MicroRNAs: Target Recognition and Regulatory Functions

MicroRNAs (miRNAs) are endogenous ∼23 nt RNAs that play important gene-regulatory roles in animals and plants by pairing to the mRNAs of protein-coding genes to direct their posttranscriptional repression. This review outlines the current understanding of miRNA target recognition in animals and discusses the widespread impact of miRNAs on both the expression and evolution of protein-coding genes. MicroRNAs (miRNAs) are endogenous ∼23 nt RNAs that play important gene-regulatory roles in animals and plants by pairing to the mRNAs of protein-coding genes to direct their posttranscriptional repression. This review outlines the current understanding of miRNA target recognition in animals and discusses the widespread impact of miRNAs on both the expression and evolution of protein-coding genes. Characterization of genes that control the timing of larval development in the worm Caenorhabditis elegans revealed two small regulatory RNAs, known as lin-4 and let-7 (Lee et al., 1993Lee R.C. Feinbaum R.L. Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14.Cell. 1993; 75: 843-854Abstract Full Text PDF PubMed Scopus (4212) Google Scholar, Reinhart et al., 2000Reinhart B.J. Slack F.J. Basson M. Pasquinelli A.E. Bettinger J.C. Rougvie A.E. Horvitz H.R. Ruvkun G. The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans.Nature. 2000; 403: 901-906Crossref PubMed Scopus (2086) Google Scholar). Homologs of let-7, soon recognized in other bilateral animals including mammals, exhibited temporal expression resembling that observed in C. elegans, suggesting that let-7 and perhaps other small temporal RNAs might be playing orthologous roles in diverse metazoan lineages (Pasquinelli et al., 2000Pasquinelli A.E. Reinhart B.J. Slack F. Martindale M.Q. Kuroda M.I. Maller B. Hayward D.C. Ball E.E. Degnan B. Muller P. et al.Conservation of the sequence and temporal expression of let-7 heterochronic regulatory RNA.Nature. 2000; 408: 86-89Crossref PubMed Scopus (1018) Google Scholar). Soon thereafter, lin-4 and let-7 RNAs were reported to represent a very populous class of small endogenous RNAs found in worms, flies and mammals—a few expressed temporally, but most not—which were named microRNAs (miRNAs) (Lagos-Quintana et al., 2001Lagos-Quintana M. Rauhut R. Lendeckel W. Tuschl T. Identification of novel genes coding for small expressed RNAs.Science. 2001; 294: 853-858Crossref PubMed Scopus (2190) Google Scholar, Lau et al., 2001Lau N.C. Lim L.P. Weinstein E.G. Bartel D.P. An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans.Science. 2001; 294: 858-862Crossref PubMed Scopus (1806) Google Scholar, Lee and Ambros, 2001Lee R.C. Ambros V. An extensive class of small RNAs in Caenorhabditis elegans.Science. 2001; 294: 862-864Crossref PubMed Scopus (1505) Google Scholar). miRNAs have since been found in plants, green algae, viruses, and more deeply branching animals (Griffiths-Jones et al., 2008Griffiths-Jones S. Saini H.K. Dongen S.V. Enright A.J. miRBase: tools for microRNA genomics.Nucleic Acids Res. 2008; 36: D154-D158Crossref PubMed Scopus (2051) Google Scholar). Meanwhile other types of small RNAs have been found in animals, plants, and fungi. These include endogenous small interfering RNAs (siRNAs) (Reinhart and Bartel, 2002Reinhart B.J. Bartel D.P. Small RNAs correspond to centromere heterochromatic repeats.Science. 2002; 297: 1831Crossref PubMed Scopus (331) Google Scholar, Ambros et al., 2003Ambros V. Lee R.C. Lavanway A. Williams P.T. Jewell D. MicroRNAs and other tiny endogenous RNAs in C. elegans.Curr. Biol. 2003; 13: 807-818Abstract Full Text Full Text PDF PubMed Scopus (385) Google Scholar) and Piwi-interacting RNAs (piRNAs) (Aravin et al., 2007Aravin A.A. Hannon G.J. Brennecke J. The Piwi-piRNA pathway provides an adaptive defense in the transposon arms race.Science. 2007; 318: 761-764Crossref PubMed Scopus (416) Google Scholar). Like miRNAs, many of these other RNAs function as guide RNAs within the broad phenomenon known as RNA silencing. However, miRNAs differ from these other classes of small RNAs in their biogenesis: miRNAs derive from transcripts that fold back on themselves to form distinctive hairpin structures (Bartel, 2004Bartel D.P. MicroRNAs: genomics, biogenesis, mechanism, and function.Cell. 2004; 116: 281-297Abstract Full Text Full Text PDF PubMed Scopus (10581) Google Scholar), whereas the other types of endogenous small RNAs derive either from much longer hairpins that give rise to a greater diversity of small RNAs (siRNAs), or from bimolecular RNA duplexes (siRNAs), or from precursors without any suspected double-stranded character (piRNAs). Once processed from the hairpin (Grishok et al., 2001Grishok A. Pasquinelli A.E. Conte D. Li N. Parrish S. Ha I. Baillie D.L. Fire A. Ruvkun G. Mello C.C. Genes and mechanisms related to RNA interference regulate expression of the small temporal RNAs that control C. elegans developmental timing.Cell. 2001; 106: 23-34Abstract Full Text Full Text PDF PubMed Scopus (1038) Google Scholar, Lee et al., 2003Lee Y. Ahn C. Han J. Choi H. Kim J. Yim J. Lee J. Provost P. Radmark O. Kim S. et al.The nuclear RNase III Drosha initiates microRNA processing.Nature. 2003; 425: 415-419Crossref PubMed Scopus (2079) Google Scholar) and loaded into the Argonaute protein of the silencing complex (Hutvagner and Zamore, 2002Hutvagner G. Zamore P.D. A microRNA in a multiple-turnover RNAi enzyme complex.Science. 2002; 297: 2056-2060Crossref PubMed Scopus (1117) Google Scholar, Mourelatos et al., 2002Mourelatos Z. Dostie J. Paushkin S. Sharma A. Charroux B. Abel L. Rappsilber J. Mann M. Dreyfuss G. miRNPs: a novel class of ribonucleoproteins containing numerous microRNAs.Genes Dev. 2002; 16: 720-728Crossref PubMed Scopus (637) Google Scholar), the miRNAs pair with mRNAs to direct posttranscriptional repression. At sites with extensive pairing complementarity, metazoan miRNAs can direct Argonaute-catalyzed mRNA cleavage (Hutvagner and Zamore, 2002Hutvagner G. Zamore P.D. A microRNA in a multiple-turnover RNAi enzyme complex.Science. 2002; 297: 2056-2060Crossref PubMed Scopus (1117) Google Scholar, Song et al., 2004Song J.J. Smith S.K. Hannon G.J. Joshua-Tor L. Crystal structure of Argonaute and its implications for RISC slicer activity.Science. 2004; 305: 1434-1437Crossref PubMed Scopus (710) Google Scholar, Yekta et al., 2004Yekta S. Shih I.H. Bartel D.P. MicroRNA-directed cleavage of HOXB8 mRNA.Science. 2004; 304: 594-596Crossref PubMed Scopus (964) Google Scholar). More commonly, though, the metazoan miRNAs direct translational repression, mRNA destabilization, or a combination of the two (Lee et al., 1993Lee R.C. Feinbaum R.L. Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14.Cell. 1993; 75: 843-854Abstract Full Text PDF PubMed Scopus (4212) Google Scholar, Wightman et al., 1993Wightman B. Ha I. Ruvkun G. Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans.Cell. 1993; 75: 855-862Abstract Full Text PDF PubMed Scopus (1639) Google Scholar, Lim et al., 2005Lim L.P. Lau N.C. Garrett-Engele P. Grimson A. Schelter J.M. Castle J. Bartel D.P. Linsley P.S. Johnson J.M. Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs.Nature. 2005; 433: 769-773Crossref PubMed Scopus (2367) Google Scholar). The various molecular processes at the heart of miRNA-directed translational repression and mRNA destabilization, which include inhibition of translation initiation and poly(A) shortening, are reviewed elsewhere (Filipowicz et al., 2008Filipowicz W. Bhattacharyya S.N. Sonenberg N. Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight?.Nat. Rev. Genet. 2008; 9: 102-114Crossref PubMed Scopus (1869) Google Scholar). The number of confidently identified miRNA genes has surpassed 110 in C. elegans, 140 in the fly Drosophila melanogaster, and 400 in humans—numbers that approach about 1%–2% of the number of protein-coding genes in these respective species (Ruby et al., 2006Ruby J.G. Jan C. Player C. Axtell M.J. Lee W. Nusbaum C. Ge H. Bartel D.P. Large-scale sequencing reveals 21U-RNAs and additional microRNAs and endogenous siRNAs in C. elegans.Cell. 2006; 127: 1193-1207Abstract Full Text Full Text PDF PubMed Scopus (507) Google Scholar, Landgraf et al., 2007Landgraf P. Rusu M. Sheridan R. Sewer A. Iovino N. Aravin A. Pfeffer S. Rice A. Kamphorst A.O. Landthaler M. et al.A mammalian microRNA expression atlas based on small RNA library sequencing.Cell. 2007; 129: 1401-1414Abstract Full Text Full Text PDF PubMed Scopus (1490) Google Scholar, Ruby et al., 2007Ruby J.G. Stark A. Johnston W.K. Kellis M. Bartel D.P. Lai E.C. Evolution, biogenesis, expression, and target predictions of a substantially expanded set of Drosophila microRNAs.Genome Res. 2007; 17: 1850-1864Crossref PubMed Scopus (246) Google Scholar). These numbers will undoubtedly increase as high-throughput sequencing continues to be applied both to miRNA discovery and to the validation of some of the many additional candidates proposed. The discovery of the abundance of miRNAs in diverse multicellular species raised many questions, including, perhaps most intriguingly, what these tiny noncoding RNAs may be doing in the cell. Key to answering this question has been to learn how to find their regulatory targets. Initial clues to miRNA target recognition came from the observation that the lin-4 RNA had some sequence complementarity to multiple conserved sites within the lin-14 mRNA (Lee et al., 1993Lee R.C. Feinbaum R.L. Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14.Cell. 1993; 75: 843-854Abstract Full Text PDF PubMed Scopus (4212) Google Scholar, Wightman et al., 1993Wightman B. Ha I. Ruvkun G. Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans.Cell. 1993; 75: 855-862Abstract Full Text PDF PubMed Scopus (1639) Google Scholar), within a region of the 3′ untranslated region (UTR) that earlier molecular genetic analyses had shown was required for the repression of lin-14 by lin-4 (Wightman et al., 1991Wightman B. Burglin T.R. Gatto J. Arasu P. Ruvkun G. Negative regulatory sequences in the lin-14 3′-untranslated region are necessary to generate a temporal switch during Caenorhabditis elegans development.Genes Dev. 1991; 5: 1813-1824Crossref PubMed Google Scholar). Similarly, lin-4 and let-7 RNAs were found to have complementarity to UTR sites of lin-28 and lin-41, respectively, which are targets that were also found with the help of genetic analyses (Moss et al., 1997Moss E.G. Lee R.C. Ambros V. The cold shock domain protein LIN-28 controls developmental timing in C. elegans and is regulated by the lin-4 RNA.Cell. 1997; 88: 637-646Abstract Full Text Full Text PDF PubMed Scopus (436) Google Scholar, Reinhart et al., 2000Reinhart B.J. Slack F.J. Basson M. Pasquinelli A.E. Bettinger J.C. Rougvie A.E. Horvitz H.R. Ruvkun G. The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans.Nature. 2000; 403: 901-906Crossref PubMed Scopus (2086) Google Scholar). What about the hundreds of miRNAs identified by cloning and computation, most of which correspond to loci without previously identified functions? In plants, many targets can be predicted with confidence simply by searching for messages with extensive complementarity to the miRNAs (Rhoades et al., 2002Rhoades M.W. Reinhart B.J. Lim L.P. Burge C.B. Bartel B. Bartel D.P. Prediction of plant microRNA targets.Cell. 2002; 110: 513-520Abstract Full Text Full Text PDF PubMed Scopus (1064) Google Scholar). In animals, extensive complementarity, with consequent cleavage of the targeted message, occasionally occurs but is much more unusual (Yekta et al., 2004Yekta S. Shih I.H. Bartel D.P. MicroRNA-directed cleavage of HOXB8 mRNA.Science. 2004; 304: 594-596Crossref PubMed Scopus (964) Google Scholar, Davis et al., 2005Davis E. Caiment F. Tordoir X. Cavaille J. Ferguson-Smith A. Cockett N. Georges M. Charlier C. RNAi-mediated allelic trans-interaction at the imprinted Rtl1/Peg11 locus.Curr. Biol. 2005; 15: 743-749Abstract Full Text Full Text PDF PubMed Scopus (161) Google Scholar). Thus, for metazoan miRNAs, the challenge has been to devise a genome-wide computational search that captures most of the regulatory targets without also bringing in too many false predictions. Initial attempts generated algorithms and sets of predictions that were difficult for experimentalists to evaluate, which was exacerbated by the poor overlap between sets of predictions from the same organism (Enright et al., 2003Enright A.J. John B. Gaul U. Tuschl T. Sander C. Marks D.S. MicroRNA targets in Drosophila.Genome Biol. 2003; 5: R1Crossref PubMed Google Scholar, Lewis et al., 2003Lewis B.P. Shih I.H. Jones-Rhoades M.W. Bartel D.P. Burge C.B. Prediction of mammalian microRNA targets.Cell. 2003; 115: 787-798Abstract Full Text Full Text PDF PubMed Scopus (2339) Google Scholar, Stark et al., 2003Stark A. Brennecke J. Russell R.B. Cohen S.M. Identification of Drosophila microRNA targets.PLoS Biol. 2003; 1: E60Crossref PubMed Scopus (437) Google Scholar, John et al., 2004John B. Enright A.J. Aravin A. Tuschl T. Sander C. Marks D.S. Human microRNA targets.PLoS Biol. 2004; 2: e363Crossref PubMed Scopus (1414) Google Scholar, Kiriakidou et al., 2004Kiriakidou M. Nelson P.T. Kouranov A. Fitziev P. Bouyioukos C. Mourelatos Z. Hatzigeorgiou A. A combined computational-experimental approach predicts human microRNA targets.Genes Dev. 2004; 18: 1165-1178Crossref PubMed Scopus (457) Google Scholar). Nonetheless, some of these efforts have provided methods and insights that helped set the stage for our current understanding of metazoan miRNA recognition. A key methodological advance was the use of preferential evolutionary conservation to evaluate the ability of an algorithm to distinguish miRNA target sites from the multitude of 3′-UTR segments that otherwise would score equally well with regard to the quality of miRNA pairing (Lewis et al., 2003Lewis B.P. Shih I.H. Jones-Rhoades M.W. Bartel D.P. Burge C.B. Prediction of mammalian microRNA targets.Cell. 2003; 115: 787-798Abstract Full Text Full Text PDF PubMed Scopus (2339) Google Scholar). To the extent that sites are conserved more than would be expected by chance, they are judged to be under selective pressure and therefore biologically functional. Thus, by summing the net yield of conserved sites after correcting for the number expected by chance, features and refinements of the algorithm can be evaluated computationally. For example, short subsegments of the miRNA can be individually screened to learn which ones are subject to preferentially conserved pairing. In this way, common features of target recognition can be distinguished from those that seem equally plausible but are rarely if ever used, thereby enabling the principles of target recognition to be elucidated and algorithms to be developed without resorting to training on a known set of targets (Lewis et al., 2003Lewis B.P. Shih I.H. Jones-Rhoades M.W. Bartel D.P. Burge C.B. Prediction of mammalian microRNA targets.Cell. 2003; 115: 787-798Abstract Full Text Full Text PDF PubMed Scopus (2339) Google Scholar, Lewis et al., 2005Lewis B.P. Burge C.B. Bartel D.P. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (4707) Google Scholar). Developing the algorithm without consideration of known targets avoids biases from sites that are more easily found experimentally and was particularly useful for mammalian miRNAs, for which no targets were known. Current prediction methods are diverse, both in approach and performance (Table 1) (Baek et al., 2008Baek D. Villen J. Shin C. Camargo F.D. Gygi S.P. Bartel D.P. The impact of microRNAs on protein output.Nature. 2008; 455: 64-71Crossref PubMed Scopus (1560) Google Scholar, Selbach et al., 2008Selbach M. Schwanhausser B. Thierfelder N. Fang Z. Khanin R. Rajewsky N. Widespread changes in protein synthesis induced by microRNAs.Nature. 2008; 455: 58-63Crossref PubMed Scopus (1493) Google Scholar), and all have room for improvement. Nonetheless, agreement is emerging on three conclusions, which are each reassuringly consistent with a growing body of experimental data. And, as further relief for the noncomputational biologist, the most critical concepts for computational target prediction can be distilled down to a few simple guidelines that can be implemented by anyone with access to the UC Santa Cruz Genome Browser and the “Find” function on their word processor.Table 1Tools for Predicting Metazoan miRNA TargetsToolaTools are listed according to criteria for prediction and ranking, which for those tools assessed with recent proteomics results generally correspond to their overall performance (Baek et al., 2008).CladesbLetters indicate predictions provided for the mammalian/vertebrate (m), fly (f), worm (w), or additional (+) clades.Criteria for Prediction and RankingWebsite URLRecent ReferenceSite Conservation ConsideredTargetScanmStringent seed pairing, site number, site type, site context (which includes factors that influence site accessibility); option of ranking by likelihood of preferential conservation rather than site contexthttp://targetscan.org(Friedman et al., 2008Friedman R.C. Farh K.K. Burge C.B. Bartel D.P. Most mammalian mRNAs are conserved targets of microRNAs.Genome Res. 2008; (in press. Published online October 27, 2008)https://doi.org/10.1101/gr.082701.108Crossref Scopus (1982) Google Scholar)TargetScanf,wStringent seed pairing, site number, site typehttp://targetscan.org(Ruby et al., 2007Ruby J.G. Stark A. Johnston W.K. Kellis M. Bartel D.P. Lai E.C. Evolution, biogenesis, expression, and target predictions of a substantially expanded set of Drosophila microRNAs.Genome Res. 2007; 17: 1850-1864Crossref PubMed Scopus (246) Google Scholar, Ruby et al., 2006Ruby J.G. Jan C. Player C. Axtell M.J. Lee W. Nusbaum C. Ge H. Bartel D.P. Large-scale sequencing reveals 21U-RNAs and additional microRNAs and endogenous siRNAs in C. elegans.Cell. 2006; 127: 1193-1207Abstract Full Text Full Text PDF PubMed Scopus (507) Google Scholar)EMBLfStringent seed pairing, site number, overall predicted pairing stabilityhttp://russell.embl-heidelberg.de(Stark et al., 2005Stark A. Brennecke J. Bushati N. Russell R.B. Cohen S.M. Animal microRNAs confer robustness to gene expression and have a significant impact on 3′UTR evolution.Cell. 2005; 123: 1133-1146Abstract Full Text Full Text PDF PubMed Scopus (631) Google Scholar)PicTarm,f,wStringent seed pairing for at least one of the sites for the miRNA, site number, overall predicted pairing stabilityhttp://pictar.mdc-berlin.de(Lall et al., 2006Lall S. Grun D. Krek A. Chen K. Wang Y.L. Dewey C.N. Sood P. Colombo T. Bray N. Macmenamin P. et al.A genome-wide map of conserved microRNA targets in C. elegans.Curr. Biol. 2006; 16: 460-471Abstract Full Text Full Text PDF PubMed Scopus (252) Google Scholar)EIMMom,f,wStringent seed pairing, site number, likelihood of preferential conservationhttp://www.mirz.unibas.ch/ElMMo2(Gaidatzis et al., 2007Gaidatzis D. van Nimwegen E. Hausser J. Zavolan M. Inference of miRNA targets using evolutionary conservation and pathway analysis.BMC Bioinformatics. 2007; 8: 69Crossref PubMed Scopus (156) Google Scholar)Mirandam,f,w,+Moderately stringent seed pairing, site number, pairing to most of the miRNAhttp://www.microrna.org(Betel et al., 2008Betel D. Wilson M. Gabow A. Marks D.S. Sander C. The microRNA.org resource: targets and expression.Nucleic Acids Res. 2008; 36: D149-D153Crossref PubMed Scopus (679) Google Scholar)miRBase Targetsm,f,w,+Moderately stringent seed pairing, site number, overall pairinghttp://microrna.sanger.ac.uk(Griffiths-Jones et al., 2008Griffiths-Jones S. Saini H.K. Dongen S.V. Enright A.J. miRBase: tools for microRNA genomics.Nucleic Acids Res. 2008; 36: D154-D158Crossref PubMed Scopus (2051) Google Scholar)PITA Topm,f,wModerately stringent seed pairing, site number, overall predicted pairing stability, predicted site accessibilityhttp://genie.weizmann.ac.il/pubs/mir07/mir07_data.html(Kertesz et al., 2007Kertesz M. Iovino N. Unnerstall U. Gaul U. Segal E. The role of site accessibility in microRNA target recognition.Nat. Genet. 2007; 39: 1278-1284Crossref PubMed Scopus (754) Google Scholar)mirWIPwModerately stringent seed pairing, site number, overall predicted pairing stability, predicted site accessibilityhttp://146.189.76.171/query(Hammell et al., 2008Hammell M. Long D. Zhang L. Lee A. Carmack C.S. Han M. Ding Y. Ambros V. mirWIP: microRNA target prediction based on microRNA-containing ribonucleoprotein-enriched transcripts.Nat. Methods. 2008; 9: 813-819Crossref Scopus (117) Google Scholar)Site Conservation Not ConsideredTargetScanmStringent seed pairing, site number, site type, site context (which includes factors that influence site accessibility)http://targetscan.org(Grimson et al., 2007Grimson A. Farh K.K. Johnston W.K. Garrett-Engele P. Lim L.P. Bartel D.P. MicroRNA targeting specificity in mammals: determinants beyond seed pairing.Mol. Cell. 2007; 27: 91-105Abstract Full Text Full Text PDF PubMed Scopus (1597) Google Scholar)PITA Allm,f,wModerately stringent seed pairing, site number, overall predicted pairing stability, predicted site accessibilityhttp://genie.weizmann.ac.il/pubs/mir07/mir07_data.html(Kertesz et al., 2007Kertesz M. Iovino N. Unnerstall U. Gaul U. Segal E. The role of site accessibility in microRNA target recognition.Nat. Genet. 2007; 39: 1278-1284Crossref PubMed Scopus (754) Google Scholar)RNA22m,f,wModerately stringent seed pairing, matches to sequence patterns generated from miRNA set, overall predicted pairing and predicted pairing stabilityhttp://cbcsrv.watson.ibm.com/rna22.html(Miranda et al., 2006Miranda K.C. Huynh T. Tay Y. Ang Y.S. Tam W.L. Thomson A.M. Lim B. Rigoutsos I. A pattern-based method for the identification of microRNA binding sites and their corresponding heteroduplexes.Cell. 2006; 126: 1203-1217Abstract Full Text Full Text PDF PubMed Scopus (712) Google Scholar)a Tools are listed according to criteria for prediction and ranking, which for those tools assessed with recent proteomics results generally correspond to their overall performance (Baek et al., 2008Baek D. Villen J. Shin C. Camargo F.D. Gygi S.P. Bartel D.P. The impact of microRNAs on protein output.Nature. 2008; 455: 64-71Crossref PubMed Scopus (1560) Google Scholar).b Letters indicate predictions provided for the mammalian/vertebrate (m), fly (f), worm (w), or additional (+) clades. Open table in a new tab The first major conclusion is that requiring conserved Watson–Crick pairing to the 5′ region of the miRNA centered on nucleotides 2–7, which is called the miRNA “seed” (Figure 1), markedly reduces the occurrence of false-positive predictions (Lewis et al., 2003Lewis B.P. Shih I.H. Jones-Rhoades M.W. Bartel D.P. Burge C.B. Prediction of mammalian microRNA targets.Cell. 2003; 115: 787-798Abstract Full Text Full Text PDF PubMed Scopus (2339) Google Scholar, Brennecke et al., 2005Brennecke J. Stark A. Russell R.B. Cohen S.M. Principles of microRNA-target recognition.PLoS Biol. 2005; 3: e85Crossref PubMed Scopus (783) Google Scholar, Krek et al., 2005Krek A. Grun D. Poy M.N. Wolf R. Rosenberg L. Epstein E.J. MacMenamin P. da Piedade I. Gunsalus K.C. Stoffel M. et al.Combinatorial microRNA target predictions.Nat. Genet. 2005; 37: 495-500Crossref PubMed Scopus (2184) Google Scholar, Lewis et al., 2005Lewis B.P. Burge C.B. Bartel D.P. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (4707) Google Scholar). The discovery that perfect seed pairing substantially improves prediction reliability implied that it was also important for miRNA target recognition (Lewis et al., 2003Lewis B.P. Shih I.H. Jones-Rhoades M.W. Bartel D.P. Burge C.B. Prediction of mammalian microRNA targets.Cell. 2003; 115: 787-798Abstract Full Text Full Text PDF PubMed Scopus (2339) Google Scholar). This assertion dovetailed nicely with previous reports that the 5′ region is the most conserved portion of the metazoan miRNAs (Lim et al., 2003Lim L.P. Lau N.C. Weinstein E.G. Abdelhakim A. Yekta S. Rhoades M.W. Burge C.B. Bartel D.P. The microRNAs of Caenorhabditis elegans.Genes Dev. 2003; 17: 991-1008Crossref PubMed Scopus (693) Google Scholar) and the 5′ region of certain Drosophila miRNAs perfectly matches 3′-UTR elements that mediate mRNA decay and translational repression (Lai, 2002Lai E.C. Micro RNAs are complementary to 3′ UTR sequence motifs that mediate negative post-transcriptional regulation.Nat. Genet. 2002; 30: 363-364Crossref PubMed Scopus (602) Google Scholar), as well as subsequent experiments showing that miRNA-like regulation was most sensitive to nucleotide substitutions that disrupt seed pairing (Doench and Sharp, 2004Doench J.G. Sharp P.A. Specificity of microRNA target selection in translational repression.Genes Dev. 2004; 18: 504-511Crossref PubMed Scopus (872) Google Scholar, Kloosterman et al., 2004Kloosterman W.P. Wienholds E. Ketting R.F. Plasterk R.H. Substrate requirements for let-7 function in the developing zebrafish embryo.Nucleic Acids Res. 2004; 32: 6284-6291Crossref PubMed Scopus (146) Google Scholar, Brennecke et al., 2005Brennecke J. Stark A. Russell R.B. Cohen S.M. Principles of microRNA-target recognition.PLoS Biol. 2005; 3: e85Crossref PubMed Scopus (783) Google Scholar, Lai et al., 2005Lai E.C. Tam B. Rubin G.M. Pervasive regulation of Drosophila Notch target genes by GY-box-, Brd-box-, and K-box-class microRNAs.Genes Dev. 2005; 19: 1067-1080Crossref PubMed Scopus (185) Google Scholar). The second conclusion is that conserved pairing to the seed region can also be sufficient on its own for predicting conserved targets above the noise of false-positive predictions (Brennecke et al., 2005Brennecke J. Stark A. Russell R.B. Cohen S.M. Principles of microRNA-target recognition.PLoS Biol. 2005; 3: e85Crossref PubMed Scopus (783) Google Scholar, Krek et al., 2005Krek A. Grun D. Poy M.N. Wolf R. Rosenberg L. Epstein E.J. MacMenamin P. da Piedade I. Gunsalus K.C. Stoffel M. et al.Combinatorial microRNA target predictions.Nat. Genet. 2005; 37: 495-500Crossref PubMed Scopus (2184) Google Scholar, Lewis et al., 2005Lewis B.P. Burge C.B. Bartel D.P. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (4707) Google Scholar). For example, mammalian targets can be predicted by simply searching for conserved 7 nt matches in aligned regions of vertebrate 3′ UTRs (Lewis et al., 2005Lewis B.P. Burge C.B. Bartel D.P. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (4707) Google Scholar). Prediction specificity increases when requiring an 8 nt match or multiple matches to the same miRNA, but systematic analysis of preferentially conserved features indicates that most targets of a given miRNA have only a single 7 nt match to that miRNA seed region. Fortunately, enough genomes have been sequenced and aligned such that these targets with single sites can now be predicted with confidence that most are authentic; when assessing the evolutionary conservation of 7 nt motifs that match miRNAs compared to those that do not match miRNAs but are of equal abundance in the UTRs, the ratio of predicted targets to estimated false positives is 3.5:1 in a five-genome analysis that extends to chicken (Lewis et al., 2005Lewis B.P. Burge C.B. Bartel D.P. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (4707) Google Scholar). Hence, a simple three-step protocol can predict evolutionarily conserved targets for a metazoan miRNA: (1) Identify the two 7 nt matches to the seed region (Figures 1A and 1B). For example, miR-1, with sequence 5′-UGGAAUGUAAAGAAGUAUGUA, would recognize the CAUUCCA match and the ACAUUCC match. (2) Use available whole-genome alignments (Karolchik et al., 2008Karolchik D. Kuhn R.M. Baertsch R. Barber G.P. Clawson H. Diekhans M. Giardine B. Harte R.A. Hinrichs A.S. Hsu F. et al.The UCSC Genome Browser Database: 2008 update.Nucleic Acids Res. 2008; 36: D773-D779Crossref PubMed Scopus (376) Google Scholar) to compile orthologous 3′ UTRs. (3) Search within the orthologous UTRs for conserved occurrence of either 7 nt match. These are predicted regulatory sites. Note that members of the same miRNA family (i.e., miRNAs with the same sequence at nucleotides 2–8) all share the same predicted targets. A search for conserved 8 nt sites comprised of both 7 nt motifs (e.g., ACAUUCCA, in the case of miR-1, Figure 1C) yields greater prediction specificity, whereas a search for conserved 6 nt seed matches (Figure 1D) yields greater sensitivity. When only a few genomes are available, those sites present at orthologous positions in all genomes examined are the ones considered conserved. When more genomes are available, more sophisticated measures of conservation increase the information gleaned from the alignments (Gaidatzis et al., 2007Gaidatzis D. van Nimwegen E. Hausser J. Zavolan M. Inference of miRNA ta