Advances in the characterization of RNA-binding proteins

Wiley Interdisciplinary Reviews: RNA

Volumn 7, Issue 6, 2016, Pages 793-810

  Marchese, Domenica ^a,b   de Groot, Natalia Sanchez ^a,b   Lorenzo Gotor, Nieves ^a,b   Livi, Carmen Maria ^a,b,c   Tartaglia, Gian G ^a,b,d  

^a BARCELONA INSTITUTE OF SCIENCE AND TECHNOLOGY   (Spain)

^b UNIVERSITAT POMPEU FABRA   (Spain)

^c FIRC INSTITUTE OF MOLECULAR ONCOLOGY   (Italy)

^d INSTITUCIÓ CATALANA DE RECERCA I ESTUDIS AVANÇATS ICREA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

RNA BINDING PROTEIN; TRANSCRIPTOME; PROTEIN BINDING; RNA;

ARTICLE; BINDING AFFINITY; IMMUNOPRECIPITATION; PRIORITY JOURNAL; PROTEIN DETERMINATION; PROTEIN INTERACTION; PROTEIN RNA BINDING; RNA METABOLISM; RNA PURIFICATION; RNA SEQUENCE; RNA SPLICING; RNA SYNTHESIS; RNA TRANSCRIPTION; ANIMAL; BINDING SITE; HUMAN; METABOLISM;

ANIMALS; BINDING SITES; HUMANS; PROTEIN BINDING; RNA; RNA-BINDING PROTEINS;

EID: 84982987715     PISSN: 17577004     EISSN: 17577012     Source Type: Journal    
DOI: 10.1002/wrna.1378     Document Type: Article

References (145)

1. Morris KV, Mattick JS. The rise of regulatory RNA. Nat Rev Genet 2014, 15:423–437.
2. Gerstberger S, Hafner M, Tuschl T. A census of human RNA-binding proteins. Nat Rev Genet 2014, 15:829–845.
3. Iwasaki YW, Siomi MC, Siomi H. PIWI-interacting RNA: its biogenesis and functions. Annu Rev Biochem 2015, 84:405–433.
4. Verschoor A, Srivastava S, Grassucci R, Frank J. Native 3D structure of eukaryotic 80s ribosome: morphological homology with E. coli 70S ribosome. J Cell Biol 1996, 133:495–505.
5. Courchaine E, Neugebauer KM. Paraspeckles: paragons of functional aggregation. J Cell Biol 2015, 210:527–528.
6. Brangwynne CP, Eckmann CR, Courson DS, Rybarska A, Hoege C, Gharakhani J, Jülicher F, Hyman AA. Germline P granules are liquid droplets that localize by controlled dissolution/condensation. Science 2009, 324:1729–1732.
7. Chen D, Huang S. Nucleolar components involved in ribosome biogenesis cycle between the nucleolus and nucleoplasm in interphase cells. J Cell Biol 2001, 153:169–176.
8. Giménez-Barcons M, Díez J. Yeast processing bodies and stress granules: self-assembly ribonucleoprotein particles. Microb Cell Fact 2011, 10:73.
9. Ward AJ, Cooper TA. The pathobiology of splicing. J Pathol 2010, 220:152–163.
10. Nussbacher JK, Batra R, Lagier-Tourenne C, Yeo GW. RNA-binding proteins in neurodegeneration: Seq and you shall receive. Trends Neurosci 2015, 38:226–236.
11. Castello A, Fischer B, Hentze MW, Preiss T. RNA-binding proteins in Mendelian disease. Trends Genet 2013, 29:318–327.
12. Lukong KE, Chang K, Khandjian EW, Richard S. RNA-binding proteins in human genetic disease. Trends Genet 2008, 24:416–425.
13. Setzer DR. Measuring equilibrium and kinetic constants using gel retardation assays. Methods Mol Biol 1999, 118:115–128.
14. Wilson, G.M, Sutphen, K, Chuang Ky, null, and Brewer, G. (2001) Folding of A + U-rich RNA elements modulates AUF1 binding. Potential roles in regulation of mRNA turnover. J Biol Chem, 276:8695–8704.
15. Walter NG, Hampel KJ, Brown KM, Burke JM. Tertiary structure formation in the hairpin ribozyme monitored by fluorescence resonance energy transfer. EMBO J 1998, 17:2378–2391.
16. Katsamba PS, Park S, Laird-Offringa IA. Kinetic studies of RNA-protein interactions using surface plasmon resonance. Methods 2002, 26:95–104.
17. Martin D, Charpilienne A, Parent A, Boussac A, D'Autreaux B, Poupon J, Poncet D. The rotavirus nonstructural protein NSP5 coordinates a [2Fe-2S] iron-sulfur cluster that modulates interaction to RNA. FASEB J 2013, 27:1074–1083.
18. Schulz S, Doller A, Pendini NR, Wilce JA, Pfeilschifter J, Eberhardt W. Domain-specific phosphomimetic mutation allows dissection of different protein kinase C (PKC) isotype-triggered activities of the RNA binding protein HuR. Cell Signal 2013, 25:2485–2495.
19. Sunwoo H, Wu JY, Lee JT. The Xist RNA-PRC2 complex at 20-nm resolution reveals a low Xist stoichiometry and suggests a hit-and-run mechanism in mouse cells. Proc Natl Acad Sci USA 2015, 112:E4216–4225.
20. Konig J, Zarnack K, Rot G, Curk T, Kayikci M, Zupan B, Turner DJ, Luscombe NM, Ule J. iCLIP—transcriptome-wide mapping of protein-RNA interactions with individual nucleotide resolution. J Vis Exp 2011, 50.
21. Ascano M, Hafner M, Cekan P, Gerstberger S, Tuschl T. Identification of RNA–protein interaction networks using PAR-CLIP. WIREs RNA 2012, 3:159–177.
22. Mann M. Functional and quantitative proteomics using SILAC. Nat Rev Mol Cell Biol 2006, 7:952–958.
23. Marshall KA, Ellington AD. In vitro selection of RNA aptamers. Methods Enzymol 2000, 318:193–214.
24. Campbell ZT, Bhimsaria D, Valley CT, Rodriguez-Martinez JA, Menichelli E, Williamson JR, Ansari AZ, Wickens M. Cooperativity in RNA-protein interactions: global analysis of RNA binding specificity. Cell Rep 2012, 1:570–581.
25. Cook KB, Hughes TR, Morris QD. High-throughput characterization of protein–RNA interactions. Brief Funct Genomics 2015, 14:74–89.
26. Livi CM, Blanzieri E. Protein-specific prediction of mRNA binding using RNA sequences, binding motifs and predicted secondary structures. BMC Bioinformatics 2014, 15:123.
27. Terribilini M, Sander JD, Lee J-H, Zaback P, Jernigan RL, Honavar V, Dobbs D. RNABindR: a server for analyzing and predicting RNA-binding sites in proteins. Nucleic Acids Res 2007, 35(Web Server issue):W578–584.
28. Klus P, Bolognesi B, Agostini F, Marchese D, Zanzoni A, Tartaglia GG. The cleverSuite approach for protein characterization: predictions of structural properties, solubility, chaperone requirements and RNA-binding abilities. Bioinformatics 2014, 30:1601–1608.
29. Castello A, Fischer B, Eichelbaum K, Horos R, Beckmann BM, Strein C, Davey NE, Humphreys DT, Preiss T, Steinmetz LM, et al. Insights into RNA biology from an atlas of mammalian mRNA-binding proteins. Cell 2012, 149:1393–1406.
30. Tartaglia GG. The grand challenge of characterizing ribonucleoprotein networks. Front Mol Biosci 2016, 3:24.
31. Tenenbaum SA, Carson CC, Lager PJ, Keene JD. Identifying mRNA subsets in messenger ribonucleoprotein complexes by using cDNA arrays. Proc Natl Acad Sci USA 2000, 97:14085–14090.
32. Licatalosi DD, Mele A, Fak JJ, Ule J, Kayikci M, Chi SW, Clark TA, Schweitzer AC, Blume JE, Wang X, et al. HITS-CLIP yields genome-wide insights into brain alternative RNA processing. Nature 2008, 456:464–469.
33. Hafner M, Landthaler M, Burger L, Khorshid M, Hausser J, Berninger P, Rothballer A, Ascano M Jr, Jungkamp A-C, Munschauer M, et al. Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell 2010, 141:129–141.
34. Van Nostrand EL, Pratt GA, Shishkin AA, Gelboin-Burkhart C, Fang MY, Sundararaman B, Blue SM, Nguyen TB, Surka C, Elkins K, et al. Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP). Nat Methods 2016, 6:508–514.
35. Ray D, Kazan H, Chan ET, Castillo LP, Chaudhry S, Talukder S, Blencowe BJ, Morris Q, Hughes TR. Rapid and systematic analysis of the RNA recognition specificities of RNA-binding proteins. Nat Biotechnol 2009, 27:667–670.
36. Lambert N, Robertson A, Jangi M, McGeary S, Sharp PA, Burge CB. RNA Bind-n-Seq: quantitative assessment of the sequence and structural binding specificity of RNA binding proteins. Mol Cell 2014, 54:887–900.
37. Buenrostro JD, Araya CL, Chircus LM, Layton CJ, Chang HY, Snyder MP, Greenleaf WJ. Quantitative analysis of RNA-protein interactions on a massively parallel array reveals biophysical and evolutionary landscapes. Nat Biotechnol 2014, 32:562–568.
38. Tome JM, Ozer A, Pagano JM, Gheba D, Schroth GP, Lis JT. Comprehensive analysis of RNA-protein interactions by high-throughput sequencing-RNA affinity profiling. Nat Methods 2014, 11:683–688.
39. Martin L, Meier M, Lyons SM, Sit RV, Marzluff WF, Quake SR, Chang HY. Systematic reconstruction of RNA functional motifs with high-throughput microfluidics. Nat Methods 2012, 9:1192–1194.
40. Hogg JR, Collins K. RNA-based affinity purification reveals 7SK RNPs with distinct composition and regulation. RNA 2007, 13:868–880.
41. Slobodin B, Gerst JE. RaPID: an aptamer-based mRNA affinity purification technique for the identification of RNA and protein factors present in ribonucleoprotein complexes. Methods Mol Biol 2011, 714:387–406.
42. Michlewski G, Cáceres JF. RNase-assisted RNA chromatography. RNA 2010, 16:1673–1678.
43. Scherrer T, Mittal N, Janga SC, Gerber AP. A screen for RNA-binding proteins in yeast indicates dual functions for many enzymes. PLoS One 2010, 5:e15499.
44. Siprashvili Z, Webster DE, Kretz M, Johnston D, Rinn JL, Chang HY, Khavari PA. Identification of proteins binding coding and non-coding human RNAs using protein microarrays. BMC Genomics 2012, 13:633.
45. Tsai BP, Wang X, Huang L, Waterman ML. Quantitative profiling of in vivo-assembled RNA-protein complexes using a novel integrated proteomic approach. Mol Cell Proteomics 2011, 10:M110.007385.
46. Chu C, Quinn J, Chang HY. Chromatin isolation by RNA purification (ChIRP). J Vis Exp 2012, 61:3912.
47. Simon MD. Capture hybridization analysis of RNA targets (CHART). Curr Protoc Mol Biol, Wiley Online Library, NY UUEE, Chapter 21, Unit 21.25, 2013.
48. Keene JD, Komisarow JM, Friedersdorf MB. RIP-Chip: the isolation and identification of mRNAs, microRNAs and protein components of ribonucleoprotein complexes from cell extracts. Nat Protoc 2006, 1:302–307.
49. Ule J, Jensen K, Mele A, Darnell RB. CLIP: a method for identifying protein-RNA interaction sites in living cells. Methods 2005, 37:376–386.
50. Faoro C, Ataide SF. Ribonomic approaches to study the RNA-binding proteome. FEBS Lett 2014, 588:3649–3664.
51. Trifillis P, Day N, Kiledjian M. Finding the right RNA: identification of cellular mRNA substrates for RNA-binding proteins. RNA 1999, 5:1071–1082.
52. Brooks SA, Rigby WF. Characterization of the mRNA ligands bound by the RNA binding protein hnRNP A2 utilizing a novel in vivo technique. Nucleic Acids Res 2000, 28:E49.
53. König J, Zarnack K, Rot G, Curk T, Kayikci M, Zupan B, Turner DJ, Luscombe NM, Ule J. iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution. Nat Struct Mol Biol 2010, 17:909–915.
54. Wang T, Xiao G, Chu Y, Zhang MQ, Corey DR, Xie Y. Design and bioinformatics analysis of genome-wide CLIP experiments. Nucleic Acids Res 2015, 43:5263–5274.
55. Ule J, Jensen KB, Ruggiu M, Mele A, Ule A, Darnell RB. CLIP identifies Nova-regulated RNA networks in the brain. Science 2003, 302:1212–1215.
56. Ince-Dunn G, Okano HJ, Jensen KB, Park W-Y, Zhong R, Ule J, Mele A, Fak JJ, Yang C, Zhang C, et al. Neuronal Elav-like (Hu) proteins regulate RNA splicing and abundance to control glutamate levels and neuronal excitability. Neuron 2012, 75:1067–1080.
57. Lu Y-C, Chang S-H, Hafner M, Li X, Tuschl T, Elemento O, Hla T. ELAVL1 modulates transcriptome-wide miRNA binding in murine macrophages. Cell Rep 2014, 9:2330–2343.
58. Denkert C, Koch I, von Keyserlingk N, Noske A, Niesporek S, Dietel M, Weichert W. Expression of the ELAV-like protein HuR in human colon cancer: association with tumor stage and cyclooxygenase-2. Mod Pathol 2006, 19:1261–1269.
59. Abdelmohsen K, Gorospe M. Posttranscriptional regulation of cancer traits by HuR. WIREs RNA 2010, 1:214–229.
60. Mukherjee N, Corcoran DL, Nusbaum JD, Reid DW, Georgiev S, Hafner M, Ascano M, Tuschl T, Ohler U, Keene JD. Integrative regulatory mapping indicates that the RNA-binding protein HuR couples pre-mRNA processing and mRNA stability. Mol Cell 2011, 43:327–339.
61. Okano HJ, Darnell RB. A hierarchy of Hu RNA binding proteins in developing and adult neurons. J Neurosci 1997, 17:3024–3037.
62. Darnell RB. HITS-CLIP: panoramic views of protein-RNA regulation in living cells. WIREs RNA 2010, 1:266–286.
63. Jankowsky E, Harris ME. Specificity and nonspecificity in RNA-protein interactions. Nat Rev Mol Cell Biol 2015, 16:533–544.
64. Ulitsky I, Bartel DP. lincRNAs: genomics, evolution, and mechanisms. Cell 2013, 154:26–46.
65. Engreitz JM, Pandya-Jones A, McDonel P, Shishkin A, Sirokman K, Surka C, Kadri S, Xing J, Goren A, Lander ES, et al. The Xist lncRNA exploits three-dimensional genome architecture to spread across the X chromosome. Science 2013, 341:1237973.
66. West JA, Davis CP, Sunwoo H, Simon MD, Sadreyev RI, Wang PI, Tolstorukov MY, Kingston RE. The long noncoding RNAs NEAT1 and MALAT1 bind active chromatin sites. Mol Cell 2014, 55:791–802.
67. McHugh CA, Chen C-K, Chow A, Surka CF, Tran C, McDonel P, Pandya-Jones A, Blanco M, Burghard C, Moradian A, et al. The Xist lncRNA interacts directly with SHARP to silence transcription through HDAC3. Nature 2015, 521:232–236.
68. Chu C, Zhang QC, da Rocha ST, Flynn RA, Bharadwaj M, Calabrese JM, Magnuson T, Heard E, Chang HY. Systematic discovery of Xist RNA binding proteins. Cell 2015, 161:404–416.
69. Baltz AG, Munschauer M, Schwanhäusser B, Vasile A, Murakawa Y, Schueler M, Youngs N, Penfold-Brown D, Drew K, Milek M, et al. The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. Mol Cell 2012, 46:674–690.
70. Kwon SC, Yi H, Eichelbaum K, Föhr S, Fischer B, You KT, Castello A, Krijgsveld J, Hentze MW, Kim VN. The RNA-binding protein repertoire of embryonic stem cells. Nat Struct Mol Biol 2013, 20:1122–1130.
71. Beckmann BM, Horos R, Fischer B, Castello A, Eichelbaum K, Alleaume A-M, Schwarzl T, Curk T, Foehr S, Huber W, et al. The RNA-binding proteomes from yeast to man harbour conserved enigmRBPs. Nat Commun 2015, 6:10127.
72. Mitchell SF, Jain S, She M, Parker R. Global analysis of yeast mRNPs. Nat Struct Mol Biol 2013, 20:127–133.
73. Ingolia NT. Ribosome profiling: new views of translation, from single codons to genome scale. Nat Rev Genet 2014, 15:205–213.
74. Bailey TL, Johnson J, Grant CE, Noble WS. The MEME suite. Nucleic Acids Res 2015, 43(W1):W39–49.
75. Paz I, Kosti I, Ares M, Cline M, Mandel-Gutfreund Y. RBPmap: a web server for mapping binding sites of RNA-binding proteins. Nucleic Acids Res 2014, 42(Web Server issue):W361–367.
76. Agostini F, Cirillo D, Ponti RD, Tartaglia GG. SeAMotE: a method for high-throughput motif discovery in nucleic acid sequences. BMC Genomics 2014, 15:925.
77. Kazan H, Ray D, Chan ET, Hughes TR, Morris Q. RNAcontext: a new method for learning the sequence and structure binding preferences of RNA-binding proteins. PLoS Comput Biol 2010, 6:e1000832.
78. Wang L, Huang C, Yang MQ, Yang JY. BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features. BMC Syst Biol 2010, 4:1–9.
79. Kumar M, Gromiha MM, Raghava GPS. Prediction of RNA binding sites in a protein using SVM and PSSM profile. Proteins 2008, 71:189–194.
80. Walia RR, Xue LC, Wilkins K, El-Manzalawy Y, Dobbs D, Honavar V. RNABindRPlus: a predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins. PLoS One 2014, 9:e97725.
81. Cirillo D, Agostini F, Tartaglia GG. Predictions of protein-RNA interactions. WIREs Comput Mol Sci 2012, 3:161–175.
82. Finn RD, Clements J, Arndt W, Miller BL, Wheeler TJ, Schreiber F, Bateman A, Eddy SR. HMMER web server: 2015 update. Nucleic Acids Res 2015, 43(W1):W30–38.
83. Livi CM, Klus P, Delli Ponti R, Tartaglia GG. catRAPID signature: identification of ribonucleoproteins and RNA-binding regions. Bioinformatics 2015, 32:773–775.
84. Towfic F, Caragea C, Gemperline DC, Dobbs D, Honavar V. Struct-NB: predicting protein-RNA binding sites using structural features. Int J Data Min Bioinform 2010, 4:21–43.
85. Maetschke SR, Yuan Z. Exploiting structural and topological information to improve prediction of RNA-protein binding sites. BMC Bioinformatics 2009, 10:341.
86. Zhao H, Yang Y, Zhou Y. Highly accurate and high-resolution function prediction of RNA binding proteins by fold recognition and binding affinity prediction. RNA Biol 2011, 8:988–996.
87. Pérez-Cano L, Fernández-Recio J. Optimal protein-RNA area, OPRA: a propensity-based method to identify RNA-binding sites on proteins. Proteins 2010, 78:25–35.
88. Yang Y, Faraggi E, Zhao H, Zhou Y. Improving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templates. Bioinformatics 2011, 27:2076–2082.
89. Zhao H, Yang Y, Janga SC, Kao CC, Zhou Y. Prediction and validation of the unexplored RNA-binding protein atlas of the human proteome. Proteins 2014, 82:640–647.
90. Ivani I, Dans PD, Noy A, Pérez A, Faustino I, Hospital A, Walther J, Andrio P, Goñi R, Balaceanu A, et al. Parmbsc1: a refined force field for DNA simulations. Nat Methods 2016, 13:55–58.
91. Cirillo D, Livi CM, Agostini F, Tartaglia GG. Discovery of protein–RNA networks. Mol BioSyst 2014, 10:1632–1642.
92. Si J, Cui J, Cheng J, Wu R. Computational prediction of RNA-binding proteins and binding sites. Int J Mol Sci 2015, 16:26303–26317.
93. Wang L, Brown SJ. BindN: a web-based tool for efficient prediction of DNA and RNA binding sites in amino acid sequences. Nucl Acids Res 2006, 34(suppl 2):W243–248.
94. Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, Ren J, Li WW, Noble WS. MEME Suite: tools for motif discovery and searching. Nucl Acids Res 2009, 37(suppl 2):W202–208.
95. Finn RD, Clements J, Eddy SR. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res 2011, 39(Web Server issue):W29–37.
96. Bellucci M, Agostini F, Masin M, Tartaglia GG. Predicting protein associations with long noncoding RNAs. Nat Methods 2011, 8:444–445.
97. Agostini F, Zanzoni A, Klus P, Marchese D, Cirillo D, Tartaglia GG. catRAPID omics: a web server for large-scale prediction of protein-RNA interactions. Bioinformatics 2013, 29:2928–2930.
98. Muppirala UK, Honavar VG, Dobbs D. Predicting RNA-protein interactions using only sequence information. BMC Bioinformatics 2011, 12:489.
99. Liu T, Geng X, Zheng X, Li R, Wang J. Accurate prediction of protein structural class using auto covariance transformation of PSI-BLAST profiles. Amino Acids 2012, 42:2243–2249.
100. Kumar M, Gromiha MM, Raghava GPS. SVM based prediction of RNA-binding proteins using binding residues and evolutionary information. J Mol Recognit 2011, 24:303–313.
101. Cheng C-W, Su EC-Y, Hwang J-K, Sung T-Y, Hsu W-L. Predicting RNA-binding sites of proteins using support vector machines and evolutionary information. BMC Bioinformatics 2008, 9(Suppl 12):S6.
102. Nagarajan R, Gromiha MM. Prediction of RNA binding residues: an extensive analysis based on structure and function to select the best predictor. PLoS One 2014, 9:e91140.
103. Agostini F, Cirillo D, Livi CM, Ponti RD, Tartaglia GG. ccSOL omics: a webserver for large-scale prediction of endogenous and heterologous solubility in E. coli. Bioinformatics 2014, 30:2975–2977.
104. Johnson R, Noble W, Tartaglia GG, Buckley NJ. Neurodegeneration as an RNA disorder. Prog Neurobiol 2012, 99:293–315.
105. Zalfa F, Giorgi M, Primerano B, Moro A, Di Penta A, Reis S, Oostra B, Bagni C. The fragile X syndrome protein FMRP associates with BC1 RNA and regulates the translation of specific mRNAs at synapses. Cell 2003, 112:317–327.
106. Myrick LK, Hashimoto H, Cheng X, Warren ST. Human FMRP contains an integral tandem Agenet (Tudor) and KH motif in the amino terminal domain. Hum Mol Genet 2015, 24:1733–1740.
107. Agostini F, Cirillo D, Bolognesi B, Tartaglia GG. X-inactivation: quantitative predictions of protein interactions in the Xist network. Nucleic Acids Res 2013, 41:e31.
108. Cirillo D, Marchese D, Agostini F, Livi CM, Botta-Orfila T, Tartaglia GG. Constitutive patterns of gene expression regulated by RNA-binding proteins. Genome Biol 2014, 15:R13.
109. Cirillo D, Agostini F, Klus P, Marchese D, Rodriguez S, Bolognesi B, Tartaglia GG. Neurodegenerative diseases: quantitative predictions of protein-RNA interactions. RNA 2013, 19:129–140.
110. Will CL, Lührmann R. Spliceosome structure and function. Cold Spring Harb Perspect Biol 2011, 3:a003707.
111. Cirillo D, Botta-Orfila T, Tartaglia GG. By the company they keep: interaction networks define the binding ability of transcription factors. Nucleic Acids Res 2015, 43:e125.
112. Levy ED, Erba EB, Robinson CV, Teichmann SA. Assembly reflects evolution of protein complexes. Nature 2008, 453:1262–1265.
113. Matia-González AM, Laing EE, Gerber AP. Conserved mRNA-binding proteomes in eukaryotic organisms. Nat Struct Mol Biol 2015, 22:1027–1033.
114. Neelamraju Y, Hashemikhabir S, Janga SC. The human RBPome: from genes and proteins to human disease. J Proteomics 2015, 127(Pt A):61–70.
115. Castello A, Horos R, Strein C, Fischer B, Eichelbaum K, Steinmetz LM, Krijgsveld J, Hentze MW. Comprehensive identification of RNA-binding proteins by RNA interactome capture. Methods Mol Biol 2016, 1358:131–139.
116. Babu MM, Kriwacki RW, Pappu RV. Structural biology. Versatility from protein disorder. Science 2012, 337:1460–1461.
117. Dunker AK, Brown CJ, Lawson JD, Iakoucheva LM, Obradović Z. Intrinsic disorder and protein function. Biochemistry 2002, 41:6573–6582.
118. Bolognesi B, Lorenzo N, Dhar R, Cirillo D, Baldrighi M, Tartaglia G, Lehner B. A concentration-dependent liquid phase separation can cause toxicity upon increased protein expression. Cell Rep 2016, 16:222–231.
119. Li P, Banjade S, Cheng H-C, Kim S, Chen B, Guo L, Llaguno M, Hollingsworth JV, King DS, Banani SF, et al. Phase transitions in the assembly of multivalent signalling proteins. Nature 2012, 483:336–340.
120. Martin JE, Mather K, Swash M, Dodd SM, Dale GE, Garofalo O, Leigh PN. Stress protein inclusions in cerebral vessels in dialysis encephalopathy. Neuropathol Appl Neurobiol 1991, 17:105–111.
121. Shah KH, Zhang B, Ramachandran V, Herman PK. Processing body and stress granule assembly occur by independent and differentially regulated pathways in Saccharomyces cerevisiae. Genetics 2013, 193:109–123.
122. Klus P, Cirillo D, Botta Orfila T, Gaetano Tartaglia G. Neurodegeneration and cancer: where the disorder prevails. Sci Rep 2015, 5:15390.
123. Klus P, Ponti RD, Livi CM, Tartaglia GG. Protein aggregation, structural disorder and RNA-binding ability: a new approach for physico-chemical and gene ontology classification of multiple datasets. BMC Genomics 2015, 16:1071.
124. Jain S, Wheeler JR, Walters RW, Agrawal A, Barsic A, Parker R. ATPase-modulated stress granules contain a diverse proteome and substructure. Cell 2016, 164:487–498.
125. Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 2012, 28:3150–3152.
126. Becker LA, Gitler AD. It's all starting to come together. Elife 2015, 4:e09853.
127. Mitrea DM, Kriwacki RW. Phase separation in biology; functional organization of a higher order. Cell Commun Signal 2016, 14:1.
128. Masuda K, Marasa B, Martindale JL, Halushka MK, Gorospe M. Tissue- and age-dependent expression of RNA-binding proteins that influence mRNA turnover and translation. Aging (Albany NY) 2009, 1:681–698.
129. Gsponer J, Babu MM. Cellular strategies for regulating functional and nonfunctional protein aggregation. Cell Rep 2012, 2:1425–1437.
130. Bossy-Wetzel E, Schwarzenbacher R, Lipton SA. Molecular pathways to neurodegeneration. Published online: 01 July 2004 10: S2–S9. doi:10.1038/nm1067.
131. Jaisson S, Gillery P. Impaired proteostasis: role in the pathogenesis of diabetes mellitus. Diabetologia 2014, 57:1517–1527.
132. Lindberg I, Shorter J, Wiseman RL, Chiti F, Dickey CA, McLean PJ. Chaperones in neurodegeneration. J Neurosci 2015, 35:13853–13859.
133. Ojha J, Masilamoni G, Dunlap D, Udoff RA, Cashikar AG. Sequestration of toxic oligomers by HspB1 as a cytoprotective mechanism. Mol Cell Biol 2011, 31:3146–3157.
134. Binger KJ, Ecroyd H, Yang S, Carver JA, Howlett GJ, Griffin MDW. Avoiding the oligomeric state: B-crystallin inhibits fragmentation and induces dissociation of apolipoprotein C-II amyloid fibrils. FASEB J 2013, 27:1214–1222.
135. Cascella R, Conti S, Tatini F, Evangelisti E, Scartabelli T, Casamenti F, Wilson MR, Chiti F, Cecchi C. Extracellular chaperones prevent Aβ42-induced toxicity in rat brains. Biochim Biophys Acta Mol Basis Dis 2013, 1832:1217–1226.
136. Mannini B, Mulvihill E, Sgromo C, Cascella R, Khodarahmi R, Ramazzotti M, Dobson CM, Cecchi C, Chiti F. Toxicity of protein oligomers is rationalized by a function combining size and surface hydrophobicity. ACS Chem Biol 2014, 9:2309–2317.
137. Wolozin B. Regulated protein aggregation: stress granules and neurodegeneration. Mol Neurodegener 2012, 7:56.
138. de Groot NS, Sabate R, Ventura S. Amyloids in bacterial inclusion bodies. Trends Biochem Sci 2009, 34:408–416.
139. King OD, Gitler AD, Shorter J. The tip of the iceberg: RNA-binding proteins with prion-like domains in neurodegenerative disease. Brain Res 2012, 1462:61–80.
140. Vanderweyde T, Youmans K, Liu-Yesucevitz L, Wolozin B. Role of stress granules and RNA-binding proteins in neurodegeneration: a mini-review. Gerontology 2013, 59:524–533.
141. Guttman M, Rinn JL. Modular regulatory principles of large non-coding RNAs. Nature 2012, 482:339–346.
142. Lee S, Kopp F, Chang T-C, Sataluri A, Chen B, Sivakumar S, Yu H, Xie Y, Mendell JT. Noncoding RNA NORAD regulates genomic stability by sequestering PUMILIO proteins. Cell 2016, 164:69–80.
143. van der Lee R, Buljan M, Lang B, Weatheritt RJ, Daughdrill GW, Dunker AK, Fuxreiter M, Gough J, Gsponer J, Jones DT, et al. Classification of intrinsically disordered regions and proteins. Chem Rev 2014, 114:6589–6631.
144. Castello A, Hentze MW, Preiss T. Metabolic enzymes enjoying new partnerships as RNA-binding proteins. Trends Endocrinol Metab 2015, 26:746–757.
145. Sanchez de Groot N, Gomes RA, Villar-Pique A, Babu MM, Coelho AV, Ventura S. Proteome response at the edge of protein aggregation. Open Biol 2015, 5:140221–140221.