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The long noncoding RNA C1QTNF1-AS1 interacts with RSRC2 to ensure mitotic fidelity

GSE284007 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/03/13 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 6 conditions, mostly with about 4 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
RSRC2 is a novel RNA-binding protein that safeguards mitotic fidelity by interacting with the lncRNA C1QTNF1-AS1Nucleic acids research · 2026
Summary (written by the submitters)
Chromosome congression, a process of chromosome alignment at the spindle equator, is a key step in cell division. While much work has addressed the role of protein networks in controlling cell division, we have very little understanding how long noncoding RNAs (lncRNAs) and RNA binding proteins (RBPs) contribute to the fidelity of cell division.
Read the full summary ↓
To investigate the role of lncRNA C1QTNF1-AS1 and its interacting protein partner RSRC2 in cell division, we depleted C1QTNF1-AS1 and RSRC2 with LNA gapmers and siRNAs, respectively, in HCT116 cells and analysed their impact on gene expression and splicing alterations.
Published in
RSRC2 is a novel RNA-binding protein that safeguards mitotic fidelity by interacting with the lncRNA C1QTNF1-AS1
Babaei P, Coomer AO, Georgieva K et al. · Nucleic acids research 2026 · PMID 41841495 · doi:10.1093/nar/gkag229
This dataset
Open GSE284007 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 GSE284007_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 PRJNA1196826 and SRA study SRP550750. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41841495) ↗
Study design
6 conditions, mostly with about 4 replicates each
HCT116,C1QTNF1-AS1,LNA1,biol ×4 HCT116,C1QTNF1-AS1,LNA4,biol ×4 HCT116,C1QTNF1-AS1,LNA5,biol ×4 HCT116,C1QTNF1-AS1,LNAA,biol ×4 HCT116,Ctlsi,biol ×4 HCT116,RSRC2si,biol ×4

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 24 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
Datasets on a similar topic

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