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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Fly (Austin). Author manuscript; available in PMC 2010 June 21.
Published in final edited form as:
Fly (Austin). 2008 May; 2(3): 123–124.
Published online 2008 May 23.
PMCID: PMC2888637

Advances in microRNA biology

This year’s meeting highlighted a few new and interesting findings relating to microRNAs (miRNAs), one of several classes of non-coding RNAs that regulate gene expression in Drosophila. microRNA genes are transcribed by RNA polymerase II to yield pre-miRNA transcripts that are then processed by the nuclear enzymes Drosha and Pasha.17 The resulting 70 mer transcript is folded into a stem loop structure that is then exported into the cytoplasm by the shuttling factor Exportin 5.8,9 Within the cytoplasm, the Dicer enzyme further processes these transcripts by cleaving away the loop thereby leaving a short 22–23 nt double stranded mature miRNA.10,11 With the help of an unknown RNA helicase, miRNAs are unwound and loaded onto the RIS complex by Dicer and Loquacious.12 Argonaute, the catalytic component of RISC, is responsible for matching the single stranded miRNAs with the appropriate target mRNAs.13,14 miRNA binding is thought to occur within the 3′ UTR regions of the mRNA. The formation of these short stretches of double stranded RNA is sufficient to interfere with translation and in some cases, lead to the active degradation of the mRNA.15 This process is depicted in Figure 1A.

Figure 1
Advances in microRNA Biology. (A) A depiction of the major steps of microRNA biogenesis. (B) A diagram demonstrating that the 5′ and 3′ arms of a microRNA can target different mRNAs. (C) A schematic showing functional microRNAs can be ...

One of the new findings presented at this year’s meeting by William McGinnis’ research group relates to the versatility of an individual microRNA. It was reported that both the 5′ and 3′ arms of the stem-loop could be used to target different mRNAs (Fig. 1B). For instance, the different arms of mir-10 target mRNA transcripts that are derived from two different homeotic genes. The 5′ arm of mir-10 binds to complementary sequences within the 3′ UTR of Sex combs reduced while the 3′ arm binds to abdominal B mRNAs. How widespread is this mechanism? This remains to be determined but it suggests that the number of known mRNA targets will increase significantly.

Dovetailing on this result is the revelation by Eric Lai and colleagues that both the sense and antisense strands of many miRNA loci are predicted to generate viable hairpin structures (Fig. 1C). However, until recently stem-loops that are generated from transcription of the antisense strand have been largely ignored. At the meeting it was demonstrated that the mir-iab-4 locus generates two transcripts, miR-iab-4 and mir-iab-8, which are generated from transcription of the sense strand and antisense strands, respectively. These miRNAs are predicted to target different mRNAs. mir-iab-8 was shown to repress the expression of two Hox genes, Ultrabithorax and abdominal A. Reduction of these genes via the newly discovered miR-iab-8 hairpin leads to dramatic transformations of the halteres into wings. Like the prior result, this demonstration has the potential to increase the number of known miRNA loci. Presumably, a subset of these novel antisense derived stem-loop structures will also make differential use of the 5′ and 3′ arms. Thus the repertoire of miRNAs and their potential effects on regulatory networks could be significantly more extensive than is currently envisioned.

One of the problems that already exist within the field of microRNAs pertains to the prediction of mRNA targets for any one given microRNA. Several computer programs that predict miRNA-mRNA interactions are in widespread usage. These algorithms take many features into account including the complementarities between the miRNA the mRNA target, the structure of the 3′ UTR and the strength of the interaction that exists between the two RNA species. But as anyone who has used and compared the resultant predictions from multiple programs can attest, each algorithm will generate a relatively long list of potential mRNA targets and often times different programs predict different mRNA targets for any given miRNA. A consequence of this has been that choosing an mRNA (from the long list of potential targets) for further study has been akin to rolling a pair of dice. Furthermore, plenty of stories exist in which the computer predictions have failed during in vivo biological validation—even when the interactions are highly ranked. But a new method described in this year’s fly meeting by Ulrike Gaul and co-workers may significantly improve the chances of a computer prediction being biologically relevant. The new algorithm that takes into account site accessibility by calculating the difference in the energy that is lost by undoing the secondary structure of the mRNA target and the energy that is gained by the formation of the miRNA-target duplex has been proposed. Results from simulations suggest that miRNAs will preferentially target areas that are highly accessible. Taking this factor into account should go a long way towards a more accurate prediction of potential targets. This will be increasingly important as the number of miRNAs rise.

In addition, this year’s meeting highlighted several interesting roles for individual miRNAs during development. miRNAs were implicated in the development of the neuromuscular junction (mir-125; Laura Johnston and colleagues), the regulation of dacapo and the cell cycle (bantam, mir-7, mir-8, mir-309, mir-125; Hannele Ruhola-Baker, Steven Reynolds and colleagues), the process of metamorphosis (let-7 locus; Laura Johnston) and in the regulation of wingless signaling (mir-8; Jennifer Kennel and Ken Cadigan). Additionally, the microRNA pathway was shown to be functional within the sponge bodies of the ovary (Paul MacDonald and co-workers). These add to the growing list of developmental processes that are under the control on miRNAs.


1. Denli AM, Tops BB, Plasterk RH, Ketting RF, Hannon GJ. Processing of primary microR-NAs by the Microprocessor complex. Nature. 2004;432:231–35. [PubMed]
2. Gregory RI, Yan KP, Amuthan G, Chendrimada T, Doratotaj B, Cooch N, Shiekhattar R. The Microprocessor complex mediates the genesis of microRNAs. Nature. 2004;432:235–40. [PubMed]
3. Han J, Lee Y, Yeom KH, Kim YK, Jin H, Kim VN. The Drosha-DGCR8 complex in primary microRNA processing. Genes Dev. 2004;18:3016–27. [PubMed]
4. Han J, Lee Y, Yeom KH, Nam JW, Heo I, Rhee JK, Sohn SY, Cho Y, Zhang BT, Kim VN. Molecular basis for the recognition of primary microRNAs by the Drosha-DGCR8 complex. Cell. 2006;125:887–901. [PubMed]
5. Landthaler M, Yalcin A, Tuschl T. The human DiGeorge syndrome critical region gene 8 and Its D. melanogaster homolog are required for miRNA biogenesis. Curr Biol. 2004;14:2162–7. [PubMed]
6. Lee Y, Ahn C, Han J, Choi H, Kim J, Yim J, Lee J, Provost P, Rådmark O, Kim S, Kim VN. The nuclear RNase III Drosha initiates microRNA processing. Nature. 2003;425:415–9. [PubMed]
7. Seitz H, Zamore PD. Rethinking the microprocessor. Cell. 2006;125:827–9. [PubMed]
8. Bohnsack MT, Czaplinski K, Gorlich D. Exportin 5 is a RanGTP-dependent dsRNA-binding protein that mediates nuclear export of pre-miRNAs. RNA. 2004;10:185–91. [PubMed]
9. Lund E, Güttinger S, Calado A, Dahlberg JE, Kutay U. Nuclear export of microRNA precursors. Science. 2004;303:95–8. [PubMed]
10. Hutvágner G, McLachlan J, Pasquinelli AE, Bálint E, Tuschl T, Zamore PD. A cellular function for the RNA-interference enzyme Dicer in the maturation of the let-7 small temporal RNA. Science. 2001;293:834–8. [PubMed]
11. Saito K, Ishizuka A, Siomi H, Siomi MC. Processing of pre-microRNAs by the Dicer-1-Loquacious complex in Drosophila cells. PLoS BioL. 2005;3:235. [PMC free article] [PubMed]
12. Förstemann K, Tomari Y, Du T, Vagin VV, Denli AM, Bratu DP, Klattenhoff C, Theurkauf WE, Zamore PD. Normal microRNA maturation and germ-line stem cell maintenance requires Loquacious, a double-stranded RNA-binding domain protein. PLoS Biol. 2005;3:236. [PMC free article] [PubMed]
13. Meister G, Landthaler M, Patkaniowska A, Dorsett Y, Teng G, Tuschl T. Human Argonaute2 mediates RNA cleavage targeted by miRNAs and siRNAs. Mol Cell. 2004;15:185–97. [PubMed]
14. Liu J, Carmell MA, Rivas FV, Marsden CG, Thomson JM, Song JJ, Hammond SM, Joshua-Tor L, Hannon GJ. Argonaute2 is the catalytic engine of mammalian RNAi. Science. 2004;305:1437–41. [PubMed]
15. Wakiyama M, Takimoto K, Ohara O, Yokoyama S. Let-7 microRNA-mediated mRNA deadenylation and translational repression in a mammalian cell-free system. Genes Dev. 2007;21:1857–62. [PubMed]