GEO series

Systemic toxicity in hepatic Propionyl-CoA Carboxylase deficiency

GSE305924 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/03/27 Platform GPL24247

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: 6 conditions, mostly with about 4 replicates eachGroups 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)

Inborn errors in Propionyl-CoA Carboxylase (Pcca/b) cause life threatening propionic acidemia. To understand the contribution of mitochondrial propionyl-CoA metabolism to cellular and systemic metabolic dysfunction, we generated inducible and tissue-specific knockout (KO) mouse models of Pcca. Adult inducible loss of Pcca results in acute metabolic decompensation resembling the inborn error.

Read the full summary ↓

The liver-specific loss of Pcca largely recapitulates this in a sexually dimorphic manner. Propionate and pyruvate converge in the TCA cycle as major anaplerotic substrates. Paradoxically, the simultaneous KO of Pyruvate Carboxylase (Pcx) rescues the lethality of liver-specific Pcca KO male mice. Most metabolites suspected as deleterious in propionic acidemia are exacerbated in Pcca;Pcx double KO mice with the noted exception of methylcitrate suggesting the centrality of this metabolite to systemic toxicity. These data clarify relevant toxic biomarkers and suggest that rebalancing hepatic TCA cycle metabolism as critical to mitigate the adverse effects of alternative propionyl-CoA metabolism.

This dataset

Open GSE305924 in finder → Find more mouse 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 GSE305924_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 PRJNA1308458 and SRA study SRP610680. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly with about 4 replicates each

ffGFP ×4 ffiCre ×4 ffffiCre ×4 ffvill ×4 PCCATAM ×4 HLCS ×4

Supports a between-group comparison across 24 samples.

How we read this: 6 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

GSM9188018 ffGFP1 ffGFP
GSM9188019 ffGFP2 ffGFP
GSM9188020 ffGFP3 ffGFP
GSM9188021 ffGFP4 ffGFP
GSM9188022 ffiCre1 ffiCre
GSM9188023 ffiCre2 ffiCre
GSM9188024 ffiCre3 ffiCre
GSM9188025 ffiCre4 ffiCre
GSM9188026 ffffiCre1 ffffiCre
GSM9188027 ffffiCre2 ffffiCre
GSM9188028 ffffiCre3 ffffiCre
GSM9188029 ffffiCre4 ffffiCre
GSM9188030 ffvill1 ffvill
GSM9188031 ffvill2 ffvill
GSM9188032 ffvill3 ffvill
GSM9188033 ffvill4 ffvill
GSM9188034 PCCATAM1 PCCATAM
GSM9188035 PCCATAM2 PCCATAM
GSM9188036 PCCATAM3 PCCATAM
GSM9188037 PCCATAM4 PCCATAM
GSM9188038 HLCS1 HLCS
GSM9188039 HLCS2 HLCS
GSM9188040 HLCS3 HLCS
GSM9188041 HLCS4 HLCS

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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.