PreprintCited by 53RNA Research and SplicingRNA and protein synthesis mechanismsCancer-related molecular mechanisms research

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The architecture of the human RNA-binding protein regulatory network

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Preprint — published as 10.1016/j.isci.2019.10.058 · Paper page

Abstract

RNA-binding proteins (RBPs) are key players of post-transcriptional regulation of gene expression. These proteins influence both cellular physiology and pathology by regulating processes ranging from splicing and polyadenylation to mRNA localization, stability, and translation. To fine-tune the outcome of their regulatory action, RBPs rely on an intricate web of competitive and cooperative interactions. Several studies have described individual interactions of RBPs with RBP mRNAs, suggestive of a RBP-RBP regulatory structure. Here we present the first systematic investigation of this structure, based on a network including almost fifty thousand experimentally determined interactions between RBPs and bound RBP mRNAs. Our analysis identified two features defining the structure of the RBP-RBP regulatory network. What we call “RBP clusters” are groups of densely interconnected RBPs which co-regulate their targets, suggesting a tight control of cooperative and competitive behaviors. “RBP chains”, instead, are hierarchical structures driven by evolutionarily ancient RBPs, which connect the RBP clusters and could in this way provide the flexibility to coordinate the tuning of a broad set of biological processes. The combination of these two features suggests that RBP chains may use the modulation of their RBP targets to coordinately control the different cell programs controlled by the RBP clusters. Under this island-hopping model, the regulatory signal flowing through the chains hops from one RBP cluster to another, implementing elaborate regulatory plans to impact cellular phenotypes. This work thus establishes RBP-RBP interactions as a backbone driving post-transcriptional regulation of gene expression to allow the fine-grained control of RBPs and their targets.

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Research works printed but not linked: 67

  1. 2013, SurpriseMe: an integrated tool for network community structure characterization using Surprise maximization, Bioinformatics, 30, 1041
  2. 10.1016/j.molcel.2012.05.021 · DOI
  3. 10.1093/nar/gki1012 · DOI · Paper page
  4. Batagelj V , Mrvar A. 2002. Pajek—Analysis and Visualization of Large Networks. In Lecture Notes in Computer Science, pp. 477–478. · DOI
  5. 10.1093/nar/gkw1040 · DOI
  6. 10.1126/science.aac7557 · DOI · Paper page
  7. 10.1093/bioinformatics/btu170 · DOI · Paper page
  8. 10.1101/gad.17446611 · DOI
  9. 10.1093/nar/gkx1020 · DOI · Paper page
  10. 10.1016/j.cell.2012.04.031 · DOI · Paper page
  11. 10.1186/s13059-015-0624-2 · DOI
  12. 10.1093/bioinformatics/btp163 · DOI · Paper page
  13. 2017, Handshakes and Fights: The Regulatory Interplay of RNA-Binding Proteins, Front Mol Biosci, 4, 67, 10.3389/fmolb.2017.00067 · DOI
  14. 10.4161/trla.27738 · DOI
  15. 10.1093/nar/gkt017 · DOI
  16. de Nooy W , Mrvar A , Batagelj V. 2005. Exploratory Social Network Analysis with Pajek. · DOI · Paper page
  17. 10.1093/bioinformatics/bts635 · DOI · Paper page
  18. 10.1038/nrg3813 · DOI · Paper page
  19. 2013, Poly(A) binding proteins: are they all created equal?, Wiley Interdiscip Rev RNA, 4, 167, 10.1002/wrna.1151 · DOI · Paper page
  20. 10.1093/nar/gkw1016 · DOI
  21. 10.1042/BST0340012 · DOI · Paper page
  22. 10.1371/journal.pone.0002051 · DOI · Paper page
  23. 10.1038/nature22366 · DOI · Paper page
  24. 10.1016/0378-8733(85)90015-2 · DOI
  25. 10.1038/msb.2009.52 · DOI
  26. 10.1038/nrg2111 · DOI · Paper page
  27. 10.1093/bioinformatics/bth351 · DOI
  28. 10.1038/nmeth.1608 · DOI
  29. 10.1038/35022643 · DOI
  30. 10.1371/journal.pone.0131673 · DOI
  31. 10.1016/j.molcel.2018.01.005 · DOI
  32. 10.1093/nar/gkx998 · DOI
  33. 10.1038/nn.3543 · DOI
  34. 10.1186/s13059-014-0550-8 · DOI · Paper page
  35. 10.1016/j.tig.2008.05.004 · DOI
  36. 10.1038/nrm2178 · DOI
  37. 10.1042/BC20080055 · DOI · Paper page
  38. 10.1126/science.1089167 · DOI
  39. 10.1126/science.298.5594.824 · DOI · Paper page
  40. 10.1016/j.molcel.2011.06.007 · DOI · Paper page
  41. 10.1016/j.cell.2012.04.040 · DOI · Paper page
  42. Newman MEJ , Girvan M. 2004. Finding and evaluating community structure in networks. Physical Review E 69. http://dx.doi.org/10.1103/physreve.69.026113. · DOI · Paper page
  43. 10.1093/nar/gkt1115 · DOI
  44. 10.1038/nature03607 · DOI · Paper page
  45. 10.1038/msb4100194 · DOI
  46. 2008, The pairwise disconnectivity index as a new metric for the topological analysis of regulatory networks, BMC Bioinformatics, 9, 227, 10.1186/1471-2105-9-227 · DOI
  47. 10.1128/MCB.00500-07 · DOI · Paper page
  48. Qijun Liu , Liu Q , Wang Z , Li M , Li D , Zhu Y. 2009. Revealing the functional modularity of yeast transcriptional regulatory network by using a novel topological measurement. In 2009 2nd IEEE International Conference on Computer Science and Information Technology http://dx.doi.org/10.1109/iccsit.2009.5234476. · DOI
  49. 10.1038/nature12311 · DOI · Paper page
  50. 2017, mA in mRNA: An Ancient Mechanism for Fine-Tuning Gene Expression, Trends Genet, 33, 380, 10.1016/j.tig.2017.04.003 · DOI · Paper page
  51. 10.1093/nar/gkp914 · DOI
  52. 10.1126/science.1242063 · DOI
  53. 10.1093/nar/gks1170 · DOI
  54. 10.1101/gr.199935.115 · DOI · Paper page
  55. 10.1093/nar/gkw937 · DOI · Paper page
  56. 10.1101/gad.231407.113 · DOI
  57. Tierney L. 2012. The R Statistical Computing Environment. In Lecture Notes in Statistics, pp. 435–447. · DOI
  58. 10.1093/nar/gkt482 · DOI
  59. 10.1038/msb.2010.59 · DOI · Paper page
  60. 10.1128/MCB.20.17.6334-6341.2000 · DOI · Paper page
  61. 2018, METTL14 Inhibits Hematopoietic Stem/Progenitor Differentiation and Promotes Leukemogenesis via mRNA mA Modification, Cell Stem Cell, 22, 191, 10.1016/j.stem.2017.11.016 · DOI
  62. 10.1093/bioinformatics/btl038 · DOI
  63. 10.1016/j.bbagrm.2014.10.001 · DOI
  64. 10.1093/bioinformatics/btq064 · DOI · Paper page
  65. 10.1093/nar/gkw1119 · DOI · Paper page
  66. 10.1093/nar/gkx1098 · DOI · Paper page
  67. 10.1038/nrg3950 · DOI

Metadata

Authors
Quattrone, A., & Dassi, E.
Affiliations
University of Trento (IT)
Corresponding author
Dassi, Erik
Venue
iScience
Publisher
openRxiv
Published
2016-02-26
Volume
21
Pages
706-719
ISSN
2589-0042 (ISSN-L)
OpenAlex
W2982891084
Cited by
53
References
1
Citations by year
2026: 5 · 2025: 5 · 2024: 5 · 2023: 6 · 2022: 18 · 2021: 9 · 2020: 4 · 2017: 1
FWCI
3.14
Type
journal article
Language
en
Open access
Locations
  • iScience (publishedVersion, cc-by-nc-nd)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Institutional Research Information System (Università degli Studi di Trento) (submittedVersion)
  • Iris (University of Trento) (submittedVersion)
Funders
  • Center for Outcomes Research and Evaluation, Yale School of Medicine
  • Università degli Studi di Trento
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
Keywords
RNA-binding proteins, post-transcriptional regulation, 3' untranslated region, regulatory networks, competition and cooperation, gene expression regulation, network topology

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