MicroRNAs are 21to 24-nucleotide long, endogenous non-coding RNAs in eukaryotes (Hannon, 2002). Mature microRNAs generated by Dicer are incorporated into an RNA-induced silencing complex (RISC), resulting in gene silencing via the cleavage of a target mRNA or the repression of target mRNA translation (Qi et al, 2005). Thus, microRNAs play a key role in post-transcriptional gene silencing, and microRNA-based gene silencing pathways are critical in developmental regulation, biotic and abiotic adaptations, and hormone responses in plants (Baulcombe, 2004; Jones-Rhoades et al., 2006). In microRNA-based gene silencing, the microRNAtarget mRNA pair determines the specificity of the biological effect. Hundreds of microRNAs have been identified in plants by cloning and deep genomic sequencing (Griffiths-Jones et al., 2008). Thus, a key step in determining the biological function of a microRNA is to identify its target. However, our knowledge of microRNA targets is incomplete due to limitations imposed by the methods used to identify microRNA targets. Traditionally, microRNA targets have been identified from computational predictions based on sequence matching between a microRNA and its target mRNA (Rhoades et al., 2002). Thus, a new approach is needed to facilitate the identification of microRNA targets on a global scale. Degradome sequencing is a new approach that integrates high-throughput sequencing, experimental approaches, and bioinformatic analyses (German et al., 2009). More than 100 microRNA targets in Arabidopsis have been isolated using this method (Addo-Quaye et al., 2008; German et al., 2008), suggesting that degradome sequencing is a powerful tool for microRNA-target pair identification. The isolation and experimental validation of microRNAtarget pairs from the monocot model plant rice using a degradome sequencing approach was reported in this issue by Dr. Xiaofeng Cao’s group (Zhou et al., 2010). They identified 177 mRNAs that were targeted by 87 unique microRNAs (Zhou et al., 2010). Among them, microRNAs known to be conserved in the plant kingdom targeted about half of the identified target mRNAs, and, interestingly, about 70% of the target mRNAs encoded transcription factors (Zhou et al., 2010). One example is the mi156SBP-box gene mRNA pair (Fig. 1A). The Arabidopsis genome encodes thirteen SBP-box genes (SPLs), ten of which are mi156 targets (Schwab et al., 2005; Wu et al., 2009; Wang et al., 2009). The mi156-SPL pathway regulates the vegetative-phase transition, flowering, leaf initiation, and apical dominance in Arabidopsis (Schwab et al., 2005; Wu et al., 2009; Wang et al., 2009). Consistent with the microRNA-target of the mi156-SPL mRNA pairs in Arabidopsis, eleven SPL mRNAs are mi156 targets in rice (Zhou et al., 2010). These conserved microRNA-target pairs may represent common regulatory nodes for the regulation of fundamental developmental processes and responses to environmental signals in the plant kingdom. The second half of the identified target genes were found to be targeted by non-conserved microRNAs (Zhou et al., 2010). These non-conserved microRNA-target pairs may be involved in riceor grass-specific processes or responses, such as osa-miR528/Os0738290 interaction (Fig. 1B). Interestingly, a large proportion of the nonconserved microRNAs targeted the 5’or 3’-untranslated region of their target mRNAs (Zhou et al., 2010). Thus, these non-conserved microRNAs may regulate gene expression via manners other than mRNA cleavage, and translational repression by microRNAs is more common in rice than in Arabidopsis. Therefore, rice is a better model than Arabidopsis to use in determining the mechanism of microRNA-mediated translational repression in plants. What will be the next step after this useful and much needed atlas of microRNA-target interactions is completed? First, it will be possible to address the biological functions of microRNA-target transcript pairs in rice. The genetic manipulation of microRNA-mRNA pairs in planta Received December 19, 2009; accepted December 23, 2009
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