← BioTransfer GEO Dataset Finder
GEO series

Early human fetal lung atlas reveals the temporal dynamics of epithelial cell plasticity [scRNAseq-fetal tissue]

GSE264407 Homo sapiens (human) Single-cell RNA-seq 20 samples Submitted 2024/06/04 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 20 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
20 samples: 6 conditions, mostly in duplicateGroups 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
Early human fetal lung atlas reveals the temporal dynamics of epithelial cell plasticityNature communications · 2024
Summary (written by the submitters)
While animal models have provided key insights into conserved mechanisms of how the lung forms during development, human-specific developmental mechanisms are not always captured. To fully appreciate how developmental defects and disease states alter the function of the lungs, studies in human lung models are important. Here, we sequenced >150,000 single single-cells from 19 healthy human fetal lung tissues from gestational weeks 10-19 and identified at least 58 unique cell types/states contributing to the developing lung.
Read the full summary ↓
We captured novel dynamic developmental trajectories from various progenitor cells that give rise to ciliated, pulmonary neuroendocrine cells, and other specialized cell types. We also identified four CFTR-expressing progenitor cell types and pinpointed the temporal emergence and spatial localization of these cell types. These developmental dynamics reveal broader epithelial cell plasticity and novel lineage hierarchies that were not previously reported. Combined with spatial transcriptomics, we identified both cell autonomous and non-cell autonomous signalling pathways that may dictate the temporal and spatial emergence of cell lineages. Finally, we showed that human pluripotent stem cell (hPSC)-derived fetal lung models capture similar cell lineage trajectories specifically through progenitor cells that express abundant levels of the CFTR gene. Overall, this study provides a comprehensive single-cell atlas of the developing human lung, outlining the temporal and spatial complexities of cell lineage development and benchmarks fetal lung cultures from hPSC differentiations to similar developmental window.
Published in
Early human fetal lung atlas reveals the temporal dynamics of epithelial cell plasticity
Quach H, Farrell S, Wu MJM et al. · Nature communications 2024 · PMID 39003323 · doi:10.1038/s41467-024-50281-5
This dataset
Open GSE264407 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 GSE264407_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 PRJNA1102355 and SRA study SRP502901. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39003323) ↗
Study design
6 conditions, mostly in duplicate
Fetal lung tissue derived from GW 16 ×3 Fetal lung tissue derived from GW 19 ×3 Fetal lung tissue derived from GW 10 ×2 Fetal lung tissue derived from GW 13 ×2 Fetal lung tissue derived from GW 15.5 sample ×2 Fetal lung tissue derived from GW 18 ×2 Fetal lung tissue derived from GW 11 ×1 Fetal lung tissue derived from GW 12 ×1 +4 more

Supports a between-group comparison across 14 samples.

How we read this: 6 replicated groups read from 20 sample titles; they account for 14 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

Search all human RNA-seq datasets in GEO →

Share this dataset

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.