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Wnt and Nodal asymmetries stratify mouse laterality phenotypes in the absence of node flow

GSE285165 Mus musculus (mouse) RNA-seq (gene expression) 42 samples Submitted 2026/06/08 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 42 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
42 samples: 42 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)
Left-right symmetry breaking in mice is considered to occur via node leftward fluid flow. The molecular cascade within the node has been reconstructed at high resolution; however, its importance for organogenesis remains poorly understood. Here we show in mutants for the motile cilium component CCDC40 that 70% of mice develop normal situs at birth despite abrogation of node flow.
Read the full summary ↓
The discrete morphospace output, including situs inversus totalis and heterotaxy with left isomerism, supports an innovative model of symmetry-breaking, in which node flow only biases asymmetry orientation, while a distinct mechanism, potentially self-amplifying, generates it. Longitudinal, quantitative and paired transcriptomic analyses uncover the molecular signature of laterality clusters, highlighting WNT in addition to NODAL pathways. We identify asymmetry of cardiopulmonary progenitors, the disruption of which is associated with combined heart and lung defects in mutants. Functional pharmacological perturbation reinforces the importance of WNT, besides the node, in the establishment of asymmetry.
This dataset
Open GSE285165 in finder → Find more mouse 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 GSE285165_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 PRJNA1201582 and SRA study SRP553175. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
42 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 42 sample titles: 42 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

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.