid/RPE and photoreceptor cells. While the physiological mechanisms behind glucose supply have been well studied and described, how glucose supply dysfunction contributes to the phenotype of retinal disease is poorly understood.

Read the full summary ↓

Now we provide evidence that retinal energetic failure dependent by glucose supply defect explains large part of the phenotype of Choroideremia (CHM), an X-linked chorioretinal dystrophy caused by mutations in the Rab escort protein-1 (REP-1) gene. By interrogating the effect of REP-1 depletion in CHM, we found that alteration of glucose transporters GLUT-4 and GLUT-1 in the RPE/retina cells contribute to the CHM phenotype. REP-1 loss induces glucose-dependent bioenergetic deficiency, altering mitochondria morphology and function. By restoring both GLUTs expression and membrane translocation through pharmacological induction of phosphatidylinositol 3-Kinase pathway, we re-established the glucose uptake and its commitment towards RPE/retina both in vitro and in vivo. This study supports the notion that, in CHM, the absence of REP-1 causes an altered glucose uptake, which determines a deficit of energy compromising retinal cell homeostasis and function.

Published in

REP-1 deficiency induces aberrant mitochondrial metabolic rewiring from glycolysis to lipid oxidation in CHM disease

Buonocore S, Giamundo G, Barone C et al. · Cell death & disease 2026 · PMID 41912478 · doi:10.1038/s41419-026-08592-6

This dataset

Open GSE299462 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 GSE299462_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 PRJNA1274478 and SRA study SRP591099. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41912478) ↗

Study design

12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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

GSM9039511 WT_1, RPE
GSM9039512 WT_2, RPE
GSM9039513 WT_3, RPE
GSM9039514 WT_4, RPE
GSM9039515 shREP1_1, RPE
GSM9039516 shREP1_2, RPE
GSM9039517 shREP1_3, RPE
GSM9039518 shREP1_4, RPE
GSM9039519 shREP1+LEP_1, RPE
GSM9039520 shREP1+LEP_2, RPE
GSM9039521 shREP1+LEP_3, RPE
GSM9039522 shREP1+LEP_4, RPE

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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.