Transcriptome wide high throughput mapping of protein-RNA interactions across human cell lines using POP-seq
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA816365 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18330923.fastq.gz | Fastqsanger.gz | |||
| SRR18330924.fastq.gz | Fastqsanger.gz | |||
| SRR18330925.fastq.gz | Fastqsanger.gz | |||
| SRR18330926.fastq.gz | Fastqsanger.gz | |||
| SRR18330927.fastq.gz | Fastqsanger.gz |
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Project description:Protein-RNA interactions are critical for post-transcriptional regulatory processes that govern RNA metabolism. Several existing high throughput methods based to detect these interactions are reported for the biases associated to the inherent crosslinking approaches. In this study, we used Protein Occupancy Profile-Sequencing (POP-seq), a phase separation based method that does not require crosslinking, to examine the regulatory protein RNA interactions in cancer cell lines: K562, HepG2, A549, MCF7, Jurkat, and HEK293. POP-seq provides unbiased protein occupancy profiles in a transcriptome wide manner due to its crosslinking free approach. Our study demonstrates that POP-seq can enrich the protein occupied sites with over 60,000 peaks identified across multiple cancer cell lines. In our initial analysis, we compared POP-seq identified interactions with two protocols in presence and absence of UV crosslinking in K562 and HepG2 cells and results showed >70% overlap between the two approaches at the gene level, indicating that POP-seq can efficiently map the unbiased protein occupied sites in transcriptome wide manner. Using downstream bioinformatics analysis we found majority of POP-seq peaks on the exonic region of the transcript followed by introns and 3’ UTRs, while less than 10% abundance was recorded for repetitive elements like SINEs and LINEs. Among the various gene types, we found abundance of POP-seq peaks on protein coding genes followed by non-coding RNAs, that are typically highly expressed in cancer cell lines. We used CRISPR Cas 9 system to evaluate the functionality of POP-seq sites and observed that identified interactions could potentially impact the expression of nearby exons. Overall, this study provides the first comprehensive resource of transcriptome wide protein-RNA interaction maps in multiple cell line using a crosslinking free approach that further opens the opportunity to implement the method in primary tissues for detecting the regulatory interactions.
2024-12-23 | GSE198655 | GEO
Project description: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.
2020-06-30 | GSE142460 | GEO
Project description:Transcriptome-wide high-throughput mapping of protein-RNA occupancy profiles using POP-seq
| PRJNA597062 | ENA
Project description: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 poly-A pull down are reported to contribute to biases and are not readily amenable for identifying interaction sites on non poly-A 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 poly-A 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.
| S-EPMC7806670 | biostudies-literature
Project description:Pelvic organ prolapse (POP) is a common multifactorial disease in a heterogeneous population of women. Due to this heterogeneity, the underlying molecular mechanisms contributing to the pathogenesis of POP are still unclear. We sought to identify dysregulated pathways by comparing gene expression profiles of prolapsed and non- prolapsed anterior vaginal wall tissue within the same patient. Biopsies were collected from 12 premenopausal women undergoing prolapse surgery (cystocele POP-Q stage ≥ 2). A full thickness anterior vaginal wall sample was taken from the POP site during anterior colporrhaphy. An additional sample was taken from the non-prolapsed apex of the anterior vaginal cuff. Micro-array analysis was performed using whole genome GE 4x44K microarrays. Beside a significance analysis of micro-array (SAM), also a visual cluster analysis was performed. 12 women with POP: 12 biopsies anterior vaginal wall (POP site) versus 12 biopies precervical anterior vaginal wall ( non POP site)
2015-07-31 | E-GEOD-53868 | biostudies-arrayexpress
Project description:Pelvic organ prolapse (POP) is a common multifactorial disease in a heterogeneous population of women. Due to this heterogeneity, the underlying molecular mechanisms contributing to the pathogenesis of POP are still unclear. We sought to identify dysregulated pathways by comparing gene expression profiles of prolapsed and non- prolapsed anterior vaginal wall tissue within the same patient. Biopsies were collected from 12 premenopausal women undergoing prolapse surgery (cystocele POP-Q stage ≥ 2). A full thickness anterior vaginal wall sample was taken from the POP site during anterior colporrhaphy. An additional sample was taken from the non-prolapsed apex of the anterior vaginal cuff. Micro-array analysis was performed using whole genome GE 4x44K microarrays. Beside a significance analysis of micro-array (SAM), also a visual cluster analysis was performed.
2015-07-31 | GSE53868 | GEO
Project description:In vivo protein-DNA interactions connect each transcription factor with its direct targets to form a gene network scaffold. To map these protein-DNA interactions comprehensively across entire mammalian genomes, we developed a large-scale chromatin immunoprecipitation assay (ChIPSeq) based on direct ultrahigh-throughput DNA sequencing. This sequence census method was then used to map in vivo binding of the neuron-restrictive silencer factor (NRSF; also known as REST, for repressor element–1 silencing transcription factor) to 1946 locations in the human genome. The data display sharp resolution of binding position [±50 base pairs (bp)], which facilitated our finding motifs and allowed us to identify noncanonical NRSF-binding motifs. These ChIPSeq data also have high sensitivity and specificity [ROC (receiver operator characteristic) area ≥ 0.96] and statistical confidence (P < 10−4), properties that were important for inferring new candidate interactions. These include key transcription factors in the gene network that regulates pancreatic islet cell development.
2008-10-24 | GSE13047 | GEO
Project description:In vivo protein-DNA interactions connect each transcription factor with its direct targets to form a gene network scaffold. To map these protein-DNA interactions comprehensively across entire mammalian genomes, we developed a large-scale chromatin immunoprecipitation assay (ChIPSeq) based on direct ultrahigh-throughput DNA sequencing. This sequence census method was then used to map in vivo binding of the neuron-restrictive silencer factor (NRSF; also known as REST, for repressor element–1 silencing transcription factor) to 1946 locations in the human genome. The data display sharp resolution of binding position [±50 base pairs (bp)], which facilitated our finding motifs and allowed us to identify noncanonical NRSF-binding motifs. These ChIPSeq data also have high sensitivity and specificity [ROC (receiver operator characteristic) area ≥ 0.96] and statistical confidence (P < 10−4), properties that were important for inferring new candidate interactions. These include key transcription factors in the gene network that regulates pancreatic islet cell development. Experiment Overall Design: Exam NRSF binding in Jurkat T cell line
2009-08-29 | E-GEOD-13047 | biostudies-arrayexpress
Project description:We describe a new method enabling the global-scale mapping of RNA-RNA duplexes cross-linked in vivo, ‘LIGation of interacting RNA followed by high-throughput Sequencing’ (LIGR-Seq). Applying this method in human cells reveals a remarkable landscape of new RNA-RNA interactions involving all major classes of ncRNA, and mRNA. LIGR-Seq data reveal unexpected interactions between small nucleolar (sno)RNAs and mRNAs, including interactions involving the orphan C/D box snoRNA, SNORD83B, that control steady-state levels of its target mRNAs. LIGR-Seq thus represents a powerful approach for illuminating the functions of the myriad of uncharacterized RNAs that act via base-pairing interactions.
2016-05-12 | GSE80167 | GEO
Project description:Exonuclease assisted mapping of protein-RNA interactions (ePRINT)
| PRJNA1108725 | ENA