Genomic competition for noise reduction shaped evolutionary landscape of mir-4673.
Journal
NPJ systems biology and applications
ISSN: 2056-7189
Titre abrégé: NPJ Syst Biol Appl
Pays: England
ID NLM: 101677786
Informations de publication
Date de publication:
06 05 2020
06 05 2020
Historique:
received:
08
05
2019
accepted:
09
04
2020
entrez:
8
5
2020
pubmed:
8
5
2020
medline:
22
9
2020
Statut:
epublish
Résumé
The genomic platform that informs evolution of microRNA cascades remains unknown. Here we capitalised on the recent evolutionary trajectory of hominin-specific miRNA-4673, encoded in intron 4 of notch-1, to uncover the identity of one such precursor genomic element and the selective forces acting upon it. The miRNA targets genes that regulate Wnt/β-catenin signalling cascade. Primary sequence of the microRNA and its target region in Wnt modulating genes evolved from homologous signatures mapped to homotypic cis-clusters recognised by TCF3/4 and TFAP2A/B/C families. Integration of homologous TFAP2A/B/C cis-clusters (short range inhibitor of β-catenin) into the transcriptional landscape of Wnt cascade genes can reduce noise in gene expression. Probabilistic adoption of miRNA secondary structure by one such cis-signature in notch-1 reflected selection for superhelical curvature symmetry of precursor DNA to localise a nucleosome that overlapped the latter cis-cluster. By replicating the cis-cluster signature, non-random interactions of the miRNA with key Wnt modulator genes expanded the transcriptional noise buffering capacity via a coherent feed-forward loop mechanism. In consequence, an autonomous transcriptional noise dampener (the cis-cluster/nucleosome) evolved into a post-transcriptional one (the miRNA). The findings suggest a latent potential for remodelling of transcriptional landscape by miRNAs that capitalise on non-random distribution of genomic cis-signatures.
Identifiants
pubmed: 32376854
doi: 10.1038/s41540-020-0131-2
pii: 10.1038/s41540-020-0131-2
pmc: PMC7203229
doi:
Substances chimiques
CTNNB1 protein, human
0
MIRN4673 microRNA, human
0
MicroRNAs
0
NOTCH1 protein, human
0
Receptor, Notch1
0
beta Catenin
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
12Références
Elowitz, M. B., Levine, A. J., Siggia, E. D. & Swain, P. S. Stochastic gene expression in a single cell. Science 297, 1183–1186 (2002).
pubmed: 12183631
doi: 10.1126/science.1070919
Raser, J. M. & O’Shea, E. K. Noise in gene expression: origins, consequences, and control. Science 309, 2010–2013 (2005).
pubmed: 16179466
pmcid: 1360161
doi: 10.1126/science.1105891
Rezaei-Lotfi, S., Hunter, N. & Farahani, R. M. beta-Catenin: a metazoan filter for biological noise? Front. Genet. 10, 1004 (2019).
pubmed: 31681432
pmcid: 6805772
doi: 10.3389/fgene.2019.01004
Vujovic, F., Hunter, N. & Farahani, R. M. Notch pathway: a bistable inducer of biological noise? Cell Commun. Signal. 17, 133 (2019).
pubmed: 31640734
pmcid: 6805690
doi: 10.1186/s12964-019-0453-0
Peterson, K. J., Dietrich, M. R. & McPeek, M. A. MicroRNAs and metazoan macroevolution: insights into canalization, complexity, and the Cambrian explosion. Bioessays 31, 736–747 (2009).
pubmed: 19472371
doi: 10.1002/bies.200900033
Hornstein, E. & Shomron, N. Canalization of development by microRNAs. Nat. Genet. 38(Suppl), S20–S24 (2006).
pubmed: 16736020
doi: 10.1038/ng1803
Waddington, C. H. Canalization of development and genetic assimilation of acquired characters. Nature 183, 1654–1655 (1959).
pubmed: 13666847
doi: 10.1038/1831654a0
Brodersen, P. & Voinnet, O. Revisiting the principles of microRNA target recognition and mode of action. Nat. Rev. Mol. Cell Biol. 10, 141–148 (2009).
pubmed: 19145236
doi: 10.1038/nrm2619
Brennecke, J., Stark, A., Russell, R. B. & Cohen, S. M. Principles of microRNA-target recognition. PLoS Biol. 3, e85 (2005).
pubmed: 15723116
pmcid: 1043860
doi: 10.1371/journal.pbio.0030085
Brummer, A. & Hausser, J. MicroRNA binding sites in the coding region of mRNAs: extending the repertoire of post-transcriptional gene regulation. Bioessays 36, 617–626 (2014).
pubmed: 24737341
doi: 10.1002/bies.201300104
Choi, P. S. et al. Members of the miRNA-200 family regulate olfactory neurogenesis. Neuron 57, 41–55 (2008).
pubmed: 18184563
pmcid: 2204047
doi: 10.1016/j.neuron.2007.11.018
Broughton, J. P., Lovci, M. T., Huang, J. L., Yeo, G. W. & Pasquinelli, A. E. Pairing beyond the seed supports microRNA targeting specificity. Mol. Cell 64, 320–333 (2016).
pubmed: 27720646
pmcid: 5074850
doi: 10.1016/j.molcel.2016.09.004
Dokumcu, K., Simonian, M. & Farahani, R. M. miR4673 improves fitness profile of neoplastic cells by induction of autophagy. Cell Death Dis. 9, 1068 (2018).
pubmed: 30341280
pmcid: 6195512
doi: 10.1038/s41419-018-1088-6
Farahani, R., Rezaei-Lotfi, S., Simonian, M. & Hunter, N. Bi-modal reprogramming of cell cycle by MiRNA-4673 amplifies human neurogenic capacity. Cell Cycle https://doi.org/10.1080/15384101.2019.1595873 (2019).
Hayward, P., Kalmar, T. & Arias, A. M. Wnt/Notch signalling and information processing during development. Development 135, 411–424 (2008).
pubmed: 18192283
doi: 10.1242/dev.000505
Kwon, C. et al. Notch post-translationally regulates beta-catenin protein in stem and progenitor cells. Nat. Cell Biol. 13, 1244–1251 (2011).
pubmed: 21841793
pmcid: 3187850
doi: 10.1038/ncb2313
Chenn, A. & Walsh, C. A. Regulation of cerebral cortical size by control of cell cycle exit in neural precursors. Science 297, 365–369 (2002).
pubmed: 12130776
doi: 10.1126/science.1074192
Huber, A. H., Stewart, D. B., Laurents, D. V., Nelson, W. J. & Weis, W. I. The cadherin cytoplasmic domain is unstructured in the absence of beta-catenin. A possible mechanism for regulating cadherin turnover. J. Biol. Chem. 276, 12301–12309 (2001).
pubmed: 11121423
doi: 10.1074/jbc.M010377200
MacRae, I. J., Zhou, K. & Doudna, J. A. Structural determinants of RNA recognition and cleavage by Dicer. Nat. Struct. Mol. Biol. 14, 934–940 (2007).
pubmed: 17873886
doi: 10.1038/nsmb1293
Valouev, A. et al. Determinants of nucleosome organization in primary human cells. Nature 474, 516–520 (2011).
pubmed: 21602827
pmcid: 3212987
doi: 10.1038/nature10002
Thastrom, A., Bingham, L. M. & Widom, J. Nucleosomal locations of dominant DNA sequence motifs for histone-DNA interactions and nucleosome positioning. J. Mol. Biol. 338, 695–709 (2004).
pubmed: 15099738
doi: 10.1016/j.jmb.2004.03.032
He, H. H. et al. Nucleosome dynamics define transcriptional enhancers. Nat. Genet. 42, 343–347 (2010).
pubmed: 20208536
pmcid: 2932437
doi: 10.1038/ng.545
Arner, E. et al. Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells. Science 347, 1010–1014 (2015).
pubmed: 25678556
pmcid: 4681433
doi: 10.1126/science.1259418
Kim, T. K. et al. Widespread transcription at neuronal activity-regulated enhancers. Nature 465, 182–187 (2010).
pubmed: 20393465
pmcid: 3020079
doi: 10.1038/nature09033
Rothbacher, U., Bertrand, V., Lamy, C. & Lemaire, P. A combinatorial code of maternal GATA, Ets and beta-catenin-TCF transcription factors specifies and patterns the early ascidian ectoderm. Development 134, 4023–4032 (2007).
pubmed: 17965050
doi: 10.1242/dev.010850
Li, Q. & Dashwood, R. H. Activator protein 2alpha associates with adenomatous polyposis coli/beta-catenin and Inhibits beta-catenin/T-cell factor transcriptional activity in colorectal cancer cells. J. Biol. Chem. 279, 45669–45675 (2004).
pubmed: 15331612
doi: 10.1074/jbc.M405025200
Jimeno-Gonzalez, S., Ceballos-Chavez, M. & Reyes, J. C. A positioned +1 nucleosome enhances promoter-proximal pausing. Nucleic Acids Res. 43, 3068–3078 (2015).
pubmed: 25735750
pmcid: 4381062
doi: 10.1093/nar/gkv149
Studitsky, V. M., Nizovtseva, E. V., Shaytan, A. K. & Luse, D. S. Nucleosomal barrier to transcription: structural determinants and changes in chromatin structure. Biochem. Mol. Biol. J. 2, 8 (2016).
Blake, W. J., M, K. A., Cantor, C. R. & Collins, J. J. Noise in eukaryotic gene expression. Nature 422, 633–637 (2003).
pubmed: 12687005
doi: 10.1038/nature01546
Nikolaou, C., Althammer, S., Beato, M. & Guigo, R. Structural constraints revealed in consistent nucleosome positions in the genome of S. cerevisiae. Epigenet. Chromatin 3, 20 (2010).
doi: 10.1186/1756-8935-3-20
Albert, I. et al. Translational and rotational settings of H2A.Z nucleosomes across the Saccharomyces cerevisiae genome. Nature 446, 572–576 (2007).
pubmed: 17392789
doi: 10.1038/nature05632
Komiya, Y. & Habas, R. Wnt signal transduction pathways. Organogenesis 4, 68–75 (2008).
pubmed: 19279717
pmcid: 2634250
doi: 10.4161/org.4.2.5851
Batzer, M. A. & Deininger, P. L. Alu repeats and human genomic diversity. Nat. Rev. Genet. 3, 370–379 (2002).
pubmed: 11988762
doi: 10.1038/nrg798
Ivany, L. C., Patterson, W. P. & Lohmann, K. C. Cooler winters as a possible cause of mass extinctions at the Eocene/Oligocene boundary. Nature 407, 887–890 (2000).
pubmed: 11057663
doi: 10.1038/35038044
Ezhevsky, S. A. et al. Hypo-phosphorylation of the retinoblastoma protein (pRb) by cyclin D:Cdk4/6 complexes results in active pRb. Proc. Natl Acad. Sci. USA 94, 10699–10704 (1997).
pubmed: 9380698
doi: 10.1073/pnas.94.20.10699
pmcid: 23451
Larrea, M. D. et al. Phosphorylation of p27Kip1 regulates assembly and activation of cyclin D1-Cdk4. Mol. Cell Biol. 28, 6462–6472 (2008).
pubmed: 18710949
pmcid: 2577417
doi: 10.1128/MCB.02300-07
Hall, I. M., Noma, K. & Grewal, S. I. RNA interference machinery regulates chromosome dynamics during mitosis and meiosis in fission yeast. Proc. Natl Acad. Sci. USA 100, 193–198 (2003).
pubmed: 12509501
doi: 10.1073/pnas.232688099
Huang, C., Wang, X., Liu, X., Cao, S. & Shan, G. RNAi pathway participates in chromosome segregation in mammalian cells. Cell Discov. 1, 15029 (2015).
pubmed: 27462427
pmcid: 4860838
doi: 10.1038/celldisc.2015.29
Vasudevan, S., Tong, Y. & Steitz, J. A. Switching from repression to activation: microRNAs can up-regulate translation. Science 318, 1931–1934 (2007).
pubmed: 18048652
doi: 10.1126/science.1149460
Wu, G. et al. Structure of a beta-TrCP1-Skp1-beta-catenin complex: destruction motif binding and lysine specificity of the SCF(beta-TrCP1) ubiquitin ligase. Mol. Cell 11, 1445–1456 (2003).
pubmed: 12820959
doi: 10.1016/S1097-2765(03)00234-X
Shtutman, M. et al. The cyclin D1 gene is a target of the beta-catenin/LEF-1 pathway. Proc. Natl Acad. Sci. USA 96, 5522–5527 (1999).
pubmed: 10318916
doi: 10.1073/pnas.96.10.5522
pmcid: 21892
Zhu, S. et al. Chromatin structure characteristics of pre-miRNA genomic sequences. BMC Genomics 12, 329 (2011).
pubmed: 21702984
pmcid: 3135579
doi: 10.1186/1471-2164-12-329
Ozsolak, F. et al. Chromatin structure analyses identify miRNA promoters. Genes Dev. 22, 3172–3183 (2008).
pubmed: 19056895
pmcid: 2593607
doi: 10.1101/gad.1706508
Liu, T. et al. Global investigation of the co-evolution of MIRNA genes and microRNA targets during soybean domestication. Plant J. 85, 396–409 (2016).
pubmed: 26714457
doi: 10.1111/tpj.13113
Jones-Rhoades, M. W. & Bartel, D. P. Computational identification of plant MicroRNAs and their targets, including a stress-induced miRNA. Mol. Cell 14, 787–799 (2004).
pubmed: 15200956
doi: 10.1016/j.molcel.2004.05.027
Rhoades, M. W. et al. Prediction of plant microRNA targets. Cell 110, 513–520 (2002).
pubmed: 12202040
doi: 10.1016/S0092-8674(02)00863-2
Hutvagner, G. & Zamore, P. D. A microRNA in a multiple-turnover RNAi enzyme complex. Science 297, 2056–2060 (2002).
pubmed: 12154197
doi: 10.1126/science.1073827
Traverse, A. Plant evolution dances to a different beat. Hist. Biol. 1, 277–301 (2009).
Tilgner, H. et al. Nucleosome positioning as a determinant of exon recognition. Nat. Struct. Mol. Biol. 16, 996–1001 (2009).
pubmed: 19684599
doi: 10.1038/nsmb.1658
Goodsell, D. S. & Dickerson, R. E. Bending and curvature calculations in B-DNA. Nucleic Acids Res. 22, 5497–5503 (1994).
pubmed: 7816643
pmcid: 332108
doi: 10.1093/nar/22.24.5497
Alharbi, B. A., Alshammari, T. H., Felton, N. L., Zhurkin, V. B. & Cui, F. nuMap: a web platform for accurate prediction of nucleosome positioning. Genomics Proteom. Bioinform. 12, 249–253 (2014).
doi: 10.1016/j.gpb.2014.08.001
Satchwell, S. C., Drew, H. R. & Travers, A. A. Sequence periodicities in chicken nucleosome core DNA. J. Mol. Biol. 191, 659–675 (1986).
pubmed: 3806678
doi: 10.1016/0022-2836(86)90452-3
Segal, E. et al. A genomic code for nucleosome positioning. Nature 442, 772–778 (2006).
pubmed: 16862119
pmcid: 2623244
doi: 10.1038/nature04979
Steger, D. J. & Workman, J. L. Transcriptional analysis of purified histone acetyltransferase complexes. Methods 19, 410–416 (1999).
pubmed: 10579936
doi: 10.1006/meth.1999.0877
Ream, J. A., Lewis, L. K. & Lewis, K. A. Rapid agarose gel electrophoretic mobility shift assay for quantitating protein: RNA interactions. Anal. Biochem. 511, 36–41 (2016).
pubmed: 27495142
pmcid: 5002362
doi: 10.1016/j.ab.2016.07.027
Dubochet, J., Ducommun, M., Zollinger, M. & Kellenberger, E. A new preparation method for dark-field electron microscopy of biomacromolecules. J. Ultrastruct. Res. 35, 147–167 (1971).
pubmed: 4931423
doi: 10.1016/S0022-5320(71)80148-X
Farahani, R. M., Rezaei-Lotfi, S., Simonian, M., Xaymardan, M. & Hunter, N. Neural microvascular pericytes contribute to human adult neurogenesis. J. Comp. Neurol. 527, 780–796 (2019).
pubmed: 30471080
doi: 10.1002/cne.24565
Zuker, M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 31, 3406–3415 (2003).
pubmed: 12824337
pmcid: 169194
doi: 10.1093/nar/gkg595
Klur, S., Toy, K., Williams, M. P. & Certa, U. Evaluation of procedures for amplification of small-size samples for hybridization on microarrays. Genomics 83, 508–517 (2004).
pubmed: 14962677
doi: 10.1016/j.ygeno.2003.09.005
Villalva, C. et al. Increased yield of PCR products by addition of T4 gene 32 protein to the SMART PCR cDNA synthesis system. Biotechniques 31(81–83), 86 (2001).
Mathelier, A. et al. JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles. Nucleic Acids Res. 44, D110–D115 (2016).
pubmed: 26531826
doi: 10.1093/nar/gkv1176
Shimazaki, H. & Shinomoto, S. A method for selecting the bin size of a time histogram. Neural Comput. 19, 1503–1527 (2007).
pubmed: 17444758
doi: 10.1162/neco.2007.19.6.1503
Hubley, R. et al. The Dfam database of repetitive DNA families. Nucleic Acids Res. 44, D81–D89 (2016).
pubmed: 26612867
doi: 10.1093/nar/gkv1272
Proctor, J. R. & Meyer, I. M. COFOLD: an RNA secondary structure prediction method that takes co-transcriptional folding into account. Nucleic Acids Res. 41, e102 (2013).
pubmed: 23511969
pmcid: 3643587
doi: 10.1093/nar/gkt174
Mathews, D. H., Sabina, J., Zuker, M. & Turner, D. H. Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. J. Mol. Biol. 288, 911–940 (1999).
pubmed: 10329189
doi: 10.1006/jmbi.1999.2700
Krzywinski, M. et al. Circos: an information aesthetic for comparative genomics. Genome Res. 19, 1639–1645 (2009).
pubmed: 19541911
pmcid: 2752132
doi: 10.1101/gr.092759.109
Gao, F. & Zhang, C. T. GC-Profile: a web-based tool for visualizing and analyzing the variation of GC content in genomic sequences. Nucleic Acids Res. 34, W686–W691 (2006).
pubmed: 16845098
pmcid: 1538862
doi: 10.1093/nar/gkl040
Zhang, C. T., Gao, F. & Zhang, R. Segmentation algorithm for DNA sequences. Phys. Rev. E 72, 041917 (2005).
doi: 10.1103/PhysRevE.72.041917
Kruger, J. & Rehmsmeier, M. RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res. 34, W451–W454 (2006).
pubmed: 16845047
pmcid: 1538877
doi: 10.1093/nar/gkl243
Jensen, L. J. et al. STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res. 37, D412–D416 (2009).
pubmed: 18940858
doi: 10.1093/nar/gkn760
Gene Ontology, C. Gene Ontology Consortium: going forward. Nucleic Acids Res. 43, D1049–D1056 (2015).
doi: 10.1093/nar/gku1179
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. & Morishima, K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353–D361 (2017).
pubmed: 27899662
doi: 10.1093/nar/gkw1092
Thomas, P. D. et al. PANTHER: a library of protein families and subfamilies indexed by function. Genome Res. 13, 2129–2141 (2003).
pubmed: 12952881
pmcid: 403709
doi: 10.1101/gr.772403
Auerbach, R., Kubai, L., Knighton, D. & Folkman, J. A simple procedure for the long-term cultivation of chicken embryos. Dev. Biol. 41, 391–394 (1974).
pubmed: 4452416
doi: 10.1016/0012-1606(74)90316-9
Hamburger, V. & Hamilton, H. L. A series of normal stages in the development of the chick embryo. 1951. Dev. Dyn. 195, 231–272 (1992).
pubmed: 1304821
doi: 10.1002/aja.1001950404
Alon, U. Network motifs: theory and experimental approaches. Nat. Rev. Genet. 8, 450–461 (2007).
pubmed: 17510665
doi: 10.1038/nrg2102
Mangan, S. & Alon, U. Structure and function of the feed-forward loop network motif. Proc. Natl Acad. Sci. USA 100, 11980–11985 (2003).
pubmed: 14530388
doi: 10.1073/pnas.2133841100
pmcid: 218699
Quarton, T. et al. Mapping the operational landscape of microRNAs in synthetic gene circuits. NPJ Syst. Biol. Appl. 4, 6 (2018).
pubmed: 29354284
pmcid: 5765153
doi: 10.1038/s41540-017-0043-y