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In vivo base editing partially rescues bone dysplasia in a mouse model of Hutchinson-Gilford Progeria Syndrome

GSE334271 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2026/06/10 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 36 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
36 samples: 36 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)
Hutchinson-Gilford Progeria Syndrome (HGPS) is a premature aging disorder affecting tissues of mesenchymal origin. Most patients harbor a c.1824C>T/p.G608= variant, commonly described as G608G, in exon 11 of LMNA that leads to aberrant splicing and production of the toxic progerin protein. In addition to cardiovascular, dermal, and adipose tissue deterioration, HGPS mouse models also develop progressive bone dysplasia that occurs in patients.
Read the full summary ↓
Here we characterize the efficacy of in vivo mutation correction with an adenine base editor (ABE) to rescue structural and functional defects in HGPS transgenic murine bone tissue. Treatment of double-copy transgenic osteoblast cultures with a lentiviral-delivered CRISPR-Cas9 ABE achieved nearly 40% gene correction in vitro, resulting in significant reduction of progerin transcripts and protein, in the absence of selective agents. Furthermore, gene correction improved progeroid osteoblasts’ capacity to deposit and mineralize extracellular matrix compared to untreated cultures. In vivo, a single intravenous dose of AAV9-delivered ABE corrected the mutation, achieving ~14%, ~22%, ~10% and <1% correction in bone by six months of age when administered at P3, P14, 1 and 4 months of age, respectively. Partially rescued bone structural and physical parameters were observed in P14-treated mice with concomitant normalization of gene transcriptional programs and intracellular signaling pathways involved in bone remodeling. This work demonstrates in vivo delivery of a locus-specific DNA base editor to bone tissue, delineates the timing of treatment required for maximum efficacy, and suggests that this system might be tailored for application to other monogenic bone disorders.
This dataset
Open GSE334271 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 GSE334271_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 PRJNA1474460 and SRA study SRP706563. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
36 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 36 sample titles: 36 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
Datasets on a similar topic

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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.