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

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

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

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

Analysis of induction in cadmium chloride-treated cells transfected with TFBS-UR plasmids.

<p>HEK293 cells transfected with a plasmid pool, that included the plasmids listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050521#pone.0050521.s003" target="_blank">Table S2</a> and pRL-SV40 and were subsequently treated with cadmium. (A) Microarray-based detection of TF derived activation of UR expression. (B) qPCR-based detection of TF-derived activation of UR expression. Values are presented as log2 treatments of the fold induction of the TFBS-directed UR expression after treatment with the inducer of interest. The grey bar represents treatment-independent changes in the system. TFBS marked with * represent treatment-dependent effects on the TF library. Numerical data is presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050521#pone.0050521.s004" target="_blank">Table S3</a>. A statistical analysis of the qPCR assay data is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050521#pone-0050521-g003" target="_blank">Figure 3</a>.</p

qPCR analysis of induction of TFBS-directed UR expression in treated cells transfected with TFBS-UR plasmids.

<p>The statistical model calculated a posterior probability distribution over the mean of the log normalized fold induction. The p-value indicated the posterior probability that there was no difference in expression levels between the control and treatment samples. 95% credible intervals were also calculated for the mean log normalized fold induction and indicate the region where there is a 95% probability that the mean effect lies within it. Bars not crossing the 0 line show significant evidence for an effect following treatment with the inducer of interest.</p

A schematic representation of the method.

<p>In each reporter plasmid, the transcription factor binding site (TFBS) and the thymidine kinase promoter (P_TK) were present upstream of the transcriptional start site (TSS) and the unique DNA reporter (UR) sequence. The cassette was flanked by two poly(A) signals to prevent transcriptional interference due to the circular plasmid. Each TFBS was assigned a specific UR sequence to act as a signature for its corresponding TF activity. These plasmids were tranfected into cells and the cells treated with compounds of interest, mRNA was isolated, reverse transcribed and analyzed on two detection platforms. For microarray analysis, cDNA was amplified by PCR using a Cy3 or Cy5-labelled universal sense forward primer (Cy3/Cy5-AG_URF) in conjunction with a universal antisense reverse primer (prMJ264) to generate a mixture of 120 bp fluorescently labelled PCR amplicons that could be analyzed on DNA microarrays. For the qPCR reaction, a forward primer, specific for each UR, was used in combination with a universal FAM-labelled hydrolysis probe (prMJ245) and a universal reverse primer (prMJ264).</p

Induction of the TF proteins of interest in HEK293 cells after treatment with forskolin, TPA and cadmium.

<p>Proteins extracted from treated and control cells were analyzed using Western blots and TF-specific antibodies. The levels of phosphorylated TFs and inactive TFs were analyzed for (A) CREB and ATF, (B) IκB, (C) c-jun and (D) SP1. Tubulin was used as a loading control. Quantification of the levels of protein on the Western blots showed a 1.6 and 1.3 fold increase in P-CREB and P-ATF after treatment with forskolin and a 1.5 and 1.6 fold increase in P-IκB, and P-c-jun after treatment with TPA. Treatment of HEK293 cells with cadmium chloride, dexamethasone, forskolin and TPA resulted in a 1.1, 1.1. 1.0 and 1.0 fold increase in the levels of SP1 protein. (E) Increased <i>hMTIIA</i> gene expression in HEK293 cells after treatment with cadmium. Expression of the cadmium-responsive <i>hMTIIa</i> gene was normalized to the expression of the chromosomal reference gene <i>B2M.</i> Abbreviations: -, carrier only control; C, cadmium; D, dexamethasone; F, forskolin; T, TPA.</p

Induction of selected TFBS-directed UR expression in HEK293 cells after treatment with cadmium, dexamethasone, TPA and forskolin.

<p>HEK293 cells transfected with a plasmid pool, that included the plasmids listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050521#pone.0050521.s003" target="_blank">Table S2</a> and pRL-SV40 and were subsequently treated with drugs of interest. (A) MRE-directed UR expression after treatment with cadmium. (B) GRE-directed UR expression after treatment with dexamethasone. (C) NF-κB-directed UR expression after treatment with TPA. (D) CREB-directed UR expression after treatment with forskolin. Values are presented as log2 treatments of the fold induction of the TFBS-directed UR expression after treatment with the inducer of interest. The error bars are calculated as 1 standard error of the mean each way.</p