Target mRNA abundance dilutes microRNA and siRNA activity

Abstract

Post-transcriptional regulation by microRNAs and siRNAs depends not only on characteristics of individual binding sites in target mRNA molecules, but also on system-level properties such as overall molecular concentrations. We hypothesize that an intracellular pool of microRNAs/siRNAs faced with a larger number of available predicted target transcripts will downregulate each individual target gene to a lesser extent. To test this hypothesis, we analyzed mRNA expression change from 178 microRNA and siRNA transfection experiments in two cell lines. We find that downregulation of particular genes mediated by microRNAs and siRNAs indeed varies with the total concentration of available target transcripts. We conclude that to interpret and design experiments involving gene regulation by small RNAs, global properties, such as target mRNA abundance, need to be considered in addition to local determinants. We propose that analysis of microRNA/siRNA targeting would benefit from a more quantitative definition, rather than simple categorization of genes as 'target' or 'not a target.' Our results are important for understanding microRNA regulation and may also have implications for siRNA design and small RNA therapeutics.

Figure 1

Mean downregulation is correlated with target abundance. (A) Schematic of the hypothesis that target abundance determines mean downregulation of individual targets. Micro/siRNAs with many targets downregulate their targets to a lesser extent than micro/siRNAs with few targets. (B) Expected correlation between target abundance and log expression ratio. This can also be considered an anti-correlation between downregulation and target abundance. (C, D) Differential downregulation by miR-155 and miR-128, where miR-155 targets are more downregulated than the targets for miR-128. (E) Predicted target concentration and mean log expression ratio across 146 micro/siRNA transfection experiments in HeLa cells. (F) Predicted target concentration and mean downregulation across 21 independently measured, single time point microRNA transfection experiments. Curves were fit to log(1−a/(x−b)), where a and b were determined by least squares error.

Figure 2

Analysis of shared targets of microRNAs. (A) Schematic of pairwise hypothesis: Given miR-A and miR-B, which both target the same gene, they will regulate differentially in proportion to their individual overall target abundance. (B) Examples of genes that may be differentially regulated (log₂ expression ratio) as a result of total target abundance. (C) All pairs of microRNAs are used to search for shared targets. Each point is the difference in mean downregulation and difference in target abundance for a given pair of microRNAs. (D) Background distribution (gray) as a result of randomizing targets. Inset shows empirical P-value of P<10⁻⁵. Real correlation line is black.

Figure 3

Target abundance determines siRNA primary target and predicted off-target downregulation. (A) Off-targets for a siRNA experiments show significant correlation. Curve was fit to log(1−a/(x−b)), where a and b were determined by least squares error. (B) The log expression ratio of the primary siRNA target is correlated with predicted off-target concentration. The downregulation for each primary target is normalized such that multiple siRNAs for different targets can be compared.