GEO series

ABHD18 is essential for cardiolipin remodeling and its inhibition restores mitochondrial function in Barth Syndrome [RNA-Seq]

GSE297335 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/05/29 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 18 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: 18 samples: 18 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.

Summary (written by the submitters)

Cardiolipin (CL) is the signature phospholipid of the inner mitochondrial membrane, where it stabilizes the electron transport chain protein complexes. The final step in CL biosynthesis concerns its remodeling: the exchange of nascent acyl chains with longer, unsaturated chains. However, the enzyme responsible for cleaving nascent CL has remained elusive.

Read the full summary ↓

Here, we describe ABDH18 as the candidate de-acylase in the CL biosynthesis pathway. Accordingly, ABHD18 converts CL into monolysocardiolipin (MLCL) in vitro and its inactivation in cells and mice results in accumulation of nascent CL in serum and tissues. Strikingly, ABHD18 deactivation rescues the mitochondrial defects in cells and the morbidity and mortality in mice associated with Barth Syndrome. This rare genetic disease is characterized by the build-up of MLCL due to inactivating mutations in TAFAZZIN (TAZ), which encodes the final enzyme in the CL remodeling cascade. We also identified a selective, covalent small molecule inhibitor of ABHD18 that restores TAZ mutant phenotypes in patient fibroblasts and fish embryos. This study highlights a striking example of genetic suppression of a monogenic disease revealing a canonical enzyme in the CL biosynthesis pathway.

This dataset

Open GSE297335 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 GSE297335_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 PRJNA1263536 and SRA study SRP585636. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

18 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 18 sample titles: 18 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

GSM8988809 WT_A_MIN
GSM8988810 WT_B_MIN
GSM8988811 WT_C_MIN
GSM8988812 WT_A_RICH
GSM8988813 WT_B_RICH
GSM8988814 WT_C_RICH
GSM8988815 T126_A_MIN
GSM8988816 T126_B_MIN
GSM8988817 T126_C_MIN
GSM8988818 T126_A_RICH
GSM8988819 T126_B_RICH
GSM8988820 T126_C_RICH
GSM8988821 T148_A_MIN
GSM8988822 T148_B_MIN
GSM8988823 T148_C_MIN
GSM8988824 T148_A_RICH
GSM8988825 T148_B_RICH
GSM8988826 T148_C_RICH

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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.