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A census of human RNA-binding proteins

Key Points

  • Recent advances in next-generation sequencing methods and quantitative mass spectrometry have renewed the interest in RNA biology and the genome-wide investigation of post-transcriptional gene regulatory proteins. A global census that systematically lists the number of factors involved in post-transcriptional gene regulation (PTGR) is currently not available. Here, we provide an overall summary of the proteins involved in interactions with all classes of RNAs based on our current knowledge of PTGR; this will guide future systems-wide studies of PTGR.

  • RNA-binding proteins (RBPs) are evolutionarily deeply conserved, and their structural domains diversified early in evolution.

  • RBPs are among the most abundant proteins in the cell and are generally ubiquitously expressed, which mirrors their central and conserved role in gene regulation.

  • Only ~2% of RBPs are tissue-specific, and most of these are mRNA- and non-coding RNA-binding proteins.

  • Diseases involving RBPs show characteristic phenotypes depending on the type of RNA (for example, mRNA, ribosomal RNA and tRNA) predominantly bound by the RBPs.

  • Correlated expression of RBPs across developmental processes can identify factors in shared PTGR pathways.

Abstract

Post-transcriptional gene regulation (PTGR) concerns processes involved in the maturation, transport, stability and translation of coding and non-coding RNAs. RNA-binding proteins (RBPs) and ribonucleoproteins coordinate RNA processing and PTGR. The introduction of large-scale quantitative methods, such as next-generation sequencing and modern protein mass spectrometry, has renewed interest in the investigation of PTGR and the protein factors involved at a systems-biology level. Here, we present a census of 1,542 manually curated RBPs that we have analysed for their interactions with different classes of RNA, their evolutionary conservation, their abundance and their tissue-specific expression. Our analysis is a critical step towards the comprehensive characterization of proteins involved in human RNA metabolism.

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Figure 1: Overview of the main post-transcriptional gene regulation pathways in eukaryotes.
Figure 2: Single or repeated presence of frequent RBDs in human genes.
Figure 3: Transcript abundance of RBPs and TFs across 16 different human tissues.
Figure 4: Target RNA classification and evolutionary conservation of RBP and TF paralogous families.
Figure 5: Tissue specificity of RBPs across 31 human tissues and organs.
Figure 6: Expression of RBPs across nine gestational stages of human fetal ovarian development.
Figure 7: Expression of RBPs across human fetal hippocampus development.

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References

  1. Cech, T. R. & Steitz, J. A. The noncoding RNA revolution — trashing old rules to forge new ones. Cell 157, 77–94 (2014). This is a concise overview of the different RNA classes in bacteria, archaea and eukaryotes, highlighting their discovery and regulatory roles.

    Article  CAS  PubMed  Google Scholar 

  2. Konig, J., Zarnack, K., Luscombe, N. M. & Ule, J. Protein–RNA interactions: new genomic technologies and perspectives. Nature Rev. Genet. 13, 77–83 (2011).

    Article  CAS  Google Scholar 

  3. Ascano, M., Hafner, M., Cekan, P., Gerstberger, S. & Tuschl, T. Identification of RNA–protein interaction networks using PAR-CLIP. Wiley Interdiscip. Rev. RNA 3, 159–177 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Gerstberger, S., Hafner, M. & Tuschl, T. Learning the language of post-transcriptional gene regulation. Genome Biol. 14, 130 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Mann, M. Functional and quantitative proteomics using SILAC. Nature Rev. Mol. Cell. Biol. 7, 952–958 (2006).

    Article  CAS  Google Scholar 

  6. Wang, Z., Gerstein, M. & Snyder, M. RNA-seq: a revolutionary tool for transcriptomics. Nature Rev. Genet. 10, 57–63 (2009).

    Article  CAS  PubMed  Google Scholar 

  7. Stoltenburg, R., Reinemann, C. & Strehlitz, B. SELEX — a (r)evolutionary method to generate high-affinity nucleic acid ligands. Biomol. Engineer. 24, 381–403 (2007).

    Article  CAS  Google Scholar 

  8. Ray, D. et al. A compendium of RNA-binding motifs for decoding gene regulation. Nature 499, 172–177 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Hamosh, A., Scott, A. F., Amberger, J. S., Bocchini, C. A. & McKusick, V. A. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 33, D514–D517 (2005).

    Article  CAS  PubMed  Google Scholar 

  10. Dreyfuss, G., Choi, Y. D. & Adam, S. A. Characterization of heterogeneous nuclear RNA–protein complexes in vivo with monoclonal antibodies. Mol. Cell. Biol. 4, 1104–1114 (1984).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Pinol-Roma, S., Choi, Y. D., Matunis, M. J. & Dreyfuss, G. Immunopurification of heterogeneous nuclear ribonucleoprotein particles reveals an assortment of RNA-binding proteins. Genes Dev. 2, 215–227 (1988).

    Article  CAS  PubMed  Google Scholar 

  12. Tenenbaum, S. A., Carson, C. C., Lager, P. J. & Keene, J. D. Identifying mRNA subsets in messenger ribonucleoprotein complexes by using cDNA arrays. Proc. Natl Acad. Sci. USA 97, 14085–14090 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Ascano, M., Gerstberger, S. & Tuschl, T. Multi-disciplinary methods to define RNA–protein interactions and regulatory networks. Curr. Opin. Genet. Dev. 23, 20–28 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. McHugh, C. A., Russell, P. & Guttman, M. Methods for comprehensive experimental identification of RNA–protein interactions. Genome Biol. 15, 203 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Murzin, A. G., Brenner, S. E., Hubbard, T. & Chothia, C. SCOP: a structural classification of proteins database for the investigation of sequences and structures. J. Mol. Biol. 247, 536–540 (1995).

    CAS  PubMed  Google Scholar 

  16. Letunic, I., Doerks, T. & Bork, P. SMART 6: recent updates and new developments. Nucleic Acids Res. 37, D229–D232 (2009).

    Article  CAS  PubMed  Google Scholar 

  17. Finn, R. D. et al. The Pfam protein families database. Nucleic Acids Res. 38, D211–D222 (2010).

    Article  CAS  PubMed  Google Scholar 

  18. Wilson, D. et al. SUPERFAMILY — sophisticated comparative genomics, data mining, visualization and phylogeny. Nucleic Acids Res. 37, D380–D386 (2009).

    Article  CAS  PubMed  Google Scholar 

  19. Marchler-Bauer, A. et al. CDD: conserved domains and protein three-dimensional structure. Nucleic Acids Res. 41, D348–D352 (2013).

    Article  CAS  PubMed  Google Scholar 

  20. Tatusov, R. L., Galperin, M. Y., Natale, D. A. & Koonin, E. V. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 28, 33–36 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Haft, D. H. et al. TIGRFAMs: a protein family resource for the functional identification of proteins. Nucleic Acids Res. 29, 41–43 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. McKee, A. E. et al. A genome-wide in situ hybridization map of RNA-binding proteins reveals anatomically restricted expression in the developing mouse brain. BMC Dev. Biol. 5, 14 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Cook, K. B., Kazan, H., Zuberi, K., Morris, Q. & Hughes, T. R. RBPDB: a database of RNA-binding specificities. Nucleic Acids Res. 39, D301–D308 (2011).

    Article  CAS  PubMed  Google Scholar 

  24. Galante, P. A. F. et al. A comprehensive in silico expression analysis of RNA binding proteins in normal and tumor tissue: Identification of potential players in tumor formation. RNA Biol. 6, 426–433 (2009).

    Article  CAS  PubMed  Google Scholar 

  25. Anantharaman, V., Koonin, E. V. & Aravind, L. Comparative genomics and evolution of proteins involved in RNA metabolism. Nucleic Acids Res. 30, 1427–1464 (2002). This is one of the first genome-wide comparative studies profiling the proteins involved in RNA metabolism, which concluded that RNA metabolism is the most evolutionary conserved of all cellular systems. It gives a detailed account of the structural, functional and phylogenetic relationships of protein domains in RNA metabolism, and analyses the number of genes containing RBDs across 30 different organisms.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Ashburner, M. et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nature Genet. 25, 25–29 (2000).

    Article  CAS  PubMed  Google Scholar 

  27. Castello, A. et al. Insights into RNA biology from an atlas of mammalian mRNA-binding proteins. Cell 149, 1393–1406 (2012).

    Article  CAS  PubMed  Google Scholar 

  28. Baltz, A. G. et al. The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. Mol. Cell 46, 674–690 (2012). References 27 and 28 describe the first large-scale crosslinking studies combined with quantitative mass spectrometry for the proteome-wide identification of poly(A)-RBPs.

    Article  CAS  PubMed  Google Scholar 

  29. Kwon, S. C. et al. The RNA-binding protein repertoire of embryonic stem cells. Nature Struct. Mol. Biol. 20, 1122–1130 (2013).

    Article  CAS  Google Scholar 

  30. Mitchell, S. F., Jain, S., She, M. & Parker, R. Global analysis of yeast mRNPs. Nature Struct. Mol. Biol. 20, 127–133 (2013).

    Article  CAS  Google Scholar 

  31. Eddy, S. R. Profile hidden Markov models. Bioinformatics 14, 755–763 (1998).

    Article  CAS  PubMed  Google Scholar 

  32. Lunde, B. M., Moore, C. & Varani, G. RNA-binding proteins: modular design for efficient function. Nature Rev. Mol. Cell. Biol. 8, 479–490 (2007). This review summarizes the most commonly found RBDs and gives an overview of their structural characteristics and binding modes.

    Article  CAS  Google Scholar 

  33. Burd, C. G. & Dreyfuss, G. Conserved structures and diversity of functions of RNA-binding proteins. Science 265, 615–621 (1994).

    Article  CAS  PubMed  Google Scholar 

  34. Arcus, V. OB-fold domains: a snapshot of the evolution of sequence, structure and function. Curr. Opin. Struct. Biol. 12, 794–801 (2002).

    Article  CAS  PubMed  Google Scholar 

  35. Kim, C. A. & Bowie, J. U. SAM domains: uniform structure, diversity of function. Trends Biochem. Sci. 28, 625–628 (2003).

    Article  CAS  PubMed  Google Scholar 

  36. Rajkowitsch, L. et al. RNA chaperones, RNA annealers and RNA helicases. RNA Biol. 4, 118–130 (2007).

    Article  CAS  PubMed  Google Scholar 

  37. Glisovic, T., Bachorik, J. L., Yong, J. & Dreyfuss, G. RNA-binding proteins and post-transcriptional gene regulation. FEBS Lett. 582, 1977–1986 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Sommerville, J. Activities of cold-shock domain proteins in translation control. Bioessays 21, 319–325 (1999).

    Article  CAS  PubMed  Google Scholar 

  39. Mihailovich, M., Militti, C., Gabaldón, T. & Gebauer, F. Eukaryotic cold shock domain proteins: highly versatile regulators of gene expression. Bioessays 32, 109–118 (2010).

    Article  CAS  PubMed  Google Scholar 

  40. Curry, S., Kotik-Kogan, O., Conte, M. R. & Brick, P. Getting to the end of RNA: structural analysis of protein recognition of 5′ and 3′ termini. Biochim. Biophys. Acta. 1789, 653–666 (2009).

    Article  CAS  PubMed  Google Scholar 

  41. Auweter, S. D., Oberstrass, F. C. & Allain, F. H. T. Sequence-specific binding of single-stranded RNA: is there a code for recognition? Nucleic Acids Res. 34, 4943–4959 (2006). This is a highly detailed review on the structural determinants of RNA binding for ssRBDs.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Singh, R. & Valcarcel, J. Building specificity with nonspecific RNA-binding proteins. Nature Struct. Mol. Biol. 12, 645–653 (2005).

    Article  CAS  Google Scholar 

  43. Kuchta, K., Knizewski, L., Wyrwicz, L. S., Rychlewski, L. & Ginalski, K. Comprehensive classification of nucleotidyltransferase fold proteins: identification of novel families and their representatives in human. Nucleic Acids Res. 37, 7701–7714 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Valverde, R., Edwards, L. & Regan, L. Structure and function of KH domains. FEBS J. 275, 2712–2726 (2008).

    Article  CAS  PubMed  Google Scholar 

  45. Masliah, G., Barraud, P. & Allain, F. H. T. RNA recognition by double-stranded RNA binding domains: a matter of shape and sequence. Cell. Mol. Life Sci. 70, 1875–1895 (2013).

    CAS  PubMed  Google Scholar 

  46. Chang, K.-Y. & Ramos, A. The double-stranded RNA-binding motif, a versatile macromolecular docking platform. FEBS J. 272, 2109–2117 (2005).

    Article  CAS  PubMed  Google Scholar 

  47. Wilusz, C. J. & Wilusz, J. Eukaryotic Lsm proteins: lessons from bacteria. Nature Struct. Mol. Biol. 12, 1031–1036 (2005).

    Article  CAS  Google Scholar 

  48. Tharun, S. Roles of eukaryotic Lsm proteins in the regulation of mRNA function. Int. Rev. Cell. Mol. Biol. 272, 149–189 (2009).

    Article  CAS  PubMed  Google Scholar 

  49. Wang, X., McLachlan, J., Zamore, P. D. & Hall, T. M. T. Modular recognition of RNA by a human pumilio-homology domain. Cell 110, 501–512 (2002).

    Article  CAS  PubMed  Google Scholar 

  50. Linder, P. & Jankowsky, E. From unwinding to clamping — the DEAD box RNA helicase family. Nature Rev. Mol. Cell. Biol. 12, 505–516 (2011).

    Article  CAS  Google Scholar 

  51. Jankowsky, E. RNA helicases at work: binding and rearranging. Trends Biochem. Sci. 36, 19–29 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Tanner, N. K. & Linder, P. DExD/H box RNA helicases: from generic motors to specific dissociation functions. Mol. Cell 8, 251–262 (2001).

    Article  CAS  PubMed  Google Scholar 

  53. Rocak, S. & Linder, P. DEAD-box proteins: the driving forces behind RNA metabolism. Nature Rev. Mol. Cell. Biol. 5, 232–241 (2004).

    Article  CAS  Google Scholar 

  54. Meister, G. Argonaute proteins: functional insights and emerging roles. Nature Rev. Genet. 14, 447–459 (2013).

    Article  CAS  PubMed  Google Scholar 

  55. Draper, D. E. & Reynaldo, L. P. RNA binding strategies of ribosomal proteins. Nucleic Acids Res. 27, 381–388 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Keren, H., Lev-Maor, G. & Ast, G. Alternative splicing and evolution: diversification, exon definition and function. Nature Rev. Genet. 11, 345–355 (2010).

    Article  CAS  PubMed  Google Scholar 

  57. Chen, M. & Manley, J. L. Mechanisms of alternative splicing regulation: insights from molecular and genomics approaches. Nature Rev. Mol. Cell. Biol. 10, 741–754 (2009).

    Article  CAS  Google Scholar 

  58. Vaquerizas, J. M., Kummerfeld, S. K., Teichmann, S. A. & Luscombe, N. M. A census of human transcription factors: function, expression and evolution. Nature Rev. Genet. 10, 252–263 (2009). Analogous to this Analysis, this article presents a catalogue for curated human TFs. It describes a census of ~1,400 TFs and gives an overview of common structural domains, tissue-specific expression and evolutionary conservation.

    Article  CAS  PubMed  Google Scholar 

  59. Kechavarzi, B. & Janga, S. C. Dissecting the expression landscape of RNA-binding proteins in human cancers. Genome Biol. 15, R14 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Boisvert, F.-M., van Koningsbruggen, S., Navascués, J. & Lamond, A. I. The multifunctional nucleolus. Nature Rev. Mol. Cell. Biol. 8, 574–585 (2007).

    Article  CAS  Google Scholar 

  61. Montanaro, L., Treré, D. & Derenzini, M. Nucleolus, ribosomes, and cancer. Am. J. Pathol. 173, 301–310 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Ruggero, D. & Pandolfi, P. P. Does the ribosome translate cancer? Nature Rev. Cancer 3, 179–192 (2003).

    Article  CAS  Google Scholar 

  63. Ma, T. et al. Suppression of eIF2α kinases alleviates Alzheimer's disease-related plasticity and memory deficits. Nature Neurosci. 16, 1299–1305 (2013).

    Article  CAS  PubMed  Google Scholar 

  64. Martin, I. et al. Ribosomal protein s15 phosphorylation mediates LRRK2 neurodegeneration in Parkinson's disease. Cell 157, 472–485 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Klein, C. & Westenberger, A. Genetics of Parkinson's disease. Cold Spring Harb. Perspect. Med. 2, a008888 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Scheper, G. C., van der Knaap, M. S. & Proud, C. G. Translation matters: protein synthesis defects in inherited disease. Nature Rev. Genet. 8, 711–723 (2007). This is a comprehensive review of mRNA-binding, tRNA-binding and ribosomal proteins involved in translation, genetic mutations of which cause human diseases.

    Article  CAS  PubMed  Google Scholar 

  67. Silvera, D., Formenti, S. C. & Schneider, R. J. Translational control in cancer. Nature Rev. Cancer 10, 254–266 (2010). This article discusses dysregulation of translation in human cancers and the factors involved, the loss or increased expression of which are found in different cancers, as well as the relevant druggable targets.

    Article  CAS  Google Scholar 

  68. Hein, N., Hannan, K. M., George, A. J., Sanij, E. & Hannan, R. D. The nucleolus: an emerging target for cancer therapy. Trends Mol. Med. 19, 643–654 (2013).

    Article  CAS  PubMed  Google Scholar 

  69. Skrticc´, M. et al. Inhibition of mitochondrial translation as a therapeutic strategy for human acute myeloid leukemia. Cancer Cell 20, 674–688 (2011).

    Article  CAS  Google Scholar 

  70. Grzmil, M. & Hemmings, B. A. Translation regulation as a therapeutic target in cancer. Cancer Res. 72, 3891–3900 (2012). This paper describes different druggable targets for regulating aberrant protein translation in diseases such as cancers.

    Article  CAS  PubMed  Google Scholar 

  71. Macias, S. et al. DGCR8 HITS-CLIP reveals novel functions for the Microprocessor. Nature Struct. Mol. Biol. 19, 760–766 (2012).

    Article  CAS  Google Scholar 

  72. Hafner, M. et al. Identification of mRNAs bound and regulated by human LIN28 proteins and molecular requirements for RNA recognition. RNA 19, 613–626 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Wilbert, M. L. et al. LIN28 binds messenger RNAs at GGAGA motifs and regulates splicing factor abundance. Mol. Cell 48, 195–206 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Cho, J. et al. LIN28A is a suppressor of ER-associated translation in embryonic stem cells. Cell 151, 765–777 (2012).

    Article  CAS  PubMed  Google Scholar 

  75. Tafforeau, L. et al. The complexity of human ribosome biogenesis revealed by systematic nucleolar screening of pre-rRNA processing factors. Mol. Cell 51, 539–551 (2013).

    Article  CAS  PubMed  Google Scholar 

  76. Henras, A. K. et al. The post-transcriptional steps of eukaryotic ribosome biogenesis. Cell. Mol. Life Sci. 65, 2334–2359 (2008).

    Article  CAS  PubMed  Google Scholar 

  77. Bratkovicˇ, T. & Rogelj, B. The many faces of small nucleolar RNAs. Biochim. Biophys. Acta. 1839, 438–443 (2014).

    Article  PubMed  CAS  Google Scholar 

  78. Yin, Q.-F. et al. Long noncoding RNAs with snoRNA ends. Mol. Cell 48, 219–230 (2012).

    Article  CAS  PubMed  Google Scholar 

  79. Phizicky, E. M. & Hopper, A. K. tRNA biology charges to the front. Genes Dev. 24, 1832–1860 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Hopper, A. K., Pai, D. A. & Engelke, D. R. Cellular dynamics of tRNAs and their genes. FEBS Lett. 584, 310–317 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Kiss, T. Biogenesis of small nuclear RNPs. J. Cell Sci. 117, 5949–5951 (2004).

    Article  CAS  PubMed  Google Scholar 

  82. Phipps, K. R., Charette, J. M. & Baserga, S. J. The small subunit processome in ribosome biogenesis — progress and prospects. Wiley Interdiscip. Rev. RNA 2, 1–21 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Hussain, S. et al. NSun2-mediated cytosine-5 methylation of vault noncoding RNA determines its processing into regulatory small RNAs. Cell Rep. 4, 255–261 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Sibbritt, T., Patel, H. R. & Preiss, T. Mapping and significance of the mRNA methylome. Wiley Interdiscip. Rev. RNA 4, 397–422 (2013).

    Article  CAS  PubMed  Google Scholar 

  85. Spencer, C. M. et al. Exaggerated behavioral phenotypes in Fmr1/Fxr2 double knockout mice reveal a functional genetic interaction between fragile X-related proteins. Hum. Mol. Genet. 15, 1984–1994 (2006).

    Article  CAS  PubMed  Google Scholar 

  86. Todd, A. E., Orengo, C. A. & Thornton, J. M. Evolution of function in protein superfamilies, from a structural perspective. J. Mol. Biol. 307, 1113–1143 (2001).

    Article  CAS  PubMed  Google Scholar 

  87. Woolford, J. L. & Baserga, S. J. Ribosome biogenesis in the yeast Saccharomyces cerevisiae. Genetics 195, 643–681 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Vilella, A. J. et al. EnsemblCompara GeneTrees: complete, duplication-aware phylogenetic trees in vertebrates. Genome Res. 19, 327–335 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Fairman-Williams, M. E., Guenther, U.-P. & Jankowsky, E. SF1 and SF2 helicases: family matters. Curr. Opin. Struct. Biol. 20, 313–324 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Krishna, S. S., Majumdar, I. & Grishin, N. V. Structural classification of zinc fingers: survey and summary. Nucleic Acids Res. 31, 532–550 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Kerner, P., Degnan, S. M., Marchand, L., Degnan, B. M. & Vervoort, M. Evolution of RNA-binding proteins in animals: insights from genome-wide analysis in the sponge Amphimedon queenslandica. Mol. Biol. Evol. 28, 2289–2303 (2011).

    Article  CAS  PubMed  Google Scholar 

  92. Granneman, S. & Baserga, S. J. Ribosome biogenesis: of knobs and RNA processing. Exp. Cell Res. 296, 43–50 (2004).

    Article  CAS  PubMed  Google Scholar 

  93. Winter, E. E., Goodstadt, L. & Ponting, C. P. Elevated rates of protein secretion, evolution, and disease among tissue-specific genes. Genome Res. 14, 54–61 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Freilich, S. et al. Relationship between the tissue-specificity of mouse gene expression and the evolutionary origin and function of the proteins. Genome Biol. 6, R56 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  95. Ramsköld, D., Wang, E. T., Burge, C. B. & Sandberg, R. An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. PLoS Comput. Biol. 5, e1000598 (2009). This is one of the first RNA-seq studies to investigate the tissue specificity of genes based on mRNA expression levels in 16 human tissues and cell types.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  96. Dezso, Z. et al. A comprehensive functional analysis of tissue specificity of human gene expression. BMC Biol. 6, 49 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  97. Guo, H., Ingolia, N. T., Weissman, J. S. & Bartel, D. P. Mammalian microRNAs predominantly act to decrease target mRNA levels. Nature 466, 835–840 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Schwanhausser, B. et al. Global quantification of mammalian gene expression control. Nature 473, 337–342 (2011).

    Article  PubMed  CAS  Google Scholar 

  99. Thomson, T. & Lin, H. The biogenesis and function of PIWI proteins and piRNAs: progress and prospect. Annu. Rev. Cell Dev. Biol. 25, 355–376 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Li, Q., Lee, J.-A. & Black, D. L. Neuronal regulation of alternative pre-mRNA splicing. Nature Rev. Neurosci. 8, 819–831 (2007).

    Article  CAS  Google Scholar 

  101. Castle, J. C. et al. Digital genome-wide ncRNA expression, including snoRNAs, across 11 human tissues using polyA-neutral amplification. PLoS ONE 5, e11779 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  102. Dittmar, K. A., Goodenbour, J. M. & Pan, T. Tissue-specific differences in human transfer RNA expression. PLoS Genet. 2, e221 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  103. Plotkin, J. B. & Kudla, G. Synonymous but not the same: the causes and consequences of codon bias. Nature Rev. Genet. 12, 32–42 (2011).

    Article  CAS  PubMed  Google Scholar 

  104. Warner, J. R. & McIntosh, K. B. How common are extraribosomal functions of ribosomal proteins? Mol. Cell 34, 3–11 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Xue, S. & Barna, M. Specialized ribosomes: a new frontier in gene regulation and organismal biology. Nature Rev. Mol. Cell. Biol. 13, 355–369 (2012).

    Article  CAS  Google Scholar 

  106. Luteijn, M. J. & Ketting, R. F. PIWI-interacting RNAs: from generation to transgenerational epigenetics. Nature Rev. Genet. 14, 523–534 (2013).

    Article  CAS  PubMed  Google Scholar 

  107. Siomi, M. C., Sato, K., Pezic, D. & Aravin, A. A. PIWI-interacting small RNAs: the vanguard of genome defence. Nature Rev. Mol. Cell. Biol. 12, 246–258 (2011).

    Article  CAS  Google Scholar 

  108. Seydoux, G. & Braun, R. E. Pathway to totipotency: Lessons from germ cells. Cell 127, 891–904 (2006).

    Article  CAS  PubMed  Google Scholar 

  109. Kotaja, N. & Sassone-Corsi, P. The chromatoid body: a germ-cell-specific RNA-processing centre. Nature Rev. Mol. Cell. Biol. 8, 85–90 (2007).

    Article  CAS  Google Scholar 

  110. Voronina, E., Seydoux, G., Sassone-Corsi, P. & Nagamori, I. RNA granules in germ cells. Cold Spring Harb. Perspect. Biol. 3, a002774 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  111. Kang, M. K. & Han, S. J. Post-transcriptional and post-translational regulation during mouse oocyte maturation. BMB Rep. 44, 147–157 (2011).

    Article  CAS  PubMed  Google Scholar 

  112. Houmard, B. et al. Global gene expression in the human fetal testis and ovary. Biol. Reprod. 81, 438–443 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Brook, M., Smith, J. W. S. & Gray, N. K. The DAZL and PABP families: RNA-binding proteins with interrelated roles in translational control in oocytes. Reproduction 137, 595–617 (2009).

    Article  CAS  PubMed  Google Scholar 

  114. Reynolds, N. & Cooke, H. J. Role of the DAZ genes in male fertility. Reprod. Biomed. Online 10, 72–80 (2005).

    Article  CAS  PubMed  Google Scholar 

  115. Lasko, P. The DEAD-box helicase Vasa: evidence for a multiplicity of functions in RNA processes and developmental biology. Biochim. Biophys. Acta. 1829, 810–816 (2013).

    Article  CAS  PubMed  Google Scholar 

  116. Frost, R. J. A. et al. MOV10L1 is necessary for protection of spermatocytes against retrotransposons by PIWI-interacting RNAs. Proc. Natl Acad. Sci. USA 107, 11847–11852 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Zheng, K. et al. Mouse MOV10L1 associates with PIWI proteins and is an essential component of the PIWI-interacting RNA (piRNA) pathway. Proc. Natl Acad. Sci. USA 107, 11841–11846 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Dufau, M. L. & Tsai-Morris, C.-H. Gonadotropin-regulated testicular helicase (GRTH/DDX25): an essential regulator of spermatogenesis. Trends Endocrinol. Metab. 18, 314–320 (2007).

    Article  CAS  PubMed  Google Scholar 

  119. Rosenberg, H. F. in Ribonucleases Ch. 2 (ed. Nicholson, A. W.) 35–53 (Springer, 2011).

    Book  Google Scholar 

  120. Yisraeli, J. K. VICKZ proteins: a multi-talented family of regulatory RNA-binding proteins. Biol. Cell 97, 87–96 (2005).

    Article  CAS  PubMed  Google Scholar 

  121. Simone, L. E. & Keene, J. D. Mechanisms coordinating ELAV/Hu mRNA regulons. Curr. Opin. Genet. Dev. 23, 35–43 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Ascano, M. et al. FMRP targets distinct mRNA sequence elements to regulate protein expression. Nature 492, 382–386 (2012). References 2, 14 and 122 give comprehensive and balanced accounts of different methods developed for the genome-wide identification of RBPs and RBP-binding sites.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Wang, T., Bray, S. M. & Warren, S. T. New perspectives on the biology of fragile X syndrome. Curr. Opin. Genet. Dev. 22, 256–263 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Mientjes, E. J. et al. Fxr1 knockout mice show a striated muscle phenotype: implications for Fxr1p function in vivo. Hum. Mol. Genet. 13, 1291–1302 (2004).

    Article  CAS  PubMed  Google Scholar 

  125. Narla, A. & Ebert, B. L. Ribosomopathies: human disorders of ribosome dysfunction. Blood 115, 3196–3205 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Lukong, K. E., Chang, K. W., Khandjian, E. W. & Richard, S. RNA-binding proteins in human genetic disease. Trends Genet. 24, 416–425 (2008).

    Article  CAS  PubMed  Google Scholar 

  127. Cooper, T. A., Wan, L. & Dreyfuss, G. RNA and disease. Cell 136, 777–793 (2009). This is a comprehensive overview of RNA- and RBP-based genetic diseases caused by mutations in RNAs and RBPs, and highlights the most prominent examples.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Ramaswami, M., Taylor, J. P. & Parker, R. Altered ribostasis: RNA–protein granules in degenerative disorders. Cell 154, 727–736 (2013). This paper highlights prion-like RBP aggregation in human diseases caused by mutations in RBPs.

    Article  CAS  PubMed  Google Scholar 

  129. Buchan, J. R., Kolaitis, R.-M., Taylor, J. P. & Parker, R. Eukaryotic stress granules are cleared by autophagy and Cdc48/VCP function. Cell 153, 1461–1474 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Liu-Yesucevitz, L. et al. Local RNA translation at the synapse and in disease. J. Neurosci. 31, 16086–16093 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Lagier-Tourenne, C., Polymenidou, M. & Cleveland, D. W. TDP-43 and FUS/TLS: emerging roles in RNA processing and neurodegeneration. Hum. Mol. Genet. 19, R46–R64 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Kim, H. J. et al. Mutations in prion-like domains in hnRNPA2B1 and hnRNPA1 cause multisystem proteinopathy and ALS. Nature 495, 467–473 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Orr, H. T. et al. Expansion of an unstable trinucleotide CAG repeat in spinocerebellar ataxia type 1. Nature Genet. 4, 221–226 (1993).

    Article  CAS  PubMed  Google Scholar 

  134. Banfi, S. et al. Identification and characterization of the gene causing type 1 spinocerebellar ataxia. Nature Genet. 7, 513–520 (1994).

    Article  CAS  PubMed  Google Scholar 

  135. Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Echeverria, G. V. & Cooper, T. A. RNA-binding proteins in microsatellite expansion disorders: mediators of RNA toxicity. Brain Res. 1462, 100–111 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Budde, B. S. et al. tRNA splicing endonuclease mutations cause pontocerebellar hypoplasia. Nature Genet. 40, 1113–1118 (2008).

    Article  CAS  PubMed  Google Scholar 

  138. Yao, P. & Fox, P. L. Aminoacyl-tRNA synthetases in medicine and disease. EMBO Mol. Med. 5, 332–343 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Rice, G. I. et al. Mutations involved in Aicardi–Goutières syndrome implicate SAMHD1 as regulator of the innate immune response. Nature Genet. 41, 829–832 (2009).

    Article  CAS  PubMed  Google Scholar 

  140. Crow, Y. J. et al. Mutations in genes encoding ribonuclease H2 subunits cause Aicardi–Goutières syndrome and mimic congenital viral brain infection. Nature Genet. 38, 910–916 (2006).

    Article  CAS  PubMed  Google Scholar 

  141. Dreyfuss, G., Kim, V. N. & Kataoka, N. Messenger-RNA-binding proteins and the messages they carry. Nature Rev. Mol. Cell. Biol. 3, 195–205 (2002).

    Article  CAS  Google Scholar 

  142. Müller-McNicoll, M. & Neugebauer, K. M. How cells get the message: dynamic assembly and function of mRNA–protein complexes. Nature Rev. Genet. 14, 275–287 (2013).

    Article  PubMed  CAS  Google Scholar 

  143. Keene, J. D. RNA regulons: coordination of post-transcriptional events. Nature Rev. Genet. 8, 533–543 (2007).

    Article  CAS  PubMed  Google Scholar 

  144. Mitchell, S. F. & Parker, R. Principles and properties of eukaryotic mRNPs. Mol. Cell 54, 547–558 (2014).

    Article  CAS  PubMed  Google Scholar 

  145. Kornblihtt, A. R. et al. Alternative splicing: a pivotal step between eukaryotic transcription and translation. Nature Rev. Mol. Cell. Biol. 14, 153–165 (2013).

    Article  CAS  Google Scholar 

  146. Smith, C. W. & Valcarcel, J. Alternative pre-mRNA splicing: the logic of combinatorial control. Trends Biochem. Sci. 25, 381–388 (2000).

    Article  CAS  PubMed  Google Scholar 

  147. Wahl, M. C., Will, C. L. & Luhrmann, R. The spliceosome: design principles of a dynamic RNP machine. Cell 136, 701–718 (2009).

    Article  CAS  PubMed  Google Scholar 

  148. Kalsotra, A. & Cooper, T. A. Functional consequences of developmentally regulated alternative splicing. Nature Rev. Genet. 12, 715–729 (2011).

    Article  CAS  PubMed  Google Scholar 

  149. Kaida, D. et al. U1 snRNP protects pre-mRNAs from premature cleavage and polyadenylation. Nature 468, 664–668 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  150. Berg, M. G. et al. U1 snRNP determines mRNA length and regulates isoform expression. Cell 150, 53–64 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Mukherjee, N. et al. Integrative regulatory mapping indicates that the RNA-binding protein HuR couples pre-mRNA processing and mRNA stability. Mol. Cell 43, 327–339 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Kedde, M. et al. A Pumilio-induced RNA structure switch in p27-3′ UTR controls miR-221 and miR-222 accessibility. Nature Cell Biol. 12, 1014–1020 (2010).

    Article  CAS  PubMed  Google Scholar 

  153. Anderson, P. & Kedersha, N. RNA granules: post-transcriptional and epigenetic modulators of gene expression. Nature Rev. Mol. Cell. Biol. 10, 430–436 (2009).

    Article  CAS  Google Scholar 

  154. Hanna, J. H., Saha, K. & Jaenisch, R. Pluripotency and cellular reprogramming: facts, hypotheses, unresolved issues. Cell 143, 508–525 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Cirillo, D. et al. Constitutive patterns of gene expression regulated by RNA-binding proteins. Genome Biol. 15, R13 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  156. Mittal, N., Roy, N., Babu, M. M. & Janga, S. C. Dissecting the expression dynamics of RNA-binding proteins in posttranscriptional regulatory networks. Proc. Natl Acad. Sci. USA 106, 20300–20305 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Norbury, C. J. Cytoplasmic RNA: a case of the tail wagging the dog. Nature Rev. Cancer 13, 643–653 (2013).

    Article  CAS  Google Scholar 

  158. Lianoglou, S., Garg, V., Yang, J. L., Leslie, C. S. & Mayr, C. Ubiquitously transcribed genes use alternative polyadenylation to achieve tissue-specific expression. Genes Dev. 27, 2380–2396 (2013). This is a detailed study profiling genome-wide alternative polyadenylation sites in mRNAs across 12 human cell lines and tissues. The authors conclude that genes with multiple 3′UTRs tend to vary 3′UTR ratios across tissues, whereas genes with single 3′UTRs vary mRNA expression levels.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  159. Di Giammartino, D. C., Nishida, K. & Manley, J. L. Mechanisms and consequences of alternative polyadenylation. Mol. Cell 43, 853–866 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. MacDonald, C. C. & McMahon, K. W. Tissue-specific mechanisms of alternative polyadenylation: testis, brain, and beyond. Wiley Interdiscip. Rev. RNA 1, 494–501 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  161. Oktem, O. & Urman, B. Understanding follicle growth in vivo. Hum. Reprod. 25, 2944–2954 (2010).

    Article  PubMed  Google Scholar 

  162. Bell, J. L. et al. Insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs): post-transcriptional drivers of cancer progression? Cell. Mol. Life Sci. 70, 2657–2675 (2013).

    Article  CAS  PubMed  Google Scholar 

  163. Kee, K., Angeles, V. T., Flores, M., Nguyen, H. N. & Reijo Pera, R. A. Human DAZL, DAZ and BOULE genes modulate primordial germ-cell and haploid gamete formation. Nature 462, 222–225 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Bramham, C. R. & Wells, D. G. Dendritic mRNA: transport, translation and function. Nature Rev. Neurosci. 8, 776–789 (2007).

    Article  CAS  Google Scholar 

  165. Jung, H., Gkogkas, C. G., Sonenberg, N. & Holt, C. E. Remote control of gene function by local translation. Cell 157, 26–40 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  166. Kandel, E. R., Dudai, Y. & Mayford, M. R. The molecular and systems biology of memory. Cell 157, 163–186 (2014).

    Article  CAS  PubMed  Google Scholar 

  167. Sutton, M. A. & Schuman, E. M. Dendritic protein synthesis, synaptic plasticity, and memory. Cell 127, 49–58 (2006).

    Article  CAS  PubMed  Google Scholar 

  168. Hawrylycz, M. J. et al. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 489, 391–399 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  169. Miller, J. A. et al. Transcriptional landscape of the prenatal human brain. Nature 508, 199–206 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Mody, M. et al. Genome-wide gene expression profiles of the developing mouse hippocampus. Proc. Natl Acad. Sci. USA 98, 8862–8867 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  171. Thornton, J. E. & Gregory, R. I. How does Lin28 let-7 control development and disease? Trends Cell Biol. 22, 474–482 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. Gehman, L. T. et al. The splicing regulator Rbfox1 (A2BP1) controls neuronal excitation in the mammalian brain. Nature Genet. 43, 706–711 (2011).

    Article  CAS  PubMed  Google Scholar 

  173. Arnold, S. E. & Trojanowski, J. Q. Human fetal hippocampal development: I. Cytoarchitecture, myeloarchitecture, and neuronal morphologic features. J. Comp. Neurol. 367, 274–292 (1996).

    Article  CAS  PubMed  Google Scholar 

  174. Greenway, M. J. et al. ANG mutations segregate with familial and 'sporadic' amyotrophic lateral sclerosis. Nature Genet. 38, 411–413 (2006).

    Article  CAS  PubMed  Google Scholar 

  175. Henneke, M. et al. RNASET2-deficient cystic leukoencephalopathy resembles congenital cytomegalovirus brain infection. Nature Genet. 41, 773–775 (2009).

    Article  CAS  PubMed  Google Scholar 

  176. Thiyagarajan, N., Ferguson, R., Subramanian, V. & Acharya, K. R. Structural and molecular insights into the mechanism of action of human angiogenin-ALS variants in neurons. Nature Commun. 3, 1121 (2012).

    Article  CAS  Google Scholar 

  177. Skorupa, A. et al. Motoneurons secrete angiogenin to induce RNA cleavage in astroglia. J. Neurosci. 32, 5024–5038 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  178. Mukherjee, N. et al. Global target mRNA specification and regulation by the RNA-binding protein ZFP36. Genome Biol. 15, R12 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  179. Fabian, M. R. et al. miRNA-mediated deadenylation is orchestrated by GW182 through two conserved motifs that interact with CCR4–NOT. Nature Struct. Mol. Biol. 18, 1211–1217 (2011).

    Article  CAS  Google Scholar 

  180. Brooks, S. A. & Blackshear, P. J. Tristetraprolin (TTP): Interactions with mRNA and proteins, and current thoughts on mechanisms of action. Biochim. Biophys. Acta. 1829, 666–679 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  181. Boulanger, L. M. Immune proteins in brain development and synaptic plasticity. Neuron 64, 93–109 (2009).

    Article  CAS  PubMed  Google Scholar 

  182. Deverman, B. E. & Patterson, P. H. Cytokines and CNS development. Neuron 64, 61–78 (2009).

    Article  CAS  PubMed  Google Scholar 

  183. Zhang, A. et al. The spatio-temporal expression of MHC class I molecules during human hippocampal formation development. Brain Res. 1529, 26–38 (2013).

    Article  CAS  PubMed  Google Scholar 

  184. Meyer, K. D. & Jaffrey, S. R. The dynamic epitranscriptome: N6-methyladenosine and gene expression control. Nature Rev. Mol. Cell. Biol. 15, 313–326 (2014).

    Article  CAS  Google Scholar 

  185. Ulitsky, I. & Bartel, D. P. lincRNAs: Genomics, evolution, and mechanisms. Cell 154, 26–46 (2013). This is a detailed review on the emerging roles of lncRNAs in gene regulation.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  186. Ingolia, N. T. Ribosome profiling: new views of translation, from single codons to genome scale. Nature Rev. Genet. 15, 205–213 (2014). This article gives an overview of ribosome profiling, which is a method to measure actively translating RNAs genome-wide. Next to mass spectrometry, ribosome profiling allows the quantification of expressed proteins in the cell and also the measurement of translation rates of mRNAs.

    Article  CAS  PubMed  Google Scholar 

  187. Wan, Y. et al. Landscape and variation of RNA secondary structure across the human transcriptome. Nature 505, 706–709 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  188. Ding, Y. et al. In vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features. Nature 505, 696–700 (2014).

    Article  CAS  PubMed  Google Scholar 

  189. Rouskin, S., Zubradt, M., Washietl, S., Kellis, M. & Weissman, J. S. Genome-wide probing of RNA structure reveals active unfolding of mRNA structures in vivo. Nature 505, 701–705 (2014).

    Article  CAS  PubMed  Google Scholar 

  190. Ozsolak, F. & Milos, P. M. RNA sequencing: advances, challenges and opportunities. Nature Rev. Genet. 12, 87–98 (2011).

    Article  CAS  PubMed  Google Scholar 

  191. Pritchard, C. C., Cheng, H. H. & Tewari, M. MicroRNA profiling: approaches and considerations. Nature Rev. Genet. 13, 358–369 (2012). References 189 and 191 describe transcriptome-wide methods for determining RNA structures in vivo , which give insights into RNA accessibility and regulation.

    Article  CAS  PubMed  Google Scholar 

  192. Jan, C. H., Friedman, R. C., Ruby, J. G. & Bartel, D. P. Formation, regulation and evolution of Caenorhabditis elegans 3′UTRs. Nature 469, 97–101 (2011). This study describes one of the first RNA-seq methods to accurately profile alternative polyadenylation sites genome-wide.

    Article  CAS  PubMed  Google Scholar 

  193. Chang, H., Lim, J., Ha, M. & Kim, V. N. TAIL-seq: Genome-wide determination of poly(A) tail length and 3′ end modifications. Mol. Cell 53, 1044–1052 (2014).

    Article  CAS  PubMed  Google Scholar 

  194. Subtelny, A. O., Eichhorn, S. W., Chen, G. R., Sive, H. & Bartel, D. P. Poly(A)-tail profiling reveals an embryonic switch in translational control. Nature 508, 66–71 (2014). This paper details a protocol to map genome-wide mRNA poly(A) tail length in vivo.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  195. Maraia, R. J. & Lamichhane, T. N. 3′ processing of eukaryotic precursor tRNAs. Wiley Interdiscip. Rev. RNA 2, 362–375 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  196. Thomson, E., Ferreira-Cerca, S. & Hurt, E. Eukaryotic ribosome biogenesis at a glance. J. Cell Sci. 126, 4815–4821 (2013).

    Article  CAS  PubMed  Google Scholar 

  197. Lafontaine, D. L. & Tollervey, D. The function and synthesis of ribosomes. Nature Rev. Mol. Cell. Biol. 2, 514–520 (2001).

    Article  CAS  Google Scholar 

  198. Mroczek, S. & Dziembowski, A. U6 RNA biogenesis and disease association. Wiley Interdiscip. Rev. RNA 4, 581–592 (2013).

    Article  CAS  PubMed  Google Scholar 

  199. Jackson, R. J., Hellen, C. U. T. & Pestova, T. V. The mechanism of eukaryotic translation initiation and principles of its regulation. Nature Rev. Mol. Cell. Biol. 11, 113–127 (2010).

    Article  CAS  Google Scholar 

  200. Buchan, J. R. & Parker, R. Eukaryotic stress granules: The ins and outs of translation. Mol. Cell 36, 932–941 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  201. Parker, R. & Sheth, U. P bodies and the control of mRNA translation and degradation. Mol. Cell 25, 635–646 (2007).

    Article  CAS  PubMed  Google Scholar 

  202. Garneau, N. L., Wilusz, J. & Wilusz, C. J. The highways and byways of mRNA decay. Nature Rev. Mol. Cell. Biol. 8, 113–126 (2007).

    Article  CAS  Google Scholar 

  203. Kim, V. N., Han, J. & Siomi, M. C. Biogenesis of small RNAs in animals. Nature Rev. Mol. Cell. Biol. 10, 126–139 (2009).

    Article  CAS  Google Scholar 

  204. Peterlin, B. M., Brogie, J. E. & Price, D. H. 7SK snRNA: a noncoding RNA that plays a major role in regulating eukaryotic transcription. Wiley Interdiscip. Rev. RNA 3, 92–103 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  205. Fox, A. H. & Lamond, A. I. Paraspeckles. Cold Spring Harb. Perspect. Biol. 2, a000687 (2010).

    PubMed  PubMed Central  Google Scholar 

  206. Yoon, J.-H. et al. LincRNA-p21 suppresses target mRNA translation. Mol. Cell 47, 648–655 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  207. Doma, M. K. & Parker, R. RNA quality control in eukaryotes. Cell 131, 660–668 (2007).

    Article  CAS  PubMed  Google Scholar 

  208. Houseley, J., LaCava, J. & Tollervey, D. RNA-quality control by the exosome. Nature Rev. Mol. Cell. Biol. 7, 529–539 (2006).

    Article  CAS  Google Scholar 

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Acknowledgements

The body map data were kindly provided by the Gene Expression Applications research group at Illumina. The authors thank P. Morozov, M. Carty, M. Brown, R. Kim and S. Lianoglou for discussions on the computational methods, as well as Z. Ozair, A. D. Haase and all laboratory members for comments on the manuscript. S.G. was supported by a Ph.D. fellowship from the Boehringer Ingelheim Fonds. M.H. is supported by the US National Institute of Arthritis and Musculoskeletal and Skin Diseases Intramural Research Program. T.T. is an Investigator of the Howard Hughes Medical Institute.

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Correspondence to Thomas Tuschl.

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T.T. is a cofounder and scientific advisor to Alnylam Pharmaceuticals and a scientific advisor to Regulus Therapeutics. S.G. and M.H. declare no competing interests.

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Glossary

Ribonucleoprotein

(RNP). Protein (or proteins) complexed with RNA as an obligate binding partner.

RNA-binding proteins

(RBPs). Proteins involved in the maturation, stability, transport and degradation of cellular RNAs. RBPs directly bind to RNA or are integral parts of macromolecular protein complexes that bind to RNA.

Non-coding RNA

(ncRNA). An RNA that does not encode a protein. In this Analysis, ncRNA is also used to specifically group together all remaining ncRNAs that are not ribosomal RNAs, tRNAs, small nuclear RNAs, small nucleolar RNAs or small Cajal body-specific RNAs.

RNA recognition elements

Short (rarely more than 4–6-nucleotide-long) sequence elements within RNA targets that are recognized and bound by RNA-binding proteins.

Crosslinking and immunoprecipitation followed by sequencing

(CLIP–seq). An experimental method to map the binding sites of RNA-binding proteins (RBPs) on RNA targets transcriptome-wide. RBPs are ultraviolet-crosslinked to RNA in vivo, followed by partial RNase treatment of cell lysates, immunoprecipitation of RBPs, recovery of covalently bound RNA, and small RNA cDNA library preparation for deep sequencing of crosslinked RNA segments.

RNA immunoprecipitation and sequencing

(RIP-seq). An experimental method to identify enrichment and targets of RNA-binding proteins (RBPs). RBPs are immunoprecipitated, and bound RNAs are library-prepared for deep sequencing.

Small Cajal body-specific RNAs

(scaRNAs). Small RNAs that have a similar structure and sequence to small nucleolar RNAs (snoRNAs), localize to the Cajal body and are involved in the methylation and pseudouridylation of snoRNAs.

RNA-binding domains

(RBDs). Structural protein domains that directly bind to RNA. In this Analysis, RBD is also used to include structural domains found exclusively in RNA-binding proteins that are able to transiently contact RNA during ribonucleoprotein assembly or disassembly.

Hidden Markov models

Statistical probability models that assume a Markov chain with unobserved (hidden) states. In protein domain predictions, HMMs are calculated from protein sequence alignments and compute the probability of a specific protein sequence.

Transcription factors

(TFs). Proteins that bind to specific DNA sequences at gene promoters, upstream and downstream elements, or within the gene body; they influence gene expression by enhancing or blocking transcription.

RPKM

(Reads per kilobase per million mapped reads). A measure for quantifying single-end read RNA-sequencing data per transcript or gene exon model; it normalizes the total number of mapped reads per transcript or gene exon model by the length of the transcript or gene exon model (in kilobases) and the library size (total number of reads mapped to the genome or transcriptome in million reads).

Small nuclear RNA

(snRNA). A type of short (~70–200-nucleotide) RNA found in the nucleus of eukaryotic cells. snRNAs associate with proteins of the spliceosome to form the spliceosomal core complexes.

Small nucleolar RNA

(snoRNA). A type of short (~50–200-nucleotide) RNA that is localized to the nucleolus and that guides methylation or pseudouridylation of ribosomal RNAs and small nuclear RNAs.

MicroRNA

(miRNA). A type of small (~21-nucleotide) non-coding RNA involved in post-transcriptional gene silencing. miRNAs form ribonucleoprotein complexes with Argonaute proteins to repress mRNA stability and protein expression by recruiting RNA deadenylation and degradation complexes to their RNA targets.

PIWI-interacting RNAs

(piRNAs). Small (~28-nucleotide) non-coding RNAs involved in post-transcriptional gene silencing that are expressed in the germ line; they form ribonucleoprotein complexes with PIWI proteins, and protect the genome from genomic instability by transcriptional and post-transcriptional repression of transposons.

Long ncRNAs

(lncRNAs). RNAs that do not encode proteins and are > 200 nucleotides long; they are found as structural components in nuclear and cytoplasmic ribonucleoprotein complexes and are transcribed by RNA polymerase II, similarly to mRNAs. Less abundant lncRNAs may influence the gene expression of neighbouring genes (in cis) at the transcriptional, post-transcriptional and translational levels.

Post-conception week

(PCW). A time measurement used to describe stages of human development in prenatal weeks. PCW records the time elapsed since the day of conception. Also commonly used is gestation week, which counts from the day of the last menstrual period. Assuming a normal 28-day menstrual cycle, PCW is 2 weeks less than gestation week.

3′ untranslated regions

(3′UTRs). 3′ ends of mRNAs, specifically the region between the stop codon and the poly(A) tail. 3′UTRs are targets of post-transcriptional regulation by many ribonucleoprotein and RNA-binding protein complexes, which determine their stability, translation and turnover.

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Gerstberger, S., Hafner, M. & Tuschl, T. A census of human RNA-binding proteins. Nat Rev Genet 15, 829–845 (2014). https://doi.org/10.1038/nrg3813

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