**7. Prediction of siRNA off-targets**

Prediction of miRNA-like off-targets involves finding the seed complementarity of the siRNA with the 3'UTR of a non-target mRNA. But considering only seed region complementarity identifies a large number of off-targets that could not be actually targeted. So, a more rational approach is needed for prediction of siRNA off-targets that needs understanding the miRNA target recognition procedure. Parameters like local AU content near the seed region or accessibility of the target site within the 3'UTR of the predicted off-target play roles in siRNA off-target detection also [21]. To have a more reliable prediction of off-targets, some siRNA designing solutions consider the stability factor of the duplex formed by siRNA guide strand seed region and mRNA 3' UTR target as the off-targets forming duplex with lower stability are less likely to be actually silenced by the siRNA [22]. These tools examine thermodynamic property of the siRNA seed-mRNA duplex and carefully choose siRNAs with seed sequences that are predicted to form less thermodynamically stable duplex with the target mRNA. Some siRNA designing solutions consider conservation of such target regions among closely related species to determine the candidate mRNAs most likely to be silenced by miRNA-like mechanism [23]. Table 4 gives the mechanism adopted by different online siRNA designing solutions for minimizing off-targets.

In a detailed investigation of all possible seed sequence and their frequency of complimenting the 3' UTRs of human mRNAs, it is shown that the seeds can be classified into low, medium and high frequency classes according to the number 3' UTR sites targeted by them [24]. The low frequency seeds have targets around 350, while the medium and high frequency seeds have targets around 2500 and more than 4800 respectively. So, it is obvious that siRNAs having a seed region that falls into the low frequency group will have fewer off-targets. But then in many cases, presence of such seed sequences can decrease the potency of the siRNA because they often contain stretches of identical nucleotides or other features unfavorable for a potent siRNA. So, there is a tradeoff between potency and specificity of a siRNA which have to be dealt with in their computational designing. Seed complement frequency (SCF) is the frequency of the complement of the hexamer/heptamer seed region within 3' UTR of an mRNA [24]. It is a major parameter which greatly enhances specificity of siRNA off-target prediction, but at the cost of decreasing sensitivity. Some microRNA target site features as uncovered by combining computational and experimental approaches, also apply to the siRNA off-target prediction problem. A study reported potential silencing of transcripts having consecutive 11 or more bases complementarity with miRNA or siRNAs including siRNA bases 9-12. These transcripts are more likely to be cleaved by the siRNA. Some other off-target prediction parameters include secondary structure analysis for target accessibility prediction and A/U base richness near target site [25]. For reliable off-target prediction, an optimized combination of all the above mentioned parameters is needed.

270 Bioinformatics

kind of off-target effect is called miRNA-like off-target effect [18, 19]. This kind of off-target cannot be fully avoided but can be reduced by computational design. Consideration for minimization of such off-target effect involves imposing a threshold for number of off-target genes. All of the present day online siRNA designing techniques consider only the quantitative approach for minimizing miRNA-like off-target effect by restricting the number of off-targets [20]. To go beyond mere quantitative approach and look for the functional correlation between the on-target and the genes off-targeted by the siRNA will certainly prove to be beneficial in minimizing miRNA-like off-target effect. A newly developed siRNA designing tool is aimed for such off-target minimization considering functional

Prediction of miRNA-like off-targets involves finding the seed complementarity of the siRNA with the 3'UTR of a non-target mRNA. But considering only seed region complementarity identifies a large number of off-targets that could not be actually targeted. So, a more rational approach is needed for prediction of siRNA off-targets that needs understanding the miRNA target recognition procedure. Parameters like local AU content near the seed region or accessibility of the target site within the 3'UTR of the predicted off-target play roles in siRNA off-target detection also [21]. To have a more reliable prediction of off-targets, some siRNA designing solutions consider the stability factor of the duplex formed by siRNA guide strand seed region and mRNA 3' UTR target as the off-targets forming duplex with lower stability are less likely to be actually silenced by the siRNA [22]. These tools examine thermodynamic property of the siRNA seed-mRNA duplex and carefully choose siRNAs with seed sequences that are predicted to form less thermodynamically stable duplex with the target mRNA. Some siRNA designing solutions consider conservation of such target regions among closely related species to determine the candidate mRNAs most likely to be silenced by miRNA-like mechanism [23]. Table 4 gives the mechanism adopted by different online siRNA designing

In a detailed investigation of all possible seed sequence and their frequency of complimenting the 3' UTRs of human mRNAs, it is shown that the seeds can be classified into low, medium and high frequency classes according to the number 3' UTR sites targeted by them [24]. The low frequency seeds have targets around 350, while the medium and high frequency seeds have targets around 2500 and more than 4800 respectively. So, it is obvious that siRNAs having a seed region that falls into the low frequency group will have fewer off-targets. But then in many cases, presence of such seed sequences can decrease the potency of the siRNA because they often contain stretches of identical nucleotides or other features unfavorable for a potent siRNA. So, there is a tradeoff between potency and specificity of a siRNA which have to be dealt with in their computational designing. Seed complement frequency (SCF) is the frequency of the complement of the hexamer/heptamer seed region within 3' UTR of an mRNA [24]. It is a major parameter which greatly enhances specificity of siRNA off-target prediction, but at the cost of decreasing sensitivity. Some microRNA target site features as uncovered by combining computational and experimental approaches, also apply to the

correlation of the off-target and the direct target (explained in section 9).

**7. Prediction of siRNA off-targets** 

solutions for minimizing off-targets.


**Table 4.** Off-target minimization techniques of different siRNA designing tools.
