Evolutionary dynamics of microRNA target sites across vertebrate evolution
Autoři:
Alfred Simkin aff001; Rene Geissler aff001; Alexa B. R. McIntyre aff001; Andrew Grimson aff001
Působiště autorů:
Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, United States of America
aff001; Department of Biology, Elon University, Elon, North Carolina, United States of America
aff002; Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America
aff003
Vyšlo v časopise:
Evolutionary dynamics of microRNA target sites across vertebrate evolution. PLoS Genet 16(2): e1008285. doi:10.1371/journal.pgen.1008285
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1008285
Souhrn
MicroRNAs (miRNAs) control the abundance of the majority of the vertebrate transcriptome. The recognition sequences, or target sites, for bilaterian miRNAs are found predominantly in the 3′ untranslated regions (3′UTRs) of mRNAs, and are amongst the most highly conserved motifs within 3′UTRs. However, little is known regarding the evolutionary pressures that lead to loss and gain of such target sites. Here, we quantify the selective pressures that act upon miRNA target sites. Notably, selective pressure extends beyond deeply conserved binding sites to those that have undergone recent substitutions. Our approach reveals that even amongst ancient animal miRNAs, which exert the strongest selective pressures on 3′UTR sequences, there are striking differences in patterns of target site evolution between miRNAs. Considering only ancient animal miRNAs, we find three distinct miRNA groups, each exhibiting characteristic rates of target site gain and loss during mammalian evolution. The first group both loses and gains sites rarely. The second group shows selection only against site loss, with site gains occurring at a neutral rate, whereas the third loses and gains sites at neutral or above expected rates. Furthermore, mutations that alter the strength of existing target sites are disfavored. Applying our approach to individual transcripts reveals variation in the distribution of selective pressure across the transcriptome and between miRNAs, ranging from strong selection acting on a small subset of targets of some miRNAs, to weak selection on many targets for other miRNAs. miR-20 and miR-30, and many other miRNAs, exhibit broad, deeply conserved targeting, while several other comparably ancient miRNAs show a lack of selective constraint, and a small number, including mir-146, exhibit evidence of rapidly evolving target sites. Our approach adds valuable perspective on the evolution of miRNAs and their targets, and can also be applied to characterize other 3′UTR regulatory motifs.
Klíčová slova:
Animal evolution – Animal phylogenetics – MicroRNAs – Natural selection – Nucleotide sequencing – Sequence alignment – Sequence motif analysis – Transcription factors
Zdroje
1. Schmitz JF, Zimmer F, Bornberg-Bauer E. Mechanisms of transcription factor evolution in Metazoa. Nucleic Acids Res. 2016;44(13):6287–97. doi: 10.1093/nar/gkw492 27288445; PubMed Central PMCID: PMC5291267.
2. Schwaiger M, Schonauer A, Rendeiro AF, Pribitzer C, Schauer A, Gilles AF, et al. Evolutionary conservation of the eumetazoan gene regulatory landscape. Genome Res. 2014;24(4):639–50. doi: 10.1101/gr.162529.113 24642862; PubMed Central PMCID: PMC3975063.
3. Vinogradov AE, Anatskaya OV. Organismal complexity, cell differentiation and gene expression: human over mouse. Nucleic Acids Res. 2007;35(19):6350–6. doi: 10.1093/nar/gkm723 17881362; PubMed Central PMCID: PMC2095826.
4. The Chimpanzee Sequencing and Analysis Consortium. Initial sequence of the chimpanzee genome and comparison with the human genome. Nature. 2005;437(7055):69–87. doi: 10.1038/nature04072 16136131.
5. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, et al. The human genome browser at UCSC. Genome Res. 2002;12(6):996–1006. doi: 10.1101/gr.229102 12045153; PubMed Central PMCID: PMC186604.
6. Won YJ, Sivasundar A, Wang Y, Hey J. On the origin of Lake Malawi cichlid species: a population genetic analysis of divergence. Proc Natl Acad Sci U S A. 2005;102 Suppl 1:6581–6. doi: 10.1073/pnas.0502127102 15851665; PubMed Central PMCID: PMC1131877.
7. Nitta KR, Jolma A, Yin Y, Morgunova E, Kivioja T, Akhtar J, et al. Conservation of transcription factor binding specificities across 600 million years of bilateria evolution. Elife. 2015;4. doi: 10.7554/eLife.04837 25779349; PubMed Central PMCID: PMC4362205.
8. Anderson DW, McKeown AN, Thornton JW. Intermolecular epistasis shaped the function and evolution of an ancient transcription factor and its DNA binding sites. Elife. 2015;4:e07864. doi: 10.7554/eLife.07864 26076233; PubMed Central PMCID: PMC4500092.
9. Nakagawa S, Gisselbrecht SS, Rogers JM, Hartl DL, Bulyk ML. DNA-binding specificity changes in the evolution of forkhead transcription factors. Proc Natl Acad Sci U S A. 2013;110(30):12349–54. doi: 10.1073/pnas.1310430110 23836653; PubMed Central PMCID: PMC3725104.
10. Presnell JS, Schnitzler CE, Browne WE. KLF/SP Transcription Factor Family Evolution: Expansion, Diversification, and Innovation in Eukaryotes. Genome Biol Evol. 2015;7(8):2289–309. doi: 10.1093/gbe/evv141 26232396; PubMed Central PMCID: PMC4558859.
11. Teichmann SA, Babu MM. Gene regulatory network growth by duplication. Nat Genet. 2004;36(5):492–6. doi: 10.1038/ng1340 15107850.
12. Thompson D, Regev A, Roy S. Comparative analysis of gene regulatory networks: from network reconstruction to evolution. Annu Rev Cell Dev Biol. 2015;31:399–428. doi: 10.1146/annurev-cellbio-100913-012908 26355593.
13. Duque T, Samee MA, Kazemian M, Pham HN, Brodsky MH, Sinha S. Simulations of enhancer evolution provide mechanistic insights into gene regulation. Mol Biol Evol. 2014;31(1):184–200. doi: 10.1093/molbev/mst170 24097306; PubMed Central PMCID: PMC3879441.
14. Otto W, Stadler PF, Lopez-Giraldez F, Townsend JP, Lynch VJ, Wagner GP. Measuring transcription factor-binding site turnover: a maximum likelihood approach using phylogenies. Genome Biol Evol. 2009;1:85–98. doi: 10.1093/gbe/evp010 20333180; PubMed Central PMCID: PMC2817405.
15. Tanay A, Gat-Viks I, Shamir R. A global view of the selection forces in the evolution of yeast cis-regulation. Genome Res. 2004;14(5):829–34. doi: 10.1101/gr.2064404 15123582; PubMed Central PMCID: PMC479109.
16. Habib N, Wapinski I, Margalit H, Regev A, Friedman N. A functional selection model explains evolutionary robustness despite plasticity in regulatory networks. Mol Syst Biol. 2012;8:619. doi: 10.1038/msb.2012.50 23089682; PubMed Central PMCID: PMC3501536.
17. Bartel DP. Metazoan MicroRNAs. Cell. 2018;173(1):20–51. doi: 10.1016/j.cell.2018.03.006 29570994; PubMed Central PMCID: PMC6091663.
18. Moran Y, Agron M, Praher D, Technau U. The evolutionary origin of plant and animal microRNAs. Nat Ecol Evol. 2017;1(3):27. doi: 10.1038/s41559-016-0027 28529980; PubMed Central PMCID: PMC5435108.
19. Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136(2):215–33. doi: 10.1016/j.cell.2009.01.002 19167326; PubMed Central PMCID: PMC3794896.
20. Chen K, Rajewsky N. Deep conservation of microRNA-target relationships and 3'UTR motifs in vertebrates, flies, and nematodes. Cold Spring Harb Symp Quant Biol. 2006;71:149–56. doi: 10.1101/sqb.2006.71.039 17381291.
21. Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB. Prediction of mammalian microRNA targets. Cell. 2003;115(7):787–98. doi: 10.1016/s0092-8674(03)01018-3 14697198.
22. Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014;42(Database issue):D68–73. doi: 10.1093/nar/gkt1181 24275495; PubMed Central PMCID: PMC3965103.
23. Xu J, Zhang R, Shen Y, Liu G, Lu X, Wu CI. The evolution of evolvability in microRNA target sites in vertebrates. Genome Res. 2013;23(11):1810–6. doi: 10.1101/gr.148916.112 24077390; PubMed Central PMCID: PMC3814881.
24. Lu J, Shen Y, Wu Q, Kumar S, He B, Shi S, et al. The birth and death of microRNA genes in Drosophila. Nat Genet. 2008;40(3):351–5. doi: 10.1038/ng.73 18278047.
25. Meunier J, Lemoine F, Soumillon M, Liechti A, Weier M, Guschanski K, et al. Birth and expression evolution of mammalian microRNA genes. Genome Res. 2013;23(1):34–45. doi: 10.1101/gr.140269.112 23034410; PubMed Central PMCID: PMC3530682.
26. Nozawa M, Miura S, Nei M. Origins and evolution of microRNA genes in Drosophila species. Genome Biol Evol. 2010;2:180–9. doi: 10.1093/gbe/evq009 20624724; PubMed Central PMCID: PMC2942034.
27. Nozawa M, Miura S, Nei M. Origins and evolution of microRNA genes in plant species. Genome Biol Evol. 2012;4(3):230–9. doi: 10.1093/gbe/evs002 22223755; PubMed Central PMCID: PMC3318440.
28. Lyu Y, Shen Y, Li H, Chen Y, Guo L, Zhao Y, et al. New microRNAs in Drosophila—birth, death and cycles of adaptive evolution. PLoS Genet. 2014;10(1):e1004096. doi: 10.1371/journal.pgen.1004096 24465220; PubMed Central PMCID: PMC3900394.
29. Mohammed J, Flynt AS, Panzarino AM, Mondal MMH, DeCruz M, Siepel A, et al. Deep experimental profiling of microRNA diversity, deployment, and evolution across the Drosophila genus. Genome Res. 2018;28(1):52–65. doi: 10.1101/gr.226068.117 29233922; PubMed Central PMCID: PMC5749182.
30. Penso-Dolfin L, Moxon S, Haerty W, Di Palma F. The evolutionary dynamics of microRNAs in domestic mammals. Sci Rep. 2018;8(1):17050. doi: 10.1038/s41598-018-34243-8 30451897; PubMed Central PMCID: PMC6242877.
31. Farh KK, Grimson A, Jan C, Lewis BP, Johnston WK, Lim LP, et al. The widespread impact of mammalian MicroRNAs on mRNA repression and evolution. Science. 2005;310(5755):1817–21. doi: 10.1126/science.1121158 16308420.
32. Pasquinelli AE, Reinhart BJ, Slack F, Martindale MQ, Kuroda MI, Maller B, et al. Conservation of the sequence and temporal expression of let-7 heterochronic regulatory RNA. Nature. 2000;408(6808):86–9. doi: 10.1038/35040556 11081512.
33. Stark A, Brennecke J, Bushati N, Russell RB, Cohen SM. Animal MicroRNAs confer robustness to gene expression and have a significant impact on 3'UTR evolution. Cell. 2005;123(6):1133–46. doi: 10.1016/j.cell.2005.11.023 16337999.
34. Wolter JM, Le HH, Linse A, Godlove VA, Nguyen TD, Kotagama K, et al. Evolutionary patterns of metazoan microRNAs reveal targeting principles in the let-7 and miR-10 families. Genome Res. 2017;27(1):53–63. doi: 10.1101/gr.209361.116 27927717; PubMed Central PMCID: PMC5204344.
35. Xie X, Lu J, Kulbokas EJ, Golub TR, Mootha V, Lindblad-Toh K, et al. Systematic discovery of regulatory motifs in human promoters and 3' UTRs by comparison of several mammals. Nature. 2005;434(7031):338–45. doi: 10.1038/nature03441 PubMed Central PMCID: PMC2923337. 15735639
36. Luo J, Wang Y, Yuan J, Zhao Z, Lu J. MicroRNA duplication accelerates the recruitment of new targets during vertebrate evolution. RNA. 2018;24(6):787–802. doi: 10.1261/rna.062752.117 29511046; PubMed Central PMCID: PMC5959248.
37. Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005;120(1):15–20. doi: 10.1016/j.cell.2004.12.035 15652477.
38. Loh YH, Yi SV, Streelman JT. Evolution of microRNAs and the diversification of species. Genome Biol Evol. 2011;3:55–65. doi: 10.1093/gbe/evq085 21169229; PubMed Central PMCID: PMC3017390.
39. Franchini P, Xiong P, Fruciano C, Meyer A. The Role of microRNAs in the Repeated Parallel Diversification of Lineages of Midas Cichlid Fish from Nicaragua. Genome Biol Evol. 2016;8(5):1543–55. doi: 10.1093/gbe/evw097 27189980; PubMed Central PMCID: PMC4898811.
40. Hatlen AM, A. Pervasive selection against microRNA target sites in human populations. bioRxiv. 2018.
41. Leclercq M, Diallo AB, Blanchette M. Prediction of human miRNA target genes using computationally reconstructed ancestral mammalian sequences. Nucleic Acids Res. 2017;45(2):556–66. doi: 10.1093/nar/gkw1085 27899600; PubMed Central PMCID: PMC5314757.
42. Nozawa M, Fujimi M, Iwamoto C, Onizuka K, Fukuda N, Ikeo K, et al. Evolutionary Transitions of MicroRNA-Target Pairs. Genome Biol Evol. 2016;8(5):1621–33. doi: 10.1093/gbe/evw092 27189995; PubMed Central PMCID: PMC4898806.
43. Shou C, Bhardwaj N, Lam HY, Yan KK, Kim PM, Snyder M, et al. Measuring the evolutionary rewiring of biological networks. PLoS Comput Biol. 2011;7(1):e1001050. doi: 10.1371/journal.pcbi.1001050 21253555; PubMed Central PMCID: PMC3017101.
44. Simkin AT, Bailey JA, Gao FB, Jensen JD. Inferring the evolutionary history of primate microRNA binding sites: overcoming motif counting biases. Mol Biol Evol. 2014;31(7):1894–901. doi: 10.1093/molbev/msu129 24723422; PubMed Central PMCID: PMC4069616.
45. Casper J, Zweig AS, Villarreal C, Tyner C, Speir ML, Rosenbloom KR, et al. The UCSC Genome Browser database: 2018 update. Nucleic Acids Res. 2018;46(D1):D762–D9. doi: 10.1093/nar/gkx1020 29106570; PubMed Central PMCID: PMC5753355.
46. Felsenstein J. PHYLIP-phylogeny inference package (Version 3.2). Cladistics. 2002;5:164–6.
47. Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP. MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol Cell. 2007;27(1):91–105. doi: 10.1016/j.molcel.2007.06.017 17612493; PubMed Central PMCID: PMC3800283.
48. Friedman RC, Farh KK, Burge CB, Bartel DP. Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2009;19(1):92–105. doi: 10.1101/gr.082701.108 18955434; PubMed Central PMCID: PMC2612969.
49. Stark A, Lin MF, Kheradpour P, Pedersen JS, Parts L, Carlson JW, et al. Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures. Nature. 2007;450(7167):219–32. doi: 10.1038/nature06340 17994088; PubMed Central PMCID: PMC2474711.
50. Ebert MS, Sharp PA. Roles for microRNAs in conferring robustness to biological processes. Cell. 2012;149(3):515–24. doi: 10.1016/j.cell.2012.04.005 22541426; PubMed Central PMCID: PMC3351105.
51. Halligan DL. Patterns of Evolutionary Constraints in Intronic and Intergenic DNA of Drosophila. Genome Research. 2004;14(2):273–9. doi: 10.1101/gr.1329204 14762063
52. Blanchette M. Aligning Multiple Genomic Sequences With the Threaded Blockset Aligner. Genome Research. 2004;14(4):708–15. doi: 10.1101/gr.1933104 15060014
53. Landgraf P, Rusu M, Sheridan R, Sewer A, Iovino N, Aravin A, et al. A mammalian microRNA expression atlas based on small RNA library sequencing. Cell. 2007;129(7):1401–14. doi: 10.1016/j.cell.2007.04.040 17604727; PubMed Central PMCID: PMC2681231.
54. Pinzon N, Li B, Martinez L, Sergeeva A, Presumey J, Apparailly F, et al. microRNA target prediction programs predict many false positives. Genome Res. 2017;27(2):234–45. doi: 10.1101/gr.205146.116 28148562; PubMed Central PMCID: PMC5287229.
55. Fridrich A, Hazan Y, Moran Y. Too Many False Targets for MicroRNAs: Challenges and Pitfalls in Prediction of miRNA Targets and Their Gene Ontology in Model and Non-model Organisms. Bioessays. 2019;41(4):e1800169. doi: 10.1002/bies.201800169 30919506; PubMed Central PMCID: PMC6701991.
56. Bartel DP, Chen CZ. Micromanagers of gene expression: the potentially widespread influence of metazoan microRNAs. Nat Rev Genet. 2004;5(5):396–400. doi: 10.1038/nrg1328 15143321.
57. Mayr C. Regulation by 3'-Untranslated Regions. Annu Rev Genet. 2017;51:171–94. doi: 10.1146/annurev-genet-120116-024704 28853924.
58. Beaudoing E, Freier S, Wyatt JR, Claverie JM, Gautheret D. Patterns of variant polyadenylation signal usage in human genes. Genome Res. 2000;10(7):1001–10. doi: 10.1101/gr.10.7.1001 10899149; PubMed Central PMCID: PMC310884.
59. Lagnado CA, Brown CY, Goodall GJ. AUUUA is not sufficient to promote poly(A) shortening and degradation of an mRNA: the functional sequence within AU-rich elements may be UUAUUUA(U/A)(U/A). Mol Cell Biol. 1994;14(12):7984–95. doi: 10.1128/mcb.14.12.7984 7969138; PubMed Central PMCID: PMC359337.
60. Li X, Quon G, Lipshitz HD, Morris Q. Predicting in vivo binding sites of RNA-binding proteins using mRNA secondary structure. RNA. 2010;16(6):1096–107. doi: 10.1261/rna.2017210 20418358; PubMed Central PMCID: PMC2874161.
61. Kheradpour P, Stark A, Roy S, Kellis M. Reliable prediction of regulator targets using 12 Drosophila genomes. Genome Res. 2007;17(12):1919–31. doi: 10.1101/gr.7090407 17989251; PubMed Central PMCID: PMC2099599.
62. Krek A, Grun D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, et al. Combinatorial microRNA target predictions. Nat Genet. 2005;37(5):495–500. doi: 10.1038/ng1536 15806104.
63. Sood P, Krek A, Zavolan M, Macino G, Rajewsky N. Cell-type-specific signatures of microRNAs on target mRNA expression. Proc Natl Acad Sci U S A. 2006;103(8):2746–51. doi: 10.1073/pnas.0511045103 16477010; PubMed Central PMCID: PMC1413820.
64. Wang Y, Luo J, Zhang H, Lu J. microRNAs in the Same Clusters Evolve to Coordinately Regulate Functionally Related Genes. Mol Biol Evol. 2016;33(9):2232–47. doi: 10.1093/molbev/msw089 27189568; PubMed Central PMCID: PMC4989102.
65. Hu F, Wang M, Xiao T, Yin B, He L, Meng W, et al. miR-30 promotes thermogenesis and the development of beige fat by targeting RIP140. Diabetes. 2015;64(6):2056–68. doi: 10.2337/db14-1117 25576051; PubMed Central PMCID: PMC4876748.
66. Peck BC, Sincavage J, Feinstein S, Mah AT, Simmons JG, Lund PK, et al. miR-30 Family Controls Proliferation and Differentiation of Intestinal Epithelial Cell Models by Directing a Broad Gene Expression Program That Includes SOX9 and the Ubiquitin Ligase Pathway. J Biol Chem. 2016;291(31):15975–84. doi: 10.1074/jbc.M116.733733 27261459; PubMed Central PMCID: PMC4965549.
67. Zaragosi LE, Wdziekonski B, Brigand KL, Villageois P, Mari B, Waldmann R, et al. Small RNA sequencing reveals miR-642a-3p as a novel adipocyte-specific microRNA and miR-30 as a key regulator of human adipogenesis. Genome Biol. 2011;12(7):R64. doi: 10.1186/gb-2011-12-7-r64 21767385; PubMed Central PMCID: PMC3218826.
68. Hua Z, Lv Q, Ye W, Wong CK, Cai G, Gu D, et al. MiRNA-directed regulation of VEGF and other angiogenic factors under hypoxia. PLoS One. 2006;1:e116. doi: 10.1371/journal.pone.0000116 17205120; PubMed Central PMCID: PMC1762435.
69. Shehadeh LA, Sharma S, Pessanha M, Wei JQ, Liu J, Yuan H, et al. MicroRNA-20a constrains p300-driven myocardial angiogenic transcription by direct targeting of p300. PLoS One. 2013;8(11):e79133. doi: 10.1371/journal.pone.0079133 24236097; PubMed Central PMCID: PMC3827282.
70. Ventura A, Young AG, Winslow MM, Lintault L, Meissner A, Erkeland SJ, et al. Targeted deletion reveals essential and overlapping functions of the miR-17 through 92 family of miRNA clusters. Cell. 2008;132(5):875–86. doi: 10.1016/j.cell.2008.02.019 18329372; PubMed Central PMCID: PMC2323338.
71. Lee HM, Kim TS, Jo EK. MiR-146 and miR-125 in the regulation of innate immunity and inflammation. BMB Rep. 2016;49(6):311–8. doi: 10.5483/BMBRep.2016.49.6.056 26996343; PubMed Central PMCID: PMC5070718.
72. Testa U, Pelosi E, Castelli G, Labbaye C. miR-146 and miR-155: Two Key Modulators of Immune Response and Tumor Development. Noncoding RNA. 2017;3(3). doi: 10.3390/ncrna3030022 29657293; PubMed Central PMCID: PMC5831915.
73. Wang X, Cao J, Yu Y, Ma B, Gao C, Lu J, et al. Role of MicroRNA 146a in Regulating Regulatory T Cell Function to Ameliorate Acute Cardiac Rejection in Mice. Transplant Proc. 2019;51(3):901–12. doi: 10.1016/j.transproceed.2019.01.026 30979483.
74. Xiao Q, Zhu X, Yang S, Wang J, Yin R, Song J, et al. LPS induces CXCL16 expression in HUVECs through the miR-146a-mediated TLR4 pathway. Int Immunopharmacol. 2019;69:143–9. doi: 10.1016/j.intimp.2019.01.011 30710793.
75. Zhang L, Fu Y, Wang H, Guan Y, Zhu W, Guo M, et al. Severe Fever With Thrombocytopenia Syndrome Virus-Induced Macrophage Differentiation Is Regulated by miR-146. Front Immunol. 2019;10:1095. doi: 10.3389/fimmu.2019.01095 31156641; PubMed Central PMCID: PMC6529556.
76. Simkin A, Wong A, Poh YP, Theurkauf WE, Jensen JD. Recurrent and recent selective sweeps in the piRNA pathway. Evolution. 2013;67(4):1081–90. doi: 10.1111/evo.12011 23550757; PubMed Central PMCID: PMC3992950.
77. Bassett AR, Azzam G, Wheatley L, Tibbit C, Rajakumar T, McGowan S, et al. Understanding functional miRNA-target interactions in vivo by site-specific genome engineering. Nat Commun. 2014;5:4640. doi: 10.1038/ncomms5640 25135198; PubMed Central PMCID: PMC4143950.
78. Lai EC. Two decades of miRNA biology: lessons and challenges. RNA. 2015;21(4):675–7. doi: 10.1261/rna.051193.115 25780186; PubMed Central PMCID: PMC4371328.
79. Lagos-Quintana M, Rauhut R, Yalcin A, Meyer J, Lendeckel W, Tuschl T. Identification of tissue-specific microRNAs from mouse. Curr Biol. 2002;12(9):735–9. doi: 10.1016/s0960-9822(02)00809-6 12007417.
80. Li X, Cassidy JJ, Reinke CA, Fischboeck S, Carthew RW. A microRNA imparts robustness against environmental fluctuation during development. Cell. 2009;137(2):273–82. doi: 10.1016/j.cell.2009.01.058 19379693; PubMed Central PMCID: PMC2674871.
81. Wu CI, Shen Y, Tang T. Evolution under canalization and the dual roles of microRNAs: a hypothesis. Genome Res. 2009;19(5):734–43. doi: 10.1101/gr.084640.108 19411598; PubMed Central PMCID: PMC3647535.
82. Cottrell KA, Chaudhari HG, Cohen BA, Djuranovic S. PTRE-seq reveals mechanism and interactions of RNA binding proteins and miRNAs. Nat Commun. 2018;9(1):301. doi: 10.1038/s41467-017-02745-0 29352242; PubMed Central PMCID: PMC5775260.
83. Geissler R, Simkin A, Floss D, Patel R, Fogarty EA, Scheller J, et al. A widespread sequence-specific mRNA decay pathway mediated by hnRNPs A1 and A2/B1. Genes Dev. 2016;30(9):1070–85. doi: 10.1101/gad.277392.116 27151978; PubMed Central PMCID: PMC4863738.
84. Rabani M, Pieper L, Chew GL, Schier AF. A Massively Parallel Reporter Assay of 3' UTR Sequences Identifies In Vivo Rules for mRNA Degradation. Mol Cell. 2017;68(6):1083–94 e5. doi: 10.1016/j.molcel.2017.11.014 29225039; PubMed Central PMCID: PMC5994907.
85. Wissink EM, Fogarty EA, Grimson A. High-throughput discovery of post-transcriptional cis-regulatory elements. BMC Genomics. 2016;17:177. doi: 10.1186/s12864-016-2479-7 26941072; PubMed Central PMCID: PMC4778349.
86. Zhao W, Pollack JL, Blagev DP, Zaitlen N, McManus MT, Erle DJ. Massively parallel functional annotation of 3' untranslated regions. Nat Biotechnol. 2014;32(4):387–91. doi: 10.1038/nbt.2851 24633241; PubMed Central PMCID: PMC3981918.
87. Salmena L, Poliseno L, Tay Y, Kats L, Pandolfi PP. A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? Cell. 2011;146(3):353–8. doi: 10.1016/j.cell.2011.07.014 21802130; PubMed Central PMCID: PMC3235919.
88. Seitz H. Redefining microRNA targets. Curr Biol. 2009;19(10):870–3. doi: 10.1016/j.cub.2009.03.059 19375315.
89. Bosson AD, Zamudio JR, Sharp PA. Endogenous miRNA and target concentrations determine susceptibility to potential ceRNA competition. Mol Cell. 2014;56(3):347–59. doi: 10.1016/j.molcel.2014.09.018 25449132; PubMed Central PMCID: PMC5048918.
90. Denzler R, Agarwal V, Stefano J, Bartel DP, Stoffel M. Assessing the ceRNA hypothesis with quantitative measurements of miRNA and target abundance. Mol Cell. 2014;54(5):766–76. doi: 10.1016/j.molcel.2014.03.045 24793693; PubMed Central PMCID: PMC4267251.
91. Garcia DM, Baek D, Shin C, Bell GW, Grimson A, Bartel DP. Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs. Nat Struct Mol Biol. 2011;18(10):1139–46. doi: 10.1038/nsmb.2115 21909094; PubMed Central PMCID: PMC3190056.
92. Blanchette M, Kent WJ, Riemer C, Elnitski L, Smit AF, Roskin KM, et al. Aligning multiple genomic sequences with the threaded blockset aligner. Genome Res. 2004;14(4):708–15. doi: 10.1101/gr.1933104 15060014; PubMed Central PMCID: PMC383317.
93. Tchebichef P. Des valeurs moyennes. Journal de Mathématiques Pures et Appliquées. 1867;2(12):177–84.
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