Analysis of off-target effects based on sequence similarity between an siRNA non-seed region and its corresponding target sequences.

<p><b>(A, B)</b> Cumulative distribution of off-target transcripts grouped by their non-seed base-pairing (Fig 4A; siVIM-270 off-target effects, 2AU (70), 1AU (52), None (27), 1GC (133), 2GC (151), Fig 4B; siVIM-805 off-target effects, 2AU (55), 1AU (52), None (20), 1GC (52), 2GC (46)). Off-target transcripts with more than 2AU or 2GC match were omitted due to their low number. <b>(C, D)</b> The average GC contents for non-seed region (positions 8–15) were calculated for each group of off-target transcripts. <b>(E, F)</b> The cumulative distribution of off-target transcripts of siVIM-270 with 1GC match (133 transcripts)(E) and 2GC matches (151 transcripts)(F), were sub-divided based on their GC contents at positions 8–15. ‘Low’ subgroups have GC content lower than the average while ‘High’ subgroups have GC content higher than the average.</p

Contribution of miRNA non-seed region to gene silencing.

<p>The list of putative targets perfectly matching the miRNA seed region (positions 2–8) was intersected with a list of experimentally validated miRNA targets [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004656#pcbi.1004656.ref023" target="_blank">23</a>]. Genes present on both lists were placed in the ‘Validated Targets’ group, while genes predicted to interact with miRNA but which have not been experimentally confirmed, were placed in ‘Remaining Genes’ group. The GC content in the positions 8–15 was calculated for both groups and compared. The difference was calculated by subtracting values of the ‘remaining’ group from the values in the ‘validated’ group.</p

The siRNA Non-seed Region and Its Target Sequences Are Auxiliary Determinants of Off-Target Effects

<div><p>RNA interference (RNAi) is a powerful tool for post-transcriptional gene silencing. However, the siRNA guide strand may bind unintended off-target transcripts via partial sequence complementarity by a mechanism closely mirroring micro RNA (miRNA) silencing. To better understand these off-target effects, we investigated the correlation between sequence features within various subsections of siRNA guide strands, and its corresponding target sequences, with off-target activities. Our results confirm previous reports that strength of base-pairing in the siRNA seed region is the primary factor determining the efficiency of off-target silencing. However, the degree of downregulation of off-target transcripts with shared seed sequence is not necessarily similar, suggesting that there are additional auxiliary factors that influence the silencing potential. Here, we demonstrate that both the melting temperature (Tm) in a subsection of siRNA non-seed region, and the GC contents of its corresponding target sequences, are negatively correlated with the efficiency of off-target effect. Analysis of experimentally validated miRNA targets demonstrated a similar trend, indicating a putative conserved mechanistic feature of seed region-dependent targeting mechanism. These observations may prove useful as parameters for off-target prediction algorithms and improve siRNA ‘specificity’ design rules.</p></div

Correlation between <i>T</i>_m values of sequence subsections within siRNA duplexes and the corresponding off-target silencing efficiency.

<p>The start of the subsection within a duplex is plotted on the Y axis (‘Start Position’) whereas the end of the subsection is plotted on the X axis (‘End Position’). The position numbering mirrors that used in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004656#pcbi.1004656.g001" target="_blank">Fig 1</a>. The analysis was performed separately for each siRNA concentration–<b>(A)</b> 0.05, <b>(B)</b> 0.5, <b>(C)</b> 5 and <b>(D)</b> 50 nM. The siRNA sequences used in the analysis, together with corresponding knockdown percentages, are listed in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004656#pcbi.1004656.s001" target="_blank">S1 Table</a>.</p

Seed and non-seed region-dependent off-target effect analyses for siVIM-270 and siVIM-805.

<p><b>(A, B)</b> Expression profiles of off-target genes with 3’UTR sequences that perfectly match the corresponding siRNA seed region (i.e. off-targets) were compared to genes without such sequence. <b>(C, D)</b> The correlation between GC content in all the subsections within mRNA targets of siRNA non-seed region (8–21) and fold change of off-target effect was calculated in a similar manner to that shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004656#pcbi.1004656.g002" target="_blank">Fig 2</a>. The correlation coefficient was grouped using quantiles as boundary values and target position corresponds to the numbering shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004656#pcbi.1004656.g001" target="_blank">Fig 1</a>. GC contents in the non-seed regions at positions 8–15 showed the highest correlation with off-target effect (Fig 3C; siVIM-270, r = 0.22, p-value = 1.13E-12, Fig 3D; siVIM-805, r = 0.15, p-value = 1.57E-05). <b>(E, F)</b> Off-target transcripts for siVIM-270 and siVIM-805 were divided into four groups defined by the number of GC nucleotides in their non-seed regions (positions 8–15). Quantiles were used as the boundary values for classification; ‘Low’ (GC content < 3), ‘Medium’ (GC content = 3), ‘High’ (GC content = 4) and ‘Very High’ (GC content ≥ 5)(out of a total of 8). The number of off-target genes was 1065 for siVIM-270 (E) and 823 for siVIM-805 (F).</p

Distinguishable <i>In Vitro</i> Binding Mode of Monomeric TRBP and Dimeric PACT with siRNA

<div><p>RNA interference (RNAi) is an evolutionally conserved posttranscriptional gene-silencing mechanism whereby small interfering RNA (siRNA) triggers sequence-specific cleavage of its cognate mRNA. Dicer, Argonaute (Ago), and either TAR-RNA binding protein (TRBP) or a protein activator of PKR (PACT) are the primary components of the RNAi pathway, and they comprise the core of a complex termed the RNA-induced silencing complex (RISC)-loading complex (RLC). TRBP and PACT share similar structural features including three dsRNA binding domains (dsRBDs), and a complex containing Dicer and either TRBP or PACT is considered to sense thermodynamic asymmetry of siRNA ends for guide strand selection. Thus, both TRBP and PACT are thought to participate in the RNAi pathway in an indistinguishable manner, but the differences in siRNA binding mode and the functional involvement of TRBP and PACT are poorly understood. Here, we show <i>in vitro</i> binding patterns of human TRBP and PACT to siRNA using electrophoresis mobility shift analysis and gel filtration chromatography. Our results clearly showed that TRBP and PACT have distinct <i>in vitro</i> siRNA binding patterns from each other. The results suggest that monomeric TRBP binds to siRNA at the higher affinity compared to the affinity for own homodimerization. In contrast, the affinity between PACT and siRNA is lower than that of homodimerization or that between TRBP and siRNA. Thus, siRNA may be more readily incorporated into RLC, interacting with TRBP (instead of PACT) <i>in vivo</i>.</p></div

Purification and EMSA of TRBP-WT protein.

<p>(A) Coomassie brilliant blue stained pattern of purified TRBP-WT protein resolved by SDS-PAGE. Arrowhead indicates 44 kDa of TRBP-WT protein. M represents the protein size markers. (B–D) The results of EMSA of TRBP-WT protein with ³²P-labeled siLuc-36 (B), siLuc-36B (C), and siLuc-36D (D). ³²P-labeled siRNA (0.50 nM) was incubated with increasing amounts of TRBP-WT protein, as indicated. Lower cases in siLuc-36D sequence in D indicate DNAs. (E) Supershift analysis of TRBP-WT protein (1.3 nM) with no antibodies, control anti-Flag, and anti-myc antibodies. (F) The result of EMSA of TRBP-WT protein (1,300 nM) mixed with ³²P-labeled siLuc-36 (0.50 nM) incubated with increasing amount of non-labeled siLuc-36. In B–F, arrows indicate positions of the first and second step migrating complexes, corresponding to TRBP-WT complexes 1 and 2, respectively, and the supershifted complex, in addition to siRNA and ATP.</p

Model of TRBP and PACT binding to siRNA.

<p>(A, B) TRBP-WT (A) or TRBP-ΔdsRBD3 (B) binds one molecule of siRNA as a monomer at low concentrations, and then each protein dimerizes due to the increased protein concentration. However, excessive amount of siRNAs were added, TRBP-WT or TRBP-ΔdsRBD3 dimer was dissociated into monomeric TRBP-WT or TRBP-ΔdsRBD3 dimer containing a single molecule of siRNA. (C) PACT-WT forms homodimers at high concentrations and binds to one or two molecules of siRNA. (D) PACT-ΔdsRBD3 binds one siRNA molecule as a monomer or binds one or two siRNA molecules as a dimer. The monomer and dimer may achieve equilibrium, although the monomeric form is predominant. In C and D, we could not determine whether the siRNA shown in gray is contained in the dimerized PACT proteins or not.</p

Gel filtration chromatography of purified PACT-WT and PACT mutant proteins with siRNA.

<p>Gel filtration chromatography patterns of non-labeled siLuc-36 (300 nM) with PACT-WT (A), PACT- dsRBDmt1 (B), PACT-dsRBDmt2 (C), and PACT-ΔdsRBD3 (D). Lower panels showed the results of Western blot (WB) by anti-myc antibody for detecting PACT proteins in the elution fractions. Histograms below WBs showed the quantified signal densities of PACT proteins detected by WBs. Arrowheads indicate the positions of molecular weight size markers.</p

The <i>K</i>_d values (nM) of TRBP-WT and PACT-WT and their mutants.

*<p>and ** indicate 21nt dsRNA with blunt ends and siRNA with 2nt DNAs at both 3′ overhangs, respectively.</p><p>ND  =  not determined.</p><p>NT  =  not tested.</p