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Beyond ACE2: DPP4 Engagement Redefines SARS-CoV-2 Receptor Tropism

GSE328992 Mus musculus (mouse) RNA-seq (gene expression) 21 samples Submitted 2026/04/28 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 21 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
21 samples: 6 conditions, mostly in triplicateGroups 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)
The continued evolution of SARS-CoV-2 has produced variants with enhanced transmissibility despite reduced binding affinity to the canonical entry receptor ACE2, suggesting the involvement of additional host factors. Here, we integrate large-scale sequence analysis, structure-informed machine learning, biochemical assays, cell-based entry models, and in vivo infection studies to examine receptor usage diversification in recent SARS-CoV-2 variants.
Read the full summary ↓
We find that multiple post-Omicron lineages, including XBB-derived variants, exhibit increased functional engagement of dipeptidyl peptidase 4 (DPP4), accompanied by reduced reliance on ACE2-mediated entry in defined experimental contexts. In human DPP4 knock-in mice, representative XBB variants display enhanced replication with limited pulmonary pathology. Together, these findings support a model in which SARS-CoV-2 evolution is characterized by diversification of receptor engagement strategies, highlighting DPP4 as a functionally relevant entry factor that may contribute to viral fitness under immune pressure.
This dataset
Open GSE328992 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 GSE328992_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 PRJNA1297797 and SRA study SRP604105. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
Lung tissues colleceted from hDPP4 mouse1 inf… ×3 Lung tissues colleceted from hDPP4 mouse2 inf… ×3 Lung tissues colleceted from hDPP4 mouse3 inf… ×3 Lung tissues colleceted from hDPP4 mouse1 inf… ×3 Lung tissues colleceted from hDPP4 mouse2 inf… ×3 Lung tissues colleceted from hDPP4 mouse3 inf… ×3 Lung tissues colleceted from hDPP4 mouse1 at … ×1 Lung tissues colleceted from hDPP4 mouse2 at … ×1 +1 more

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 21 sample titles; they account for 18 of them. 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.