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Single-cell RNA-seq of Atg7 knockout mice reveals ATG7’s role in antimicrobial immunity against nontuberculous mycobacteria

GSE297620 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2025/07/09 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 2 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
2 samples
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
ATG7 in innate immune cells is required for host defense against nontuberculous mycobacterial pulmonary infectionsNature communications · 2025
Summary (written by the submitters)
We performed single-cell RNA sequencing (scRNA-seq) using the 10X Genomics platform to investigate the role of the autophagy-related protein ATG7 in the context of nontuberculous mycobacterial (NTM) infection. ATG7 in innate immune cells plays a critical role in controlling NTM infection and protecting lung tissue from pathological inflammation. This study represents single-cell analysis of Mice deletion of Atg7 in innate immune cells and reveals the importance of ATG7 in mediating antimicrobial responses during infection and its essential role in host defense mechanisms against NTM.
Published in
ATG7 in innate immune cells is required for host defense against nontuberculous mycobacterial pulmonary infections
Jeon SM, Lee YJ, Lee SH et al. · Nature communications 2025 · PMID 40730835 · doi:10.1038/s41467-025-61791-1
This dataset
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.

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 GSE297620_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1265277 and SRA study SRP586406. Searching any of these in the dataset finder brings you back here.

Samples in this study

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