GSE240521
GSE GEOAn in situ method for identification of transcriptome-wide protein-RNA interactions in cells [eCLIP-seq ]
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Summary
RNA-binding proteins (RBPs) play important roles in RNA metabolism including splicing, stability, localization, and translation. RBP-RNA interaction profiles are indicative of many diseases. Existing methods for mapping RBP-RNA interactions transcriptome-wide have notable limitations: immunoprecipitation (IP)-based technologies require large quantities of input materials, and RNA shearing during processing prevents identification of RNA isoforms. Meanwhile, profiling methods using RNA-modifying enzymes require ectopic expression of fusion proteins in cells of interest, potentially distorting interaction profiles. Here we report in situ STAMP, an RBP-RNA profiling method that overcomes the limitations of existing methods. In situ STAMP utilizes a chimeric fusion of the cytosine deaminase APOBEC1 and an IgG-targeting single-domain antibody (nanobody). We demonstrate that this fusion protein can be specifically targeted to proteins of interest including the RBPs RBFOX2 and TDP-43 when combined with primary antibodies targeting these proteins, enabling identification of their binding sites in un-engineered HEK293T cells. The canonical binding motifs of both RBFOX2 (UGCAUG) and TDP43 (UGUGUG) could be identified by de novo motif analysis from in situ STAMP data, demonstrating the methodâs high specificity. In situ STAMP preserves intact RNAs and is therefore compatible with direct cDNA PacBio long-read sequencing, enabling the method to distinguish between RNA isoforms. Importantly, in situ STAMP is compatible with multiple fixation methods including methanol and formaldehyde fixation, enabling its application to tissue samples collected in research or clinical settings. Thus, in situ STAMP enables the profiling of authentic RBP-RNA interactions using small quantities of primary cells or tissues, thereby bridging a critical gap in uncovering the roles of RBPs in RNA-related disease mechanisms in authentic biological contexts.
Overall Design
eCLIP-seq with RBFOX2 specific antibody in mouse whole brain samples
Analysis (9 steps)
View Data Processing- Data was processed using the eCLIP pipeline and available at: http://github.com/yeolab/eclip
- Unique Molecular Identifiers (UMIs) were extracted from raw sequencing reads with umi_tools extract
- Post-umi-extracted reads were trimmed for adapter sequences and barcode sequences (eCLIP samples) using cutadapt.
- Trimmed reads were mapped against RepBase with STAR to remove reads mapping to repetitive sequences (--outFilterMultimapNmax 30 --alignEndsType EndToEnd --outFilterMultimapScoreRange 1 --outSAMmode Full --outFilterType BySJout --outSAMtype BAM Unsorted --outFilterScoreMin 10 --outReadsUnmapped Fastx --outSAMattributes All)
- Remaining reads were mapped to the appropriate genome build (mm10) using STAR aligner (--outFilterMultimapNmax 1 --alignEndsType EndToEnd --outFilterMultimapScoreRange 1 --outSAMmode Full --outFilterType BySJout --outSAMtype BAM Unsorted --outFilterScoreMin 10 --outReadsUnmapped Fastx --outSAMattributes All)
- Uniquely mapped reads were removed of PCR duplicates with umi_tools
- Peak clusters were identified with CLIPper, available at: https://github.com/YeoLab/clipper
- Clusters enriched over corresponding size-matched input (SMInput) were identified using a custom Perl script, available in the main eCLIP repository as: overlap_peakfi_with_bam.pl
Supplementary Files (1)
GEO Samples (2)
SRA Experiments (2) and Runs (2)
Total: 2545 MBSample attributes
Original files (1)
Runs (1)
| Run | Spots | Bases | Size (MB) | Files | Link |
|---|---|---|---|---|---|
| SRR25594684 | 11242451 | 1124245100 | 513.28 | YS6_S2_L001_R1_001.fastq.gz, YS6_S2_L001_R2_001.fastq.gz, SRR25594684… | SRA |
Sample attributes
Original files (1)
Runs (1)
| Run | Spots | Bases | Size (MB) | Files | Link |
|---|---|---|---|---|---|
| SRR25594683 | 43661955 | 4366195500 | 2031.71 | YS4_S14_L002_R1_001.fastq.gz, YS4_S14_L002_R2_001.fastq.gz, SRR255946… | SRA |