Specificity of microRNA target selection in translational repression
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Abstract
MicroRNAs (miRNAs) are a class of noncoding RNAs found in organisms as evolutionarily distant as plants and mammals, yet most of the mRNAs they regulate are unknown. Here we show that the ability of an miRNA to translationally repress a target mRNA is largely dictated by the free energy of binding of the first eight nucleotides in the 5′ region of the miRNA. However, G:U wobble base-pairing in this region interferes with activity beyond that predicted on the basis of thermodynamic stability. Furthermore, an mRNA can be simultaneously repressed by more than one miRNA species. The level of repression achieved is dependent on both the amount of mRNA and the amount of available miRNA complexes. Thus, predicted miRNA:mRNA interactions must be viewed in the context of other potential interactions and cellular conditions.
The canonical RNA interference (RNAi) pathway begins with the cleavage of long, double-stranded RNA into an intermediate RNA species of ∼21 nt known as short, interfering RNA (siRNA; for review, see Zamore 2002; Dykxhoorn et al. 2003). These siRNAs are double-stranded, with 5′ phosphates and 2-nt 3′ overhangs, indicators of RNase III cleavage, and, indeed, the enzyme Dicer was identified as responsible for their generation (Bernstein et al. 2001). One of the two strands of the siRNA is incorporated into the RNA induced silencing complex (RISC; Hammond et al. 2000; Martinez et al. 2002; Khvorova et al. 2003; Schwarz et al. 2003). This strand then guides RISC to perfectly complementary mRNAs and cleaves them, resulting in their degradation. Several labs cloned short RNA species to find endogenous siRNAs, and these efforts led to the discovery of miRNAs as a large class of noncoding RNAs (Lagos-Quintana et al. 2001; Lau et al. 2001; Lee and Ambros 2001).
MicroRNAs are ∼22-nt single-stranded RNA species found in a wide variety of organisms, ranging from plants to worms to humans (for review, see Lai 2003; Bartel 2004). The founding member of the miRNA class, the Caenorhabditis elegans gene lin-4, as well as its target, the nuclear protein lin-14, were first identified in a screen for worms with defects in cell lineage progression (Horvitz and Sulston 1980; Chalfie et al. 1981). After more than a decade of research, it was determined that lin-4 did not code for a protein, but rather a small RNA species with imperfect complementarity to several sites in the 3′ untranslated region (UTR) of lin-14 (Lee et al. 1993). Because expression of lin-4 led to a decrease in lin-14 protein level without a decrease in mRNA level, this phenomenon was dubbed translational repression (Wightman et al. 1991, 1993). Biochemical analysis revealed that the repressed mRNAs remain in polysomes, suggesting that the block in expression occurs after translation initiation, although little is known about the mechanism (Olsen and Ambros 1999; Seggerson et al. 2002).
Although the mechanism of miRNA action remains elusive, their biogenesis is rapidly becoming clear. Primary miRNA transcripts are first processed in the nucleus by the RNase III enzyme Drosha to produce a hairpin RNA of ∼70 nt (Lee et al. 2003). In a pathway dependent on Exportin-5, this pre-miRNA is then exported into the cytoplasm (Yi et al. 2003; Lund et al. 2004), where Dicer then cuts the hairpin (Grishok et al. 2001; Hutvagner et al. 2001; Ketting et al. 2001; Knight and Bass 2001; Lee et al. 2002). Correlative evidence suggests that the same rules governing siRNA strand choice also hold for determining which side of the hairpin becomes the mature strand of the miRNA (Schwarz et al. 2003). The complex containing active miRNAs and the RISC involved in RNAi are similar if not identical, as endogenous miRNAs can cleave mRNAs with perfect complementarity (Hutvagner and Zamore 2002), and exogenously introduced siRNAs can translationally repress mRNAs bearing imperfectly complementary binding sites (Doench et al. 2003; Saxena et al. 2003; Zeng et al. 2003).
In addition to lin-4 regulation of lin-14, there are now several other miRNAs with known targets. In C. elegans,let-7 regulates both lin-41 (Reinhart et al. 2000; Slack et al. 2000) and hbl-1 (Abrahante et al. 2003; Lin et al. 2003), and lin-4 also regulates lin-28 (Moss et al. 1997). In Drosophila, the bantam gene was found to encode an miRNA that regulates the proapoptotic gene hid (Brennecke et al. 2003). miR-2 and miR-13 were predicted to regulate genes containing the K-box motif (Lai 2002), and recent experimental work has validated this prediction (Boutla et al. 2003). MicroRNAs have also been implicated in fat metabolism (Xu et al. 2003) and hematopoietic lineage differentiation (Chen et al. 2004), although no targets were confirmed in these studies. Of note, these mRNAs tend to contain several binding sites for the miRNA, emphasizing the potential importance of synergistic binding of the miRNA to the target. This synergism has been directly demonstrated, as addition of multiple binding sites into a 3′ UTR resulted in more efficient inhibition of translation than that expected from the sum of the effect of each binding site individually (Doench et al. 2003).
Computational approaches have recently been used to identify potential miRNA targets (Enright et al. 2003; Lewis et al. 2003; Stark et al. 2003). The methods used by Lewis et al. (2003) and Stark et al. (2003) incorporated conservation of the mRNA target site in related organisms to separate signal from noise. Additionally, the studies by Enright et al. (2003) and Stark et al. (2003) relied on inferences from known miRNA:mRNA interactions, a relatively small data set. There are hundreds of identified miRNAs, with the vast majority of their potential targets unknown, and we thus decided to experimentally investigate the miRNA:mRNA pairing rules.
Acknowledgments
The authors thank C. Petersen for consistently helpful discussions and R. Bodner and D. Bartel for a critical reading of the manuscript. We also thank the Burge and Bartel labs for sharing data prior to its publication. J.G.D. is a Howard Hughes Medical Institute Predoctoral Fellow. This work was supported by United States Public Health Service MERIT Award R37-GM34277 from the National Institutes of Health and PO1-CA42063 from the National Cancer Institute to P.A.S. and partially by a Cancer Center Support (core) grant P30-CA14051 from the National Cancer Institute.
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Notes
Article published online ahead of print. Article and publication date are at http://www.genesdev.org/cgi/doi/10.1101/gad.1184404.