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siRNA mediated gene silencing enables the study
of gene function with unprecedented power and
ease. However, currently available siRNAs to
the same target do not always give the same phenotype
due to a combination of inconsistent silencing
and sequence specific off-target effects. Consequently,
much time and money are wasted to confirm results.
Silencer Select siRNAs:
• Incorporate the latest improvements
in siRNA design, off-target effect prediction
algorithms, and chemistry
• Provide unrivalled silencing consistency,
potency and specificity
• Result in fewer failed experiments
due to poor silencing
• Yield cleaner, more consistent phenotypic
data |
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The Concept Behind Silencer Select
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Current siRNA design algorithms predict effective
siRNAs that induce 70% target mRNA knockdown
with only ~80% confidence and are inadequate
for predicting more efficient siRNAs. Many RNAi
applications demand better efficiency than current
algorithms offer. Therefore, we used a powerful
machine learning method and performance data
from thousands of siRNAs to better understand
the link between an siRNA’s sequence, target
location, and thermodynamic properties and its
silencing efficiency. The result is the Silencer Select
siRNA Design Algorithm.
New Silencer Select Design
Algorithm:
• Incorporates >90 different sequence
and thermodynamic parameters
• Increases predictive accuracy 28%
over previous generation siRNA design
algorithm
• Yields siRNAs that are up to 100 fold
more potent than both modified and
unmodified siRNAs from other suppliers
• Provides significantly higher percentage of “on-target” phenotypes compared
to other siRNAs |
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Silencer Select
siRNA Design Algorithm Significantly Improves
Effective siRNA Prediction Accuracy. The Silencer Select
siRNA design algorithm was used to design 155
siRNAs to 40 different targets. These siRNAs
were tested side by side with siRNAs designed
using the previous algorithm at 5 nM in HeLa
cells. mRNA knockdown was measured 48 h post-transfection
via qRT-PC R using TaqMan® Gene Expression
Assays. Results are expressed as percent of
mRNA remaining compared to Silencer Negative
Control #1 siRNA treated cells. The inset shows
the percentage of siRNAs that elicited ≥70%
and ≥80% mRNA knockdown.
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Multiple publications confirm that higher siRNA
concentrations lead to increased off-target effects
(1,2).
The need to design more potent siRNAs that can
be used at lower concentrations was therefore
a key driver in our siRNA design algorithm improvement
efforts.
Silencer Select siRNAs:
• Are up to 100X more potent than competitor
siRNAs
• Can be routinely transfected at ≤5
nM and retain their silencing power
• Result in fewer off-target effects
when used at these lower concentrations
• Cost less per experiment than siRNAs
used at higher concentrations |
References
1. Semizarov D, Frost L, Sarthy A, Kroeger P,
Halbert DN, Fesik SW (2003) Specificity of
short interfering RNA determined through gene
expression signatures. Proc Natl Acad Sci USA
100(11):6347–6352.
2. Jackson AL, Bartz SR, Schelter J, Kobayashi
SV, Burchard J, Mao M, Li B, Cavet G, Linsley
PS (2003) Expression profiling reveals off-target
gene regulation by RNAi. Nat Biotechnol 21(6):635–637.
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Silencer Select
siRNAs Provide Up to 100X Higher Potency Compared
to Other siRNAs. Silencer Select siRNAs
to 10 different targets and siRNAs from two
other suppliers to the same 10 different targets
were individually transfected into HeLa cells
in triplicate at the indicated siRNA concentration.
mRNA knockdown levels were tested 48 h later
as described in Figure 1. Average percent mRNA
remaining is shown for each set of siRNAs.
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The main goal of an RNAi experiment is to examine
the biological effect of knocking down a target
of interest, often with a cell based assay. However,
to elicit that phenotype, some minimum threshold
level of knockdown is
required, and this threshold level will vary
depending on the target.
Silencer Select siRNAs:
• More reliably elicit maximum knockdown
levels
• More consistently reach the threshold
level of knockdown required to see a loss-of-function
phenotype
• In side-by-side tests, result in a
higher percentage of expected, silenced phenotypes
than siRNAs
from other vendors |
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Silencer Select siRNAs Elicit
Expected Phenotype at a Higher Rate than Other
siRNAs. siRNAs to seven gene targets
with well understood RNAi induced phenotypes
were individually transfected at 3 nM and phenotypes
measured 48 hours later. Each bar represents
the percent of siRNAs that gave the expected,
silenced phenotype. siRNAs to BUB1B, AURKB,
WEE 1, and PL K1 were assessed using a multi-parametric
cell growth / apoptosis assay in U2OS human
osteosarcoma cells. siRNAs to HMGCR, LDLR,
and FDFT 1 were assessed using an LDL uptake
assay in HUH7 human hepatoma cells.
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Although using siRNAs at low concentrations
decreases off-target effects, further specificity
gains can be made using bioinformatic filtering
to predict and eliminate potentially “bad” siRNAs.
The Design Process for Silencer Select
siRNAs:
• Includes the rigorous, five-step process
shown at right to remove siRNAs with
a high propensity for off-target effects
• Incorporates the newly developed Silencer Select
Toxicity Classifier, which eliminates sequences
predicted to elicit an off-target apoptotic
phenotype
• Minimizes miRNA pathway related off-target
effects by removing siRNAs with seed regions
that resemble naturally occurring miRNAs
and selecting siRNAs with the fewest seed
region matches in the 3’UTRs of off-target
transcripts |
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Five-step Bioinformatic
Filtering Process that Eliminates siRNAs
Predicted to Elicit Off-target Effects
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Strong guide strand bias, where the guide strand
of the siRNA is selectively taken up into RISC
over the passenger strand, is important both
for maximizing siRNA silencing potency and for
decreasing passenger strandrelated off-target
effects. Although incorporating the right siRNA
design parameters can help, siRNA design alone
is not sufficient to ensure strong guide strand
bias.
The Chemical Modifications in Silencer Select
siRNAs:
• Consistently enhance guide strand
bias, which has been shown to correlate strongly
with knockdown
efficiency
• Prevent the passenger strand from
inducing silencing, which serves to reduce
off-target effects
• Result in no loss—and in many
cases an improvement—in siRNA silencing
potency |
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Luciferase reporter gene constructs
with siRNA targets cloned in either the sense
(guide strand target) or antisense (passenger
strand target) orientation were co-transfected
with the corresponding siRNA and a ß-galactosidase
encoding control vector. Luciferase and ß-galactosidase
assays were performed 72 hours later, and knockdown
for each strand was calculated relative to negative
control siRNA transfected cells. (A) The
ratio of guide to passenger strand knockdown
is shown for 46 siRNAs with and without the Silencer Select
modifications. (B) The average
ratio of guide to passenger strand knockdown
is plotted versus luciferase knockdown for 6 Silencer Select
and 36 competitor siRNAs.
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Sequence specific off-target effects are one
of the primary reasons for false positive results
in RNAi experiments. In addition to the potency
improvements afforded by the new algorithm and
state-of-the-art bioinformatic filtering criteria, Silencer Select
siRNAs incorporate novel modifications demonstrated
to improve siRNA specificity.
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The Chemical Modifications in Silencer Select
siRNAs:
• Reduce the number of non-targeted,
differentially expressed genes detected
by gene expression array by up to 90% as
compared to unmodified siRNAs
• Result in a dramatic reduction of
off-target phenotypes as measured by multi-parametric
cell-based assays
• Do not negatively impact silencing
efficiency and therefore do not compromise
the expected on-target phenotypes
• Yield cleaner, more consistent cell
biology data
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Silencer Select
siRNA Modifications Reduce the Number of Off-target,
Differentially Expressed Genes. Three
negative control siRNAs with and without the Silencer Select
modifications were individually transfected
in quadruplicate into HeLa cells at 30 nM.
RNA was extracted and analyzed on an Affymetrix
Human Genome U133 Plus 2.0 Array in triplicate.
The y-axis indicates the average number of
differentially expressed genes — those
showing ≥2-fold change
in expression versus mock transfected samples

Silencer Select siRNA Modifications
Reduce Off-target Effects and Yield More Reliable
Phenotypic Data. 53 different siRNAs,
including older designs previously noted to
elicit offtarget phenotypes, were transfected
into U2OS cells at 30 nM in both unmodified
and Silencer Select modified formats.
Mitosis and apoptosis were measured 48 hours
later. Data is expressed relative to negative
control siRNA transfected cells. Black = similar
mitosis/apoptosis levels as control. Green
= down-regulation. Red = up-regulation. Note
that the expected mitotosis and apoptosis phenotypes
for PLK and WEE1 siRNAs are preserved with
the modifications. In contrast the off-target
apoptotic phenotypes elicited by 10 unmodified
siRNAs were completely eliminated with addition
of the Silencer Select modifications.
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| 100% Guarantee – The
BEST in the Industry |
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•Buy 2 Silencer® Select
Pre-designed siRNAs to a target, and we guarantee
that BOTH will knockdown by ≥70%
•Buy 3 Silencer® Select
Pre-designed siRNAs to a target, and we guarantee
that 2 of 3 will knockdown by ≥80%
•Silencer® Select
Validated siRNAs are guaranteed to knockdown
by ≥80%
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