Dataset Information

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 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?

SUBMITTER: Srivastava M

PROVIDER: S-EPMC7806670 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Srivastava Mansi M Srivastava Rajneesh R Janga Sarath Chandra SC

Scientific reports 20210113 1

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 p ...[more]

PMID: 33441968

Similar Datasets

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.

Project description:Long non-coding RNA (lncRNA) mediated transcriptional regulation is increasingly recognized as an important gene regulatory mechanism during development and disease. LncRNAs are emerging as critical regulators of chromatin state; yet the nature and the extent of their interactions with chromatin remain to be fully revealed. We have previously identified Ppp1r1b-lncRNA as an essential epigenetic regulator of myogenic differentiation in cardiac and skeletal myocytes in mice and humans. We further demonstrated that Ppp1r1b-lncRNA function is mediated by the interaction with the chromatin-modifying complex polycomb repressive complex 2 (PRC2) at the promoter of myogenic differentiation transcription factors, TBX5 and MyoD1. Herein, we employed an unbiased chromatin isolation by RNA purification (ChIRP) and high throughput sequencing to map the repertoire of Ppp1r1b-lncRNA chromatin occupancy genome-wide in the mouse muscle myoblast cell line. We uncovered a total of 99732 true peaks corresponding to Ppp1r1b-lncRNA binding sites at high confidence (P-value < 1e-5 and enrichment score ≥ 10). The Ppp1r1b-lncRNA-binding sites averaged 558 bp in length and were distributed widely within the coding and non-coding regions of the genome. Approximately 46% of these true peaks were mapped to gene elements, of which 1180 were mapped to experimentally validated promoter sequences. Importantly, the promoter-mapped binding sites were enriched in myogenic transcription factors and heart development while exhibiting focal interactions with known motifs of proximal promoters and transcription initiation by RNA polII, including TATA, transcription initiator, CCAAT-box, and GC-box, supporting Ppp1r1b-lncRNA role in transcription initiation of myogenic regulators. Remarkably, nearly 40% of Ppp1r1b-lncRNA-binding sites mapped to gene introns, were enriched with the Homeobox family of transcription factors, and exhibited TA-rich motif sequences, suggesting potential motif specific Ppp1r1b-lncRNA-bound introns. Lastly, more than 136521enhancer sequences were detected in Ppp1r1b-lncRNA-occupancy sites at high confidence. Among these enhancers,12% exhibited cell type/tissue-specific enrichment in fetal heart and muscles. Together, our findings provide further insights into the genome-wide Ppp1r1b-lncRNA: Chromatin interactome that may potentially dictate its function in myogenic differentiation and potentially other cellular and biological processes.

Project description:To persist in their dynamic human host environments, fungal pathogens must sense and adapt by modulating their gene expression to fulfill their cellular needs. Understanding transcriptional regulation on a global scale would uncover cellular processes linked to persistence and virulence mechanisms that could be targeted for antifungal therapeutics. Infections associated with the yeast Candida albicans, a highly prevalent fungal pathogen, and the multiresistant related species Candida auris are becoming a serious public health threat. To define the set of a gene regulated by a transcriptional regulator in C. albicans, chromatin immunoprecipitation (ChIP)-based techniques, including ChIP with microarray technology (ChIP-chip) or ChIP-DNA sequencing (ChIP-seq), have been widely used. Here, we describe a new set of PCR-based micrococcal nuclease (MNase)-tagging plasmids for C. albicans and other Candida spp. to determine the genome-wide location of any transcriptional regulator of interest using chromatin endogenous cleavage (ChEC) coupled to high-throughput sequencing (ChEC-seq). The ChEC procedure does not require protein-DNA cross-linking or sonication, thus avoiding artifacts related to epitope masking or the hyper-ChIPable euchromatic phenomenon. In a proof-of-concept application of ChEC-seq, we provided a high-resolution binding map of the SWI/SNF chromatin remodeling complex, a master regulator of fungal fitness in C. albicans, in addition to the transcription factor Nsi1 that is an ortholog of the DNA-binding protein Reb1 for which genome-wide occupancy was previously established in Saccharomyces cerevisiae The ChEC-seq procedure described here will allow a high-resolution genomic location definition which will enable a better understanding of transcriptional regulatory circuits that govern fungal fitness and drug resistance in these medically important fungi.IMPORTANCE Systemic fungal infections caused by Candida albicans and the "superbug" Candida auris are becoming a serious public health threat. The ability of these yeasts to cause disease is linked to their faculty to modulate the expression of genes that mediate their escape from the immune surveillance and their persistence in the different unfavorable niches within the host. Comprehensive knowledge on gene expression control of fungal fitness is consequently an interesting framework for the identification of essential infection processes that could be hindered by chemicals as potential therapeutics. Here, we expanded the use of ChEC-seq, a technique that was initially developed in the yeast model Saccharomyces cerevisiae to identify genes that are modulated by a transcriptional regulator, in pathogenic yeasts from the genus Candida This robust technique will allow a better characterization of key gene expression regulators and their contribution to virulence and antifungal resistance in these pathogenic yeasts.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets