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Analysis of Complementarity Requirements for Plant MicroRNA Targeting Using a Nicotiana benthamiana Quantitative Transient Assay
Author(s) -
Qikun Liu,
Feng Wang,
Michael J. Axtell
Publication year - 2014
Publication title -
the plant cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.324
H-Index - 341
eISSN - 1532-298X
pISSN - 1040-4651
DOI - 10.1105/tpc.113.120972
Subject(s) - nicotiana benthamiana , biology , microrna , gene silencing , complementarity (molecular biology) , psychological repression , arabidopsis , computational biology , rna interference , genetics , rna , microbiology and biotechnology , gene expression , gene , mutant
MicroRNAs (miRNAs) guide RNA-induced silencing complexes to target RNAs based on miRNA-target complementarity. Using a dual-luciferase based sensor system in Nicotiana benthamiana, we quantitatively assessed the relationship between miRNA-target complementarity and silencing efficacy measured at both the RNA and protein levels, using several conserved miRNAs and their known target sites from Arabidopsis thaliana. We found that naturally occurring sites have variable efficacies attributable to their complementarity patterns. We also observed that sites with a few mismatches to the miRNA 3' regions, which are common in plants, are often equally effective and sometimes more effective than perfectly matched sites. By contrast, mismatches to the miRNA 5' regions strongly reduce or eliminate repression efficacy but are nonetheless present in several natural sites, suggesting that in some cases, suboptimal miRNA efficacies are either tolerated or perhaps selected for. Central mismatches fully abolished repression efficacy in our system, but such sites then became effective miRNA target mimics. Complementarity patterns that are functional in animals (seed sites, 3'-supplementary sites, and centered sites) did not reliably confer repression, regardless of context (3'-untranslated region or open reading frame) or measurement type (RNA or protein levels). Overall, these data provide a robust and empirical foundation for understanding, predicting, and designing functional miRNA target sites in plants.

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