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1 Introduction

Genus Begomovirus belonging to family Geminiviridae subgroup III (bean golden mosaic virus group) is the largest and most devastating group of plant viruses. Begomoviruses commonly found in tropical, subtropical, and warm climates, infecting mainly dicot crops, are transmitted by Bemisia tabaci (Gennadius) also known as whiteflies. These whiteflies suck the plant sap and secrete a sugary, sticky liquid that attracts several fungi and other pests. These pests in turn infest fields of crops and cause huge losses to farmers. Once these viruliferous whiteflies, i.e., carrying begomovirus, settle on leaves, they ingest phloem sap of plants and transmit virus resulting in curling, distortion, and yellowing of leaves with reduced overall plant growth.

Non-enveloped virions are 38 nm long and 22 nm in diameter, while the enveloped forms have geminate twinned appearance with icosahedral symmetry. The capsid contains 22 pentameric capsomeres, which are made up of 110 capsid proteins (CP) with single circular ssDNA in each geminate particle. The begomovirus genome is present in either a monopartite or a bipartite form. Monopartite begomoviruses have only DNA-A as a genomic component, whereas bipartite begomoviruses contain DNA-A and DNA-B, and both the DNAs are equally required for complete systemic infection. Both the components A and B are approximately 2.6 Kb in size, whereas the satellites may have genomic component ranging from 700 bp to 1.5 kb. The coding regions or open reading frames (ORFs) are present over ssDNA genome in both the virion (+) and complementary (−) sense strands. DNA-A comprises six ORFs in sense and complementary orientation. DNA-A virion (+) orientation comprises two ORFs, i.e., AV1 and AV2, which encode coat protein (CP) and precoat protein, respectively (Padidam et al. 1996), while complementary (−) sense has four ORFs, namely, AC1, AC2, AC3, and AC4. AC1 encodes very important replication-associated protein required for viral DNA replication (Hanley-Bowdoin et al. 1999), AC2 and AC3 encode transcription activator protein (TrAP) and replication enhancer protein (REn), respectively (Sunter et al. 1990; Sunter and Bisaro 1992), and AC4 is mainly reported to counteract against posttranscriptional gene silencing (Vanitharani et al. 2003; Hanley-Bowdoin et al. 2013). DNA-B component contains two proteins, namely, BC1 in sense (+) strand which encodes movement protein (MP) and BV1 in sense (−) strand encoding nuclear shuttle protein (NSP). Both the DNA components contain a common region, acting as origin of replication, and help in bidirectional transcription. On the other end, few monopartite begomoviruses such as Tomato yellow leaf curl virus (TYLCV), Tomato leaf curl virus (ToLCV), Tomato yellow leaf curl Sardinia virus (TYLCSV), and Ageratum yellow vein virus (AYVV) comprise single genomic component equivalent to DNA-A that encodes on an average six proteins, Rep, TrAP, CP, REn, C4, and V2 (Begomovirus 2017).

Monopartite begomoviruses are often found to be present along with satellite (incomplete defective genomic components) components. In this case the DNA-A component acts as a helper DNA and provides machinery to the satellite molecules for replication and transcription of its ORF. Three types of satellite DNAs associated with begomoviruses are alphasatellite (α), betasatellite (β), and deltasatellite (δ). α- and β-satellites have circular ssDNA with single ORF that encodes alpha-Rep and βC1, respectively. Both coding regions are highly conserved and contain adenine-rich sequence regions: a hairpin containing the conserved nonanucleotide region (TAATATTAC). These α- and β-satellites coinfect with helper DNA and cause disease symptoms and devastating diseases (Briddon et al. 2003; Zhou 2013). The α-satellites have no obvious function in symptom development but to help in β-satellite replication. However, βC1 is a symptom determinant, i.e., it can suppress both transcriptional and posttranscriptional gene silencing and thus antagonize plant defense mechanisms (Cui et al. 2004, 2005). The begomoviruses and their associated satellites cause economically significant diseases in a wide range of crop plants worldwide. The δ-satellite molecules share similarity to β-satellites except that they have one more hairpin loop-containing region and are mostly noncoding in nature (Lozano et al. 2016).

Once present inside their host tissue, these viruses impose an imminent threat and are very difficult to control even through various approaches such as physical, mechanical, chemical, or even biological. Management of virus infection in commercial crops greatly affects total agricultural yield, farmers, horticulturist, etc. The control measures are not so easy as virus-infected diseases are not amenable to direct methods of intervention. Symptoms of virus-infected crops can occur right from early to late stages of plant development depending upon virus inoculum load and vector population. The first step in control of begomovirus is to stop their transmission through whiteflies by using mechanical barriers and biological predators of Bemisia sp. The chemical approaches though sound very attractive, but they result in heavy metal pollution in environment due to slow degradation rate of most insecticides and ever-increasing resistance against them. Considering these above facts, various transgenic approaches using pathogen-derived resistance, antisense RNA and siRNA, and other genomic intervention strategies have emerged as a necessary tool to develop begomovirus-resistant crops for sustainable crop production.

2 RNA Interference (RNAi)

Discovery of small (20–30 nt) noncoding RNA molecule is one of the most important scientific breakthroughs in the past 20 years and has contributed to a significant advancement in research areas under molecular biology. Andrew Z. Fire and Craig C. Mello shared the Nobel Prize in Physiology or Medicine in 2006 for their work on RNA interference (RNAi) (Napoli et al. 1990; Cogoni et al. 1996; Fire et al. 1998). RNAi is a novel gene regulatory mechanism in which small RNAs (sRNAs) suppress transcription via degradation of target mRNA in a sequence-specific manner earlier known as co-suppression. The suppression which occurs at transcriptional level is known as posttranscriptional gene silencing (PTGS), whereas at chromatin level, it is known as transcriptional gene silencing (TGS). The recent information on translational repression of target mRNAs suggests that even partial complementarity of miRNAs leads to translational suppression of mRNA transcript in mammals (Meister and Tuschl 2004). PTGS involves production of 19–30 nt long sRNAs, produced from their lengthy precursor dsRNAs. These dsRNA precursors interact with silencing machinery consisting of Argonaute (AGO), Dicer, and other associated proteins of RNA-induced silencing complex (RISC). This interaction with RISC results into formation of 21–23 nt long sRNAs, and one of the strand known as guide RNA gets loaded onto RISC complex. This guides RNA-RISC complex and then binds to their target mRNA site in a homology-dependent manner resulting in cleavage of target site into smaller fragments incapable of any function. Thus, a posttranscriptional gene silencing phenomenon occurs resulting in RNA silencing (Hamilton and Baulcombe 1999; Matranga et al. 2005; MacRae et al. 2006; Siomi and Siomi 2009).

Based on the origin and nature of precursor molecule and their biological function, the sRNAs can be categorized into microRNAs (miRNAs), small interfering RNA (siRNAs), and piwi RNAs (piRNAs). piRNAs are the largest (26–31 nt) class of small noncoding RNA (sncRNA) molecules (Molecular biology select 2006; Seto et al. 2007), whereas the miRNAs and siRNAs are smaller counterparts (19–24 nt). These small regulatory RNAs are present in eukaryotes only and are derived from dsRNA; however, piRNAs are derived from long single-stranded precursor molecules (Lu et al. 2005). The biogenesis of these piRNAs is distinct from that of other sRNAs and is hypothesized to be either based on piRNA phasing or a ping-pong mechanism of generation (Brennecke et al. 2007). Both the groups of regulatory RNAs need different subsets of effector proteins, i.e., siRNA and miRNA need AGO proteins, whereas piRNA interacts with piwi proteins to mediate epigenetic and posttranscriptional gene silencing (Carmell et al. 2002; Carthew and Sontheimer 2009; Siomi and Siomi 2009; Siomi et al. 2011; Burgess 2013). Being endogenous in origin, miRNA regulates expression of host genes, whereas the exogenous origin of siRNAs allows them to protect genome integrity of host from foreign or invasive nucleic acids derived from viruses, transposons, or transgenes. In Drosophila, the endogenous siRNAs have been shown to provide resistance against Drosophila transposons; hence, the siRNAs can have both types of biogenesis mechanisms inside hosts (Chung et al. 2008; Czech et al. 2008). Exogenously supplied synthetic siRNAs or endogenously produced siRNAs are reported to regulate the expression of endogenous genes, e.g., in mice and various cell lines (Watanabe et al. 2008; Stein et al. 2011).

Transgenic approaches to develop virus-resistant plants involve introduction of viral protein-coding sequences conferring pathogen-derived resistance (PDR). Usually the mRNAs targeted are those involved in the translation of capsomeres, viral replication, suppression of host immune response, and expression of RNA-dependent RNA polymerases (RdRPs) (Abel et al. 1986; Hong et al. 1995; Ahlquist 2002). The most popular transgenic plant developed using PDR strategy targeting viral coat protein was the Hawaiian papaya resistant against Papaya ringspot virus (Fitch et al. 1992; Ferreira et al. 2002; Gonsalves et al. 2004). The papaya transgenics thus produced saved a huge amount of papaya produced in Hawaii thus helping farmers to incur financial gains from its export. Now we have the technical know-how about the exact mechanism of RNAi conferring virus resistance in plants and realize that antisense RNA technology was nothing but a step into the RNAi realms. In this chapter we intend to propose a strategy to develop a generic resistance based on siRNA technique against begomoviruses infecting various crops.

3 RNAi-Based Strategies

RNAi vectors consisting of inverted repeats of siRNAs in sense and antisense orientation under the control of a strong promoter have produced mixed results in conferring resistance against begomoviruses. The precursor regions of putative siRNAs are introduced into host plants that provide significantly effective resistance against begomovirus challenge in the first generation. Eventually, the efficacy of resistance is lost or diluted as further progenies are studied. This is due to recombination, higher than critical inoculum of virus in the beginning, or due to the uncontrolled plant growth conditions (Ghoshal and Sanfaçon 2015). Though various strategies are reported for construction of RNAi vectors (Hirai and Kodama 2008), the two most popular strategies for RNAi experiments are inverted repeats containing short hairpin construct (shRNA) and artificial microRNA (amiRNA) harboring target siRNA within an miRNA backbone, thus acting like a natural miRNA (Zhou and Luo 2013).

Several studies have reported siRNA approach as a key tool to develop virus-resistant crops, e.g., transgenic Nicotiana benthamiana using antisense RNA technique designed against C1 (recently known as AC1) encoding Rep protein mRNA of Tomato yellow leaf curl virus (TYLCV). This transgenic tobacco line expressing C1 antisense RNA shows effective resistance to TYLCV through at least two generations of progeny (Bendahmane and Gronenborn 1997). A study has reported a transgenic tobacco resistant to Cotton leaf curl virus (CLCuV). CLCuV is a begomovirus that causes severe leaf curl symptom leading to overall economic losses to farmers in Asian subcontinent. This transgenic tobacco carries various siRNA fragments derived from CLCuV. The resistance conferred by these fragments is sustained for up to 120 days upon exposure to viruliferous whiteflies from T1 to T3 generations (Asad et al. 2003) suggesting it to be an effective resistance in case the occurrence of whiteflies overlaps this time period and thus giving a sustainable resistance approach.

Further, as one step ahead, black gram (Vigna mungo) infected with Vigna mungo yellow mosaic virus (VMYMV) is reported to recover successfully after expressing dsRNA against promoter region of viral DNA-A and established the fact that DNA of a replicating virus can also be an effective target of transcriptional gene silencing (Pooggin et al. 2003). Another study reported the recovery of Potato spindle tuber viroid (PSTVd) infected tomato plants using RNAi via sequence-specific degradation of viroid (Sano and Matsuura 2004). Zhang et al. (2005) developed African cassava mosaic virus (ACMV) resistant cassava transgenics using antisense RNA technology by targeting viral mRNAs of Rep (AC1), TrAP (AC2), and REn (AC3).

Thus, various siRNA-based resistance strategies were effective in controlling whitefly-mediated infection of begomoviruses, yet the transfer of resistance across generations of transgenic progenies is not effective probably due to dilution of siRNA expression. Therefore, there is a need to develop effective strategy for resistant transgenic crops that are able to withstand viral attacks through many generations irrespective of initial viral titer.

Several geminiviral proteins with silencing suppressor activities have been identified which makes them potential target for RNA interference-based resistance, e.g., Citrus tristeza virus (CTV) resistant transgenic Mexican lime was developed by posttranscriptional gene silencing of p23, a silencing suppressor of Citrus tristeza virus (Fagoaga et al. 2006). In another interesting study, designing siRNA construct was reported for the first time, targeting v1 gene encoding coat protein (CP) of Tomato yellow leaf curl virus (TYLCV) (Zrachya et al. 2007). The transgenic tomato plants expressing siRNA did not develop disease symptoms 7 weeks postinoculation with the virus, while non-transgenic control plants developed disease symptoms within 2 weeks postinoculation. Hence, this strategy confers resistance to the TYLCV in transgenic plants and enables a good yield of flowers and fruit.

In case of cassava crop, Patil and coworkers developed RNAi-mediated resistance against different isolates of Cassava brown streak virus (CBSV) and Cassava brown streak Uganda virus (CBSUV) causing severe cassava brown streak disease (Patil et al. 2011). In this strategy, CP gene regions of the two Potyvirus species were targeted; the region consists of N-terminal 397 nt and C-terminal 491 nt constituting the full-length coat protein (FL-CP) gene of CBSV and CBSUV. The transgenic tobacco homozygous line expressing FL-CP region showed significant resistance (approximately 85% plants were completely resistant) against CBSUV-[UG:Nam:04] challenge, while the N-terminal and C-terminal expressing transgenic tobacco lines showed resistance in decreasing order. Therefore, the RNAi strategy appeared to be effective in case of cassava-infecting Potyvirus species.

Using a novel approach, designing siRNA against the most conserved region among coat protein (AV1) and replicase (AC1) genes of different isolates of geminiviruses infecting Papaya leaf curl virus (PLCV) and Tomato leaf curl virus (TLCV) was done to address generic resistance by Saxena et al. (2011). Subsequently, Saxena et al. (2013) proposed an improvised strategy to target three important genes, i.e., AV2, AC2, and AC4, which suppress plants’ RNA silencing machinery. In this study, an approach to control begomovirus-infecting papaya crop was given by designing siRNA against these three suppressors using bioinformatics tools. Studies have also reported that these viral silencing suppressors may regulate functioning of the host plant with reference to resistance against the viruses by interfering with regulatory activity of some miRNAs in host gene expression (Kasschau et al. 2003; Chen et al. 2004; Bisaro 2006).

3.1 Artificial microRNA (amiRNA)

Structurally, amiRNAs span 21 nt length, generally designed by manipulation of seed region of mature miRNA sequences within double-stranded pre-miRNA. These artificial sRNAs are designed to target one or more endogenous genes in an organism or a cell line; amiRNA precursors are generated either by PCR overlapping methods or by substitution of a natural stem loop for artificial one with restriction sites between upstream and downstream regions in the backbone of natural miRNA (Liang et al. 2012). The amiRNA sequence selection requires that there should be no mismatches within seed region (9–11 bp) though one or two mismatches are allowed near 18–21 nt positions. The hybridization energy of target and amiRNA should also favor their strong interaction leading to efficient silencing (Alvarez et al. 2006). The above parameters are not the only factors required for amiRNA-mediated silencing. Various miRNAs have been employed to introduce amiRNAs in Arabidopsis thaliana, e.g., miR159a, miR167b, miR169d, miR171a, miR172a, and miR319, and rice, e.g., miR528 and miR395. The use of miRNA backbone is limited, and not one miRNA can be employed for all types of silencing. Therefore, careful selection of miRNA backbone is essential for amiRNA-based strategy to be effective in viral RNA suppression (Khraiwesh et al. 2008; Tiwari et al. 2014; Carbonell et al. 2014).

The efficacy of target RNA silencing through amiRNA technology depends not only on the nature of amiRNAs but also on the accessibility of the 3′ untranslated region (UTR) of target mRNAs. The accessibility in turn depends upon the local secondary structure of the target mRNA, e.g., the tRNA-like structure found within the 3′UTR region of cucumber mosaic virus (CMV) was found to restrict target site access thus inhibiting amiRNA-RISC-mediated silencing of putative target viral RNA (Duan et al. 2008). Therefore, the target site accessibility governed by local structure at 3′UTR is as important as sequence specificity, and the target site cleavage is greatly dependent upon the interaction and thermodynamics of the small RNA-programmed RNA-induced silencing complex (siRISC) (Tafer et al. 2008; Pratt and MacRae 2009).

The concept of amiRNA with an aim to develop virus-resistant transgenic Arabidopsis plants was validated by modifying miR159a precursor backbone. This amiRNA backbone targets two gene silencing suppressors of viral mRNA sequence; one is P69 of Turnip yellow mosaic virus (TYMV) and the other is HC-Pro of Turnip mosaic virus (TuMV). Transgenic A. thaliana plants expressing amiR-P69159 and amiR-HC-Pro159 were resistant to TYMV and TuMV, respectively. The transgenic plants carrying the amiR-P59169 and amiR-HC-Pro159 within the same construct were resistant against both the viruses (Niu et al. 2006). A comparative study was conducted to evaluate efficacy of amiRNA and short hairpin RNA (shRNA) construct targeting viral silencing suppressor protein 2b derived from cucumber mosaic virus (CMV). Here, 2b gene expression was inhibited in a much more effective manner by amiRNA strategy when compared to the shRNA construct in transient assays (Qu et al. 2007). Therefore, the amiRNA technique has a potential to provide an effective and specific resistance against viral suppressors of plant RNAi machinery.

amiRNAs were studied in Arabidopsis, rice, wheat, maize, Chlamydomonas reinhardtii, etc. where they actually function like natural miRNAs (Schwab et al. 2006; Alvarez et al. 2006; Qu et al. 2007; Warthmann et al. 2008; Molnar et al. 2009; Yan et al. 2012; Fahim et al. 2012, Fahim and Larkin 2013; Xuan et al. 2015) (refer Table 8.1). These small regulatory RNAs based on miRNA precursors to express artificial amiRNAs are capable enough to induce silencing of putative target gene and confer virus resistance in plants.

Table 8.1 Different RNAi strategies against Begomovirus
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Studies discussed above were successful experiments where the construction and introduction of artificial miRNA precursor has been one of the most effective strategy to develop broad-spectrum resistance against multiple regions of viral genes at a time, e.g., miRNA construct expressing multiple artificial miRNAs (amiRNAs) against various viral genomic regions (Bucher et al. 2006). The advantage with amiRNA strategy is that it is easier to optimize amiRNA sequences for broad-spectrum targeting and has minimal off-target effect, i.e., enhanced specificity with high efficacy.

3.2 In Silico Strategy for Designing Effective siRNA Target in Plants

In silico analysis of target sequence is a critical step in the development of an effective strategy against begomoviruses. The selection parameter evaluation of siRNA should be performed in such a way that ensures optimal conditions and effective targeting of the gene of interest. The previously suggested guidelines are subdivided into first-, second-, and third-generation rules that have laid the foundation for the modern and most advanced parameters followed nowadays (Liu et al. 2012).

3.2.1 General Guidelines for a Potent siRNA Selection

The siRNA selection criterion is derived from popular studies and algorithms, which tried to validate parameters for potent siRNA prediction (Freier et al. 1986; Zecherle et al. 1996; Tuschl et al. 1999; Elbashir et al. 2002; Yu et al. 2002; Harborth et al. 2003; Khvorova et al. 2003; Reynolds et al. 2004; Ui-Tei et al. 2004; Jackson et al. 2006; Klingelhoefer et al. 2009; Wang et al. 2010; Liu et al. 2012). The following is the summary of various parameters based upon the above studies that control efficacy and specificity of the siRNA thus designed:

  1. 1.

    The target site must lie deep inside coding sequence or open reading frame (ORF), generally advised to start from 100 bp from the initiation codon and avoid the last 100–200 bp region.

  2. 2.

    Regions of high homology, i.e., 15–20 bp, tend to be more specific in silencing the gene expression of target mRNA.

  3. 3.

    Targets with polymorphic loci must be avoided.

  4. 4.

    Isoforms tend to decrease specificity; thus, the regions that are amenable to alternative splicing should be avoided.

  5. 5.

    The presence of secondary structure, i.e., stem loops in the siRNA sequence, decreases the RISC accessibility and hinders the formation of RISC-siRNA complex.

  6. 6.

    A siRNA antisense strand with low 5′ end thermodynamic energy is favorable as it eases the loading of RISC complex. Therefore, the sense and antisense strands should have a difference in binding energy.

  7. 7.

    Target sites with low GC content, i.e., less than 50%, have higher potential to be processed as functional siRNA regions.

  8. 8.

    The siRNA designed against target regions should not be having off-targets, i.e., seed region homology, with other functional mRNA sequences of the host and associated organisms, e.g., plants and their pests (helpful as well as harmful). It is also to be considered that the off-targets if present should not be a functional component of the upstream pathway or an important regulator of plant development and functions which might lead to nonspecific and insufficient handling of miRNA-like off-target effects (Schultz et al. 2011).

Elsewhere, useful guidelines for efficient designing of amiRNA-based backbone have been proposed (Vu and Do 2016). The guidelines intend to improve amiRNA design, backbone, efficiency, and specificity. However, it is impossible to design an amiRNA that fully mimics the natural miRNA function, specificity, and efficacy.

Apart from abovementioned parameters, the siRNA datasets, efficacy prediction models, and algorithms provide a useful tool to inspect the siRNA prior to its introduction into a plant. This helps to save time, resources, and labor involved in the process and enhances the probability of success.

3.2.2 General Strategy for siRNA Designing

The Begomovirus replicates by forming double-stranded intermediate after entering the host nucleus. The replication starts by replication-associated protein, and here, the virus genome might undergo recombination with plant genome or any other virus present in the vicinity (in case of mixed infection). This gives rise to genetic variations that help begomoviruses to evade the siRNA machinery of host. In present context, we have seen that the begomoviruses impose an imminent threat to global crop production due to evolution of genome, thus giving rise to genetic diversity which cannot be handled by a specific siRNA approach. It is however possible to generate some resistance if we target the genetic diversity by choosing conserved sequences to design siRNAs. This strategy will help in providing a solution to more than one isolate of same species or even phylogenetically similar begomovirus species. A study proposed that if we can find out the siRNA-generating “hot spots” in the begomovirus genome, then it is quite possible to target genera of begomoviruses (Sharma et al. 2015). This seems quite possible, as an in silico analysis of various leaf curl-causing begomoviruses has yielded regions ranging from 88% to 100% conservation among phylogenetically similar isolates around the world (unpublished data).

Here we present a strategy for efficient siRNA designing that considers and fulfills the latest guidelines and rules (Fig. 8.1).

STEP 1::

Sequence retrieval from various databases such as NCBI (https://www.ncbi.nlm.nih.gov), EMBL (http://www.ebi.ac.uk/embl.html), or Swiss-Prot (http://web.expasy.org/docs/swiss-prot_guideline.html).

STEP 2::

Multiple sequence alignment using popular tools such as Clustal X (http://www.clustal.org/clustal2), Clustal Omega (http://www.clustal.org/omega), T-COFFEE (http://www.tcoffee.org/), and MUSCLE (http://www.ebi.ac.uk/Tools/msa/muscle). In order to find out conserved region among different viral isolates, we prefer multiple sequence alignment using software package MEGA 6.0 (http://megasoftware.net/mega.php).

STEP 3::

Selection of conserved regions (85–100%) (Fig. 8.2).

STEP 4::

Use of siRNA prediction tools, i.e., pssRNAit (http://plantgrn.noble.org/pssRNAit/), for prediction of siRNA target regions. Here one has to choose species according to the model being used for conducting silencing experiments. The software accordingly selects the cDNA/transcript library database for off-target effect-based analysis.

STEP 5::

Analyze the parameters for the most effective siRNA-generating region. This process requires “hit and trial” approach. It is important to vary the parameters according to the sequence under study and refine them in order to achieve maximum specificity and efficacy (Figs. 8.3 and 8.4).

STEP 6::

Choose siRNAs with minimal off-target score (Fig. 8.5).

STEP 7::

Select hot spot regions, i.e., conserved regions producing more than two efficient siRNAs, fulfilling all rules and parameters.

Fig. 8.1
figure 1

Outline of the siRNA designing strategy

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Fig. 8.2
figure 2

Multiple sequence alignment of the Begomovirus sequences using MEGA 6 package. Selection of conserved sequence regions

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Fig. 8.3
figure 3

Designing siRNAs using pssRNAit online tool available with various parameters

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Fig. 8.4
figure 4

Details of the pssRNAit result providing various efficiency scores for a predicted siRNA (http://plantgrn.noble.org/pssRNAit/)

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Fig. 8.5
figure 5

Details of the predicted off-targets for one of the siRNA

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Several studies have introduced large inverted hairpin siRNA construct in N. benthamiana without prediction of siRNAs and yet found some success in begomovirus intervention just on the basis of conservation criteria (Bucher et al. 2006; Medina-Hernandez et al. 2013). Few studies have proposed to incorporate a conserved nonanucleotide (hairpin loop) region along with large inverted repeat fragments for RNAi-based resistance due to its conserved nature (Wesley et al. 2001; Khatoon et al. 2016). Therefore, the strategy of introducing hot spots rather than a single specific siRNA has an advantage over the later strategy.

4 Conclusion

RNAi being a popular tool to downregulate the gene expression at posttranscriptional level has helped in the development of various strategies that succeeded in conferring some amount of resistance against begomoviruses. Yet, the suppression of resistance is imminent in case of begomoviruses due to their recombination-dependent replication and RNAi suppression components that antagonize the plant immune response and bypass the siRNA-based silencing. Therefore, no strategy could be a complete solution for the global problem of begomovirus diseases; still, the generic solution for a particular crop in a specific region could be a possible solution until the virus isolate evolves itself into a new recombinant. Here, we have discussed few aspects of RNAi and the basis of siRNA-based strategies employed in the past in an attempt to develop begomovirus-free transgenic crops for sustainable food resources and global food security. The strategy presented here may not be the ideal solution but provides a perspective for researchers to pursue research in the very area in order to develop generic resistance against begomoviruses.