Transcriptome-wide mapping of RNA:protein interactions of PRPF8 and SNRNP200 (BRR2) with retinitis pigmentosa (RP) mutations by iCLIP
Single-nucleus RNA-seq · human · 27 samples
- What it is
- Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 27 samples: 27 samples, each with a distinct title — no replicated groupsGroups 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
- Retinitis pigmentosa-linked mutations impair the snRNA unwinding activity of SNRNP200 and reduce pre-mRNA binding of PRPF8Cellular and molecular life sciences : CMLS · 2025
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE213806_RAW.tar (it can run to tens of gigabytes).
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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA882472 and SRA study SRP398282. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 27 sample titles: 27 distinct titles with little repetition. 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.
- GSM6594616 iCLIP_PRPF8_HeLa_WT_noUV_CCGG_Rep1
- GSM6594617 iCLIP_PRPF8_HeLa_WT_GGTT_Rep1
- GSM6594618 iCLIP_PRPF8_HeLa_WT_TTGT_Rep2
- GSM6594619 iCLIP_PRPF8_HeLa_WT_TGGC_Rep3
- GSM6594620 iCLIP_PRPF8_HeLa_F2314L_noUV_CCAC_Rep1
- GSM6594621 iCLIP_PRPF8_HeLa_F2314L_GGTC_Rep1
- GSM6594622 iCLIP_PRPF8_HeLa_F2314L_GGCA_Rep2
- GSM6594623 iCLIP_PRPF8_HeLa_Y2334N_noUV_CCGG_Rep1
- GSM6594624 iCLIP_PRPF8_HeLa_Y2334N_GGTT_Rep1
- GSM6594625 iCLIP_PRPF8_HeLa_Y2334N_TTGT_Rep2
- GSM6594626 iCLIP_PRPF8_HeLa_Y2334N_TGGC_Rep3
- GSM6594627 iCLIP_BRR2_HeLa_WT_noUV_CCGG_Rep1
- GSM6594628 iCLIP_BRR2_HeLa_WT_GGTT_Rep1
- GSM6594629 iCLIP_BRR2_HeLa_WT_TTGT_Rep2
- GSM6594630 iCLIP_BRR2_HeLa_WT_TGGC_Rep3
- GSM6594631 iCLIP_BRR2_HeLa_S1087L_noUV_CCGG_Rep1
- GSM6594632 iCLIP_BRR2_HeLa_S1087L_GGTT_Rep1
- GSM6594633 iCLIP_BRR2_HeLa_S1087L_TTGT_Rep2
- GSM6594634 iCLIP_BRR2_HeLa_S1087L_TGGC_Rep3
- GSM6594635 iCLIP_BRR2_HeLa_R1090L_GGTT_Rep1
- GSM6594636 iCLIP_BRR2_HeLa_R1090L_TTGT_Rep2
- GSM6594637 iCLIP_BRR2_HeLa_R1090L_TGGC_Rep3
- GSM6594638 iCLIP_PRPF8_RPE_WT_noUV_CCGG_Rep1
- GSM6594639 iCLIP_PRPF8_RPE_WT_CGGA_Rep1
- GSM6594640 iCLIP_PRPF8_RPE_WT_TATT_Rep2
- GSM6594641 iCLIP_PRPF8_RPE_Y2334N_CGGA_Rep1
- GSM6594642 iCLIP_PRPF8_RPE_Y2334N_TATT_Rep2
- GSE213805 RNA-seq of RPE cells that harbor a C-terminal GFP-tag on the splicing factor PRPF8 and the retinitis pigmentosa mutation Y2334N 4 samples shares prpf8, pigmentosa, retinitis
- GSE248461 An in situ method for identification of transcriptome-wide protein-RNA interactions in cells [in_situ_STAMP II] 14 samples shares transcriptome-wide, interactions
- GSE73941 Transcriptome-wide mapping reveals reversible and dynamic N1-methyladenosine methylome 24 samples shares transcriptome-wide
- GSE248476 Transcriptome-wide profiles and ac4c modification profile in RA FLS with NAT10 knockdown 18 samples shares transcriptome-wide
- GSE264667 Transcriptome-wide characterization of genetic perturbations 224 samples shares transcriptome-wide
- GSE261913 Disulfide Tethering to Map Small Molecule Binding Sites Transcriptome-Wide 134 samples shares transcriptome-wide
- GSE77634 Enhanced CLIP (eCLIP) enables robust and scalable transcriptome-wide discovery and characterization of RNA binding protein binding sites 100 samples shares transcriptome-wide
- GSE301521 FOCAS: Transcriptome-wide screening of individual m6A sites functionally dissects epitranscriptomic control of gene expression in cancer [FOCAS_4cellline_RNAseq] 72 samples shares transcriptome-wide
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.