Animal genomes contain hundreds of microRNAs (miRNAs), small regulatory RNAs that control gene expression by binding to complementary sites in target mRNAs. Some rules that govern miRNA/target interaction have been elucidated but their general applicability awaits further experimentation on a case-by-case basis. We use here an assay system in transgenic nematodes to analyze the interaction of the Caenorhabditis elegans
lsy-6 miRNA with 3'' UTR sequences. In contrast to many previously described assay systems used to analyze miRNA/target interactions, our assay system operates within the cellular context in which
lsy-6 normally functions, a single neuron in the nervous system of C. elegans. Through extensive mutational analysis, we define features in the known and experimentally validated target of
lsy-6, the 3'' UTR of the
cog-1 homeobox gene, that are required for a functional miRNA/target interaction. We describe that both in the context of the
cog-1 3'' UTR and in the context of heterologous 3'' UTRs, one or more seed matches are not a reliable predictor for a functional miRNA/target interaction. We rather find that two nonsequence specific contextual features beyond miRNA target sites are critical determinants of miRNA-mediated 3'' UTR regulation. The contextual features reside 3'' of
lsy-6 binding sites in the 3'' UTR and act in a combinatorial manner; mutation of each results in limited defects in 3'' UTR regulation, but a combinatorial deletion results in complete loss of 3'' UTR regulation. Together with two
lsy-6 sites, these two contextual features are capable of imparting regulation on a heterologous 3'' UTR. Moreover, the contextual features need to be present in a specific configuration relative to miRNA binding sites and could either represent protein binding sites or provide an appropriate structural context. We conclude that a given target site resides in a 3'' UTR context that evolved beyond target site complementarity to support regulation by a specific miRNA. The large number of 3'' UTRs that we analyzed in this study will also be useful to computational biologists in designing the next generation of miRNA/target prediction algorithms.