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Transcriptome-wide high-throughput mapping of protein-RNA occupancy profiles using POP-seq

ABSTRACT: Interaction between proteins and RNA is critical for post-transcriptional regulatory processes. Existing high throughput methods based on crosslinking of the protein-RNA complexes and polyA pull down are reported to contribute to biases and are not readily amenable for identifying interaction sites on non polyA RNAs. We present Protein Occupancy Profile-Sequencing (POP-seq), a phase separation based method in three versions, one of which does not require crosslinking, thus providing unbiased protein occupancy profiles on whole cell transcriptome without the requirement of polyA pulldown. Our study demonstrates that ~68% of the total POP-seq peaks exhibited an overlap with publicly available protein-RNA interaction profiles of 97 RNA binding proteins (RBPs) in K562 cells. We show that POP-seq variants consistently capture protein-RNA interaction sites across a broad range of genes including on transcripts encoding for transcription factors (TFs), RNA-Binding Proteins (RBPs) and long non-coding RNAs (lncRNAs). POP-seq identified peaks exhibited a significant enrichment (p value < 2.2e-16) for GWAS SNPs, phenotypic, clinically relevant germline as well as somatic variants reported in cancer genomes, suggesting the prevalence of uncharacterized genomic variation in protein occupied sites on RNA. We demonstrate that the abundance of POP-seq peaks increases with an increase in expression of lncRNAs, suggesting that highly expressed lncRNA are likely to act as sponges for RBPs, contributing to the rewiring of protein-RNA interaction network in cancer cells. Overall, our data supports POP-seq as a robust and cost-effective method that could be applied to primary tissues for mapping global protein occupancies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE142460 | GEO | 2020/06/30

REPOSITORIES: GEO

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Project description:Protein-RNA interactions are integral components of nearly every aspect of biology including regulation of gene expression, assembly of cellular architectures, and pathogenesis of human diseases. However, studies in the past few decades have only uncovered a small fraction of the vast landscape of the protein-RNA interactome in any organism, and even less is known about the dynamics of protein-RNA interactions under changing developmental and environmental conditions. Here, we describe the gPAR-CLIP (global photoactivatable-ribonucleoside-enhanced crosslinking and immunopurification) approach for capturing regions of the transcriptome bound by RNA-binding proteins (RBPs) in budding yeast. We report over 13,000 RBP crosslinking sites in untranslated regions (UTR) covering 72% of protein-coding transcripts encoded in the genome, confirming 3M-bM-^@M-^Y UTRs as major sites for RBP interaction. Comparative genomic analyses reveal that RBP crosslinking sites are highly conserved, and RNA folding predictions indicate that secondary structural elements are constrained by protein binding and may serve as generalizable modes of RNA recognition. Finally, 38% of 3M-bM-^@M-^Y UTR crosslinking sites show changes in RBP occupancy upon glucose or nitrogen deprivation, with major impacts on metabolic pathways as well as mitochondrial and ribosomal gene expression. Our study offers an unprecedented view of the pervasiveness and dynamics of protein-RNA interactions in vivo. Duplicate gPAR-CLIP and mRNA-seq libraries were sequenced from yeast strains for each of three conditions: log-phase growth, growth after 2 hour glucose starvation, and growth after 2 hour nitrogen starvation. Additional duplicate mRNA-seq libraries were sequenced from yeast strains grown in the absence of 4-thiouracil. gPAR-CLIP libraries were used to determine regions of mRNA bound by proteins. mRNA-seq libraries served as controls for mRNA abundance. A Puf3p PAR-CLIP library was sequenced to determine how well gPAR-CLIP captured the binding signatures of a single RNA-binding protein.

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Transcriptome-wide high-throughput mapping of protein-RNA occupancy profiles using POP-seq

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