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The Pack Hunterapproach The Pack Hunter Approach for Superior Gene Silencing siPOOLsTM Clean, Reliable & Hassle-Free RNAi Dealing with How siPOOLs improve specificity RNA interference and reliability of gene silencing Scientists have been using RNA interference (RNAi) as a rapid and efficient tool to establish gene function. Yet the off-target effects and variable The siPOOL concept performance of short interfering RNAs (siRNAs) remain a troubling drawback, consuming precious time and resources in validation efforts. off-target Key Problem - Off-target effects of siRNAs Leading cause: miRNA-like transcript downregulation RNA siRNA siPOOLTM 5‘ Fully complementary siRNA-based RNAi AAAAA 3‘ 5‘ RNA cleavage siRNA target RNA Partially 5‘ complementary AAAAA miRNA-based RNAi 5‘ siPOOLs are high complexity, defined siRNA pools containing 30 distinct siRNAs. siPOOLs have a significantly reduced off-target profile and Seed RNA degradation / translation inhibition 3‘ miRNA more robust on-target gene knockdown. This is attributed to three key features: (2-7 nt) siRNAs typically bind with full complementarity to target RNA transcripts, guiding their degradation by the RNAi machinery. Off-target effects are largely caused by siRNAs mimicking endogenous gene regulators, micro RNAs (miRNAs). As miRNAs require only a 6 base seed Feature 1 match to 3’ untranslated regions (UTR) to trigger transcript downregulation, siRNAs can alter the expression of numerous unintended targets when High complexity pooling processed via this mechanism. Reduced concentration of individual siRNAs Increased diversity of siRNA sequences High siRNA concentrations produce more off-target effects1,2,3. A high Single siRNAs dominate performance of low complexity pools. The high The consequences: complexity pool allows individual siRNAs to be administered at very low complexity of siPOOLs reduces off-target effects more efficiently than Wide-spread off-target gene deregulation Variable on-target gene knockdown concentrations. This substantially dilutes siRNA off-target signatures. low complexity siRNA pools (see Box 1, pg 4). siRNA conc (nM) 25 10 1 100 nM siRNA 25 Effect 20 Reduced off-target effects Target gene 15 expression % genes 10 5 Expression Benefits fold-change 0 0 – 20 30 – 40 50 – 60 70 – 80 90 – 100 Less false results +4 0 -4 20 – 30 40 – 50 60 – 70 80 – 90 Clean, reliable phenotypes % KD with siRNA Gene expression changes after STAT3 siRNA treatment by microarray analysis. Arrow shows Gene knockdown efficiency by branched DNA assay. Data reconstructed from Simpson et al. STAT3 expression. Data reconstructed from Caffrey et al., 20111 20084 Multiple expression studies like this one show wide-spread off-target Off-target effects reduce the efficiency of on-target knockdown (KD). gene deregulation by siRNAs2,3. High siRNA concentrations produce At 100 nM, nearly half of commercial siRNAs (220 of 541 tested, 41%) had more off-targeteffects. Off-target genes are enriched for 3’ UTR seed-se- knockdown efficiency of < 70% with 4% of siRNAs showing little to no quence matches, indicating significant miRNA-like activity. activity. 2 3 How siPOOLs improve specificity How siPOOLs improve specificity and reliability of gene silencing and reliability of gene silencing Feature 2 Feature 3 Detailed Bioinformatics-Based Design Quality Production Process siRNAs Transcript Length Mapping image siRNAs Transcript Length Mapping image 30/30 NM_001123066.3 6816 30/30 XM_005257364.4 6767 siPOOL esiRNA Defined, equimolar siRNAs 30/30 NM_001123067.3 5724 30/30 XM_005257365.4 6761 The patented siPOOL production process ensures every siRNA within a 30/30 NM_001203251.1 5631 29/30 XM_005257366.3 6722 marker Scyl1 PolG Traf5 Ago2 Scyl1 PolG Traf5 Ago2 42bp 30/30 NM_001203252.1 5718 30/30 XM_005257367.4 6656 siPOOL is present in equimolar amounts. 30/30 NM_005910.5 5811 30/30 XM_005257368.4 6563 29/30 NM_016834.4 5637 30/30 XM_005257369.4 5789 Highest purity levels 30/30 NM_016835.4 6762 30/30 XM_005257370.4 5766 siPOOLs undergo polyacrylamide gel electrophoresis (PAGE) purificati- 29/30 NM_016841.4 5544 29/30 XM_005257371.4 5615 on to remove impurities and extract full-length siRNAs. This results in the 30/30 XM_005257362.4 6854 highest achievable purity levels of siRNAs. siPOOL: MAPT Symbol: MAPT Gene ID 4137 siRNA CDS boundaries siPOOLs/esiRNAs loaded on a 20% polyacrylamide gel and visualized by EtBr staining5. Complete transcript coverage Optimal siRNA thermodynamics Avoidance of paralogues Multiple siRNAs allow for more robust and Proprietary design algorithms select most Genes sharing highly similar sequences Effects complete transcript isoform coverage. potent siRNAs based on thermodynamic (paralogues) are avoided by siPOOLs. Paralo- siPOOLs target XM as well as NM transcripts properties that favour guide strand loading into gue filtering is applied genome-wide. Defined, highly pure siRNA that evade immune stimulation (Box 2) the RNA-induced silencing complex (RISC). Effects Benefits Co-operative knockdown Maximal potency High specificity Avoid toxicity and off-target effects from immune stimulation Benefits Robust, efficient and specific on-target knockdown Box 2 Off-targets from immune stimulation esiRNA siPOOL Box 1 siRNA with known Long double-stranded RNA fragments tend to off-target activity stimulate the immune response as seen in this 6 6 Why 30? Because 4 are not enough! transcriptome-wide expression profile of Scyl1 Low complexity pools of 4 siRNAs are commonly siPOOL esiRNA-treated MCF7 cells (left). Upregulated 4 4 complexity genes in esiRNA-treated cells were largely inter- used and marketed as “smart pools”. We show here 2 2 that an siRNA with known off-target activity against # siRNAs / pool 1 4 15 60 feron response genes which were not induced 0 0 MAD2 gene required high complexity pools of > 15 single „smart in siPOOL-treated cells (right). The immune log2 fold change log2 fold change Control siRNA Pool„ siPOOL siRNAs to sufficiently reduce off-target effects. response can also be stimulated by impurities -2 Scyl 1 -2 Scyl 1 1.4 in siRNA preparations, producing toxicity and Similar results were obtained when off-target activity 1.2 off-target effects that interfere with functional 2 4 6 8 10 12 2 4 6 8 10 12 was assayed by a MAD2 3’UTR-linked luciferase 1 read-outs. average expression average expression reporter, MAD2 protein expression and MAD2 functi- 0.8 off-target effect onal assay (mitotic escape). off-target % 0.4 luciferase activity 0.2 0 conc.(nM) 1 3 10 1 3 10 1 3 10 1 3 10 1 3 10 4 5 Data with siPOOLs – Data with siPOOLs – Proof of concept Proof of concept Reduced off-target effects with siPOOLs Efficient on-target knockdown with siPOOLs 1 nM siPOOL siRNA siPOOL 35 3 3 HeLa cells 30 Various standard cell lines 2 2 25 1 1 3 nM 20 1 nM 0 0 % genes 15 log2 fold change log2 fold change 48 h -1 -1 10 24 h -2 -2 target gene target gene 5 Human Gene 1.0 ST Real-time quantitati- 4 6 8 10 12 14 4 6 8 10 12 14 microarray 0 ve PCR (rtqPCR) average expression average expression (Affymetrix) 0 – 20 20 – 30 30 – 40 40 – 50 50 – 60 60 – 70 70 – 80 80 – 90 90 – 100 % KD siPOOL Specific reagents should only affect their target. siPOOLs exhibit potent knockdown efficiencies at low nanomolar concentrations. At 1 nM, a large proportion of siPOOLs (178 of 233 tested, 76%) Transcriptome-wide profiling revealed a single siRNA can induce numerous off-target genes (red dots) while a siPOOL against the same target gene had > 70% gene knockdown efficiency1 (for indirect comparison, refer pg 2). (green dot), and containing the non-specific siRNA, had greatly reduced off-target effects. Robust on-target knockdown with siPOOLs Phenotypes you can trust with siPOOLs siRNA siPOOL siRNA siPOOL 120 120 2.0 2.0 • • • •• • 100 • 100 A549 cells • • A549 cells • • • • • • • 1.5 • 1.5 • • • • • • • • • • siRNA 1 80 80 • • siPOOL 1 • • • • • • • • • • • • • • • •• • • • • • • • • • 1 nM • • • • • • • • • 3 nM • • 60 • • 60 siRNA 1 1.0 • • • •• • 1.0 • • • • • • siPOOL 1 • • • • • • • • • • • • • • • • • •••• • • • • • • • • • • • • • • •• • • • • • •• • •• • 40 • 40 • • • • • •• • viability • • • • • • • • viability • • • • • • 0.5 • • • • 0.5 • • • • • • • 72 h • • • • • 24 h •• • ••• • •• • •• • • • • % remaining mRNA % remaining • • • 20 •••• • • • mRNA % remaining 20 • •• • • • • • • • • • • • • • •• • •• • • •• • • •• • 2 2 0 R=0.4 0 R=0.9 0.0 R =0.19 0.0 R =0.71 Real-time quantitati- AlamarBlue cell 0 20 40 60 80 100 120 0 20 40 60 80 100 120 ve PCR (rtqPCR) 0.0 0.5 1.0 1.5 2.0 0.0 0.5 1.0 1.5 2.0 viability assay % remaining mRNA siRNA 2 % remaining mRNA siPOOL 2 viability siRNA 2 viability siPOOL 2 (Thermo Fisher) If reliable and specific, two reagents that target the same gene should produce similar phenotypes6. siRNAs vary strongly in their knockdown efficiency. We screened 36 genes using two siPOOLs per gene and three siRNAs per gene from a commercially available library and measured their effect on Two siPOOLs against the same gene gave similar knockdown efficiencies (good correlation, R=0.9) while knockdown with single siRNAs was far cell viability. Only siPOOLs produced consistent phenotypes. more variable (poor correlation, R=0.4). This shows greater robustness and reproducibility of siPOOL-mediated knockdown. 6 7 Further benefits of using siPOOLs Customer Data with siPOOLs ■ One gene – one siPOOL. Unlike other siRNA reagents that require ■ Custom siPOOL design with sequence information available. Case study 1: Highly efficient and paralogue-specific knockdown testing of multiple reagents, a single siPOOL is sufficient to reliably All siPOOL design is undertaken by us and custom design requests knockdown the gene of interest. siPOOLs have been cited in various can be incorporated e.g. custom species, isoforms or transcript publications - refer to website: Resources > Publications. Our land- regions. Sequence information of the siRNAs within the siPOOL is SMARCA2 siPOOL SMARCA4 siPOOL mark paper, Hannus et al., 2014, can be referenced when using available upon request.
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