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First published online August 18, 2006; 10.1104/pp.106.083295 Plant Physiology 142:429-440 (2006) © 2006 American Society of Plant Biologists OPEN ACCESS ARTICLE
Computational Estimation and Experimental Verification of Off-Target Silencing during Posttranscriptional Gene Silencing in Plants1,[W],[OA]Plant Biology Division, The Samuel Roberts Noble Foundation, Ardmore, Oklahoma 73401
Successful application of posttranscriptional gene silencing (PTGS) for gene function study in both plants and animals depends on high target specificity and silencing efficiency. By computational analysis with genome and/or transcriptome sequences of 25 plant species, we predicted that about 50% to 70% of gene transcripts in plants have potential off-targets when used for PTGS that could obscure experimental results. We have developed a publicly available Web-based computational tool called siRNA Scan to identify potential off-targets during PTGS. Some of the potential off-targets obtained from this tool were tested by measuring the amount of off-target transcripts using quantitative reverse transcription-PCR. Up to 50% of the predicted off-target genes tested in plants were actually silenced when tested experimentally. Our results suggest that a high risk of off-target gene silencing exists during PTGS in plants. Our siRNA Scan tool is useful to design better constructs for PTGS by minimizing off-target gene silencing in both plants and animals.
Posttranscriptional gene silencing (PTGS), also known as RNA interference (RNAi) in animals, cosuppression in plants, and RNA quelling in fungi, is an epigenetic phenomenon that results in sequence-specific degradation of endogenous mRNAs (Cogoni and Macino, 2000  ). PTGS is mediated by 21- to 24-nucleotide (nt) double-strand RNA (dsRNA) molecules, termed short/small interference RNAs (siRNAs). The siRNAs are incorporated into a multisubunit protein complex, the RNAi-induced silencing complex, which directs the siRNA to and degrades the complementary mRNA (Baulcombe, 2004). Because PTGS allows silencing of a specific target gene, it has become a popular tool to study gene function in plants and animals (Kamath et al., 2003; Baulcombe, 2004; Hannon and Rossi, 2004; Kuttenkeuler and Boutros, 2004).
In plants, PTGS can be induced by antisense and sense transgenic technology and it is also achieved by expressing dsRNA through stable or transient transformation with RNAi constructs (binary vectors) to knock down the expression of target genes (Wesley et al., 2001
Theoretically, PTGS functions in a siRNA-specific rather than a target-specific manner. However, analyses of mammalian cells transfected with different siRNAs against a target gene by two different research groups led to contradictory conclusions about silencing unintended genes (Chi et al., 2003 Investigating off-target gene silencing is crucial for accurate interpretation of gene function by PTGS and for use of PTGS application in agriculture. In this study, we estimate potential off-targets based on sequence identity for 25 plant species whose genomic or expressed sequence tag (EST) sequences are publicly available. Experimentally, we investigated the expression level of several potential off-target genes in an RNAi transgenic Arabidopsis (Arabidopsis thaliana) line and in gene-silenced (by VIGS) Nicotiana benthamiana plants. To assist the design of PTGS constructs to minimize off-target gene silencing or to identify potential off-targets from a particular PTGS construct, we have developed a Web-based computational tool. The tool provides an integrated sequence similarity search environment for plant and animal species, identifies potential off-targets, and predicts putatively effective siRNAs from the target query sequences.
Computational Analysis of Potential Off-Targets during PTGS
PTGS in plants is mediated by siRNAs derived from the cleavage of dsRNA produced through binary vector-based RNAi or VIGS constructs. The siRNAs recognize their targets by base pairing. Therefore, the potential off-targets are identified by a direct sequence identity and reverse complimentary sequence identity search. In this study, we define the cDNA producing dsRNA for silencing of the intended target gene (from which the cDNA comes) as the trigger and the unintended genes that share a contiguous
Using the full-length cDNA sequence of every transcript in the Arabidopsis genome mRNA dataset (ATH1) as a trigger, we estimated the patterns of potential off-targets by searching for identical or reverse complementary regions of
On average, 68.7% of Arabidopsis transcripts can potentially silence 3.9 off-target genes (Table I). Each candidate off-target has an average of three off-target regions with an average length of over 40 nt (Table I). However, this could be an overestimation because not all siRNAs derived from the cleavage of dsRNAs are efficient at silencing (Khvorova et al., 2003 ; Schwarz et al., 2003). Because little is known about the efficacy of specific siRNAs in plants, we adapted the rules developed by Ui-Tei et al. (2004) to predict whether and how many of the trigger sequences mentioned above produce efficient siRNAs to silence their potential off-targets. Specifically, the rules for a 21-nt siRNA duplex with a 2-nt overhang include: (1) antisense strand starts with A/U; (2) sense strand starts with G/C; (3) at least five of the first seven residues at the 5' terminus of the antisense strand should be A/U; and (4) there is no G/C stretch of more than 9 nt in length (Ui-Tei et al., 2004). As shown in Table I, 68.7% of all trigger sequences in the ATH1 database are predicted to generate an average of 35 efficient 21-nt siRNAs to cause potential off-target silencing.
In addition to Arabidopsis, we also estimated the potential off-targets in 24 other plant species, using Gene Indices assembled from ESTs and other expressed transcripts provided by The Institute for Genomic Research (TIGR; Quackenbush et al., 2001
Off-target silencing, however, may be desirable in PTGS applications to generate a loss-of-function phenotype if the target and off-targets are functionally redundant. For example, the same family members or genes encoding proteins that share conserved functional protein domains may be simultaneously silenced. Arabidopsis gene family information at The Arabidopsis Information Resource (TAIR) Web site (http://www.arabidopsis.org) was used to evaluate the chance that potential off-targets belong to the same gene family as the target gene. The data from the TAIR ftp site, after removing ambiguous entries and single-member families, contain 5,842 genes from 674 families (see Supplemental Table S1), with family size ranging from two to 307 members. Our analysis indicates that 4,677 gene sequences (79.9% of 5,842 genes) of these families may trigger off-target silencing of other members of the same family when a full-length sequence is used as a trigger. Among the families with different numbers of gene members, the number of off-targets was different but generally fewer than six (Fig. 2
; Supplemental Table S1). Moreover, only 418 genes from 192 families containing fewer than 10 members share an identical region of
An Integrated Search Environment for PTGS
An online tool (available at http://bioinfo2.noble.org/RNAiScan.htm) has been developed to evaluate and minimize the risk of off-target effects during PTGS. The tool is a search environment with several integrated components, including a sequence similarity search to identify potential off-targets, efficiency estimation of siRNAs, and functional analysis of off-target genes. In the sequence similarity search, the query sequence is compared with a gene transcript dataset using the BLASTn program (Altschul et al., 1997
Expression of at Least Three Off-Target Genes Was Knocked Down in BTI1 RNAi Transgenic Lines
To rule out the possibility that the lowered expression of some of these selected genes might be due to the loss of function of the BTI1 protein instead of off-target silencing, we analyzed the expression levels of all the above investigated genes in an Arabidopsis bti1-2 null mutant line (T-DNA knockout line; Salk-032220). As expected, the expression of BTI1 was below the detectable levels in the mutant plants, but the expression levels of all the other genes tested were similar to those in nontransgenic Arabidopsis plants (Fig. 3). Expression of two additional housekeeping genes, eIF4 and actin II, was also investigated for the confirmation of equal RNA amounts used for real-time qRT-PCR. Expression levels were similar among the samples from the three groups, further confirming the equal loading of total RNA in the reactions (Fig. 3). Thus, it is off-target silencing caused by BTI1-derived dsRNA that down-regulated the expression of three of the five selected potential off-targets in BTI1 RNAi transgenic plants. In addition, there is a striking phenotypic difference between BTI1 RNAi transgenic lines and the bti1-2 mutant line. Plants from four independent BTI1 RNAi transgenic lines flowered earlier than the wild-type and bti1-2 mutant plants (Fig. 4 ) and this is probably due to off-target gene silencing in the RNAi plants.
Expression of Some Potential Off-Targets Was Down-Regulated in N. benthamiana Plants Infiltrated with VIGS Constructs Computational analysis showed that more than one-half of the EST contigs (TCs) in the N. benthamiana database have multiple potential off-targets during PTGS (Table I). We randomly chose two genes for experimental analyses. They were TC381 and TC1146 encoding the U2 small nuclear ribonucleoprotein A (snRNAP A) and pyruvate decarboxylase, respectively. Partial fragments from both genes were separately cloned into the tobacco rattle virus (TRV) RNA2 vector (Liu et al., 2002 ) for VIGS analysis (their sequences can be found in Supplemental Fig. S2). The search with siRNA Scan using both fragments as trigger sequences revealed several potential off-targets (Table III
). Clone TC381 shares contiguous identity of at least 21-nt identity to the following unique sequence entries in the current N. benthamiana database: CK286172, CK288691, CK289650, TC10748, and TC7796. These genes encode proteins that are unrelated to snRNAP A. Three of these potential off-targets, CK286172, CK288691, and TC10748, were selected for expression analysis by real-time qRT-PCR in TC381 VIGS-silenced plants. Expression levels of these genes, as well as that of the target gene TC381, were compared with their expression in the plants infiltrated with TRV1 (RNA1) + TRV2::00 (RNA2 empty vector). The EF-1 gene was used as the endogenous reaction control to normalize the relative quantity and expression of the  -tubulin gene was investigated to confirm the equal loading of total RNA. The results showed a greater silencing of TC10748 than the target gene TC381 and very little silencing (not statistically significant) for CK286172 and CK288691 genes (Fig. 5A
). The analysis was repeated twice with two different groups of plants and similar results were observed.
A similar scenario was found in TRV2::TC1146-infiltrated plants. Five unique EST entries share at least 21 nt of contiguous reverse complementary sequences to the cloned TC1146 fragment (Table III). They are CK282591 encoding a protein similar to the VPI/ABI3 family regulatory protein, CK292351 encoding a Ser carboxypeptidase II-2 precursor, and CK287535, CK296810, and TC8666 encoding three different members of the auxin efflux protein family. The expression levels of these genes and TC1146 in silenced plants were compared between the silenced plants and TRV-RNA1 + TRV2:00-infiltrated plants. The expression of target gene TC1146 was decreased to about 50% in TC1146-silenced plants, whereas among the five analyzed potential off-targets, CK287535, CK296810, and TC8666 were down-regulated to a greater extent than TC1146 (Fig. 5B). These three genes all belong to the auxin efflux protein family and have the same 22-nt reverse complementary sequences to TC1146. The expression level of CK282591 was slightly reduced, whereas there was no significant change in the expression of CK292351 in TC1146-silenced plants. These experiments were repeated twice with two individual silenced plants and the results were similar. In conclusion, some of the potential off-target genes were silenced to different degrees when VIGS was used to silence target genes of interest in N. benthamiana. Because we do not have null mutations of these target genes in N. benthamiana, we cannot rule out the possibility that the reduced transcripts of the off-target genes result from the reduction in the amount of target protein.
The use of RNA silencing/interference for suppressing gene expression has become a powerful and promising approach in gene function exploration and disease treatment in both plants and animals. Its successful application relies on specific and efficient silencing of particular genes or gene families. Exquisite specificity of RNAi through siRNA in animal cells has been supported by several studies (Tuschl et al., 1999 ; Elbashir et al., 2001; Chi et al., 2003; Semizarov et al., 2003). However, some contradictory reports indicated that siRNA used for RNA silencing can cause off-target suppression at both transcriptional and translational levels in animals. For example, siRNA causes silencing of unintended genes that lack complete sequence identity and sometimes induces nonspecific interferon responses in animals (Holen et al., 2002; Amarzguioui et al., 2003; Bridge et al., 2003; Saxena et al., 2003; Sledz et al., 2003; Jackson and Linsley, 2004; Scacheri et al., 2004). Recently, a computational study using the genome and transcriptome sequence data of Homo sapiens, Caenorhabditis elegans, and Schizosaccharomyces pombe suggested that the risk of transcriptional off-target silencing by siRNA is considerable in all of these organisms (Qiu et al., 2005). However, to date there is no experimental evidence in plants to show that off-target silencing of unrelated genes can occur as a result of nucleotide sequence similarity with siRNA.
Direct introduction of siRNA into plant protoplasts for PTGS was reported, but it is difficult to apply in intact plant tissues (Vanitharani et al., 2003
Statistically, longer siRNAs should be less likely to silence unintended genes by chance. Therefore, predicted off-target risk might be overestimated for siRNAs longer than 21 nt. However, because on average each predicted off-target for all plant species analyzed here has multiple off-target regions and each average off-target region is longer than the longest siRNAs reported in plants (Table I), the overall trend of off-target risk predicted from this study should be valid for longer siRNAs such as 22 to 26 nt. More importantly, because siRNAs of various lengths simultaneously coexist within the plant cell (Hamilton et al., 2002
Although our computational analysis showed a high risk of off-target gene silencing during PTGS in plants, the efficiency of off-target gene silencing should be the main factor that affects the functional analysis of a particular target gene. Results from our experimental analyses showed a varied reduction of expression levels of the potential off-targets in both Arabidopsis and N. benthamiana. The reduction ranges from none to a greater reduction than that of the target gene expression. The underlying mechanisms for this variation in expression levels of off-targets are not yet clear. Gene silencing efficiency is correlated with siRNA sequence-specific features (Khvorova et al., 2003
Short reverse complementary sequences (over 21 nt) were found in some completely unrelated genes in our computational analyses. In animals, siRNAs can simultaneously induce sequence-specific degradation of two endogenous mammalian transcripts oriented in opposite directions (Hu et al., 2004
The understanding of off-target silencing is crucial for accurate interpretation of gene function by PTGS. Our computational analyses with the genome and transcriptome sequences from 25 plant species showed a high risk of off-target gene silencing when a full-length sequence of each transcript entry in the datasets was used as an RNAi trigger. This off-target gene silencing risk was confirmed by our experimental analysis with both RNAi transgenic Arabidopsis lines and N. benthamiana plants infected by VIGS constructs. So far, the contribution of silenced off-targets to the silencing phenotype is not known and needs to be analyzed in exploring target gene function. For example, although the BTI1 RNAi lines had off-target gene silencing, the transformation recalcitrant phenotype of these lines is not in question because it was confirmed by null mutant lines of the target gene (Hwang and Gelvin, 2004 ). Nevertheless, no approach used to inactivate gene function is free from potential problems, and the reality of off-target silencing does not override the enormous potential of RNAi as a tool for individual or high-throughput studies of gene function. On the other hand, off-target silencing in PTGS provides an advantage in overcoming gene functional redundancy and in its potential to be applied in heterologous gene silencing across species. Hopefully, a further understanding of the molecular mechanisms of RNAi will add more restraining rules for off-target prediction and reveal possible approaches to overcome off-target effects for target specificity. At this point, our siRNA Scan should provide an extremely useful tool in searching for the potential off-targets of an RNAi trigger of interest and will also help to design more specific RNAi triggers and appropriate controls in experiments.
Datasets Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa subsp. japonica) genome mRNAs were downloaded from TIGR (http://www.tigr.org). Gene Indices for 25 plant organisms were downloaded from TIGR. The Gene Ontology (GO) database was provided by the GO Consortium (http://geneontology.org). Arabidopsis gene family information and GO annotation were downloaded from TAIR (http://www.arabidopsis.org). Protein domain data (http://pfam.wustl.edu) was also downloaded for off-target function analysis.
The gene transcript sequence dataset for each organism was searched against itself for contiguous
Arabidopsis (ecotype Columbia) and BTI1 RNAi transgenic lines (Hwang and Gelvin, 2004
The sequences of TC381 and TC1146 were obtained from the TIGR database of N. benthamiana. cDNA fragments, including the sequences with >20-nt continuous identity or complementarity to their potential off-target genes, were amplified by RT-PCR. Primers for the amplification of specific TC381 and TC1146 fragments are shown in Supplemental Table S2. About 5 µg total RNA from N. benthamiana leaves were used for RT at 42°C with NNpoly(dT)20 as the primer for 2 h. The RT product was used for PCR amplification for TC381 and TC1146 fragments, respectively, in a PTC-100 Peltier thermal cycler (M.J. Research). The PCR products were cloned into the pGEM-T-easy vector (Promega). Clones with inserts that are identical to the area in the target genes were amplified by PCR with primers that contain attb recombination sequences adapted to the previous primer pairs. PCR products were purified, sequenced, and cloned into the pTRV2 VIGS vector using the GATEWAY cloning system with the protocol from the manufacturer (Invitrogen). The recombinant plasmids were named TRV2::TC381 and TRV2::TC1146.
Agrobacterium strain GV2260 containing pTRV1, TRV2::00, TRV2::TC381, and TRV2::TC1146 were grown in an incubator at 28°C on Luria-Bertani broth with 10 µg L–1 rifampicin and 50 µg L–1 kanamycin for 2 d. Inoculum was prepared with the protocol published previously (Ryu et al., 2004
For Arabidopsis, total RNA was isolated from leaf tissues using TRIzol reagent (Invitrogen), followed by RNase-free DNase treatment (Promega). First-strand cDNA was synthesized with the Omniscript RT kit (Qiagen) using oligo(dT)15 according to the manufacturer's instructions. For qRT-PCR, real-time experiments were conducted in an ABI PRISM 7000 sequence detection system (Applied Biosystems), using the intercalation dye SYBR Green I as a fluorescent reporter. Quantification of PCR products was performed via a calibration curve procedure using EF-1 For N. benthamiana, total RNA from each plant at 15 d postinfiltration was extracted using TRIzol reagent with the protocol provided by the manufacturer (Molecular Research Center). First-strand cDNA was synthesized with 2 µg of total RNA using primer NNpoly(dT)20 as described above. Semiquantitative RT-PCR was performed with the modified program from the one described in "Plasmid Construction" with annealing temperature at 60°C and 20 cycles for TC381, 33 cycles for TC1146. The primer sequences are listed in Supplemental Table S2. Further real-time qRT-PCR analysis for each comparison was done with the total RNA of one TRV2::00-infiltrated and one recombinant clone-infiltrated plant, as described above for Arabidopsis samples. The analysis was repeated twice with two different groups of plants for each combination. The primer sequences used for real-time qRT-PCR are listed in Supplemental Table S3.
Data were subjected to ANOVA using Student's t test software of Excel 2003 with 98% confidence.
The following materials are available in the online version of this article.
We thank Dr. Stan Gelvin and Dr. Hau-Hsuan Hwang for sending us the Arabidopsis seeds of BTI1 RNAi lines and the bti1-2 T-DNA mutant; Dr. S.P. Dinesh-Kumar for providing GATEWAY-ready TRV-VIGS vectors; Dr. Choong-Min Ryu for help with infiltrations and discussions; and Dr. Elison Blancaflor, Dr. Stan Gelvin, and Dr. Jianzhong Liu for reviewing this manuscript. Received May 8, 2006; accepted August 7, 2006; published August 18, 2006.
1 This work was supported by The Samuel Roberts Noble Foundation. 
2 These authors contributed equally to the paper. The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Kirankumar S. Mysore (ksmysore{at}noble.org).
[W] The online version of this article contains Web-only data.
[OA] Open Access articles can be viewed online without a subscription. www.plantphysiol.org/cgi/doi/10.1104/pp.106.083295 * Corresponding author; e-mail ksmysore{at}noble.org; fax 580–224–6692.
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TOP
ABSTRACT
RESULTS
21-nt region of identity or reverse complementary identity to the trigger as off-targets. The continuous identical or reverse complementary sequence to a trigger region in an off-target is defined as an off-target region. 
