Identification of Drosophila MicroRNA Targets

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.

MicroRNA miR-124 regulates neurite outgrowth during neuronal differentiation

“…As a control, nucleotides 2-7 of the mature miR-124 sequence in the miR-124-1 vector were mutated to make the miR-124-1m expression vector. These nucleotides have been shown to be essential for target recognition by miRNAs [64][65][66][67][68]. The miR-124 expression constructs were cotransfected with plasmids expressing MASH1 and GFP into P19 cells.…”

“…Basepairing between nucleotides 2-8 of a miRNA (numbered from the 5' end), often referred to as the "seed sequence" [68], and a target mRNA are thought to be essential for target mRNA recognition and inhibition [64,[66][67][68]. However, the terminal 5' nt of the miRNA (position 1) is not required to basepair with the target mRNA sequence for inhibition.…”

Principles and effects of microRNA-mediated post-transcriptional gene regulation

“…Another function of the 3 0 region of a miRNA is to give specificity to the members of miRNA families that share identical seeds but they diverge in their 3 0 sequences (Brennecke et al, 2005). The recognition of the principles of miRNA targeting accelerated the development and improvement of a series of bio-computational approaches to predict miRNA targets in animals that produced a remarkably large number of putative miRNA-regulated transcripts further emphasizing the significance of miRNAs (Enright et al, 2003;Stark et al, 2003;Kiriakidou et al, 2004;Lewis et al, 2005;Lall et al, 2006).…”

Les microARN

“…Aucune autre homologie complète entre microARN et ARNm n'a été identifiée chez les métazoaires. Avant la mise au point, très récente, de deux logiciels performants pour la recherche de cibles [31,32], les appariements imparfaits entre les séquences des microARN et des ARNm cibles rendaient l'identification de celles-ci très délicate. Chez les métazoaires, les analyses bio-informatiques ont révélé que les résidus deux à huit de la région 5' des microARN étaient très conservés entre microARN homologues.…”