pssRNAit: A Web Server for Designing Effective and Specific Plant siRNAs with Genome-Wide Off-Target Assessment

Abstract

We report an advanced web server, the plant-specific small noncoding RNA interference tool pssRNAit, which can be used to design a pool of small interfering RNAs (siRNAs) for highly effective, specific, and nontoxic gene silencing in plants. In developing this tool, we integrated the transcript dataset of plants, several rules governing gene silencing, and a series of computational models of the biological mechanism of the RNA interference (RNAi) pathway. The designed pool of siRNAs can be used to construct a long double-strand RNA and expressed through virus-induced gene silencing (VIGS) or synthetic transacting siRNA vectors for gene silencing. We demonstrated the performance of pssRNAit by designing and expressing the VIGS constructs to silence Phytoene desaturase (PDS) or a ribosomal protein-encoding gene, RPL10 (QM), in Nicotiana benthamiana We analyzed the expression levels of predicted intended-target and off-target genes using reverse transcription quantitative PCR. We further conducted an RNA-sequencing-based transcriptome analysis to assess genome-wide off-target gene silencing triggered by the fragments that were designed by pssRNAit, targeting different homologous regions of the PDS gene. Our analyses confirmed the high accuracy of siRNA constructs designed using pssRNAit The pssRNAit server, freely available at https://plantgrn.noble.org/pssRNAit/, supports the design of highly effective and specific RNAi, VIGS, or synthetic transacting siRNA constructs for high-throughput functional genomics and trait improvement in >160 plant species.

Figure 1.

Workflow depicting the design of GST for VIGS/siRNAs by pssRNAit pipeline.

Figure 2.

Input interfaces of pssRNAit. Users can paste mRNA sequences in FASTA format (A), select plant species (B), and exclude toxic and non-specific sequence motifs (C) for siRNA design.

Figure 3.

Screenshots of a sample output. A, The query interface for adjusting parameters to filter analysis results. B, A list of output GST candidates for VIGS. C, A list of output siRNA candidates.

Figure 4.

Silencing efficiency of pssRNAit-designed RNAi fragments against the PDS gene in N. benthamiana. A, Phenotypic response of minimum (Min OT)/maximum (Max OT) off-target regions in comparison with other VIGS construct. B, Effectiveness of the silencing as assessed by the number of leaves that turned white versus the number of green leaves. C, Percent reduction in chlorophyll content compared to the GFP fragment used as a control. A minimum of five leaves from each plant and 10 plants were used to assess efficiency. Bars represent the mean ± se. Different lowercase letters on data points indicate a significant difference (P < 0.05) between the control and PDS-silenced plants determined by two-way ANOVA with Tukey's HSD mean-separation test.

Figure 5.

Expression analysis of off-target genes in N. benthamiana plants expressing maximum off-target (MaxOT), minimum off-target (MinOT), VIGS-SGN, and pssRNAit predicted RNAi constructs in comparison with the vector control (VC) and NbPDS fragment. A and B, Expression level of off-target genes when using the minimum (A) and maximum (B) off-target construct. C and D, VIGS-SGN predicted (C) and pssRNAit–predicted (D) constructs. The off-target genes were identified using pssRNAit and the levels of expression were assessed using RT-qPCR. In each case, a minimum of three biological replicates were used for expression analysis. Bars represent the mean ± se. Different lowercase letters on data points indicate a significant difference (P < 0.05) between PDS and the respective minimum or maximum off-targets, determined by two-way ANOVA with Tukey's HSD mean-separation test.

Figure 6.

VIGS constructs and their effectiveness in silencing the PDS gene in N. benthamiana. A, Schematic representation of the VIGS fragments located on the NbPDS gene, based on the webserver prediction. Ps series VIGS fragments and TRV2::NbPDS pssRNAit fragments were predicted using pssRNAit. The TRV2::NbPDS SGN VIGS fragment was designed using the VIGS SGN tool. B, Expression analysis showing silencing of NbPDS in N. benthamiana VIGS plants. C, Phenotype of the silenced plants. The top three leaves were photographed and assessed for effectiveness. D, Effectiveness of the silencing as assessed by the number of leaves that turned white versus the number of green leaves. E, Percent reduction in chlorophyll content in silenced plants compared to the GFP fragment as a control. Average values of three biological replicates were used to generate bar graphs and experiments were repeated three times with similar results. Error bars indicate the se. Different letters above the bars indicate a significant difference from two-way ANOVA at P < 0.05 with Tukey’s HSD mean-separation test (α = 0.05).

Figure 7.

Differential expression of genes from VIGS plants. A, Venn diagrams showing the number of genes that are up- or downregulated in VIGS N. benthamiana plants. B, Heat map of transcript levels of off-target genes identified in respective VIGS plants. At right are the genes predicted to be off-targets for the fragments used for VIGS. RNA-Seq analysis was carried out from the 3-week-old VIGS plants with three biological replicates. The expression values were transformed into Z-scores (across each row).

Figure 8.

Expression analysis of off-target genes of VIGS PDS fragment. Off-target genes were identified using pssRNAit, and level of expression was assessed using RT-qPCR. Average values of three biological replicates were used to generate bar graphs. Error bars indicate the se. Different letters above the bars indicate a significant difference from two-way ANOVA at P < 0.05 with Tukey’s HSD mean-separation test (α = 0.05).

Figure 9.

Target and off-target gene expression analysis from whole-genome RNA-seq analysis from the QM/RPL10 gene silenced N. benthamiana plants. A, Nucleotide sequence of the NbQM gene used for VIGS in N. benthamiana. B, Predicted off-targets using pssRNAit for the NbQM gene. C, Niben 101Scf04436g06002.1 is a target gene showing 50% downregulation in QM-silenced plants relative to the vector control (VC). Niben101Scf03978g07013 and Niben101scf08047g03019 are predicted off-targets, the former of which was not detected in either sample, whereas Niben101scf08047g03019 showed a 50% reduction in expression. As predicted, the expression of off-target sites is reduced in the QM-silenced plants, indicating that pssRNAit could identify off-targets precisely. Error bars indicate the se from three biological replicates. Different letters above the bars indicate a significant difference from two-way ANOVA at P < 0.05 determined by Tukey’s HSD mean-separation test (α = 0.05).