W448–W450 Nucleic Acids Research, 2006, Vol. 34, Web Server issue
doi:10.1093/nar/gkl214

siVirus: web-based antiviral siRNA design software
for highly divergent viral sequences
Yuki Naito1,*, Kumiko Ui-Tei1,2, Toru Nishikawa3, Yutaka Takebe4 and Kaoru Saigo1
1

Received February 14, 2006; Revised and Accepted March 24, 2006

ABSTRACTsiVirus (http://siVirus.RNAi.jp/) is a web-based online
software system that provides efficient short interfering RNA (siRNA) design for antiviral RNA interference (RNAi). siVirus searches for functional,
off-target minimized siRNAs targeting highly conserved regions of divergent viral sequences. ThesesiRNAs are expected to resist viral mutational
escape, since their highly conserved targets likely
contain structurally/functionally constrained elements. siVirus will be a useful tool for designing
optimal siRNAs targeting highly divergent pathogens, including human immunodeficiency virus(HIV), hepatitis C virus (HCV), influenza virus and
SARS coronavirus, all of which pose enormousthreats to global human health.

500 entries of near full-length sequences of HIV-1
group M, which is largely responsible for global pandemic,
are stored in the sequence databases, but it proved impossible
to select a common 21mer from among all of them. Moreover,RNAi-resistant viral mutants achieved through point mutation
or deletion emerge rapidly when targeting viruses in cell culture. These problems suggest a strong need to select highly
conserved target sites for designing antiviral siRNAs. Furthermore, the off-target silencing effects of siRNA are also a
serious problem that could affect host gene expression (9).
Off-target silencing effects arise when an siRNA has sequencesimilarities with unrelated genes. In antiviral RNAi, it is desirable to minimize off-target effects against human genes.
Consequently, only a limited fraction of 21mers is suitablefor use as antiviral siRNAs. In this study, we developed a novel
web-based online software system, siVirus, which provides
functional, off-target minimized siRNAs targeting highly conserved regions of divergent viral sequences.

INTRODUCTION
RNA interference (RNAi) is now widely used to knockdown
gene expression in a sequence-specific manner, making it apowerful tool not only for studying gene function, but also fortherapeutic purposes, including antiviral treatments (1–4).
Currently, the replication of a wide range of viruses can beinhibited successfully using RNAi, with both short interfering
RNAs (siRNAs) and siRNA expression vectors (5).
In mammalian RNAi, the efficacy of each siRNA varies
widely depending on its sequence; only a limited fractionof randomly designed siRNAs is highly effective. Manyexperiments have been conducted to clarify possible sequencerequirements of functional siRNAs. Of these, our work incorporates guidelines from three major studies (6–8) of selecting
functional siRNAs. However, designing functional siRNAs
that target viral sequences is problematic because of their
extraordinarily high genetic diversity. For example, about

METHODS
Selection of highly conserved siRNA target sites
Highly conserved siRNA sequences are selected based on theirdegree of conservation, defined as the proportion of viralsequences that are targeted by the corresponding siRNA,
with complete matches (i.e. 21/21 matches). All possible
siRNA candidates targeting every other position of userselected viral sequences are generated and their degrees ofconservation are computed. Users can arbitrarily specify aset of viral sequences for the computation; e.g. sequences
can be selected from a specific geographic region(s) or a
specific genotype(s) to design the best siRNAs tailored to
specific user needs. siVirus also accepts user’s own sequences
in a multi-FASTA format and shows whether each siRNA cantarget the posted sequences.

*To whom correspondence should be addressed. Tel: +81 3 5841 4404; Fax: +81 3 5841 4400; Email: y-naito@RNAi.jp
 The Author 2006. Published by Oxford University Press. All rights reserved.
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open accessversion of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press
are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but
only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

Downloaded from nar.oxfordjournals.org at Ekigaku-Kyoshitsu (UNIV OF TOKYO) on October 17, 2010

Department of Biophysics and Biochemistry, Graduate School of Science, 2Undergraduate Program for
Bioinformatics and Systems Biology, School of Science and, 3Department of Computer Science, Graduate School ofInformation Science and Technology, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and4Laboratory of Molecular Virology and Epidemiology, AIDS Research Center, National Institute of Infectious Diseases,
1-23-1 Toyama, Shinjuku-ku, Tokyo 162-8640, Japan

Nucleic Acids Research, 2006, Vol. 34, Web Server issue

A
0%
0%

Degree of conservation
50%

B
100%

All possible siRNA candidates targeting
495 HIV-1 sequences
0%siRNAs1%50%(4,417,157 siRNAs = 100%)

Ui-Tei et al. 18.3%
0.8%

2.1%

2%
6.9%

1.7%

4%
100%
(4,417,157 siRNAs)
0%

siRNA target site
21bp target + 2bp overhang
map to HXB2

AGCCTCAATAAAGCTTGCCTTga

50%
Degree of conservation

5%100%

siRNA efficacy prediction
2 mismatch
Ui-Tei Reynolds Amarzguioui off-target hits

yes

AAGCCTCAATAAAGCTTGCCTtg

yes

2 [detail]97.3% (148/152)yes

1 [detail]96.0% (146/152)yes

2 [detail]92.8% (169/182)

ATTCAAAATTTTCGGGTTTATtayes

0 [detail]92.3% (168/182)

yes

2 [detail]92.3% (168/182)

AGGAGAGAGATGGGTGCGAGAgc

yes

2 [detail]92.1% (152/165)

GGAGGCTAGAAGGAGAGAGATggyes

4 [detail]91.5% (151/165)

AGCGGAGGCTAGAAGGAGAGAgayes

4 [detail]90.9% (150/165)

0 [detail]90.8% (149/164)yes

7 [detail]90.3% (149/165)

yes

1 [detail]90.2% (148/164)

0 [detail]89.6% (147/164)

3 [detail]88.4% (161/182)

2 [detail]88.2% (135/153)

yes

GACTAGCGGAGGCTAGAAGGAga

yes

CGGAGGCTAGAAGGAGAGAGAtg

yes

CTAGCGGAGGCTAGAAGGAGAga
yes

TTTGACTAGCGGAGGCTAGAAgg

yes

GACAGCAGTACAAATGGCAGTat
TGCTTAAGCCTCAATAAAGCTtg

yes

AGGGGAAGTGACATAGCAGGAacyes

2 [detail]87.9% (160/182)

GGGGAAGTGACATAGCAGGAActyes

3 [detail]87.9% (160/182)

1 [detail]87.5% (134/153)yes

3 [detail]87.3% (159/182)

yes

1 [detail]87.1% (129/148)yes

2 [detail]87.1% (129/148)

yes

CCACTGCTTAAGCCTCAATAAag
CAGCAGTACAAATGGCAGTATtc

yes

AACCCACTGCTTAAGCCTCAAta
ACCCACTGCTTAAGCCTCAATaa

yes

yes

Reynolds et al.
19.0%

5.9%

Amarzguioui et al.
23.0%

Conservation in the selected sequences( :conserved, :not conserved, :sequence not available)

TCAAAATTTTCGGGTTTATTAca
TTCAAAATTTTCGGGTTTATTac

8.5%

9.6%

Figure 1. (A) The degree of conservation is calculated for all possible siRNA candidates (total 4 417 157) targeting every other position of 495 HIV-1 sequences.
(B) The efficacy predictions of these 4 417 157 siRNA candidates based on three different guidelines: Ui-Tei et al. (6), Reynolds et al. (7) and Amarzguioui et al. (8).
(C) Typical output of siVirus for designing anti-HIV siRNAs. Sequence information, efficacy predictions, off-target search results and the degrees of conservation areshown.

siRNA efficacy prediction
In mammalian RNAi, the efficacy of each siRNA varies markedly depending on its sequence; hence, several groups havereported guidelines for selecting functional siRNAs. siVirus
incorporates the guidelines of Ui-Tei et al. (6), Reynolds et al.
(7) and Amarzguioui et al. (8) and shows whether each siRNA
satisfies these guidelines.

These sequences were downloaded from the Los Alamos
HIV Sequence Database (http://hiv-web.lanl.gov/), the Los
Alamos HCV Sequence Database (12), the NCBI Influenza
Virus Sequence Database (http://www.ncbi.nlm.nih.gov/
genomes/FLU/FLU.html), and NCBI GenBank (13), respectively. siVirus will be updated continuously as these databases
are revised. We also plan to incorporate other viruses if
sufficient numbers of their sequences are available.

Off-target searches
Off-target searches were performed for each siRNA using
siDirect (10,11). siVirus shows the number of off-target hits
within two mismatches against the non-redundant database ofhuman transcripts (10).
Database maintenance
Currently, siVirus incorporates viral genome sequences ofHIV-1, HCV, influenza A virus and SARS coronavirus.

RESULTS AND DISCUSSION
To design anti-HIV siRNA, we analyzed the 495 near fulllength HIV-1 sequences listed in Supplementary Table 1. A
total of 4 417 157 possible siRNA candidates (i.e. substrings oflength 21) targeting every other position of the HIV-1
sequences were produced from the 495 viral sequences.
The analysis of these siRNA candidates revealed that highly

Downloaded from nar.oxfordjournals.org at Ekigaku-Kyoshitsu (UNIV OF TOKYO) on October 17, 2010

3%CW449

W450

Nucleic Acids Research, 2006, Vol. 34, Web Server issueSUPPLEMENTARY DATA
Supplementary Data are available at NAR Online.
ACKNOWLEDGEMENTS
This work was supported in part by grants from the Ministry ofEducation, Culture, Sports, Science and Technology of Japan toK.S., K.U.-T. and Y.T., and by grants from the Ministry ofHealth, Labour and Welfare of Japan to Y.T. Funding to pay
the Open Access publication charges for this article was provided by the Ministry of Education, Culture, Sports, Scienceand Technology of Japan. Y.N. is a Research Fellow of theJapan Society for the Promotion of Science.
Conflict of interest statement. None declared.

REFERENCES
1. Fire,A., Xu,S., Montgomery,M.K., Kostas,S.A., Driver,S.E. andMello,C.C. (1998) Potent and specific genetic interference bydouble-stranded RNA in Caenorhabditis elegans. Nature, 391, 806–811.
2. Mello,C.C. and Conte,D. Jr (2004) Revealing the world of RNAinterference. Nature, 431, 338–342.
3. Hannon,G.J. and Rossi,J.J. (2004) Unlocking the potential of the humangenome with RNA interference. Nature, 431, 371–378.
4. Voinnet,O. (2005) Induction and suppression of RNA silencing: insightsfrom viral infections. Nature Rev. Genet., 6, 206–220.
5. Leonard,J.N. and Schaffer,D.V. (2006) Antiviral RNAi therapy:
emerging approaches for hitting a moving target. Gene Ther., 13,532–540.
6. Ui-Tei,K., Naito,Y., Takahashi,F., Haraguchi,T., Ohki-Hamazaki,H.,
Juni,A., Ueda,R. and Saigo,K. (2004) Guidelines for the selection ofhighly effective siRNA sequences for mammalian and chick RNAinterference. Nucleic Acids Res., 32, 936–948.
7. Reynolds,A., Leake,D., Boese,Q., Scaringe,S., Marshall,W.S. andKhvorova,A. (2004) Rational siRNA design for RNA interference. Nat.
Biotechnol., 22, 326–330.
8. Amarzguioui,M. and Prydz,H. (2004) An algorithm for selection offunctional siRNA sequences. Biochem. Biophys. Res. Commun., 316,1050–1058.
9. Jackson,A.L. and Linsley,P.S. (2004) Noise amidst the silence:
off-target effects of siRNAs? Trends Genet., 20, 521–524.
10. Naito,Y., Yamada,T., Ui-Tei,K., Morishita,S. and Saigo,K. (2004)
siDirect: highly effective, target-specific siRNA design software formammalian RNA interference. Nucleic Acids Res., 32, W124–W129.
11. Yamada,T. and Morishita,S. (2005) Accelerated off-target searchalgorithm for siRNA. Bioinformatics, 21, 1316–1324.
12. Kuiken,C., Yusim,K., Boykin,L. and Richardson,R. (2005) The Los
Alamos hepatitis C sequence database. Bioinformatics, 21, 379–384.
13. Benson,D.A., Karsch-Mizrachi,I., Lipman,D.J., Ostell,J. andWheeler,D.L. (2006) GenBank. Nucleic Acids Res., 34, D16–D20.

Downloaded from nar.oxfordjournals.org at Ekigaku-Kyoshitsu (UNIV OF TOKYO) on October 17, 2010

conserved siRNAs constituted only 0.3% of the possible
siRNAs if >90% conservation is expected (Figure 1A). The
fraction is still as small as 0.8% even if the threshold of theconservation is relaxed to 80%. On the other hand, siRNAs
predicted to be functional by one or more guidelines (6–8)
constituted 35.5% of the 4 417 157 siRNAs (Figure 1B). Taken
together, siRNAs that are >80% conserved, and satisfy at least
one guideline constitute only 0.2% of the siRNAs. In thiscondition, 20–30 siRNAs can be designed for each full-length
sequence of HIV-1. These indicate that most of the randomly
designed siRNAs are not suited for targeting HIV-1 efficiently.
Figure 1C shows typical output from siVirus for designinganti-HIV siRNAs. A total of 182 sequences from HIV-1
subtypes B, C and CRF01_AE, which are the most prevalent
HIV-1 genotypes circulating in Asia, were selected. The
results were sorted by their degree of conservation, andfiltered to display siRNAs that satisfy at least one efficacy
guideline. The off-target search results against human genes
are also shown. It is desirable to select an siRNA that has lessoff-target hits.
To test the validity of siVirus, 35 siRNAs satisfying
the guideline by Ui-Tei et al. (6) were designed against theconserved regions of HIV-1 genomes using siVirus and wereassayed for inhibition of viral replication. Among them, 31
siRNAs effectively inhibited HIV-1 replication by >80%
when each siRNA duplex was transfected at 5 nM (Y. Naito,K. Ui-Tei, K. Saigo and Y. Takebe, unpublished data).