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Tissue factor binds to and inhibits interferon-α receptor-1 signaling

GSE241209 Mus musculus (mouse) RNA-seq (gene expression) 21 samples Submitted 2024/12/31 Platform GPL24676Platform 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: 7 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)
Tissue factor (TF), which is a member of the cytokine receptor family, promotes coagulation and coagulation-dependent inflammation. TF also exerts protective effects through unknown mechanisms. Here, we showed that TF binds to interferon-α receptor 1 (IFNAR1) and antagonizes its signaling, preventing spontaneous sterile inflammation and maintaining immune homeostasis.
Read the full summary ↓
Structural modeling and direct binding studies revealed binding of the TF C-terminal fibronectin III domain to IFNAR1, which restricted the expression of interferon-stimulated genes (ISGs). Podocyte-specific loss of TF in mice (TFΔPOD) resulted in sterile renal inflammation, which was characterized by JAK/STAT signaling, proinflammatory cytokine expression, disrupted immune homeostasis, and glomerulopathy. Inhibiting IFNAR1 signaling or the loss of IFNAR1 expression in podocytes attenuated or prevented these effects in TFΔPOD mice, respectively. Intriguingly, in the heteromer, TF and IFNAR1 are both inactive, while dissociation of the TF-IFNAR1 heteromer promotes TF activity and IFNAR1 signaling. These data suggest that the TF-IFNAR1 heteromer is a new molecular switch that controls thrombo-inflammation.
This dataset
Open GSE241209 in finder → Find more 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 GSE241209_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 PRJNA1006729 and SRA study SRP455855. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 conditions, mostly in triplicate
mouse primary podocytes from TFLoxP mice ×3 mouse primary podocytes from TFΔPOD mice ×3 Human podocytes wild type ×3 Human podocytes TF knockout ×3 Human podocytes TF knockout and IFNAR1 Knocko… ×3 TFLoxP mice kidney ×3 TFΔPOD mice kidney ×3

Supports a case/control comparison: 6 samples read as cases, 3 as controls.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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
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