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 interact...

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Autores principales:	Mansi Srivastava, Rajneesh Srivastava, Sarath Chandra Janga
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e005abf55b5f4c2183e62b75a48df238
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spelling	oai:doaj.org-article:e005abf55b5f4c2183e62b75a48df2382021-12-02T14:12:07ZTranscriptome-wide high-throughput mapping of protein–RNA occupancy profiles using POP-seq10.1038/s41598-020-80846-52045-2322https://doaj.org/article/e005abf55b5f4c2183e62b75a48df2382021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-80846-5https://doaj.org/toc/2045-2322Abstract 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.Mansi SrivastavaRajneesh SrivastavaSarath Chandra JangaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Mansi Srivastava Rajneesh Srivastava Sarath Chandra Janga Transcriptome-wide high-throughput mapping of protein–RNA occupancy profiles using POP-seq
description	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 < 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.
format	article
author	Mansi Srivastava Rajneesh Srivastava Sarath Chandra Janga
author_facet	Mansi Srivastava Rajneesh Srivastava Sarath Chandra Janga
author_sort	Mansi Srivastava
title	Transcriptome-wide high-throughput mapping of protein–RNA occupancy profiles using POP-seq
title_short	Transcriptome-wide high-throughput mapping of protein–RNA occupancy profiles using POP-seq
title_full	Transcriptome-wide high-throughput mapping of protein–RNA occupancy profiles using POP-seq
title_fullStr	Transcriptome-wide high-throughput mapping of protein–RNA occupancy profiles using POP-seq
title_full_unstemmed	Transcriptome-wide high-throughput mapping of protein–RNA occupancy profiles using POP-seq
title_sort	transcriptome-wide high-throughput mapping of protein–rna occupancy profiles using pop-seq
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/e005abf55b5f4c2183e62b75a48df238
work_keys_str_mv	AT mansisrivastava transcriptomewidehighthroughputmappingofproteinrnaoccupancyprofilesusingpopseq AT rajneeshsrivastava transcriptomewidehighthroughputmappingofproteinrnaoccupancyprofilesusingpopseq AT sarathchandrajanga transcriptomewidehighthroughputmappingofproteinrnaoccupancyprofilesusingpopseq
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Transcriptome-wide high-throughput mapping of protein–RNA occupancy profiles using POP-seq

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