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MicroInspector: a web tool for detection of miRNA binding sites in an RNA sequence

MicroInspector: a web tool for detection of miRNA binding sites in an RNA sequence W696–W700 Nucleic Acids Research, 2005, Vol. 33, Web Server issue doi:10.1093/nar/gki364 MicroInspector: a web tool for detection of miRNA binding sites in an RNA sequence 1,2 1,2 2 1, Ventsislav Rusinov , Vesselin Baev , Ivan Nikiforov Minkov and Martin Tabler * Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology—Hellas, PO Box 1527, GR-71110 Heraklion/Crete, Greece and Department of Plant Physiology and Molecular Biology, University of Plovdiv, 24, Tsar Assen St, 4000 Plovdiv, Bulgaria Received February 3, 2005; Accepted February 23, 2005 function of miRNAs, which can be found in animals and plants ABSTRACT (4–11). MiRNAs operate by base-pairing interactions with an Regulation of post-transcriptional gene expression by mRNA target. However, perfect sequence complementarity to microRNAs (miRNA) has so far been validated for only an miRNA is observed only for some plant mRNAs (12), but in a few mRNA targets. Based on the large number of the majority of residual cases, including the first identified miRNA genes and the possibility that one miRNA miRNA target pairs (13), the base-pairing interaction between might influence gene expression of several targets the mRNA target and the riboregulator is imperfect. There simultaneously, the quantity of ribo-regulated genes seems to be a preference for a strong interaction at the 5 side of the miRNA (14) and a symmetrical interaction is pre- is expected to be much higher. Here, we describe the ferred (15), and most likely, the RNA–RNA interaction web tool MicroInspector that will analyse a user- requires assistance of protein factors. Collectively, >1500 defined RNA sequence, which is typically an mRNA miRNAs have been identified so far for plants, nematodes, or a part of an mRNA, for the occurrence of binding insects and mammals. This large number of recognized sites for known and registered miRNAs. The program miRNAs contrasts with only a few dozen of target RNAs, allows variation of temperature, the setting of energy for which a regulatory miRNA binding has been experiment- values as well as the selection of different miRNA ally verified. Some miRNAs are expected to form regulatory databases to identify miRNA-binding sites of different networks controlling several mRNA targets. Lai (16) has strength. MicroInspector could spot the correct sites found that some short sequence elements (boxes) that had for miRNA-interaction in known target mRNAs. Using been previously recognized as negative modulators of trans- lational gene expression are actually binding sites for certain other mRNAs, for which such an interaction has not classes of miRNAs. For example, the K box is negatively yet been described, we discovered frequently poten- regulating gene expression in several gene families, which tial miRNA binding sites of similar quality, which can are involved in early developmental processes in Drosophila now be analysed experimentally. The MicroInspector melanogaster and at least four miRNAs (miR2, miR6, miR11 program is easy to use and does not require specific and miR13) are at their 5 end complementary to the K box. computer skills. The service can be accessed via However, not every miRNA of the K-box family will bind to the MicroInspector web server at http://www.imbb. each K box containing mRNA, suggesting that at least some forth.gr/microinspector. subsets of miRNAs are composed of at least two modular elements, which we had termed ‘first name’ and ‘family’ motif (17). Several attempts have been made to identify miRNA targets by bioinformatics (18–22). In Arabidopsis INTRODUCTION thaliana, this approach was quite successful, since plant Micro RNAs (miRNA) are a class of genome-encoded small, miRNAs seem to base-pair with higher stringency (23,24). single-stranded RNAs of 20 nt that are negative regulators of For animal miRNAs and especially for mammalian miRNAs, gene expression. Discovered three years ago (1–3), miRNAs this computational strategy will only identify those mRNA have attracted a lot of attention and a large number of recent targets that have a high degree of sequence complementarity. reviews summarize the biogenesis, phylogenetic relation and However, some of the genetically verified miRNA/mRNA *To whom correspondence should be addressed. Tel: +30 2810 394365; Fax: +30 2810 394408; Email: [email protected] The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors ª The Author 2005. Published by Oxford University Press. All rights reserved. The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact [email protected] W697 Nucleic Acids Research, 2005, Vol. 33, Web Server issue interactions (13,25) are not particularly strong in terms of RNA–RNA interaction. On the other hand, if one allows weak interactions, the number of false positive hits will raise in computational screens. Brennecke and Cohen (26) have addressed these difficulties by incorporation of phylogenetic parameters into the computer algorithm, which improves target identification. Here, we describe a different computational approach to identify miRNA/mRNA interactions. Whereas most pro- grams available start with a specific miRNA and attempt the identification of as many mRNA targets as possible, we ask a different and more modest question by analysing whether, in a given mRNA sequence a binding site can be found for any miRNA that originates from this organism and that is available in the database. The MicroInspector program will generate a list of possible target sites, sorted by free energy values. Adaptation of temperature and free energy settings, followed by visual inspection of secondary structures allows a detailed analysis. This approach allows more detailed examination of an mRNA sequence, identifying also weaker interactions, which can then be subjected to experimental tests. Several mRNAs that contain validated miRNA binding sites were subjected to analysis by the MicroInspector software, and all these interactions could be identified. However, in many other cases, we identified so far non-described inter- actions with lower energy values than those of the validated targets, suggesting that many more miRNAs/mRNA inter- actions are likely to exist. Their biological relevance requires subsequent experimental validation. Usage of the program MicroInspector is a web-based tool for searching miRNA bind- ing sites in a target RNA sequence, potentially regulated by such a small RNA. The interface of the program is given in Figure 1. The user needs to follow a few simple steps to perform a quest for potential miRNA binding sites. The first step is ‘entering the sequence’ to be analysed, which is typically an mRNA (the program treats DNA sequences as RNA). This can be done in two ways, either by providing the GenBank or TAIR accession number or by simply typing or pasting in the sequence (the program is designed that all gaps, numbers and non-defined characters will be ignored), which is useful for the analysis of unknown sequences or for detailed analysis of certain 0 0 mRNA domains, e.g. 3 -untranslated regions (3 -UTRs). As a next step, the user needs to set a ‘hybridization temperature’: the default is 37 C, but evidently this value is not relevant for plants and insects, for which we recommend the values in Figure 2. Further, a value for the ‘free energy’ cut-off needs to be entered (default 20 kcal/mol), which characterizes the stability of the miRNA/mRNA interaction. Only results with lower energy than the cut-off value will be Figure 1. The MicroInspector interface. The user has to enter three categories displayed, so that this parameter will influence the number of of input parameters for scanning a target RNA for miRNA binding sites. There hits. The energy value should be varied in accordance with the is a help pop-up window with brief explanations for each of the data fields. temperature according to Figure 2. As an indication, it might be helpful to add that the free energies of validated miRNA/ mRNA interactions range from 17 kcal/mol (bantam/hid5 local miRNA databases (in multifasta format) are based on at 25 C—Drosophila melanogaster)to 41 kcal/mol (CUC/ entries of ’the miRNA registry’ (http://www.sanger.ac.uk/ miR164 at 25 C—Arabidopsis thaliana). Software/Rfam/mirna/index.shtml). Unless automatic retriev- Finally, the user needs to select an ‘miRNA database’, ing of new miRNA entries will be possible, we will update matching the biological origin of the target sequence. These the databases manually in regular intervals. W698 Nucleic Acids Research, 2005, Vol. 33, Web Server issue Principle of the program simultaneously and independently with two windows of 6 nt. The first 6-nt window represents nucleotides 1–6 (from the 5 Initial scanning and filtering. The user-defined target sequence of the miRNA), and the second window nucleotides 2–7. They is analysed for every miRNA sequence of the chosen data- are slid through the target sequence (by steps of 1 nt) and the base in a consecutive manner. The target sequence is scanned program performs analysis of complementarity. It is known that pairing to the 5 portion of the miRNA, particularly nucleotides 2–7, appears to be most important for target recog- nition by vertebrate miRNAs. The most 5 -terminal miRNA nucleotide may or may not participate in binding. A complementarity pre-filter seeks for each of the two 6-nt windows for domains having 5 Watson–Crick base pairs or 4 Watson–Crick base pairs with at least one additional G:U pair. If neither of the two windows fulfil this requirement, the data are ignored and the 6-nt windows are moved by 1 nt towards the 5 end of the mRNA. When the sequence analysis identifies at least one 6-nt window as described above, the program will initiate a detailed analysis of this site. It extracts a 32-nt Figure 2. Recommended settings for hybridization temperatures ( C) and corresponding free energy cut-off values in kcal/mol for different species. sequence of the mRNA terminating at the nucleotide that Figure 3. Example of a data output of a MicroInspector analysis seeking for miRNA binding sites in the 3 -UTR sequence of the Caenorhabditis elegans gene lin-41. Please note that the verified interaction of miRNA let-7 is identified at position 726. In addition, the program identifies other interactions, including the interaction with miR-38 (top result on table), which is stronger than the interaction with let-7. The significance of each identified interaction can be analysed by activating the link that will display the secondary structure of the specific interaction as demonstrated in Figure 4; for further details see text. W699 Nucleic Acids Research, 2005, Vol. 33, Web Server issue 0 0 matches the 5 end of the miRNA, i.e. the 5 -terminal nucle- In the ‘free energy’ column the Gibbs free energy (DG)of otide of the first 6-nt window. Subsequently, the miRNA the duplex structure is indicated in kcal/mol. Entries are sorted sequence and the 32-nt potential target sequence domain by free energy (lowest values on top). However, the DG value are subjected to a pair-wise hybridization folding algorithm. is not the only characteristic feature of a good binding site. For example, a longer miRNA, or a miRNA that is rich in GC, Dynamic hybridization and folding algorithm. MicroInspector is more likely to yield predicted low energy binding sites. uses a dynamic algorithm for the primary window alignment Also the symmetry of binding is an important factor, as is that is based on the complementarity of nucleotides—it allows the stability of the base-pairing at the 5 end of the miRNA. Watson–Crick and G:U wobble basepairs. For calculation of These restrictions require a detailed manual inspection of a thermodynamic properties of a predicted duplex in the algo- particular binding site. For this reason, the rightmost column rithm, we integrated some folding routines from the Vienna contains a link to the graphics (PostScript format) displaying RNA secondary structure programming library (RNAlib) from the secondary structure of the actual RNA–RNA interaction as the Vienna RNA 1.5 version package (27,28) (see http:// exemplified in Figure 4. Inspection of the individual structures www.tbi.univie.ac.at/~ivo/RNA/RNAlib.html), which itself revealed that the binding site of miR-38 (top of the list in makes use of the RNA energy parameters of the Turner labor- Figure 3) might not be functional despite its low free energy atory (29) (http://rna.chem.rochester.edu/). (Figure 4A), while the interaction with miR-249 (number 6 on This folding analysis will reveal the free energy, as well as the list of Figure 3) results a in symmetrical RNA–RNA inter- the secondary structure of this RNA–RNA interaction. We action (Figure 4B) that is likely to be biologically relevant. chose a limit of 32 nt, because most miRNA–mRNA interac- The MicroInspector program also offers the download of tions will cover a smaller region than this. Therefore, only few the results as a single file for off-line analysis. A link to the significant hits are likely to be missed, in cases where longer result file is located at the bottom of the table—‘Results in binding domains are present. Hits below the selected threshold .CSV format’. The file format ‘Comma separated value’ can be value for the free energy will be saved and subjected to a post- imported into Excel tables. The result file contains additional filter analysis. helpful information such as the date of analysis, the filename of the secondary structure graph and a schematic representa- tion of the secondary structure of the duplex as shown in Post-filter—2D analysis. The second filter of the program can Figure 4C. discard binding sites that do not fit known features of miRNA– At the very bottom of the result page, the positions of the mRNA duplexes. This filter inspects the RNA–RNA structure binding sites of the miRNAs with respect to the mRNA target after folding, and eliminates any hit characterized by two 0 0 are shown as an overview. Every potential interaction lists the unpaired nucleotides on either the 5 or the 3 side of the name of the miRNA and the binding strength (DG value). If miRNA sequence. The filter will also exclude structures binding sites overlap, the potential interactions will be sorted with low folding energy values that are the result of self- so that those with the lowest free energy are on top. complementarity in one of the two RNA strands. For example, this applies when the target domain forms an intramolecular hairpin. Further, entries will be eliminated if too large interior or bulge loops are predicted, or if large loops are located too close to the end of the secondary structure (>10 unpaired nucleotides). Central interior loops will be tolerated even if the loop size is large. Output of the program To illustrate the output given by MicroInspector, we present as an example an analysis of the miRNA binding sites for the 3 - UTR sequence of the Caenorhabditis elegans gene lin-41, which is known to interact with miRNA let7 (Entry name 3CEL000914 3 -UTR in Caenorhabditis elegans LIN41A (lin41A) mRNA, complete cds, from LION SRS database). The main results of this MicroInspector query are repres- ented as a table (see example in Figure 3). The first column of the table lists the ‘position’ of the 5 end of the binding-site in the target RNA. The second column indicates the ‘target RNA Figure 4. Representation of pair-wise interaction between miRNA and mRNA name’ (accession number) which can be used as a link to target. Examples of secondary structure graphics that can be displayed when the access the sequence entry of the GenBank database. This link of the right column in the result table (see Figure 3) is activated. (A) This column will be empty if the sequence has been entered by specific example displays the predicted interaction of miR-38 with lin-41 (top typing or pasting in. The third column indicates the ‘target result in table of Figure 3), which shows that the interaction of the miRNA and 0 0 the target mRNA is restricted to the 5 side of the miRNA; at the 3 side the sequence’ (capital letters) of the domain potentially interacting interaction is rather weak. Despite the low DG value, this interaction might not with the miRNA, followed by the ‘miRNA name’ (according be functional. (B) The interaction of miR-249 with lin-41 is symmetrical and to ‘the miRNA registry’) and the ‘miRNA sequence’ (lower- more likely to be relevant. (C) The same interaction as in (B) in a schematic case letters) of the matching miRNA in columns four and five. representation; this simplified illustration of an RNA–RNA interaction is used 0 0 Both sequences are given 5 to 3 . in the downloadable results file ‘Results in .CSV format’ (see Figure 3). W700 Nucleic Acids Research, 2005, Vol. 33, Web Server issue Implementation (computer data) 7. He,L. and Hannon,G.J. (2004) MicroRNAs: small RNAs with a big role in gene regulation. Nature Rev. Genet., 5, 522–531. The program is implemented as a Perl CGI-script, taking 8. Nelson,P., Kiriakidou,M., Sharma,A., Maniataki,E. and Mourelatos,Z. advantage of the modular design, allowing the use of special- (2003) The microRNA world: small is mighty. Trends Biochem. Sci., 28, 534–540. ized packages such as BioPerl (modules for developers of Perl- 9. Murchison,E.P. and Hannon,G.J. (2004) miRNAs on the move: miRNA based software for life science research). The program was biogenesis and the RNAi machinery. Curr. Opin. Cell. Biol., 16, tested on a PC with an Intel Pentium IV processor 2.8 GHz and 223–229. 1 GB RAM memory. The operation system is Fedora Core 2.0 10. He,Z. and Sontheimer,E.J. (2004) ‘siRNAs and miRNAs’: a meeting report on RNA silencing. RNA, 10, 1165–1173. by Red Hat Linux. The versions used are 5.8.5 for Perl (www. 11. Lai,E.C. (2003) microRNAs: runts of the genome assert themselves. perl.com) and version 1.4 for BioPerl (www.bioperl.org). The Curr. Biol., 13, R925–R936. access to the multi-fasta format sequence files and to the online 12. Reinhart,B.J., Weinstein,E.G., Rhoades,M.W., Bartel,B. and Bartel,D.P. databases is accomplished by the BioPerl modules. The results (2002) MicroRNAs in plants. Genes Dev., 16, 1616–1626. and all additional pieces of information are saved in a mySQL 13. Lee,R.C., Feinbaum,R.L. and Ambros,V. (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense database for each session. The tables and files with the sec- complementarity to lin-14. Cell, 75, 843–854. ondary structures will remain available for 3 days after the 14. Doench,J.G. and Sharp,P.A. (2004) Specificity of microRNA target researcher’s query. Every target analysis is loaded in an indi- selection in translational repression. Genes Dev., 18, 504–511. vidual table in the corresponding mySQL database. 15. Kiriakidou,M., Nelson,P.T., Kouranov,A., Fitziev,P., Bouyioukos,C., Mourelatos,Z. and Hatzigeorgiou,A. (2004) A combined computational-experimental approach predicts human microRNA targets. Genes Dev., 18, 1165–1178. ACKNOWLEDGEMENTS 16. Lai,E.C. (2002) Micro RNAs are complementary to 3 UTR sequence motifs that mediate negative post-transcriptional regulation. Nature We thank Viktor Ivanov (University of Plovdiv) for the graphic Genet., 30, 363–364. design of the site. V.R. and V.B. have been supported by the 17. Boutla,A., Delidakis,C. and Tabler,M. (2003) Developmental defects by European Union (EU) via Marie Curie training fellowships antisense-mediated inactivation of micro-RNAs 2 and 13 in Drosophila and the identification of putative target genes. Nucleic Acids Res., (contract HPMT-CT-2000-00175) and are currently supported 31, 4973–4980. in the same program under contract EST-7295-FAMED. 18. Adai,A., Johnson,C., Mlotshwa,S., Archer-Evans,S., Manocha,V., Further, this work was supported in parts by grants to I.M. by Vance,V. and Sundaresan,V. (2005) Computational prediction of the projects G3-02 and K1202/02 of the Bulgarian National miRNAs in Arabidopsis thaliana. Genome Res., 15, 78–91. 19. Lai,E.C., Tomancak,P., Williams,R.W. and Rubin,G.M. (2003) Science Council and to M.T. by the General Secretariat for Computational identification of Drosophila microRNA genes. Genome Research and Technology of the Hellenic Ministry of Biol., 4, R42. Development via the Bulgarian-Greek cooperation program 20. Lim,L.P., Lau,N.C., Weinstein,E.G., Abdelhakim,A., Yekta,S., (PN18/3-1-2003) and by the European Union FP6-2003- Rhoades,M.W., Burge,C.B. and Bartel,D.P. (2003) The microRNAs of Caenorhabditis elegans. Genes Dev., 17, 991–1008. LIFESCIHEALTH-I program, within project FOSRAK (con- 21. Enright,A.J., John,B., Gaul,U., Tuschl,T., Sander,C. and Marks,D.S. tract LSH-CT-2004-005120). The Open Access publication (2003) MicroRNA targets in Drosophila. Genome Biol., 5, R1. charges for this article were waived by Oxford University Press. 22. John,B., Enright,A.J., Aravin,A., Tuschl,T., Sander,C. and Marks,D.S. (2004) Human MicroRNA Targets. PLoS Biol., 2, e363. Conflict of interest statement. None declared. 23. Bartel,D.P. and Chen,C.Z. (2004) Micromanagers of gene expression: the potentially widespread influence of metazoan microRNAs. Nature Rev. Genet., 5, 396–400. 24. Carrington,J.C. and Ambros,V. 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(1994) Fast folding and comparison of RNA secondary 4. Ambros,V. (2001) microRNAs: tiny regulators with great potential. structures. Monatshefte f. Chemie, 125, 167–188. Cell, 107, 823–826. 28. Hofacker,I.L. (2003) Vienna RNA secondary structure server. 5. Ambros,V. (2003) MicroRNA pathways in flies and worms: Nucleic Acids Res., 31, 3429–3431. growth, death, fat, stress, and timing. Cell, 113, 673–676. 29. Serra,M.J. and Turner,D.H. (1995) Predicting thermodynamic properties 6. Ambros,V. (2004) The functions of animal microRNAs. Nature, of RNA. Methods Enzymol., 259, 242–261. 431, 350–355. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Nucleic Acids Research Oxford University Press

MicroInspector: a web tool for detection of miRNA binding sites in an RNA sequence

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© The Author 2005. Published by Oxford University Press. All rights reserved
 The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact [email protected]
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W696–W700 Nucleic Acids Research, 2005, Vol. 33, Web Server issue doi:10.1093/nar/gki364 MicroInspector: a web tool for detection of miRNA binding sites in an RNA sequence 1,2 1,2 2 1, Ventsislav Rusinov , Vesselin Baev , Ivan Nikiforov Minkov and Martin Tabler * Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology—Hellas, PO Box 1527, GR-71110 Heraklion/Crete, Greece and Department of Plant Physiology and Molecular Biology, University of Plovdiv, 24, Tsar Assen St, 4000 Plovdiv, Bulgaria Received February 3, 2005; Accepted February 23, 2005 function of miRNAs, which can be found in animals and plants ABSTRACT (4–11). MiRNAs operate by base-pairing interactions with an Regulation of post-transcriptional gene expression by mRNA target. However, perfect sequence complementarity to microRNAs (miRNA) has so far been validated for only an miRNA is observed only for some plant mRNAs (12), but in a few mRNA targets. Based on the large number of the majority of residual cases, including the first identified miRNA genes and the possibility that one miRNA miRNA target pairs (13), the base-pairing interaction between might influence gene expression of several targets the mRNA target and the riboregulator is imperfect. There simultaneously, the quantity of ribo-regulated genes seems to be a preference for a strong interaction at the 5 side of the miRNA (14) and a symmetrical interaction is pre- is expected to be much higher. Here, we describe the ferred (15), and most likely, the RNA–RNA interaction web tool MicroInspector that will analyse a user- requires assistance of protein factors. Collectively, >1500 defined RNA sequence, which is typically an mRNA miRNAs have been identified so far for plants, nematodes, or a part of an mRNA, for the occurrence of binding insects and mammals. This large number of recognized sites for known and registered miRNAs. The program miRNAs contrasts with only a few dozen of target RNAs, allows variation of temperature, the setting of energy for which a regulatory miRNA binding has been experiment- values as well as the selection of different miRNA ally verified. Some miRNAs are expected to form regulatory databases to identify miRNA-binding sites of different networks controlling several mRNA targets. Lai (16) has strength. MicroInspector could spot the correct sites found that some short sequence elements (boxes) that had for miRNA-interaction in known target mRNAs. Using been previously recognized as negative modulators of trans- lational gene expression are actually binding sites for certain other mRNAs, for which such an interaction has not classes of miRNAs. For example, the K box is negatively yet been described, we discovered frequently poten- regulating gene expression in several gene families, which tial miRNA binding sites of similar quality, which can are involved in early developmental processes in Drosophila now be analysed experimentally. The MicroInspector melanogaster and at least four miRNAs (miR2, miR6, miR11 program is easy to use and does not require specific and miR13) are at their 5 end complementary to the K box. computer skills. The service can be accessed via However, not every miRNA of the K-box family will bind to the MicroInspector web server at http://www.imbb. each K box containing mRNA, suggesting that at least some forth.gr/microinspector. subsets of miRNAs are composed of at least two modular elements, which we had termed ‘first name’ and ‘family’ motif (17). Several attempts have been made to identify miRNA targets by bioinformatics (18–22). In Arabidopsis INTRODUCTION thaliana, this approach was quite successful, since plant Micro RNAs (miRNA) are a class of genome-encoded small, miRNAs seem to base-pair with higher stringency (23,24). single-stranded RNAs of 20 nt that are negative regulators of For animal miRNAs and especially for mammalian miRNAs, gene expression. Discovered three years ago (1–3), miRNAs this computational strategy will only identify those mRNA have attracted a lot of attention and a large number of recent targets that have a high degree of sequence complementarity. reviews summarize the biogenesis, phylogenetic relation and However, some of the genetically verified miRNA/mRNA *To whom correspondence should be addressed. Tel: +30 2810 394365; Fax: +30 2810 394408; Email: [email protected] The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors ª The Author 2005. Published by Oxford University Press. All rights reserved. The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact [email protected] W697 Nucleic Acids Research, 2005, Vol. 33, Web Server issue interactions (13,25) are not particularly strong in terms of RNA–RNA interaction. On the other hand, if one allows weak interactions, the number of false positive hits will raise in computational screens. Brennecke and Cohen (26) have addressed these difficulties by incorporation of phylogenetic parameters into the computer algorithm, which improves target identification. Here, we describe a different computational approach to identify miRNA/mRNA interactions. Whereas most pro- grams available start with a specific miRNA and attempt the identification of as many mRNA targets as possible, we ask a different and more modest question by analysing whether, in a given mRNA sequence a binding site can be found for any miRNA that originates from this organism and that is available in the database. The MicroInspector program will generate a list of possible target sites, sorted by free energy values. Adaptation of temperature and free energy settings, followed by visual inspection of secondary structures allows a detailed analysis. This approach allows more detailed examination of an mRNA sequence, identifying also weaker interactions, which can then be subjected to experimental tests. Several mRNAs that contain validated miRNA binding sites were subjected to analysis by the MicroInspector software, and all these interactions could be identified. However, in many other cases, we identified so far non-described inter- actions with lower energy values than those of the validated targets, suggesting that many more miRNAs/mRNA inter- actions are likely to exist. Their biological relevance requires subsequent experimental validation. Usage of the program MicroInspector is a web-based tool for searching miRNA bind- ing sites in a target RNA sequence, potentially regulated by such a small RNA. The interface of the program is given in Figure 1. The user needs to follow a few simple steps to perform a quest for potential miRNA binding sites. The first step is ‘entering the sequence’ to be analysed, which is typically an mRNA (the program treats DNA sequences as RNA). This can be done in two ways, either by providing the GenBank or TAIR accession number or by simply typing or pasting in the sequence (the program is designed that all gaps, numbers and non-defined characters will be ignored), which is useful for the analysis of unknown sequences or for detailed analysis of certain 0 0 mRNA domains, e.g. 3 -untranslated regions (3 -UTRs). As a next step, the user needs to set a ‘hybridization temperature’: the default is 37 C, but evidently this value is not relevant for plants and insects, for which we recommend the values in Figure 2. Further, a value for the ‘free energy’ cut-off needs to be entered (default 20 kcal/mol), which characterizes the stability of the miRNA/mRNA interaction. Only results with lower energy than the cut-off value will be Figure 1. The MicroInspector interface. The user has to enter three categories displayed, so that this parameter will influence the number of of input parameters for scanning a target RNA for miRNA binding sites. There hits. The energy value should be varied in accordance with the is a help pop-up window with brief explanations for each of the data fields. temperature according to Figure 2. As an indication, it might be helpful to add that the free energies of validated miRNA/ mRNA interactions range from 17 kcal/mol (bantam/hid5 local miRNA databases (in multifasta format) are based on at 25 C—Drosophila melanogaster)to 41 kcal/mol (CUC/ entries of ’the miRNA registry’ (http://www.sanger.ac.uk/ miR164 at 25 C—Arabidopsis thaliana). Software/Rfam/mirna/index.shtml). Unless automatic retriev- Finally, the user needs to select an ‘miRNA database’, ing of new miRNA entries will be possible, we will update matching the biological origin of the target sequence. These the databases manually in regular intervals. W698 Nucleic Acids Research, 2005, Vol. 33, Web Server issue Principle of the program simultaneously and independently with two windows of 6 nt. The first 6-nt window represents nucleotides 1–6 (from the 5 Initial scanning and filtering. The user-defined target sequence of the miRNA), and the second window nucleotides 2–7. They is analysed for every miRNA sequence of the chosen data- are slid through the target sequence (by steps of 1 nt) and the base in a consecutive manner. The target sequence is scanned program performs analysis of complementarity. It is known that pairing to the 5 portion of the miRNA, particularly nucleotides 2–7, appears to be most important for target recog- nition by vertebrate miRNAs. The most 5 -terminal miRNA nucleotide may or may not participate in binding. A complementarity pre-filter seeks for each of the two 6-nt windows for domains having 5 Watson–Crick base pairs or 4 Watson–Crick base pairs with at least one additional G:U pair. If neither of the two windows fulfil this requirement, the data are ignored and the 6-nt windows are moved by 1 nt towards the 5 end of the mRNA. When the sequence analysis identifies at least one 6-nt window as described above, the program will initiate a detailed analysis of this site. It extracts a 32-nt Figure 2. Recommended settings for hybridization temperatures ( C) and corresponding free energy cut-off values in kcal/mol for different species. sequence of the mRNA terminating at the nucleotide that Figure 3. Example of a data output of a MicroInspector analysis seeking for miRNA binding sites in the 3 -UTR sequence of the Caenorhabditis elegans gene lin-41. Please note that the verified interaction of miRNA let-7 is identified at position 726. In addition, the program identifies other interactions, including the interaction with miR-38 (top result on table), which is stronger than the interaction with let-7. The significance of each identified interaction can be analysed by activating the link that will display the secondary structure of the specific interaction as demonstrated in Figure 4; for further details see text. W699 Nucleic Acids Research, 2005, Vol. 33, Web Server issue 0 0 matches the 5 end of the miRNA, i.e. the 5 -terminal nucle- In the ‘free energy’ column the Gibbs free energy (DG)of otide of the first 6-nt window. Subsequently, the miRNA the duplex structure is indicated in kcal/mol. Entries are sorted sequence and the 32-nt potential target sequence domain by free energy (lowest values on top). However, the DG value are subjected to a pair-wise hybridization folding algorithm. is not the only characteristic feature of a good binding site. For example, a longer miRNA, or a miRNA that is rich in GC, Dynamic hybridization and folding algorithm. MicroInspector is more likely to yield predicted low energy binding sites. uses a dynamic algorithm for the primary window alignment Also the symmetry of binding is an important factor, as is that is based on the complementarity of nucleotides—it allows the stability of the base-pairing at the 5 end of the miRNA. Watson–Crick and G:U wobble basepairs. For calculation of These restrictions require a detailed manual inspection of a thermodynamic properties of a predicted duplex in the algo- particular binding site. For this reason, the rightmost column rithm, we integrated some folding routines from the Vienna contains a link to the graphics (PostScript format) displaying RNA secondary structure programming library (RNAlib) from the secondary structure of the actual RNA–RNA interaction as the Vienna RNA 1.5 version package (27,28) (see http:// exemplified in Figure 4. Inspection of the individual structures www.tbi.univie.ac.at/~ivo/RNA/RNAlib.html), which itself revealed that the binding site of miR-38 (top of the list in makes use of the RNA energy parameters of the Turner labor- Figure 3) might not be functional despite its low free energy atory (29) (http://rna.chem.rochester.edu/). (Figure 4A), while the interaction with miR-249 (number 6 on This folding analysis will reveal the free energy, as well as the list of Figure 3) results a in symmetrical RNA–RNA inter- the secondary structure of this RNA–RNA interaction. We action (Figure 4B) that is likely to be biologically relevant. chose a limit of 32 nt, because most miRNA–mRNA interac- The MicroInspector program also offers the download of tions will cover a smaller region than this. Therefore, only few the results as a single file for off-line analysis. A link to the significant hits are likely to be missed, in cases where longer result file is located at the bottom of the table—‘Results in binding domains are present. Hits below the selected threshold .CSV format’. The file format ‘Comma separated value’ can be value for the free energy will be saved and subjected to a post- imported into Excel tables. The result file contains additional filter analysis. helpful information such as the date of analysis, the filename of the secondary structure graph and a schematic representa- tion of the secondary structure of the duplex as shown in Post-filter—2D analysis. The second filter of the program can Figure 4C. discard binding sites that do not fit known features of miRNA– At the very bottom of the result page, the positions of the mRNA duplexes. This filter inspects the RNA–RNA structure binding sites of the miRNAs with respect to the mRNA target after folding, and eliminates any hit characterized by two 0 0 are shown as an overview. Every potential interaction lists the unpaired nucleotides on either the 5 or the 3 side of the name of the miRNA and the binding strength (DG value). If miRNA sequence. The filter will also exclude structures binding sites overlap, the potential interactions will be sorted with low folding energy values that are the result of self- so that those with the lowest free energy are on top. complementarity in one of the two RNA strands. For example, this applies when the target domain forms an intramolecular hairpin. Further, entries will be eliminated if too large interior or bulge loops are predicted, or if large loops are located too close to the end of the secondary structure (>10 unpaired nucleotides). Central interior loops will be tolerated even if the loop size is large. Output of the program To illustrate the output given by MicroInspector, we present as an example an analysis of the miRNA binding sites for the 3 - UTR sequence of the Caenorhabditis elegans gene lin-41, which is known to interact with miRNA let7 (Entry name 3CEL000914 3 -UTR in Caenorhabditis elegans LIN41A (lin41A) mRNA, complete cds, from LION SRS database). The main results of this MicroInspector query are repres- ented as a table (see example in Figure 3). The first column of the table lists the ‘position’ of the 5 end of the binding-site in the target RNA. The second column indicates the ‘target RNA Figure 4. Representation of pair-wise interaction between miRNA and mRNA name’ (accession number) which can be used as a link to target. Examples of secondary structure graphics that can be displayed when the access the sequence entry of the GenBank database. This link of the right column in the result table (see Figure 3) is activated. (A) This column will be empty if the sequence has been entered by specific example displays the predicted interaction of miR-38 with lin-41 (top typing or pasting in. The third column indicates the ‘target result in table of Figure 3), which shows that the interaction of the miRNA and 0 0 the target mRNA is restricted to the 5 side of the miRNA; at the 3 side the sequence’ (capital letters) of the domain potentially interacting interaction is rather weak. Despite the low DG value, this interaction might not with the miRNA, followed by the ‘miRNA name’ (according be functional. (B) The interaction of miR-249 with lin-41 is symmetrical and to ‘the miRNA registry’) and the ‘miRNA sequence’ (lower- more likely to be relevant. (C) The same interaction as in (B) in a schematic case letters) of the matching miRNA in columns four and five. representation; this simplified illustration of an RNA–RNA interaction is used 0 0 Both sequences are given 5 to 3 . in the downloadable results file ‘Results in .CSV format’ (see Figure 3). W700 Nucleic Acids Research, 2005, Vol. 33, Web Server issue Implementation (computer data) 7. He,L. and Hannon,G.J. (2004) MicroRNAs: small RNAs with a big role in gene regulation. Nature Rev. Genet., 5, 522–531. The program is implemented as a Perl CGI-script, taking 8. Nelson,P., Kiriakidou,M., Sharma,A., Maniataki,E. and Mourelatos,Z. advantage of the modular design, allowing the use of special- (2003) The microRNA world: small is mighty. Trends Biochem. Sci., 28, 534–540. ized packages such as BioPerl (modules for developers of Perl- 9. Murchison,E.P. and Hannon,G.J. (2004) miRNAs on the move: miRNA based software for life science research). The program was biogenesis and the RNAi machinery. Curr. Opin. Cell. Biol., 16, tested on a PC with an Intel Pentium IV processor 2.8 GHz and 223–229. 1 GB RAM memory. The operation system is Fedora Core 2.0 10. He,Z. and Sontheimer,E.J. (2004) ‘siRNAs and miRNAs’: a meeting report on RNA silencing. RNA, 10, 1165–1173. by Red Hat Linux. The versions used are 5.8.5 for Perl (www. 11. Lai,E.C. (2003) microRNAs: runts of the genome assert themselves. perl.com) and version 1.4 for BioPerl (www.bioperl.org). The Curr. Biol., 13, R925–R936. access to the multi-fasta format sequence files and to the online 12. Reinhart,B.J., Weinstein,E.G., Rhoades,M.W., Bartel,B. and Bartel,D.P. databases is accomplished by the BioPerl modules. The results (2002) MicroRNAs in plants. Genes Dev., 16, 1616–1626. and all additional pieces of information are saved in a mySQL 13. Lee,R.C., Feinbaum,R.L. and Ambros,V. (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense database for each session. The tables and files with the sec- complementarity to lin-14. Cell, 75, 843–854. ondary structures will remain available for 3 days after the 14. Doench,J.G. and Sharp,P.A. (2004) Specificity of microRNA target researcher’s query. Every target analysis is loaded in an indi- selection in translational repression. Genes Dev., 18, 504–511. vidual table in the corresponding mySQL database. 15. Kiriakidou,M., Nelson,P.T., Kouranov,A., Fitziev,P., Bouyioukos,C., Mourelatos,Z. and Hatzigeorgiou,A. (2004) A combined computational-experimental approach predicts human microRNA targets. Genes Dev., 18, 1165–1178. ACKNOWLEDGEMENTS 16. Lai,E.C. (2002) Micro RNAs are complementary to 3 UTR sequence motifs that mediate negative post-transcriptional regulation. Nature We thank Viktor Ivanov (University of Plovdiv) for the graphic Genet., 30, 363–364. design of the site. V.R. and V.B. have been supported by the 17. Boutla,A., Delidakis,C. and Tabler,M. (2003) Developmental defects by European Union (EU) via Marie Curie training fellowships antisense-mediated inactivation of micro-RNAs 2 and 13 in Drosophila and the identification of putative target genes. Nucleic Acids Res., (contract HPMT-CT-2000-00175) and are currently supported 31, 4973–4980. in the same program under contract EST-7295-FAMED. 18. Adai,A., Johnson,C., Mlotshwa,S., Archer-Evans,S., Manocha,V., Further, this work was supported in parts by grants to I.M. by Vance,V. and Sundaresan,V. (2005) Computational prediction of the projects G3-02 and K1202/02 of the Bulgarian National miRNAs in Arabidopsis thaliana. Genome Res., 15, 78–91. 19. Lai,E.C., Tomancak,P., Williams,R.W. and Rubin,G.M. (2003) Science Council and to M.T. by the General Secretariat for Computational identification of Drosophila microRNA genes. Genome Research and Technology of the Hellenic Ministry of Biol., 4, R42. Development via the Bulgarian-Greek cooperation program 20. Lim,L.P., Lau,N.C., Weinstein,E.G., Abdelhakim,A., Yekta,S., (PN18/3-1-2003) and by the European Union FP6-2003- Rhoades,M.W., Burge,C.B. and Bartel,D.P. (2003) The microRNAs of Caenorhabditis elegans. Genes Dev., 17, 991–1008. LIFESCIHEALTH-I program, within project FOSRAK (con- 21. Enright,A.J., John,B., Gaul,U., Tuschl,T., Sander,C. and Marks,D.S. tract LSH-CT-2004-005120). The Open Access publication (2003) MicroRNA targets in Drosophila. Genome Biol., 5, R1. charges for this article were waived by Oxford University Press. 22. John,B., Enright,A.J., Aravin,A., Tuschl,T., Sander,C. and Marks,D.S. (2004) Human MicroRNA Targets. PLoS Biol., 2, e363. Conflict of interest statement. None declared. 23. Bartel,D.P. and Chen,C.Z. (2004) Micromanagers of gene expression: the potentially widespread influence of metazoan microRNAs. Nature Rev. Genet., 5, 396–400. 24. Carrington,J.C. and Ambros,V. 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Nucleic Acids Research – Oxford University Press

Published: Jul 1, 2005

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