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Genome organization around nuclear speckles drives mRNA splicing efficiency

GSE247833 Homo sapiens (human) RNA-seq (gene expression) 26 samples Submitted 2024/03/22 Platform GPL20301Platform GPL21103Platform GPL30172Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 26 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
26 samples: 12 × Muscle SPRITE vs 12 × Human H1 DNA SPRITEGroups 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
Genome organization around nuclear speckles drives mRNA splicing efficiencyNature · 2024
Summary (written by the submitters)
The nucleus is highly organized such that factors involved in transcription and processing of distinct classes of RNA are organized within specific nuclear bodies. One example is the nuclear speckle, which is defined by high concentrations of protein and non-coding RNA regulators of pre-mRNA splicing. What functional role, if any, speckles might play in the process of mRNA splicing remains unknown.
Read the full summary ↓
Here we show that genes localized near nuclear speckles display higher spliceosome concentrations, increased spliceosome binding to their pre-mRNAs, and higher co-transcriptional splicing levels relative to genes that are located farther from nuclear speckles. We show that directed recruitment of a pre-mRNA to nuclear speckles is sufficient to increase mRNA splicing levels. Finally, we show that gene organization around nuclear speckles is highly dynamic with differential localization between cell types corresponding to differences in splicing efficiency. Together, our results integrate the longstanding observations of nuclear speckles with the biochemistry of mRNA splicing and demonstrate a critical role for dynamic 3D spatial organization of genomic DNA in driving spliceosome concentrations and controlling the efficiency of mRNA splicing.
Published in
Genome organization around nuclear speckles drives mRNA splicing efficiency
Bhat P, Chow A, Emert B et al. · Nature 2024 · PMID 38720076 · doi:10.1038/s41586-024-07429-6
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 GSE247833_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 PRJNA1040796 and SRA study SRP472090. Searching any of these in the dataset finder brings you back here.

Study design
12 × Muscle SPRITE vs 12 × Human H1 DNA SPRITE

Supports a between-group comparison across 24 samples.

How we read this: 2 replicated groups read from 26 sample titles; they account for 24 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
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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.