GEO series

Integrating microbial GWAS and single cell transcriptomics reveals associations between host cell populations and the gut microbiome

GSE289267 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2025/03/01 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.

Summary (written by the submitters)

Microbial genome-wide association studies (GWAS) have uncovered numerous host genetic variants associated with gut microbiota. However, links between host genetics, the gut microbiome and specific cellular context remains unclear. Here, we use a computational framework, scBPS (single-cell Bacteria Polygenic Score), to integrate existing microbial GWAS and single-cell RNA-sequencing profiles of 24 human organs, including the liver, pancreas, lung, and intestine, to identify host tissues and cell types relevant to gut microbes.

Read the full summary ↓

Analyzing 207 microbial taxa and 254 host cell types, scBPS-inferred cellular enrichments confirmed known biology such as dominant communications between gut microbes and the digestive tissue module and liver epithelial cell compartment. scBPS also identified a robust association between Collinsella and central-veinal hepatocyte subpopulation. We experimentally validated the causal effects of Collinsella on cholesterol metabolism in mice through single-nuclei RNA sequencing on liver tissue to identify relevant cell subpopulations. Mechanistically, oral gavage of Collinsella modulated cholesterol pathway gene expression in central-veinal hepatocytes. We further validated our approach using independent microbial GWAS data, alongside single-cell and bulk transcriptomic analyses, demonstrating its robustness and reproducibility. Together, scBPS enables a systematic mapping of the host-microbe crosstalk by linking cell populations to their interacting gut microbes.

This dataset

Open GSE289267 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 GSE289267_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 PRJNA1222311 and SRA study SRP563168. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

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