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Systematically characterizing the roles of E3-ligase family members in inflammatory responses with massively parallel Perturb-seq

GSE327057 Mus musculus (mouse) RNA-seq (gene expression) 169 samples Submitted 2026/04/06 Platform GPL24247Platform GPL34290Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 169 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
169 samples: 169 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)
E3 ligases regulate key processes, but many of their roles remain unknown. Using Perturb-seq, we interrogated the function of 1,130 E3 ligases, partners and substrates in the inflammatory response in primary dendritic cells (DCs). Dozens impacted the balance of DC1, DC2, migratory DC and macrophage states and a gradient of DC maturation.
Read the full summary ↓
Family members grouped into co-functional modules that were enriched for physical interactions and impacted specific programs through substrate transcription factors. E3s and their adaptors co-regulated the same processes, but partnered with different substrate recognition adaptors to impact distinct aspects of the DC life cycle, several of which we validated experimentally. Genetic interactions were more prevalent within than between modules, and a deep learning model, comBVAE, leveraged modularity to predict the outcome of combinations. We experimentally validated 91 combinations inferring molecular mechanisms producing non-aditivity. The E3 regulatory network was associated with heritable variation and aberrant gene expression in immune cells in human inflammatory diseases. Our study provides a general approach to dissect gene function.
This dataset
Open GSE327057 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 GSE327057_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 PRJNA1449386 and SRA study SRP689525. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
169 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 169 sample titles: 169 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

+ 129 more — browse all 169 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.