GEO series

Single-cell atlas of the human brain vasculature across development, adulthood and disease (Extra Individuals)

GSE256491 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2024/02/29 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 16 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 16 samples: 2 × TL_patient9_EC vs 2 × TL_patient9_all cells vs 2 × TL_patient10_EC vs 2 × TL_patient10_all cellsGroups 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: Single-cell atlas of the human brain vasculature across development, adulthood and diseaseNature · 2024

Summary (written by the submitters)

A broad range of brain pathologies critically relies on the vasculature, and cerebrovascular disease is a leading cause of death worldwide. However, the cellular and molecular architecture of the human brain vasculature remains incompletely understood. Here, we performed single-cell RNA sequencing of 606,380 freshly isolated endothelial, perivascular and other tissue-derived cells from 117 samples, from 68 human fetuses and adult patients to construct a molecular atlas of the developing fetal, adult control and diseased human brain vasculature.

Read the full summary ↓

We uncover extensive molecular heterogeneity of the vasculature of healthy fetal and adult human brains and across eight vascular-dependent Central Nervous System (CNS) pathologies including brain tumors and brain vascular malformations. We identify alteration of arteriovenous differentiation and reactivated fetal as well as conserved dysregulated genes and pathways in the diseased vasculature. Pathological endothelial cells display a loss of CNS-specific properties and reveal an upregulation of MHC class II molecules, indicating atypical features of CNS endothelial cells. Cell-cell interaction analyses predict numerous endothelial-to-perivascular cell ligand-receptor crosstalk including immune-related and angiogenic pathways, thereby unraveling a central role for the endothelium within brain neurovascular unit signaling networks. Our single-cell brain atlas provides insight into the molecular architecture and heterogeneity of the developing, adult/control and diseased human brain vasculature and serves as a powerful reference for future studies

Published in

Single-cell atlas of the human brain vasculature across development, adulthood and disease

Wälchli T, Ghobrial M, Schwab M et al. · Nature 2024 · PMID 38987604 · doi:10.1038/s41586-024-07493-y

This dataset

Open GSE256491 in finder → Find more human 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 GSE256491_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 PRJNA1079775 and SRA study SRP491411. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38987604) ↗

Study design

2 × TL_patient9_EC vs 2 × TL_patient9_all cells vs 2 × TL_patient10_EC vs 2 × TL_patient10_all cells

Supports a between-group comparison across 8 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 8 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

GSM8101593 TL_patient9_EC_1 TL_patient9_EC
GSM8101594 TL_patient9_EC_2 TL_patient9_EC
GSM8101595 TL_patient9_all cells_1 TL_patient9_all cells
GSM8101596 TL_patient9_all cells_2 TL_patient9_all cells
GSM8101597 TL_patient7_EC
GSM8101598 TL_patient10_EC_1 TL_patient10_EC
GSM8101599 TL_patient10_EC_2 TL_patient10_EC
GSM8101600 TL_patient10_all cells_1 TL_patient10_all cells
GSM8101601 TL_patient10_all cells_2 TL_patient10_all cells
GSM8101602 LGG_patient6_EC
GSM8101603 LGG_patient5_EC
GSM8101604 GBM_patient6_EC
GSM8101605 GBM_patient7_EC
GSM8101606 FETAL_brain_8_all cells
GSM8101607 FETAL_brain_6_all cells
GSM8101608 GBM_patient8_EC

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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.