Date Published: December 13, 2003
Publisher: Public Library of Science
Author(s): Alexander Stark, Julius Brennecke, Robert B Russell, Stephen M Cohen
Abstract: MicroRNAs (miRNAs) are short RNA molecules that regulate gene expression by binding to target messenger RNAs and by controlling protein production or causing RNA cleavage. To date, functions have been assigned to only a few of the hundreds of identified miRNAs, in part because of the difficulty in identifying their targets. The short length of miRNAs and the fact that their complementarity to target sequences is imperfect mean that target identification in animal genomes is not possible by standard sequence comparison methods. Here we screen conserved 3′ UTR sequences from the Drosophila melanogaster genome for potential miRNA targets. The screening procedure combines a sequence search with an evaluation of the predicted miRNA–target heteroduplex structures and energies. We show that this approach successfully identifies the five previously validated let-7, lin-4, and bantam targets from a large database and predict new targets for Drosophila miRNAs. Our target predictions reveal striking clusters of functionally related targets among the top predictions for specific miRNAs. These include Notch target genes for miR-7, proapoptotic genes for the miR-2 family, and enzymes from a metabolic pathway for miR-277. We experimentally verified three predicted targets each for miR-7 and the miR-2 family, doubling the number of validated targets for animal miRNAs. Statistical analysis indicates that the best single predicted target sites are at the border of significance; thus, target predictions should be considered as tentative until experimentally validated. We identify features shared by all validated targets that can be used to evaluate target predictions for animal miRNAs. Our initial evaluation and experimental validation of target predictions suggest functions for two miRNAs. For others, the screen suggests plausible functions, such as a role for miR-277 as a metabolic switch controlling amino acid catabolism. Cross-genome comparison proved essential, as it allows reduction of the sequence search space. Improvements in genome annotation and increased availability of cDNA sequences from other genomes will allow more sensitive screens. An increase in the number of confirmed targets is expected to reveal general structural features that can be used to improve their detection. While the screen is likely to miss some targets, our study shows that valid targets can be identified from sequence alone.
Partial Text: MicroRNAs (miRNAs) are small RNAs, typically of approximately 21–23 nt, that direct posttranscriptional regulation of gene expression by binding to messenger RNAs (mRNAs). Many endogenously encoded miRNAs have been cloned from plants and animals (Lagos-Quintana et al. 2001, 2002; Lau et al. 2001; Lee and Ambros 2001; Mourelatos et al. 2002; Reinhart et al. 2002; Ambros et al. 2003; Aravin et al. 2003; Lim et al. 2003). Combining these data with computational cross-genome comparison predicts 100–120 miRNA-encoding genes in Caenorhabditis and Drosophila and approximately 250 in mouse and human (Ambros et al. 2003; Grad et al. 2003; Lai et al. 2003; Lim et al. 2003a, 2003b). However, functions have been assigned to only four animal miRNAs (Reinhart et al. 2000; Brennecke et al. 2003; Lee et al. 1993; Wightman et al. 1993; Xu et al. 2003), in part owing to the difficulty in identifying mutations in such small genes. A method to identify the target genes that are regulated by miRNAs would greatly help the study of miRNA function in animals (Ambros 2001).
One of the major limitations in studying animal miRNA function is the difficulty in identifying miRNA targets. Our screening strategy has proven to be useful for predicting new miRNA targets. Three new targets have been experimentally validated for miR-7 and for miR-2, bringing the total number of validated targets of animal miRNAs to 11. In addition, we predict a number of miRNA–target pairs or target families that seem likely to be valid, but require experimental validation. Our study depended on the high-quality annotation of the D. melanogaster genome and the availability of the D. pseudoobscura genome sequence. Where possible, we have extended the analysis to include evaluation of predicted sites in the A. gambiae genome. More complete annotations of the fly and mosquito genomes, aided by cDNA sequencing projects, will increase the number of genes for which orthologous UTR sequences can be defined. This will permit more sensitive and more extensive cross-genome comparison. We also expect improvements to come from further knowledge of the structural requirements of miRNA-target pairing.