Dataset Information

Transcriptome-scale RNase-footprinting of RNA-protein complexes.

ABSTRACT: Ribosome profiling is widely used to study translation in vivo, but not all sequence reads correspond to ribosome-protected RNA. Here we describe Rfoot, a computational pipeline that analyzes ribosomal profiling data and identifies native, nonribosomal RNA-protein complexes. We use Rfoot to precisely map RNase-protected regions within small nucleolar RNAs, spliceosomal RNAs, microRNAs, tRNAs, long noncoding (lnc)RNAs and 3' untranslated regions of mRNAs in human cells. We show that RNAs of the same class can show differential complex association. Although only a subset of lncRNAs show RNase footprints, many of these have multiple footprints, and the protected regions are evolutionarily conserved, suggestive of biological functions.

SUBMITTER: Ji Z

PROVIDER: S-EPMC4824641 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Transcriptome-scale RNase-footprinting of RNA-protein complexes.

Ji Zhe Z Song Ruisheng R Huang Hailiang H Regev Aviv A Struhl Kevin K

Nature biotechnology 20160222 4

Ribosome profiling is widely used to study translation in vivo, but not all sequence reads correspond to ribosome-protected RNA. Here we describe Rfoot, a computational pipeline that analyzes ribosomal profiling data and identifies native, nonribosomal RNA-protein complexes. We use Rfoot to precisely map RNase-protected regions within small nucleolar RNAs, spliceosomal RNAs, microRNAs, tRNAs, long noncoding (lnc)RNAs and 3' untranslated regions of mRNAs in human cells. We show that RNAs of the s ...[more]

PMID: 26900662

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Project description: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

Dataset Information

Transcriptome-scale RNase-footprinting of RNA-protein complexes.

Publications

Transcriptome-scale RNase-footprinting of RNA-protein complexes.

Similar Datasets

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