Unknown,Transcriptomics,Genomics,Proteomics

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Transcriptome-wide ribonuclease footprinting to identify RNA-protein interaction sites

ABSTRACT: RNA-binding proteins (RBPs) are intimately involved in all aspects of RNA processing and regulation and are linked to neurodegenerative diseases and cancer. Therefore, understanding the relationship between RBPs and their RNA targets is critical for a broader understanding of post-transcriptional regulation in normal and disease processes. The majority of approaches to study RNA-protein interactions focus on single RBPs, however there are many hundreds RBPs encoded in the human genome, and each cell type expresses a different catalog of these regulatory molecules, greatly limiting the ability of these single RBP approaches to capture the global landscape of RNA-protein interactions. We and others have developed approaches to globally catalog regions of mRNAs that are bound by proteins in an unbiased manner. Here we describe a detailed protocol for performing our RNase-mediated protein footprint sequencing approach, termed protein interaction profile sequencing (PIP-seq). In this protocol, RNA-protein interactions are stabilized by cross-linking, and un-bound regions are digested with RNases, leaving only the protein-bound regions intact. To control for RNase insensitive regions, proteins are first denatured and then RNP complexes are subject to RNase treatment. After high-throughput sequencing of remaining fragments, peak calling is performed to identify protein protected sites (PPSs). We describe the application of this protocol to a human embryonic kidney cell line and perform basic quality control, reproducibility and benchmarking analyses. Finally, we describe the landscape of protein-interactions in HEK293T cells, underscoring the value of this approach. Future applications of this method to study the dynamics of RNA-protein interactions in developmental processes will help to uncover the role of RBPs in post-transcriptional regulation. Protein interaction profile sequencing (PIP-seq) in HEK293T cells. Three replicates of formaldehyde cross-linked PIP-seq are described

ORGANISM(S): Homo sapiens

SUBMITTER: Ian Silverman

PROVIDER: E-GEOD-57881 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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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.

Project description:RNA-binding proteins (RBPs) are critical regulators of gene expression and elucidating the interactions of RBPs with their RNA targets is necessary to understand how combinations of RBPs control transcriptome expression. The Quaking-related (QR) sub-family of STAR domain RBPs includes developmental regulators and tumor suppressors such as C. elegans GLD-1, which functions as a master regulator of germ line development. To understand how GLD-1 interacts with the transcriptome, we identified GLD-1 associated mRNAs by a ribonomic approach. The scale of GLD-1 mRNA interactions allowed us to determine rules governing GLD-1 target selection and to derive a predictive model where GLD-1 association with mRNA is based on the number and strength of 7-mer GLD-1 binding elements (GBEs) within UTRs. GLD-1/mRNA interactions were quantified, and predictions were verified both in vitro and in live animals, including by M-bM-^@M-^XtransplantationM-bM-^@M-^Y experiments where M-bM-^@M-^XweakM-bM-^@M-^Y and M-bM-^@M-^XstrongM-bM-^@M-^Y GBEs imposed translational repression of increasing strength on a non-target mRNA.Importantly, this study provides a unique quantitative picture of how an RBP interacts with its mRNA targets. As combinatorial regulation by multiple RBPs is thought to regulate gene expression, quantification of RBP/mRNA interactions should be a way to predict and potentially modify biological outcomes of complex posttranscriptional regulatory networks, and our analysis suggests that such an approach is possible. Wild-type (N2) or gld-1(q485); ozIs2 [gld-1::gfp::flag] worms were synchronized and harvested as young adults. To identify GLD-1 associated transcripts, two independent IP strategies were performed: 1. Comparison of anti-FLAG IP to anti-MYC IP on the gld-1(q485); ozIs2 [gld-1::gfp::flag] worm extract, 2. Comparison of anti-FLAG IP on the gld-1(q485); ozIs2 [gld-1::gfp::flag] worm extract to anti-FLAG IP on wild type extract. All IPs were performed in triplicate (12 IPs).

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Transcriptome-wide ribonuclease footprinting to identify RNA-protein interaction sites

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