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A genome-wide functional analysis of conserved intronic regions reveals essential roles for speckle-associated detained introns [RNAseq_candidates.RPE1]

GSE296306 Homo sapiens (human) RNA-seq (gene expression) 34 samples Submitted 2026/06/18 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 34 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
34 samples: 17 conditions, mostly in duplicateGroups 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)
Thousands of human introns harbour extended regions of high evolutionarily conservation that have not been previously characterized. A survey of these sequences reveals that they are associated with intron retention and enriched in genes that function in RNA processing, chromatin remodelling and neuronal biology. Using a dual CRISPR-Cas editing approach, we targeted 2,600 of these regions for deletion and observe that a subset of these perturbations affectaffects cell growth.
Read the full summary ↓
Many of these ‘fitness’ sequences affect intron retention and or expression levels of their host genes. Deletions in nuclear speckle-associated retained introns in the FNBP4 and DDX5 genes are further linked to downstream effects on cell growth-related genes and intron retention, respectively. The DDX5 deletion additionally results in the accumulation of R-loops overlapping first introns in speckle-proximal genes. Overall, the results highlight multifactetedmultifaceted, critical roles of highly conserved intronic sequences in the control of gene regulation, R-loop resolution and cell growth.
This dataset
Open GSE296306 in finder → Find more human 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 GSE296306_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 PRJNA1258898 and SRA study SRP583210. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
17 conditions, mostly in duplicate
RPE-1 intergenic control hgRNA 1, ×2 RPE-1 intergenic control hgRNA 2, ×2 RPE-1 DDX5 intronic deletion hgRNA 1, ×2 RPE-1 DDX5 intronic deletion hgRNA 2, ×2 RPE-1 DDX17 intronic deletion hgRNA 1, ×2 RPE-1 DDX17 intronic deletion hgRNA 2, ×2 RPE-1 FNBP4 intronic deletion hgRNA 1, ×2 RPE-1 FNBP4 intronic deletion hgRNA 2, ×2 +9 more

Supports a case/control comparison: 8 samples read as cases, 4 as controls.

How we read this: 17 replicated groups read from 34 sample titles; they account for 34 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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