Higher-Order Organization Principles of Pre-translational mRNPs [RIPPLiT]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE115788 | GEO | 2018/11/14
REPOSITORIES: GEO
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Project description:Compared to noncoding RNAs (ncRNAs), such as rRNAs and ribozymes, for which high-resolution structures abound, little is known about the tertiary structures of mRNAs. In eukaryotic cells, newly made mRNAs are packaged with proteins in highly compacted mRNA particles (mRNPs), but the manner of this mRNA compaction is unknown. Here, we developed and implemented RIPPLiT (RNA immunoprecipitation and proximity ligation in tandem), a transcriptome-wide method for probing the 3D conformations of RNAs stably associated with defined proteins, in this case, exon junction complex (EJC) core factors. EJCs multimerize with other mRNP components to form megadalton-sized complexes that protect large swaths of newly synthesized mRNAs from endonuclease digestion. Unlike ncRNPs, wherein strong locus-specific structures predominate, mRNPs behave more like flexible polymers. Polymer analysis of proximity ligation data for hundreds of mRNA species demonstrates that nascent and pre-translational mammalian mRNAs are compacted by their associated proteins into linear rod-like structures.
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Project description:Higher-Order Organization Principles of Pre-translational mRNPs [RIPPLiT]
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Project description:Background: Alternative splicing (AS), which generates multiple mRNA isoforms from single genes, is crucial for the regulation of eukaryotic gene expression. The flux through competing AS pathways cannot be determined by traditional RNA-Seq, however, because different mRNA isoforms can have widely differing decay rates. Indeed, some mRNA isoforms with extremely short half-lives, such as those subject to translation-dependent nonsense-mediated decay (AS-NMD), may be completely overlooked in even the most extensive RNA-Seq analyses. Results: RNA immunoprecipitation in tandem (RIPiT) of exon junction complex (EJC) components allows for purification of post-splicing mRNA-protein particles (mRNPs) not yet subject to translation (pre-translational mRNPs) and, therefore, translation-dependent mRNA decay. Here we compared EJC RIPiT-Seq to whole cell RNA-Seq data from HEK293 cells. Consistent with expectation, the flux through known AS-NMD pathways is substantially higher than that captured by RNA-Seq. Our EJC RIPiT-Seq also definitively demonstrates that the splicing machinery itself has no ability to detect reading frame. We identified thousands of previously unannotated splicing events; while many can be attributed to “splicing noise”, others are evolutionarily-conserved events that produce new AS-NMD isoforms likely involved in maintenance of protein homeostasis. Several of these occur in genes whose overexpression has been linked to poor cancer prognosis. Conclusions: Deep sequencing of RNAs in post-splicing, pre-translational mRNPs provides a means to identify and quantify splicing events without the confounding influence of differential mRNA decay. For many known AS-NMD targets, the NMD-linked AS pathway predominates. EJC RIPiT-Seq also enabled identification of numerous conserved but previously unknown AS-NMD events.
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Project description:Networks are a fundamental tool for understanding and modeling complex systems in physics, biology, neuroscience, engineering, and social science. Many networks are known to exhibit rich, lower-order connectivity patterns that can be captured at the level of individual nodes and edges. However, higher-order organization of complex networks--at the level of small network subgraphs--remains largely unknown. Here, we develop a generalized framework for clustering networks on the basis of higher-order connectivity patterns. This framework provides mathematical guarantees on the optimality of obtained clusters and scales to networks with billions of edges. The framework reveals higher-order organization in a number of networks, including information propagation units in neuronal networks and hub structure in transportation networks. Results show that networks exhibit rich higher-order organizational structures that are exposed by clustering based on higher-order connectivity patterns.
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Project description:Affymetrix microarrays were used to determine the mRNA composition of mRNPs obtained by immunoprecipitation with IRP2 (iron regulatory protein 2).
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Project description:Affymetrix microarrays were used to determine the mRNA composition of mRNPs obtained by immunoprecipitation with IRP1 (iron regulatory protein 1).
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Project description:We isolated nuclear mRNPs from yeast using an endogenous bi-molecular tagging approach on Sub2 and Hpr1. To validate the nature of these isolated particles, extracted RNA was sequenced and differential enrichment, as well as metagene coverage analysis were performed.
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