MicroRNAs (miRNAs) are small regulatory molecules that repress the translational processes of their target genes by binding to their 3′ untranslated regions (3′ UTRs). Because the target genes are predominantly determined by their sequence complementarity to the miRNA seed regions (nucleotides 2–7) which are evolutionarily conserved, it is inferred that the target relationships and functions of the miRNA family members are conserved across many species. Therefore, detecting the relevant miRNA families with confidence would help to clarify the conserved miRNA functions, and elucidate miRNA-mediated biological processes. We present a mixture model of position weight matrices for constructing miRNA functional families. This model systematically finds not only evolutionarily conserved miRNA family members but also functionally related miRNAs, as it simultaneously generates position weight matrices representing the conserved sequences. Using mammalian miRNA sequences, in our experiments, we identified potential miRNA groups characterized by similar sequence patterns that have common functions. We validated our results using score measures and by the analysis of the conserved targets. Our method would provide a way to comprehensively identify conserved miRNA functions.
References
[1]
Altuvia Y, Landgraf P, Lithwick G, Elefant N, Pfeffer S, Aravin A, Brownstein MJ, Tuschl T, Margalit H. 2005. Clustering and conservation patterns of human microRNAs. Nucleic Acids Research 33(8):2697-2706
[2]
Ambros V. 2004. The functions of animal microRNAs. Nature 431:350-355
[3]
Ambs S, Prueitt RL, Yi M, Hudson RS, Howe TM, Petrocca F, Wallace TA, Liu CG, Volinia S, Calin GA, Yfantis HG, Stephens RM, Croce CM. 2008. Genomic profiling of microRNA and messenger RNA reveals deregulated microRNA expression in prostate cancer. Cancer Research 68(15):6162-6170
[4]
Ason B, Darnell DK, Wittbrodt B, Berezikov E, Kloosterman WP, Wittbrodt J, Antin PB, Plasterk RH. 2006. Differences in vertebrate microRNA expression. Proceedings of the National Academy of Sciences of the United States of America 103:14385-14389
[5]
Axtell MJ, Bartel DP. 2005. Antiquity of microRNAs and their targets in land plants. The Plant Cell 17(6):1658-1673
[6]
Bailey TL, Elkan C. 1995. The value of prior knowledge in discovering motifs with MEME. Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology 3:21-29
[7]
Bak M, Silahtaroglu A, Mller M, Christensen M, Rath MF, Skryabin B, Tommerup N, Kauppinen S. 2008. MicroRNA expression in the adult mouse central nervous system. RNA 14(3):432-444
Berezikov E. 2011. Evolution of microRNA diversity and regulation in animals. Nature Reviews Genetics 12:846-860
[11]
Borenstein E, Ruppin E. 2006. Direct evolution of genetic robustness in microRNA. Proceedings of the National Academy of Sciences of the United States of America 103:6593-6598
[12]
Burge SW, Daub J, Eberhardt R, Tate J, Barquist L, Nawrocki EP, Eddy SR, Gardner PP, Bateman A. 2013. Rfam 11.0: 10 years of RNA families. Nucleic Acids Research 41:D226-D232
[13]
Bushati N, Cohen SM. 2007. microRNA functions. Annual Review of Cell and Developmental Biology 23:175-205
[14]
Chen JF, Mandel EM, Thomson JM, Wu Q, Callis TE, Hammond SM, Conlon FL, Wang DZ. 2006. The role of microRNA-1 and microRNA-133 in skeletal muscle proliferation and differentiation. Nature Genetics 38(2):228-233
[15]
Cimmino A, Calin GA, Fabbri M, Iorio MV, Ferracin M, Shimizu M, Wojcik SE, Aqeilan RI, Zupo S, Dono M, Rassenti L, Alder H, Volinia S, Liu CG, Kipps TJ, Negrini M, Croce CM. 2005. miR-15 and miR-16 induce apoptosis by targeting BCL2. Proceedings of the National Academy of Sciences of the United States of America 102(39):13944-13949
[16]
Cory S, Adams JM. 2002. The Bcl2 family: regulators of the cellular life-or-death switch. Nature Reviews Cancer 2(9):647-656
[17]
Costa T, Boccignone G, Ferraro M. 2012. Gaussian mixture model of heart rate variability. PLoS ONE 7(5):e37731
[18]
Costinean S, Zanesi N, Pekarsky Y, Tili E, Volinia S, Heerema N, Croce CM. 2006. Pre-B cell proliferation and lymphoblastic leukemia/high-grade lymphoma in Eμ-miR155 transgenic mice. Proceedings of the National Academy of Sciences of the United States of America 103(18):7024-7029
[19]
Crooks GE, Hon G, Chandonia JM, Brenner SE. 2004. WebLogo: a sequence logo generator. Genome Research 14(6):1188-1190
[20]
Flicek P, Ahmed I, Amode MR, Barrell D, Beal K, Brent S, Carvalho-Silva D, Clapham P, Coates G, Fairley S, Fitzgerald S, Gil L, García-Girón C, Gordon L, Hourlier T, Hunt S, Juettemann T, Khri AK, Keenan S, Komorowska M, Kulesha E, Longden I, Maurel T, McLaren WM, Muffato M, Nag R, Overduin B, Pignatelli M, Pritchard B, Pritchard E, Riat HS, Ritchie GR, Ruffier M, Schuster M, Sheppard D, Sobral D, Taylor K, Thormann A, Trevanion S, White S, Wilder SP, Aken BL, Birney E, Cunningham F, Dunham I, Harrow J, Herrero J, Hubbard TJ, Johnson N, Kinsella R, Parker A, Spudich G, Yates A, Zadissa A, Searle SM. 2013. Ensembl 2013. Nucleic Acids Research 41:D48-D55
[21]
Floyd SK, Bowman JL. 2004. Gene regulation: ancient microRNA target sequences in plants. Nature 428(6982):485-486
[22]
Friedman RC, Farh KK-H, Burge CB, Bartel DP. 2009. Most mammalian mRNAs are conserved targets of microRNAs. Genome Research 19:92-105
[23]
Gardner PP, Daub J, Tate JG, Nawrocki EP, Kolbe DL, Lindgreen S, Wilkinson AC, Finn RD, Griffiths-Jones S, Eddy SR, Bateman A. 2009. Rfam: updates to the RNA families database. Nucleic Acids Research 37:D136-D140
[24]
Griffiths-Jones S, Saini HK, van Dongen S, Enright AJ. 2008. miRBase: tools for microRNA genomics. Nucleic Acids Research 36:D154-D158
[25]
Guerra-Assuno JA, Enright AJ. 2012. Large-scale analysis of microRNA evolution. BMC Genomics 13:218.49
[26]
Gerlach D, Kriventseva EV, Rahman N, Vejmar CE, Zdobnov EM. 2009. miROrtho: computational survey of microRNA genes. Nucleic Acids Research 37(Suppl 1):D111-D117
[27]
Hannenhalli S, Wang LS. 2005. Enhanced position weight matrices using mixture models. Bioinformatics 21(Suppl 1):i204-i212
[28]
Houseman EA, Christensen BC, Yeh RF, Marsit CJ, Karagas MR, Wrensch M, Nelson HH, Wiemels J, Zheng S, Wiencke JK, Kelsey KT. 2008. Model-based clustering of DNA methylation array data: a recursive-partitioning algorithm for high-dimensional data arising as a mixture of beta distributions. BMC Bioinformatics 9:365
[29]
Huang DW, Sherman BT, Lempicki RA. 2009. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols 4:44-57
[30]
Hyun S, Lee JH, Jin H, Nam J-W, Namkoong B, Lee G, Chung J, Kim VN. 2009. Conserved microRNA miR-8/miR-200 and its target USH/FOG2 control growth by regulating PI3K. Cell 139(6):1096-1108
[31]
Jones RH. 2011. Bayesian information criterion for longitudinal and clustered data. Statistics in Medicine 30(25):3050-30566
[32]
Kel AE, Gossling E, Reuter I, Cheremushkin E, Kel-Margoulis OV, Wingender E. 2003. MATCH: a tool for searching transcription factor binding sites in DNA sequences. Nucleic Acids Research 31(13):3576-3579
[33]
Koh W, Sheng CT, Tan B, Lee QY, Kuznetsov V, Kiang LS, Tanavde V. 2010. Analysis of deep sequencing microRNA expression profile from human embryonic stem cells derived mesenchymal stem cells reveals possible role of let-7 microRNA family in downstream targeting of hepatic nuclear factor 4 alpha. BMC Genomics 11(Suppl 1):S6
[34]
Kozomara A, Griffiths-Jones S. 2011. miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Research 39:D152-D157
[35]
Lewis BP, Burge CB, Bartel DP. 2005. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120(1):15-20
[36]
Lindow M, Jacobsen A, Nygaard S, Mang Y, Krogh A. 2007. Intragenomic matching reveals a huge potential for miRNA-mediated regulation in plants. PLoS Computational Biology 3(11):e238
[37]
Linsley PS, Schelter J, Burchard J, Kibukawa M, Martin MM, Bartz SR, Johnson JM, Cummins JM, Raymond CK, Dai H, Chau N, Cleary M, Jackson AL, Carleton M, Lim L. 2007. Transcripts targeted by the microRNA-16 family cooperatively regulate cell cycle progression. Molecular and Cellular Biology 27(6):2240-2252
[38]
Li J, Liu Y, Dong D, Zhang Z. 2010. Evolution of an X-linked primate-specific microRNA cluster. Molecular Biology and Evolution 27:671-683
[39]
Liu C, Kelnar K, Vlassov AV, Brown D, Wang J, Tang DG. 2012. Distinct microRNA expression profiles in prostate cancer stem/progenitor cells and tumor-suppressive functions of let-7. Cancer Research 72(13):3393-3404
[40]
McNicholas PD, Murphy TB. 2010. Model-based clustering of microarray expression data via latent Gaussian mixture models. Bioinformatics 26(21):2705-2712
[41]
Melnykov V, Maitra R. 2010. Finite mixture models and model-based clustering. Statistics Surveys 4:80-116
[42]
Moss EG, Tang L. 2003. Conservation of the heterochronic regulator lin-28, its developmental expression and microRNA complementary sites. Developmental Biology 258(2):432-442
[43]
Naguibneva I, Ameyar-Zazoua M, Polesskaya A, Ait-Si-Ali S, Groisman R, Souidi M, Cuvellier S, Harel-Bellan A. 2006. The microRNA miR-181 targets the homeobox protein Hox-A11 during mammalian myoblast differentiation. Nature Cell Biology 8(3):278-284
[44]
Orenstein Y, Linhart C, Shamir R. 2012. Assessment of algorithms for inferring positional weight matrix motifs of transcription factor binding sites using protein binding microarray data. PLoS ONE 7(9):e46145
[45]
Park CY, Choi YS, McManus MT. 2010. Analysis of microRNA knockouts in mice. Human Molecular Genetics 19(R2):R169-R175
[46]
Pasquinelli AE, Reinhart BJ, Slack F, Martindale MQ, Kuroda MI, Maller B, Hayward DC, Ball EE, Degnan B, Müller P, Spring J, Srinivasan A, Fishman M, Finnerty J, Corbo J, Levine M, Leahy P, Davidson E, Ruvkun G. 2000. Conservation of the sequence and temporal expression of let-7 heterochronic regulatory RNA. Nature 408(6808):86-89
[47]
Pekarsky Y, Santanam U, Cimmino A, Palamarchuk A, Efanov A, Maximov V, Volinia S, Alder H, Liu CG, Rassenti L, Calin GA, Hagan JP, Kipps T, Croce CM. 2006. Tcl1 expression in chronic lymphocytic leukemia is regulated by miR-29 and miR-181. Cancer Research 66(24):11590-11593
[48]
Petrocca F, Visone R, Onelli MR, Shah MH, Nicoloso MS, de Martino I, Iliopoulos D, Pilozzi E, Liu CG, Negrini M, Cavazzini L, Volinia S, Alder H, Ruco LP, Baldassarre G, Croce CM, Vecchione A. 2008. E2F1-regulated microRNAs impair TGFβ-dependent cell-cycle arrest and apoptosis in gastric cancer. Cancer Cell 13(3):272-286
[49]
Roush S, Slack FJ. 2008. The let-7 family of microRNAs. Trends in Cell Biology 18(10):505-516
[50]
Rousseeuw P. 1987. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics 20:53-65
[51]
Schwarz G. 1978. Estimating the dimension of a model. The Annals of Statistics 6(2):461-464
[52]
Shi B, Gao W, Wang J. 2012. Sequence fingerprints of microRNA conservation. PLoS ONE 7(10):e48256
[53]
Tzur G, Levy A, Meiri E, Barad O, Spector Y, Bentwich Z, Mizrahi L, Katzenellenbogen M, Ben-Shushan E, Reubinoff BE, Galun E. 2008. MicroRNA expression patterns and function in endodermal differentiation of human embryonic stem cells. PLoS ONE 3(11):e3726
[54]
Xia H, Qi Y, Ng SS, Chen X, Chen S, Fang M, Li D, Zhao Y, Ge R, Li G, Chen Y, He ML, Kung HF, Lai L, Lin MC. 2009. MicroRNA-15b regulates cell cycle progression by targeting cyclins in glioma cells. Biochemical and Biophysical Research Communications 380(2):205-210
[55]
Zhang ZJ, Zhang H, Kang Y, Sheng PY, Ma YC, Yang ZB, Zhang ZQ, Fu M, He AS, Liao WM. 2012. miRNA expression profile during osteogenic differentiation of human adipose-derived stem cells. Journal of Cellular Biochemistry 113(3):888-898
