Discovery of protein-RNA networks.

Coding and non-coding RNAs associate with proteins to perform important functions in the cell. Protein-RNA complexes are essential components of the ribosomal and spliceosomal machinery; they are involved in epigenetic regulation and form non-membrane-bound aggregates known as granules. Despite the functional importance of ribonucleoprotein interactions, the precise mechanisms of macromolecular recognition are still poorly understood. Here, we present the latest developments in experimental and computational investigation of protein-RNA interactions. We compare performances of different algorithms and discuss how predictive models allow the large-scale investigation of ribonucleoprotein associations. Specifically, we focus on approaches to decipher mechanisms regulating the activity of transcripts in protein networks. Finally, the catRAPID omics express method is introduced for the analysis of protein-RNA expression networks.

[1]  Petr Klus,et al.  The cleverSuite approach for protein characterization: predictions of structural properties, solubility, chaperone requirements and RNA-binding abilities , 2014, Bioinform..

[2]  Christopher R. Sibley,et al.  iCLIP: Protein–RNA interactions at nucleotide resolution , 2014, Methods.

[3]  Carmen Maria Livi,et al.  Constitutive patterns of gene expression regulated by RNA-binding proteins , 2014, Genome Biology.

[4]  C. Dobson,et al.  Widespread aggregation and neurodegenerative diseases are associated with supersaturated proteins. , 2013, Cell reports.

[5]  Yang Li,et al.  HMDD v2.0: a database for experimentally supported human microRNA and disease associations , 2013, Nucleic Acids Res..

[6]  Giovanni Bussi,et al.  Ligand-induced stabilization of the aptamer terminal helix in the add adenine riboswitch , 2013, RNA.

[7]  Carmen Maria Livi,et al.  Principles of self-organization in biological pathways: a hypothesis on the autogenous association of alpha-synuclein , 2013, Nucleic acids research.

[8]  Petr Klus,et al.  catRAPID omics: a web server for large-scale prediction of protein–RNA interactions , 2013, Bioinform..

[9]  Mani Ramaswami,et al.  Altered Ribostasis: RNA-Protein Granules in Degenerative Disorders , 2013, Cell.

[10]  Corissa L. Lamphear,et al.  Discovering RNA-protein interactome by using chemical context profiling of the RNA-protein interface. , 2013, Cell reports.

[11]  L. Malinovska,et al.  Protein disorder, prion propensities, and self-organizing macromolecular collectives. , 2013, Biochimica et biophysica acta.

[12]  S. Altman.  The RNA-Protein World. , 2013, RNA.

[13]  Federico Agostini,et al.  Predictions of protein–RNA interactions , 2013 .

[14]  D. Cirillo,et al.  Neurodegenerative diseases: quantitative predictions of protein-RNA interactions. , 2013, RNA.

[15]  Xiang-Sun Zhang,et al.  De novo prediction of RNA-protein interactions from sequence information. , 2013, Molecular bioSystems.

[16]  Xing Chen,et al.  LncRNADisease: a database for long-non-coding RNA-associated diseases , 2012, Nucleic Acids Res..

[17]  B. Wolozin.  Regulated protein aggregation: stress granules and neurodegeneration , 2012, Molecular Neurodegeneration.

[18]  P. Northcott,et al.  The RNA-binding protein Musashi1 affects medulloblastoma growth via a network of cancer-related genes and is an indicator of poor prognosis. , 2012, The American journal of pathology.

[19]  Federico Agostini,et al.  X-inactivation: quantitative predictions of protein interactions in the Xist network , 2012, Nucleic acids research.

[20]  J. Bujnicki,et al.  Computational methods for prediction of protein-RNA interactions. , 2012, Journal of structural biology.

[21]  Bronwen L. Aken,et al.  GENCODE: The reference human genome annotation for The ENCODE Project , 2012, Genome research.

[22]  H. Moriya,et al.  Robustness analysis of cellular systems using the genetic tug-of-war method. , 2012, Molecular bioSystems.

[23]  M. Vendruscolo,et al.  Sequence-based prediction of protein solubility. , 2012, Journal of molecular biology.

[24]  K. Neugebauer,et al.  RNA-protein interactions in vivo: global gets specific. , 2012, Trends in biochemical sciences.

[25]  A. Guillaumet-Adkins,et al.  Characterization of Novel Paternal ncRNAs at the Plagl1 Locus, Including Hymai, Predicted to Interact with Regulators of Active Chromatin , 2012, PloS one.

[26]  Richard Bonneau,et al.  The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. , 2012, Molecular cell.

[27]  Norman E. Davey,et al.  Insights into RNA Biology from an Atlas of Mammalian mRNA-Binding Proteins , 2012, Cell.

[28]  J. Rinn,et al.  Modular regulatory principles of large non-coding RNAs , 2012, Nature.

[29]  J. Ule,et al.  Protein–RNA interactions: new genomic technologies and perspectives , 2012, Nature Reviews Genetics.

[30]  D. Dobbs,et al.  Predicting RNA-Protein Interactions Using Only Sequence Information , 2011, BMC Bioinformatics.

[31]  Brad A Chapman,et al.  The genomic binding sites of a noncoding RNA , 2011, Proceedings of the National Academy of Sciences.

[32]  Hui Xiao,et al.  NONCODE v3.0: integrative annotation of long noncoding RNAs , 2011, Nucleic Acids Res..

[33]  Shandar Ahmad,et al.  Prediction of dinucleotide-specific RNA-binding sites in proteins , 2011, BMC Bioinformatics.

[34]  Howard Y. Chang,et al.  Genomic maps of long noncoding RNA occupancy reveal principles of RNA-chromatin interactions. , 2011, Molecular cell.

[35]  C. Sander,et al.  RNA targets of wild-type and mutant FET family proteins , 2011, Nature Structural &Molecular Biology.

[36]  T. Kawano,et al.  ALS mutations in FUS cause neuronal dysfunction and death in Caenorhabditis elegans by a dominant gain-of-function mechanism , 2011, Human molecular genetics.

[37]  Howard Y. Chang,et al.  Understanding the transcriptome through RNA structure , 2011, Nature Reviews Genetics.

[38]  Glyn L. Devlin,et al.  Metastability of native proteins and the phenomenon of amyloid formation. , 2011, Journal of the American Chemical Society.

[39]  M. Zavolan,et al.  A quantitative analysis of CLIP methods for identifying binding sites of RNA-binding proteins , 2011, Nature Methods.

[40]  Cole Trapnell,et al.  Multiplexed RNA structure characterization with selective 2′-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq) , 2011, Proceedings of the National Academy of Sciences.

[41]  Andrew McCallum,et al.  Database of NIH grants using machine-learned categories and graphical clustering , 2011, Nature Methods.

[42]  J. Rinn,et al.  RNA-protein interactions in human health and disease. , 2011, Seminars in cell & developmental biology.

[43]  J. Bähler,et al.  In silico characterization and prediction of global protein–mRNA interactions in yeast , 2011, Nucleic acids research.

[44]  Jernej Ule,et al.  TDP‐43 regulates its mRNA levels through a negative feedback loop , 2011, The EMBO journal.

[45]  Michele Vendruscolo,et al.  Amyloid-like Aggregates Sequester Numerous Metastable Proteins with Essential Cellular Functions , 2011, Cell.

[46]  John S. Mattick,et al.  lncRNAdb: a reference database for long noncoding RNAs , 2010, Nucleic Acids Res..

[47]  Lincoln Stein,et al.  Reactome: a database of reactions, pathways and biological processes , 2010, Nucleic Acids Res..

[48]  Michael Briese,et al.  iCLIP Predicts the Dual Splicing Effects of TIA-RNA Interactions , 2010, PLoS biology.

[49]  Howard Y. Chang,et al.  Genome-wide measurement of RNA secondary structure in yeast , 2010, Nature.

[50]  Howard Y. Chang,et al.  Long Noncoding RNA as Modular Scaffold of Histone Modification Complexes , 2010, Science.

[51]  Vasant Honavar,et al.  PRIDB: a protein–RNA interface database , 2010, Nucleic Acids Res..

[52]  S. Richard,et al.  Sam68 sequestration and partial loss of function are associated with splicing alterations in FXTAS patients , 2010, The EMBO journal.

[53]  Scott B. Dewell,et al.  Transcriptome-wide Identification of RNA-Binding Protein and MicroRNA Target Sites by PAR-CLIP , 2010, Cell.

[54]  Gene W. Yeo,et al.  Genome-wide analysis of PTB-RNA interactions reveals a strategy used by the general splicing repressor to modulate exon inclusion or skipping. , 2009, Molecular cell.

[55]  M. Vendruscolo,et al.  Correlation between mRNA expression levels and protein aggregation propensities in subcellular localisations. , 2009, Molecular bioSystems.

[56]  J. Rinn,et al.  Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression , 2009, Proceedings of the National Academy of Sciences.

[57]  Ben Lehner,et al.  Intrinsic Protein Disorder and Interaction Promiscuity Are Widely Associated with Dosage Sensitivity , 2009, Cell.

[58]  Andrew D. Ellington,et al.  Widespread reorganization of metabolic enzymes into reversible assemblies upon nutrient starvation , 2009, Proceedings of the National Academy of Sciences.

[59]  M. Heiner,et al.  Auto- and Cross-Regulation of the hnRNP L Proteins by Alternative Splicing , 2009, Molecular and Cellular Biology.

[60]  Alan F. Scott,et al.  McKusick's Online Mendelian Inheritance in Man (OMIM®) , 2008, Nucleic Acids Res..

[61]  Tim R. Mercer,et al.  NRED: a database of long noncoding RNA expression , 2008, Nucleic Acids Res..

[62]  Michele Vendruscolo,et al.  Prediction of aggregation-prone regions in structured proteins. , 2008, Journal of molecular biology.

[63]  M. Vendruscolo,et al.  The Zyggregator method for predicting protein aggregation propensities. , 2008, Chemical Society reviews.

[64]  Ronny Lorenz,et al.  The Vienna RNA Websuite , 2008, Nucleic Acids Res..

[65]  Jae-Hyung Lee,et al.  RNABindR: a server for analyzing and predicting RNA-binding sites in proteins , 2007, Nucleic Acids Res..

[66]  Michele Vendruscolo,et al.  Life on the edge: a link between gene expression levels and aggregation rates of human proteins. , 2007, Trends in biochemical sciences.

[67]  A. Ivanov,et al.  Human ribosomal protein S13 inhibits splicing of its own pre-mRNA , 2007, Molecular Biology.

[68]  T. Hughes,et al.  Mapping pathways and phenotypes by systematic gene overexpression. , 2006, Molecular cell.

[69]  Lan Chen,et al.  NPInter: the noncoding RNAs and protein related biomacromolecules interaction database , 2005, Nucleic Acids Res..

[70]  Amedeo Caflisch,et al.  Prediction of aggregation rate and aggregation‐prone segments in polypeptide sequences , 2005, Protein science : a publication of the Protein Society.

[71]  A. Pastore,et al.  Fragile X Mental Retardation Protein (FMRP) Binds Specifically to the Brain Cytoplasmic RNAs BC1/BC200 via a Novel RNA-binding Motif* , 2005, Journal of Biological Chemistry.

[72]  J. Steitz,et al.  Evidence for reassociation of RNA-binding proteins after cell lysis: implications for the interpretation of immunoprecipitation analyses. , 2004, RNA.

[73]  P. Hagerman,et al.  The fragile-X premutation: a maturing perspective. , 2004, American journal of human genetics.

[74]  K. Becker,et al.  The Genetic Association Database , 2004, Nature Genetics.

[75]  Ivo L. Hofacker,et al.  Vienna RNA secondary structure server , 2003, Nucleic Acids Res..

[76]  Yael Mandel-Gutfreund,et al.  Annotating nucleic acid-binding function based on protein structure. , 2003, Journal of molecular biology.

[77]  B. Oostra,et al.  The Fragile X Syndrome Protein FMRP Associates with BC1 RNA and Regulates the Translation of Specific mRNAs at Synapses , 2003, Cell.

[78]  C. Ehresmann,et al.  The fragile X mental retardation protein binds specifically to its mRNA via a purine quartet motif , 2001, The EMBO journal.

[79]  A Sureau,et al.  SC35 autoregulates its expression by promoting splicing events that destabilize its mRNAs , 2001, The EMBO journal.

[80]  G. Dreyfuss,et al.  RNA-binding proteins as regulators of gene expression. , 1997, Current opinion in genetics & development.

[81]  G. Maley,et al.  Thymidylate synthase binds to c-myc RNA in human colon cancer cells and in vitro , 1995, Molecular and cellular biology.

[82]  P C Elwood,et al.  Autoregulation of human thymidylate synthase messenger RNA translation by thymidylate synthase. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[83]  L. Gold,et al.  Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. , 1990, Science.

[84]  C R Woese,et al.  The molecular basis for the genetic code. , 1966, Proceedings of the National Academy of Sciences of the United States of America.

[85]  Donny D. Licatalosi,et al.  RNA processing and its regulation: global insights into biological networks , 2010, Nature Reviews Genetics.

[86]  P. Anderson,et al.  Mammalian stress granules and processing bodies. , 2007, Methods in enzymology.

[87]  Jordan M. Komisarow,et al.  RIP-Chip: the isolation and identification of mRNAs, microRNAs and protein components of ribonucleoprotein complexes from cell extracts , 2006, Nature Protocols.

[88]  鄭素梅,et al.  Nature Publishing Group , 2006 .