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IFRD1 orchestrates hepatocyte metabolism and macrophage interactions to facilitate liver regeneration

GSE315498 Mus musculus (mouse) Single-nucleus RNA-seq 10 samples Submitted 2026/07/29 Platform GPL24247
At a glance

Single-nucleus RNA-seq · mouse · 10 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
10 samples: 10 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
IFRD1 orchestrates hepatocyte metabolism and macrophage interactions to facilitate liver regenerationJournal of hepatology · 2026
Summary (written by the submitters)
Background & Aims Liver regeneration is a tightly regulated process requiring coordinated interactions between hepatocytes and non-parenchymal cells; however, its molecular mechanisms remain incompletely defined. Here, we aimed to investigate the role of interferon-related developmental regulator 1 (IFRD1) in regulating metabolic–immune crosstalk during liver regeneration.
Read the full summary ↓
Methods We integrated public transcriptomic datasets, human liver disease samples, and multiple in-house–generated experimental models to characterize the dynamic expression of IFRD1 during liver regeneration. Genetic loss-of-function approaches, including global and cell type–specific knockout mice, together with adeno-associated virus–mediated gain-of-function strategies, were combined with single-nucleus RNA-seq, ATAC-seq, metabolic and biochemical assays, protein interaction analyses, and in vivo rescue experiments to elucidate the underlying mechanisms and clinical relevance. Results Hepatocyte IFRD1 was rapidly induced during the early phase of liver regeneration in mice but markedly diminished in human chronic liver disease. Hepatocyte-specific loss of IFRD1 impaired liver repair and regeneration, whereas IFRD1 overexpression enhanced regenerative responses across multiple models, including partial hepatectomy, toxic liver injury, and hepatic ischemia–reperfusion injury. Mechanistically, IFRD1 was required to sustain hepatocyte β-oxidation and mitochondrial ATP production by stabilizing SLC25A5 through competition with the E3 ubiquitin ligase TRIM21. This ATP boost enables chromatin remodeling in hepatocytes, promoting CCL/CXC chemokine expression to recruit CCR2+ monocytes and expand the regenerative GPNMB+ macrophage pool. Notably, IFRD1 overexpression restored liver regenerative capacity after partial hepatectomy in mice with metabolic dysfunction–associated steatohepatitis or DEN-induced liver fibrosis. Conclusions Our findings define IFRD1 as a key immunometabolic regulator of liver regeneration, mediating hepatocyte metabolic control to macrophage-driven regenerative responses, and support the therapeutic potential of targeting IFRD1 to enhance regenerative capacity in liver disease.
Published in
IFRD1 orchestrates hepatocyte metabolism and macrophage interactions to facilitate liver regeneration
Zeng T, Huang Y, He H et al. · Journal of hepatology 2026 · PMID 41861961 · doi:10.1016/j.jhep.2026.03.012
This dataset
Open GSE315498 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 GSE315498_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1397983. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41861961) ↗
Study design
10 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 10 sample titles: 10 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
Datasets on a similar topic

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