Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs

• Published in: Nature structural & molecular biology Vol. 18; no. 10; pp. 1139 - 1146
• Main Authors: Baek, Daehyun, Bartel, David P, Garcia, David M, Shin, Chanseok, Bell, George W, Grimson, Andrew
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01-10-2011; Nature Publishing Group
• Subjects: 3' Untranslated Regions; 631/337/384/2053; 631/337/384/331; Animals; Biochemistry; Biological Microscopy; Biomedical and Life Sciences; Caenorhabditis elegans; Caenorhabditis elegans - genetics; Cellular biology; Gene expression; Genes; Genetic aspects; HeLa Cells; Humans; Life Sciences; Mammals; Membrane Biology; MicroRNA; MicroRNAs - genetics; MicroRNAs - metabolism; Physiological aspects; Protein Structure; Proteins; Ribonucleic acid; RNA; United States
• ISSN: 1545-9993; 1545-9985
• DOI: 10.1038/nsmb.2115

A single miRNA can target hundreds of distinct transcripts, but some miRNAs such as
C. elegans lsy-6
have very low target proficiency. The reasons behind this are now identified as weak seed-pairing stability and high target-site abundance. These findings have implications for understanding off-target effects of siRNAs and improving miRNA target predictions.
Most metazoan microRNAs (miRNAs) target many genes for repression, but the nematode
lsy-6
miRNA is much less proficient. Here we show that the low proficiency of
lsy-6
can be recapitulated in HeLa cells and that miR-23, a mammalian miRNA, also has low proficiency in these cells. Reporter results and array data indicate two properties of these miRNAs that impart low proficiency: their weak predicted seed-pairing stability (SPS) and their high target-site abundance (TA). These two properties also explain differential propensities of small interfering RNAs (siRNAs) to repress unintended targets. Using these insights, we expand the TargetScan tool for quantitatively predicting miRNA regulation (and siRNA off-targeting) to model differential miRNA (and siRNA) proficiencies, thereby improving prediction performance. We propose that siRNAs designed to have both weaker SPS and higher TA will have fewer off-targets without compromised on-target activity.