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Structural perturbation of chromatin domains with multiple developmental regulators can severely impact gene regulation and development [RNA-seq-blastocyst]

GSE274230 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2024/08/07 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 4 × E4.5_C7-C10_WT_SC vs 4 × E4.5_C7-C10_HOM_SC vs 4 × E4.5_C5-C6_HOM_SC vs 4 × E4.5_C5-C6_WT_SCGroups 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
Structural perturbation of chromatin domains with multiple developmental regulators can severely impact gene regulation and developmentbioRxiv : the preprint server for biology · 2024
Summary (written by the submitters)
Chromatin domain boundaries delimited by CTCF motifs can restrict the range of enhancer action. However, disruption of domain structure often results in mild gene dysregulation and thus predicting the impact of boundary rearrangements on animal development remains challenging. Here, we tested whether structural perturbation of a chromatin domain with multiple developmental regulators can result in more acute gene dysregulation and severe developmental phenotypes.
Read the full summary ↓
We targeted clusters of CTCF motifs in a domain of the mouse genome containing three FGF ligand genes¬—Fgf3, Fgf4, and Fgf15—that regulate several developmental processes¬. Deletion of the 23.9kb cluster that defines the centromeric boundary of this domain¬ resulted in ectopic interactions of the FGF genes with enhancers located across the deleted boundary that are active in the developing brain. This caused strong induction of FGF expression and perinatal lethality with encephalocele and orofacial cleft phenotypes. Heterozygous boundary deletion was sufficient to cause these fully penetrant phenotypes, and strikingly, loss of a single CTCF motif within the cluster also recapitulated ectopic FGF expression and caused encephalocele. However, such phenotypic sensitivity to perturbation of domain structure did not extend to all CTCF clusters of this domain, nor to all developmental processes controlled by these three FGF genes¬—for example, the ability to undergo lineage specification in the blastocyst and pre-implantation development were not affected. By tracing the impact of different chromosomal rearrangements throughout mouse development, our work starts to uncover the determinants of phenotypic robustness and sensitivity to perturbation of chromatin boundaries. Our data show how small sequence variants at certain domain boundaries can have a surprisingly outsized effect and must be considered as potential sources of gene dysregulation during development and disease.
Published in
Structural perturbation of chromatin domains with multiple developmental regulators can severely impact gene regulation and development
Chakraborty S, Wenzlitschke N, Anderson MJ et al. · bioRxiv : the preprint server for biology 2024 · PMID 39372737 · doi:10.1101/2024.08.03.606480
This dataset
Open GSE274230 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 GSE274230_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 PRJNA1145435 and SRA study SRP524824. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39372737) ↗
Study design
4 × E4.5_C7-C10_WT_SC vs 4 × E4.5_C7-C10_HOM_SC vs 4 × E4.5_C5-C6_HOM_SC vs 4 × E4.5_C5-C6_WT_SC

Supports a between-group comparison across 16 samples.

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

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