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Highly multiplexed mRNA quantitation with CRISPR-Cas13

GSE289345 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/10/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
Homo sapiens (human)
Samples
18 samples
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)
RNA quantitation tools are often either high-throughput or cost-effective, but rarely are they both. Existing methods can profile the transcriptome at great expense or are limited to quantifying a handful of genes by labor constraints. A technique that permits more throughput at a reduced cost could enable multi-gene kinetic studies, gene regulatory network analysis, and combinatorial genetic screens.
Read the full summary ↓
Here, we introduce quantitative Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (qCARMEN): an RNA quantitation technique which leverages the programmable RNA-targeting capabilities of CRISPR-Cas13 to address this challenge by quantifying over 4,500 gene-sample pairs in a single experiment. Using qCARMEN, we studied the response profiles of interferon-stimulated genes (ISGs) during interferon (IFN) stimulation and flavivirus infection. Additionally, we observed isoform switching kinetics during epithelial-mesenchymal transition. qCARMEN is a simple and inexpensive technique that greatly enhances the scalability of RNA quantitation for novel applications with performance similar to gold-standard methods.
This dataset
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.

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 GSE289345_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1222449 and SRA study SRP563285. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 18 more — browse all 18 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.