GEO series

Mapping the Dialogue: Decoding Alveolar Stem-Niche Interactions [I]

GSE307112 Mus musculus (mouse) RNA-seq (gene expression) 886 samples Submitted 2026/06/29 Platform GPL35012

At a glance

RNA-seq (gene expression) · mouse · 886 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: 886 samples: 886 samples, each with a distinct title — no replicated groupsGroups 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)

Cellular atlases reveal diverse cellular phenotypes, but how cells traverse this phenotypic landscape to impact tissues requires systematic study. We present an alveolosphere screening platform for investigating interactions between lung epithelial stem cells and their fibroblast niche. We assessed the role of 201 candidate genes in stem cells via imaging, then used RNAseq analysis for a transcriptome-wide understanding of cell-autonomous effects on stem cells and non-cell-autonomous effects on the niche.

Read the full summary ↓

This phenome-transcriptome map uncovered new cellular states and pathways regulating stem cell growth, metabolism, and immune signaling. Notably, stem cells influenced scar-forming and immune programs in fibroblasts. This injury response was dependent on stem cell identity; loss of Nkx2.1, the transcription factor conferring lung epithelial identity, disrupted stem cell-niche interactions and had a greater non-cell-autonomous effect than eliminating the cancer genes Trp53, Egfr, or Cdkn2b. Our study highlights how functional atlases complement the cellular diversity revealed by descriptive methods.

This dataset

Open GSE307112 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 GSE307112_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 PRJNA1314575 and SRA study SRP616810. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

886 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from the first 400 of 886 sample titles: 400 distinct titles with little repetition. 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

GSM9215859 lung alveolar organoid, Met knockout, plate1-1 well B02
GSM9215860 lung alveolar organoid, Glis3 knockout, plate1-1 well B03
GSM9215861 lung alveolar organoid, Tigit knockout, plate1-1 well B04
GSM9215862 lung alveolar organoid, Tdtomato knockout, plate1-1 well B05
GSM9215863 lung alveolar organoid, Trp53 knockout, plate1-1 well B06
GSM9215864 lung alveolar organoid, Acp6 knockout, plate1-1 well B07
GSM9215865 lung alveolar organoid, Pink1 knockout, plate1-1 well B08
GSM9215866 lung alveolar organoid, Eif2ak3 knockout, plate1-1 well B09
GSM9215867 lung alveolar organoid, Ccbe1 knockout, plate1-1 well B10
GSM9215868 lung alveolar organoid, Gdf2 knockout, plate1-1 well B11
GSM9215869 lung alveolar organoid, Tead1 knockout, plate1-1 well C02
GSM9215870 lung alveolar organoid, Mecom knockout, plate1-1 well C03
GSM9215871 lung alveolar organoid, Huwe1 knockout, plate1-1 well C04
GSM9215872 lung alveolar organoid, Sftpd knockout, plate1-1 well C05
GSM9215873 lung alveolar organoid, Trp63 knockout, plate1-1 well C06
GSM9215874 lung alveolar organoid, Il1a knockout, plate1-1 well C07
GSM9215875 lung alveolar organoid, Prkn knockout, plate1-1 well C08
GSM9215876 lung alveolar organoid, Tigit knockout, plate1-1 well C09
GSM9215877 lung alveolar organoid, Bmp10 knockout, plate1-1 well C10
GSM9215878 lung alveolar organoid, Pla2g15 knockout, plate1-1 well C11
GSM9215879 lung alveolar organoid, Ror1 knockout, plate1-1 well D02
GSM9215880 lung alveolar organoid, Npnt knockout, plate1-1 well D03
GSM9215881 lung alveolar organoid, Rnf43 knockout, plate1-1 well D04
GSM9215882 lung alveolar organoid, Tns1 knockout, plate1-1 well D05
GSM9215883 lung alveolar organoid, Ttf1 knockout, plate1-1 well D06
GSM9215884 lung alveolar organoid, Tigit knockout, plate1-1 well D07
GSM9215885 lung alveolar organoid, Keap1 knockout, plate1-1 well D08
GSM9215886 lung alveolar organoid, Tfeb knockout, plate1-1 well D09
GSM9215887 lung alveolar organoid, Fgf7 knockout, plate1-1 well D10
GSM9215888 lung alveolar organoid, Il1a knockout, plate1-1 well D11
GSM9215889 lung alveolar organoid, Tfcp2l1 knockout, plate1-1 well E02
GSM9215890 lung alveolar organoid, Tigit knockout, plate1-1 well E03
GSM9215891 lung alveolar organoid, Sox4 knockout, plate1-1 well E04
GSM9215892 lung alveolar organoid, Twist1 knockout, plate1-1 well E05
GSM9215893 lung alveolar organoid, Nkx21 knockout, plate1-1 well E06
GSM9215894 lung alveolar organoid, Usp30 knockout, plate1-1 well E07
GSM9215895 lung alveolar organoid, Nfe2l2 knockout, plate1-1 well E08
GSM9215896 lung alveolar organoid, Ulk1 knockout, plate1-1 well E09
GSM9215897 lung alveolar organoid, Inhba knockout, plate1-1 well E10
GSM9215898 lung alveolar organoid, Manf knockout, plate1-1 well E11

+ 846 more — browse all 886 samples with per-sample file links →

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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.