BMC Genomics 2005, 6:88 http://www.biomedcentral.com/1471-2164/6/88 regulation may be a general phenomenon. Several hun- dred miRNAs have since been identified in a variety of plants and animals through cloning and computational methods, including 78 miRNAs in Drosophila [6]. Many of these miRNAs are expressed in a temporal or tissue-spe- cific dependent manner [1]. miRNAs in animals usually act to repress translation of their target genes through imperfect hybridization to com- plementary sites in target 3' UTRs [2,7,8]. This transla- tional repression occurs post-initiation, since miRNA- induced gene silencing does not change the abundance or polysome profile of target mRNA, at least in the examples tested [9,10]. This is in contrast to RNAi, in which short RNAs called siRNAs are usually perfectly complementary to their target mRNA and result in its degradation [11-14]. A miRNA directed against a perfectly complementary 3' UTR target site also results in mRNA degradation [15,16], indicating that a miRNA can function in the RNAi path- way given a perfectly complementary target site. miRNAs are produced from a larger transcript through stepwise processing by ribonuclease III-like endonucleases in the nucleus and cytoplasm [17-19]. Following maturation, miRNAs reside in a miRNA ribonucleoprotein complex (miRNP) which shares many similarities to the RNA- induced silencing complex (RISC) involved in RNAi [1,16,20-22]. While many animal miRNAs have been identified, only a few have a known function or target [2,23-28]. Incom- plete base pairing of miRNA to target causes inherent dif- ficulty in the prediction of miRNA targets due to the high levels of noise involved in any simple alignment of miR- NAs to 3' UTRs. In addition, the very few experimentally derived miRNA/target pairs provide limited biological information needed to define the necessary and sufficient characteristics for a miRNA/target pair. Therefore, miRNA target prediction programs for which the selection param- eters can easily be adjusted based on current interpreta- tion of miRNA/target constraints, and on newly discovered rules governing miRNA/target interactions, are a valuable resource to the research community. Implementation Our bioinformatics approach to identifying miRNA tar- gets includes two steps: the creation of a database of potential targets, and screening all possible miRNA/target pairs for adherence to constraints suggested by analysis of the known miRNA/target interactions. Potential miRNA target database The selection of sequences for the database was guided by progress in understanding the actions and features of miR- NAs and their targets. All known animal miRNAs appear to target regions in the 3' UTRs of mRNAs [2,23-28], and so the database was limited to 3' UTR sequences. miRNAs are highly conserved, particularly in closely related species [1,5], and 68 of the 78 known D. mela- nogaster miRNAs are identical to their predicted counter- parts from D. pseudoobscura. The constraint on miRNA evolution is thought to be a consequence of their interac- tion with multiple targets, thereby restricting the rate of change of both the miRNA and its targets [29]. In addi- tion, miRNA targets that have been experimentally derived are very highly conserved in other species [1,5,7,24,27]. Therefore, the database was further limited to highly conserved regions of 3' UTRs. Finally, the majority of experimentally derived miRNA targets contain multiple predicted target sites[1,2,23-28]. Our approach to allow detection of multiple targets in a single 3' UTR was to fragment the database sequences into segments no longer than 50 nt, each of which is tested for target sites. For conserved 3' UTR segments longer than 50 nt, overlapping 50 nt segments with end points differing by 5 nt were added to the database (i.e. a 100 nt sequence would be fragmented into 11 overlapping 50 nt seg- ments). We chose 50 nt for the maximum target site length since all predicted target sites of known miRNA tar- gets are less than this size [2,23-28]. The Berkeley Genome Pipeline [30,31] was accessed to obtain all 3' UTR sequences which are at least 80% con- served between D. melanogaster and D. pseudoobscura, and are at least 12 nt long [the smallest predicted target site of known miRNA targets that we are aware of is 13 nts in length [2]]. The D. pseudoobscura genome sequence is largely known, but the last stages of sequence finishing (to allow assembly of the final sequence from the large number of shorter contigs) and annotation are not com- plete. Thus some regions of the D. pseudoobscura sequence that are highly conserved with D. melanogaster 3' UTRs have not been definitively linked to a coding region. Nevertheless, these conserved sequences were included to ensure that the largest fraction of potential miRNA target sites would be evaluated in the prediction process. Using D. melanogaster genome annotation release 3.1 (BDGP) we obtained 14,287 annotated 3' UTRs. Of these, 6702 contained unique segments, at least 12 nt in length and 80% conserved with D. pseudoob- scura DNA, that were included in the database. The 6702 database entries correspond to 6399 different genes, with some genes represented more than once because of alter- nate splicing. Biological miRNA target constraints The MovingTargets algorithm applies a set of five biologi- cal constraints to all possible alignments of each miRNA Page 2 of 11 (page number not for citation purposes)