GEO series

A high-fidelity CRISPR-Cas13 system improves abnormalities associated with C9ORF72-linked ALS/FTD

GSE250633 Mus musculus (mouse) RNA-seq (gene expression) 27 samples Submitted 2024/11/28 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 27 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: 27 samples: 6 conditions, mostly with about 6 replicates eachGroups 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: A high-fidelity CRISPR-Cas13 system improves abnormalities associated with C9ORF72-linked ALS/FTDNature communications · 2025

Summary (written by the submitters)

An abnormal expansion of a G4C2 hexanucleotide repeat in the C9ORF72 gene is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), two debilitating neurodegenerative disorders driven in part by gain-of-function mechanisms involving transcribed forms of the repeat expansion. By utilizing a Cas13 variant with reduced collateral effects, we developed a high-fidelity RNA-targeting CRISPR-based system for C9ORF72-linked ALS/FTD.

Read the full summary ↓

When delivered to the brain of a transgenic rodent model, this Cas13-based platform curbed the expression of the G4C2 repeat-containing RNA without affecting normal C9ORF72 levels, which in turn decreased the formation of RNA foci, reduced the production of a dipeptide repeat protein, and reversed transcriptional deficits. This high-fidelity system possessed improved transcriptome-wide specificity compared to its native form and mediated targeting in motor neuron-like cells derived from a patient with ALS. These results lay the foundation for the implementation of RNA-targeting CRISPR technologies for C9ORF72-linked ALS/FTD.

Published in

A high-fidelity CRISPR-Cas13 system improves abnormalities associated with C9ORF72-linked ALS/FTD

McCallister TX, Lim CKW, Singh M et al. · Nature communications 2025 · PMID 39779681 · doi:10.1038/s41467-024-55548-5

This dataset

Open GSE250633 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 GSE250633_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 PRJNA1054656 and SRA study SRP479008. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39779681) ↗

Study design

6 conditions, mostly with about 6 replicates each

Tg_NTG_RHMC ×6 Tg_S13_RHMC ×6 nTg_NTG_RHMC ×5 nTg_GFP_RHMC ×4 Tg_GFP_RHMC ×3 nTg_S13_RHMC ×3

Supports a between-group comparison across 27 samples.

How we read this: 6 replicated groups read from 27 sample titles; they account for 27 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

GSM7983298 Tg_GFP_RHMC_2 Tg_GFP_RHMC
GSM7983299 Tg_GFP_RHMC_3 Tg_GFP_RHMC
GSM7983300 Tg_GFP_RHMC_5 Tg_GFP_RHMC
GSM7983301 Tg_NTG_RHMC_1 Tg_NTG_RHMC
GSM7983302 Tg_NTG_RHMC_2 Tg_NTG_RHMC
GSM7983303 Tg_NTG_RHMC_3 Tg_NTG_RHMC
GSM7983304 Tg_NTG_RHMC_4 Tg_NTG_RHMC
GSM7983305 Tg_NTG_RHMC_5 Tg_NTG_RHMC
GSM7983306 Tg_NTG_RHMC_6 Tg_NTG_RHMC
GSM7983307 Tg_S13_RHMC_1 Tg_S13_RHMC
GSM7983308 Tg_S13_RHMC_2 Tg_S13_RHMC
GSM7983309 Tg_S13_RHMC_3 Tg_S13_RHMC
GSM7983310 Tg_S13_RHMC_4 Tg_S13_RHMC
GSM7983311 Tg_S13_RHMC_6 Tg_S13_RHMC
GSM7983312 Tg_S13_RHMC_7 Tg_S13_RHMC
GSM7983313 nTg_GFP_RHMC_2 nTg_GFP_RHMC
GSM7983314 nTg_GFP_RHMC_3 nTg_GFP_RHMC
GSM7983315 nTg_GFP_RHMC_4 nTg_GFP_RHMC
GSM7983316 nTg_GFP_RHMC_5 nTg_GFP_RHMC
GSM7983317 nTg_NTG_RHMC_1 nTg_NTG_RHMC
GSM7983318 nTg_NTG_RHMC_2 nTg_NTG_RHMC
GSM7983319 nTg_NTG_RHMC_3 nTg_NTG_RHMC
GSM7983320 nTg_NTG_RHMC_4 nTg_NTG_RHMC
GSM7983321 nTg_NTG_RHMC_5 nTg_NTG_RHMC
GSM7983322 nTg_S13_RHMC_1 nTg_S13_RHMC
GSM7983323 nTg_S13_RHMC_2 nTg_S13_RHMC
GSM7983324 nTg_S13_RHMC_5 nTg_S13_RHMC

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