**9. Importance of functional off-target filtering**

272 Bioinformatics

**siRNA selection tool** 

Ambion siRNA Target

[http://www.ambion.c om/techlib/misc/siRN A\_finder.html].

[http://www.biopredsi.

siRNA Target Finder [https://www.genscrip

[https://rnaidesigner.invit rogen.com/rnaiexpress].

Finder

AsiDesigner [http://sysbio.kribb.re. kr:8080/AsiDesigner/m enuDesigner.jsf]

BIOPREDsi

org/].

t.com/sslbin/app/rnai].

BLOCK-iT RNAi Designer

IDT RNAi Design [http://www.idtdna.com /Scitools/Applications/R NAi/RNAi.aspx].

MicroSynth siRNA

[http://www.microsynt h.ch/499.0.html].

design

**8. Discussion about selected siRNA designing tools** 

designing solutions with their designing parameters.

**Thermodynamic deference between sense and antisense strand 5' end** 

Several siRNA sequence selection algorithms have been developed in the past decade that relies on intrinsic sequence, stability and target accessibility features of functional siRNAs. Different siRNA selection algorithms follow different set of rules derived from some wellknown siRNA design parameters as discussed above. In general, these algorithms rely on features like- low GC content, absence of siRNA self-alignment, absence of internal repeat, thermodynamic conditions favouring efficient RISC entry, absence of homology to other mRNAs and some position specific nucleotide compositions. Few of them also consider silencing of alternatively spliced isoforms of the given gene. Different algorithms use different techniques for combination of parameters and their weight distribution- ranging from empirical observation to sophisticated machine learning. In spite of a large number of online siRNA design solutions, few of them consider miRNA-like off-targeting potential of synthetic siRNAs. Consideration for minimization of such off-target effect involves imposing a threshold for number of off-target genes. Table 5 lists some of the online siRNA

> **Target accessibility**

Considered Not Considered Not

Considered Not Considered Not

Considered Considered Not

Considered Considered Not

Considered Considered Not

Considered Not Considered Not

**Alternative splicing** 

Considered Considered Considered Considered Not

**Off-target(near complementary)** 

Considered Considered Not

Considered Considered Considered

Considered Considered Considered

Considered Considered Not

Considered Considered Not

Considered Considered Not

**miRNA-like off-target** 

Considered

considered

Considered

Considered

Considered

Considering only quantity of the off-targets and not the functions of individual off-targets can lead to inefficient handling of the miRNA-like off-target issue. Often in siRNA screening experiments, it has been reported that the desired output is affected because of silencing of unintended off-targets those sometimes are themselves member of the upstream pathway components of the direct target gene [26]. In such cases it can be useful to avoid specifically some off-targets that can cause more harmful or undesirable effects. It should be considered that during silencing process siRNA should not silence any mRNA from the same pathway the target mRNA is part of. In case of investigation of a gene function, if any gene from the same pathway is silenced rather than target gene then it will be difficult to investigate the actual phenotype of silencing the gene under investigation. For e.g. in a siRNA screening experiment designed for novel members of the transforming growth factor (TGF)-b pathway in a human keratinocyte cell line, dominant off-target effect was observed due to unintended silencing of two known upstream pathway components, the TGF-b receptors 1 and 2 (TGFBR1 and TGFBR2). Such off-target silencing activity poses threats of confusing and misleading results. Also the siRNAs suggested by the online siRNA selection tools often are predicted to have offtargets that belong to the same pathway or somehow related to the direct target.

Das et al reported designing of a siRNA designing tool using a simple approach towards minimizing miRNA-like off-target effect through user feedback. Here, the user can actually choose from the list of potential off-target genes, the off-targets he/she wants to filter out, by considering the effect of silencing of those off-target genes. This tool statistically evaluates present day siRNA design rules such as- low GC content, absence of long stretches of identical nucleotides, thermodynamic conditions favouring efficient RISC entry, absence of homology to other mRNAs, absence of immune stimulatory motifs in the RISC entering strand of the siRNA duplex and some position specific nucleotide compositions, in a database of validated siRNAs [12] used in experiments to examine the threshold parameters. A support vector machine, trained with the optimal features set, is used for classifying potential and effective siRNAs. Moreover, with other parameters, it predicts the potential miRNA-like off-target genes for each candidate siRNA, sets a threshold for the number of off-targets to minimize miRNA-like off-target effect and presents the list of predicted off-target genes. A feedback mechanism allows the user to choose specific genes that needs to be filtered out from the list of predicted off-target genes recursively until his/her needs are met. This technique gives a more rational approach towards handling the miRNA-like off- target issue.

Computational Approaches for Designing Efficient and Specific siRNAs 275

issue arising from miRNA-like off-targets of a siRNA from a different point of view, like the functional off-target filtering discussed in previous section, may prove to be beneficial and may emerge as a new paradigm for designing efficient siRNAs with customized specificity.

We thank Sanga Mitra and Smarajit Das of Indian Association for the Cultivation of Science

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**Author details** 

**Acknowledgement** 

**11. References** 

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Suman Ghosal, Shaoli Das and Jayprokas Chakrabarti *Indian Association for the Cultivation of Science, Kolkata, India* 

**Figure 1.** An example of off-target filtering by user feedback
