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Transcriptional Responses of in vitro Blood-Brain Barrier Models to Shear Stress

GSE277559 Rattus norvegicus (rat) RNA-seq (gene expression) 26 samples Submitted 2025/03/05 Platform GPL25947Platform GPL24676
At a glance

RNA-seq (gene expression) · rat · 26 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
Rattus norvegicus (rat)
Samples
26 samples: 8 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.
Paper
Transcriptional Responses of In Vitro Blood-Brain Barrier Models to Shear StressBiomolecules · 2025
Summary (written by the submitters)
Endothelial cells throughout the body sense blood flow, eliciting transcriptional and phenotypic responses. Brain endothelium, known as the blood-brain barrier (BBB), possesses unique barrier and transport properties which are in part regulated by blood flow. We utilized next generation sequencing to analyze the transcriptome of primary cultured rat brain microvascular endothelial cells (BMECs) as well as three human induced pluripotent stem cell-derived models.
Read the full summary ↓
We compared the transcriptional responses of these cells to either low (~0.5 dyne/cm2) or high (12 dyne/cm2) shear stresses, and subsequent analysis identified genes and pathways that were influenced by shear including key BBB-associated genes (SLC2A1, LSR, PLVAP) and canonical endothelial shear stress response transcription factors (KLF2, KLF4). In addition, our analysis suggests that shear alone is insufficient to rescue de-differentiation caused by in vitro primary BMEC culture. Overall, these datasets and analyses provide new insights into the role of shear on BBB models that will aid in model selection and guide further model development.
Published in
Transcriptional Responses of In Vitro Blood-Brain Barrier Models to Shear Stress
Foreman KL, Gastfriend BD, Katt ME et al. · Biomolecules 2025 · PMID 40001496 · doi:10.3390/biom15020193
This dataset
Open GSE277559 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 GSE277559_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 PRJNA1162799 and SRA study SRP533599. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40001496) ↗
Study design
8 conditions, mostly in triplicate
rat BMEC, high shear, ×4 rat BMEC, low shear, ×4 iPSC-"BMEC-like", high shear, ×3 iPSC-"BMEC-like", low shear, ×3 iPSC-EC, high shear, ×3 iPSC-EC, low shear, ×3 iPSC-EC + Wnt, high shear, ×3 iPSC-EC + Wnt, low shear, ×3

Supports a between-group comparison across 26 samples.

How we read this: 8 replicated groups read from 26 sample titles; they account for 26 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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