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Single-cell activation screen identifies hepatic maturation regulators with zonal resolution

GSE242934 Mus musculus (mouse) Single-cell RNA-seq 24 samples Submitted 2025/09/05 Platform GPL24247Platform GPL21103Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 24 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
24 samples: 24 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
Single-cell activation screen identifies hepatic maturation regulators with zonal resolutionDevelopmental cell · 2026
Summary (written by the submitters)
The maturation of lineage-committed embryonic hepatocytes requires both the timed activation of metabolic gene regulatory networks (GRNs) and silencing of embryonic programs to achieve adult hepatic functions. However, in vitro derivation of mature hepatocytes remains imperfect, and key transcriptional regulators governing GRN rewiring during late development are still insufficiently defined.
Read the full summary ↓
To address this, we generated a developmental reference atlas and employed a dCas9 activation screen with single-cell transcriptomics on primary mouse embryonic hepatocytes, enabling effect ranking among late-onset transcription regulators. We identify Nr1i3 as a potent inducer of pericentrally expressed metabolic genes and Nfix as a critical suppressor of embryonic and periportal signatures. Supplementing liver zonation patterning signals with these regulators further enhanced the expression of pericentrally zonated metabolic genes, emphasizing the importance of a microenvironment-targeted approach. Our screening and analysis therefore highlight regulatory mechanisms underlying organ maturation and offer general strategies for improving the functionality of in vitro-derived cells.
Published in
Single-cell activation screen identifies hepatic maturation regulators with zonal resolution
Taguchi A, Magalhães AP, Bolondi A et al. · Developmental cell 2026 · PMID 41270741 · doi:10.1016/j.devcel.2025.10.014
This dataset
Open GSE242934 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 GSE242934_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 PRJNA1015558 and SRA study SRP459905. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41270741) ↗
Study design
24 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 24 sample titles: 24 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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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.