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Transcriptome Analysis and Systemic RNAi Response in the African Sweetpotato Weevil (Cylas puncticollis, Coleoptera, Brentidae)

  • Katterinne Prentice,

    Affiliations Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, B-9000 Ghent, Belgium, Department of Molecular Biotechnology, Faculty of Bioscience Engineering, Ghent University, B-9000 Ghent, Belgium, International Potato Center (CIP), Genomics and Biotechnology Program, Nairobi 00603, Kenya

  • Ine Pertry,

    Affiliations VIB, Institute of Plant Biotechnology Outreach, Technologiepark 3, B-9052 Ghent, Belgium, Ghent University, Department Molecular Biotechnology, Institute of Plant Biotechnology Outreach, Technologiepark 3, B-9052 Ghent, Belgium

  • Olivier Christiaens,

    Affiliation Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, B-9000 Ghent, Belgium

  • Lander Bauters,

    Affiliation Department of Molecular Biotechnology, Faculty of Bioscience Engineering, Ghent University, B-9000 Ghent, Belgium

  • Ana Bailey,

    Affiliation Venganza Inc., St. Augustine, FL 32080, United States of America

  • Chuck Niblett,

    Affiliation Venganza Inc., St. Augustine, FL 32080, United States of America

  • Marc Ghislain,

    Affiliation International Potato Center (CIP), Genomics and Biotechnology Program, Nairobi 00603, Kenya

  • Godelieve Gheysen,

    Affiliation Department of Molecular Biotechnology, Faculty of Bioscience Engineering, Ghent University, B-9000 Ghent, Belgium

  • Guy Smagghe

    guy.smagghe@ugent.be

    Affiliation Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, B-9000 Ghent, Belgium

Transcriptome Analysis and Systemic RNAi Response in the African Sweetpotato Weevil (Cylas puncticollis, Coleoptera, Brentidae)

  • Katterinne Prentice, 
  • Ine Pertry, 
  • Olivier Christiaens, 
  • Lander Bauters, 
  • Ana Bailey, 
  • Chuck Niblett, 
  • Marc Ghislain, 
  • Godelieve Gheysen, 
  • Guy Smagghe
PLOS
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Abstract

The African sweetpotato weevil (SPW) Cylas puncticollis Boheman is one of the most important constraints of sweetpotato production in Sub-Saharan Africa and yet is largely an uncharacterized insect pest. Here, we report on the transcriptome analysis of SPW generated using an Illumina platform. More than 213 million sequencing reads were obtained and assembled into 89,599 contigs. This assembly was followed by a gene ontology annotation. Subsequently, a transcriptome search showed that the necessary RNAi components relevant to the three major RNAi pathways, were found to be expressed in SPW. To address the functionality of the RNAi mechanism in this species, dsRNA was injected into second instar larvae targeting laccase2, a gene which encodes an enzyme involved in the sclerotization of insect exoskeleton. The body of treated insects showed inhibition of sclerotization, leading eventually to death. Quantitative Real Time PCR (qPCR) confirmed this phenotype to be the result of gene silencing. Together, our results provide valuable sequence data on this important insect pest and demonstrate that a functional RNAi pathway with a strong and systemic effect is present in SPW and can further be explored as a new strategy for controlling this important pest.

Introduction

Sweetpotato Ipomoea batatas (L.) Lam. is an important food security crop in Sub-Saharan Africa (SSA), covering around 1.8 million hectares with an estimated production of 11.3 million tons [1]. As this crop is highly adaptable to areas with seasonal rainfalls or long drought periods, it improves consumers’ livelihoods and fulfills their daily food needs particularly for subsistence farmers [2, 3]. Sweetpotato production can be devastated by the infestation of two African sweetpotato weevils (SPW) of which Cylas puncticollis Boheman is one [4], resulting in total crop loss especially during periods of pronounced droughts [5]. The primary cause of damage in sweetpotato is the SPW larvae, which tunnel and feed through vines and storage roots. As a result, plants wilt or even die whereas storage roots are reduced in size and number [6]. Furthermore, roots develop a bitter taste due to the presence of terpenoid compounds in response to microbial infection generated by the weevil tunneling. This damage reduces the quality of storage roots for human consumption and causes significant economic losses [7]. Historically, conventional breeding has been applied to develop weevil-resistant plants but the lack of varieties with high level of resistance against SPW [8] together with the complex genetic nature of sweetpotato make it difficult to develop these varieties [3, 9]. In addition, the use of insecticides and diverse techniques of integrated pest management (IPM) have also been ineffective in SSA because of the mode of growth of SPW [10, 11]. Therefore, there is a high need to use other strategies to control SPW which have been proven effective to control other pests for other crops [3].

RNA interference (RNAi) can be a powerful biological tool to achieve sweetpotato resistance against SPW as achieved for other coleopteran pest [12]. This relatively new technique, which triggers gene silencing typically by double-stranded RNA (dsRNA), has become a significant tool to knockdown target genes in plants as well as in insects. To induce an RNAi response in the insect, dsRNA can be delivered into the body through different methods: ingestion, soaking and microinjection. The latter is more frequently used in the laboratory because of the effective delivery of a known dose into the insect, whereas uptake by ingestion or soaking is more appropriate for screening of target genes for future control strategies [13]. After introduction into the cell, dsRNA is recognized as foreign by an RNaseIII nuclease called Dicer and processed into small interfering RNAs (siRNAs). One strand of the siRNA, the “guide strand” is assembled into an RNA-induced silencing complex (RISC) in conjunction with the Argonaute multi-domain protein, which is responsible for target recognition and degradation [14, 15]. At the post-transcriptional level, this complex binds to mRNA complementary to the siRNAs and the mRNA is degraded enzymatically, reducing the amount of mRNA available for protein translation.

In eukaryotes, three main RNAi pathways have been described: microRNAs (miRNAs), small interfering (siRNAs) and Piwi-interacting RNAs (piRNAs) [16], which differ in their biogenesis, type of Argonaute family proteins, mode of target regulation and substrates [17]. The RNAi machinery involved is evolutionarily conserved in most eukaryotic organisms, including insects [18]. In addition, the high sequence specificity of RNAi results in minimal, if any, effects on non-target organisms, including beneficial insects [19]. To date, the potential for RNAi in pest control has been successfully demonstrated for different insect groups [20]. Fourteen essential genes were down-regulated in the coleopteran species Diabrotica virgifera virgifera after feeding on an artificial diet containing dsRNA, resulting in very high mortality of the target species [20]. Another Coleopteran insect pest, the red flour beetle Tribolium castaneum, also exhibits a very strong RNAi response, including systemic RNAi and a long lasting effect [21, 22]. The evolutionary conservation within eukaryotic organisms and the successful application to control other Coleoptera pests suggest this approach might also be successful against the Coleopteran SPW. However, even within insect groups a high variability of RNAi response has been observed [23]. In fact, RNAi efficacy varies among insect species, genes, mode of dsRNA delivery, dsRNA uptake, spread of silencing signal and life stage [24, 25].

The RNAi response in SPW is uncertain. Therefore, it is necessary to identify the presence of the RNAi machinery in SPW and to determine its functionality. As no substantial gene information was available for C. puncticollis prior to this study, we sequenced its transcriptome using an Illumina platform, which has been used in transcriptome analysis of many other species [2628]. After annotation using reference insect sequence databases, the genes involved in the RNAi machinery were searched for. In addition, the present study aimed to demonstrate the functionality of the RNAi pathway in C. puncticollis by applying dsRNA nanoinjection targeting laccase2, a gene involved in the insect cuticle tanning [29], which is expected to provide a rapid and clear phenotypic evidence for gene silencing. Effective downregulation of laccase2 can indicate the potential of C. puncticollis to initiate a systemic RNAi response.

Material and Methods

Sweetpotato weevil rearing

A SPW colony was maintained in plastic cages at standard laboratory conditions of 27°C, 65% RH under a 16:8 light:dark regime. Insects were kept for feeding and oviposition on sweetpotato storage roots. Fresh storage roots were added every 3 days in order to obtain second instar larvae for nanoinjection. Larvae were removed from the roots at 7–9 days after oviposition.

cDNA libraries and Illumina sequencing for transcriptome analysis

Total RNA was extracted from second instar larvae of C. puncticollis using the RNeasy Mini Kit (Qiagen). The cDNA library preparation and Illumina sequencing were conducted at the North Carolina State University Genomic Sciences Laboratory. The RNA quality and concentration were examined on the Agilent 2100 Bioanalyzer using a RNA Pico Chip. One microgram of total RNA was used following the requirements of TruSeq RNA sample preparation v2 protocol (Illumina). Total RNA was purified using oligo (dT) magnetic beads to isolate poly-A containing mRNA and fragmented into short sequences using divalent cations. The purified mRNA fraction was then used for synthesis of first and second strand cDNA. After the end repair on the double-stranded cDNA, 3’ ends were adenylated and adapters with indexes were ligated for multiplexing. The cDNA library was amplified by PCR and then AmpureXP beads were used for purification. The final library was quantified using Agilent’s Bioanalyzer High Sensitivity DNA Chip prior to clustering on the Illumina cBot. The cDNA libraries were sequenced on the Illumina sequencing platform (HiSeq2000) where each sample was collocated in one lane of a 100bp single-end run.

The Trinity software (http://trinityrnaseq.sourceforge.net/) was used for de novo assembly of the raw reads to generate a set of contigs. The software used a Bruijn graph algorithm and a k-mer length of 25. The generated dataset was assembled independently under three different conditions: A full assembly of all reads, an assembly of a reduced representation of the reads, and an assembly following computational normalization of the reads in the dataset via the Trinity In Silico read normalization tool.

Homology search and gene ontology annotation

The generated contigs were analyzed by searching the non-redundant (nr) insect protein database at the National Center of Biotechnology Information (NCBI) with the BLASTX algorithm (http://www.ncbi.nlm.gov), using a cut-off bitscore >50. For gene ontology (GO) annotation, a second homology search was performed to annotate the generated contigs by searching the Swiss-Prot database with the BLASTX algorithm from NCBI database using a cut-off bitscore >50. The generated gene identifiers were used as input in QuickGo from EBI (http://www.ebi.ac.uk/QuickGO/GAnnotation) and to calculate GO terms.

Sequence submission

All raw reads have been deposited in the sequence reads archive (SRA) at NCBI, and could be accessed using SRX732288 accession number.

RNAi-related genes

A list of RNAi-related genes employed by Swevers et al. [30] was selected, covering the RNAi core machinery (Table 1), auxiliary factors (Table 2) nucleases, antiviral RNAi and dsRNA uptake (Table 3) (Accession numbers are listed in Tables 1, 2 and 3). Homologous sequences from T. castaneum corresponding to these genes were used as a query to search the transcriptome from C. puncticollis for the presence of RNAi-related genes using the BLAST tool (http://brcclusterrac.statgen.ncsu.edu/Niblet/). The contigs obtained from the search with bitscore >150 were used for further analysis to verify their identity.

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Table 1. Overview of identified genes related to the RNAi pathways in C. puncticollis.

https://doi.org/10.1371/journal.pone.0115336.t001

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Table 2. Overview of identified genes associated to RISC complex in C. puncticollis. (FS) frame shift; (RF) reading frame.

https://doi.org/10.1371/journal.pone.0115336.t002

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Table 3. Overview of identified genes associated to RNAi in C. puncticollis. (FS) frame shift; (RF) reading frame.

https://doi.org/10.1371/journal.pone.0115336.t003

The program ORF Finder from NCBI was used to detect open reading frames. Homologous proteins were searched with the Protein Basic Local Alignment Tool (Protein BLAST) against the non-redundant protein database at NCBI. Upon indication of the presence of frame shifts, sequences were further analyzed with BLASTX against the non-redundant protein database at NCBI.

dsRNA synthesis and purification

The dsRNAs for laccase2 (362 bp) and gfp (495 bp) were synthesized using the MEGAscript kit (Ambion). The C. puncticollis transcriptome was searched for the laccase2 sequence using the homologous sequence from T. castaneum as a query. The fragment was amplified by PCR using cDNA of second-instar C. puncticollis larvae as template, prepared with SuperScript First-Strand Synthesis System (Invitrogen). The primers used for the PCR are listed in Table 4. The PCR products were cloned into the pJET1.2/blunt cloning vector (Thermo Scientific). The insertions were confirmed by Sanger sequencing. The dsRNA templates were produced by PCR using DNA plasmids linearized with NcoI and primers with a T7 promoter region (TAATACGACTCACTATAGGGAGA) at the 5’ end of each primer (Table 4). The PCR products were purified using the CyclePure E.Z.N.A. kit (Omega Bio-Tek) and immediately used for in vitro transcription using MEGAscript kit (Ambion) according to the manufacturer’s instructions. Nuclease-free water was used for dsRNA elution. The dsRNA synthesis was verified by gel electrophoresis and quantified in a NanoDrop ND-1000 (Thermo Scientific).

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Table 4. Primers used in PCR for cloning and real-time quantitative PCR.

https://doi.org/10.1371/journal.pone.0115336.t004

Larval injection

Nanoinjection was performed using second-instar larvae of C. puncticollis. Larvae were anesthetized with diethyl ether for 5 min and immobilized in an agarose plate at 1.5%. The dsRNA for laccase2 and gfp (control) was injected into the hemocoel at a concentration of 0.2 μg/mg body weight (BW) using a nanoinjector (FemtoJet, Eppendorf) and needles prepared with glass capillary tubes. At least 85 larvae were injected per treatment of which 25 and 60 individuals were used for phenotypic evaluation and real-time quantitative PCR (qPCR), respectively. After injection, larvae were placed into sweetpotato root slices of 1x1 cm in petri dishes and incubated at 27°C and 65% RH. Larvae were evaluated phenotypically every day for 15–20 days.

Real-time quantitative PCR

Total RNA was extracted from the whole insect body at 1, 3, 5 and 10 days after injection, each time point containing three biological samples of 5 pooled insects. The RNeasy Mini Kit (Qiagen) was used for RNA extraction following the manufacturers’ instructions. After DNaseI treatment (Ambion), RNA was quantified using a NanoDrop ND-1000 (Thermo Scientific) and verified by 1.5% agarose gel electrophoresis. Total RNA (0.9 µg) was reverse transcribed using the SuperScript II kit (Invitrogen) according to manufacturer’s instructions. Real time quantitative PCR was performed in the CFX 96TM real-time system and the CFX manager software (Biorad). The primers used in the analysis (Table 4) were validated with a standard curve based on a serial dilution of cDNA to determine the primer annealing efficiency and a melting curve analysis with temperature range from 60 to 95°C. The reaction included 10 μl of SsoFastTM EvaGreen Supermix (Biorad), 0.4 μl of 10 μM forward primer (Invitrogen), 0.4 μl of 10 μM of reverse primer (Invitrogen), 8.2 μl of nuclease-free water and 1 μl of cDNA, in a total volume of 20 μl. The amplification conditions were 3 min at 95°C followed by 39 cycles of 10 s at 95°C and 30 s at 58°C. The reactions were set-up in 96-well format Microseal PCR plates (Biorad) in triplicates. The endogenous controls, ribosomal protein L32e (rpl32) and β-actin, were used for normalization of the data. Appropriate controls, no-template control and no reverse transcriptase control, were also included in the assay. Relative transcript levels of laccase2 were normalized to the endogenous reference genes rpl32 and β-actin by the equation ratio 2-ΔΔCt [31]

Results and Discussion

Analysis of Cylas puncticollis transcriptome

The C. puncticollis transcriptome was sequenced to gain insights into the RNAi-related genes and for further exploration of essential genes to be silenced through RNAi technology. Sequencing was performed using an Illumina platform, which generated a total of 213,207,004 reads of 100 bp long, corresponding to an accumulated length of 21,320,700,400 bp. The full dataset was assembled using Trinity software resulting into 89,599 contigs with a mean length of 1,630 bp and an average GC content of 39%.

For BLAST annotation, contigs were first searched for similar insect protein sequences using BLASTX against the non-redundant (nr) protein NCBI database, This BLASTX analysis produced 44,824 hits, representing 50.0% of total contigs (Fig. 1). The number of non-significant hits (50.0%) indicates that the C. puncticollis transcriptome contains unknown sequences that are not yet described in the insect protein sequences databases. For those sequences with a significant match, 87.68% of the contigs are most similar to sequences from coleopteran species: 40.31% to the red flour beetle Tribolium castaneum, which is a worldwide pest of stored food products, 36.51% to the mountain pine beetle Dendroctonus ponderosae sequences, which is a serious forest pest [32] and 10.87% to the Asian long-horn beetle Anoplophora glabripennis sequences, also found to be destructive of forest trees [33]. The remaining 12.32% of all contigs were more similar to the hemipterans Acyrthosiphon pisum (1.78%) and Triatoma infestans (0.94%), the hymenopterans Camponotus floridanus (0.78%) and Cerapachys biroi (0.60%), the dipteran Corathrella appendiculata (0.65%), the lepidopteran Bombyx mori (0.57%) and others (7.1%).

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Figure 1. Sequence comparison to other insect genera from the distribution of BLASTX hit (bitscore >50) against the nr protein database of the National Center for Biotechnology Information.

https://doi.org/10.1371/journal.pone.0115336.g001

Gene ontology classification

To functionally classify the generated contigs, BLASTX similarity searches were performed against the Swiss-Prot database (bitscore >50), resulting in 36,198 (40.4%) significant hits. The resulting identifiers from this search were used to calculate GO terms, which were grouped into 3 main categories: cellular component, biological process and molecular function. A total of 706,945 predicted GO terms were obtained. The most dominant GO terms within the cellular component were nucleus (29,759; 14.8%), for the biological processes it was metabolic processes (7,607; 2.5%) and for the molecular function it was protein binding (24,774; 12%) (Fig. 2). Similar results were found in the D. ponderosae transcriptome, which was the second best hit in the homology search. The most dominant GO term within the biological process was metabolic process as in C. puncticollis. However, for the cellular component and molecular function, cell part and binding were the most dominant, respectively [31].

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Figure 2. Percentage of Cylas puncticollis contigs assigned to a certain gene ontology term as predicted by QuickGO from EBI.

https://doi.org/10.1371/journal.pone.0115336.g002

Identification of RNAi-related genes

To gain insight in the potential of C. puncticollis to exhibit an RNAi response, the C. puncticollis transcriptome was screened for the presence of the most important genes related to the RNAi machinery. T. castaneum, like C. puncticollis, belongs to the order of Coleoptera and is more phylogenetically related to C. puncticollis than C. elegans and D. melanogaster. Moreover, the complete genome of T. castaneum has also been sequenced and fully annotated [34]. Therefore, homology searches were performed using as reference the T. castaneum sequences for the homologous genes listed by [30]. Accordingly, 47 RNAi-related genes from C. puncticollis could be annotated. After identification of these contigs, a BLASTp similarity search was performed against the NCBI database to confirm their identity. Sequences of D. ponderosae and T. castaneum showed closest similarity to C. puncticollis.

Core RNAi machinery. The core components of the RNAi machinery are proteins that, together with the small RNA fragments, are involved in gene silencing. There are three major pathways studied in eukaryotes: miRNAs, siRNAs and piRNAs [35]. The miRNA and siRNA pathways have an important role in gene regulation by suppressing mRNA translation or inducing mRNA degradation [36]. The difference between the miRNA and siRNA pathways is in their biogenesis, but not in their function. The piRNA pathway has been less characterized and is, in contrast to the two first classes, restricted to germlines [37].

In the miRNA and siRNA pathways, orthologous sequences to the three RNaseIII proteins Drosha, Dicer-1 and Dicer-2, were identified in C. puncticollis with a bitscore >150. The main domains of the typical Drosha and Dicer proteins were found to be conserved in C. puncticollis. The Dicer domains are: amino-terminal DExH-box helicase domains, PAZ domain, two RNaseIII domains, and carboxi-terminal dsRNA-binding domain (dsRBD). Unlike Dicer, Drosha has no PAZ and amino-terminal DExH-box helicase domain [38]. Three cofactors with conserved domains, Pasha, Loquacious and R2D2, were also identified in C. puncticollis. These proteins are required to interact with the RNaseIII genes Drosha, Dicer-1 and Dicer-2, respectively (Table 1, S1 Supporting Information).

Drosha, Dicer1 and Dicer2 are key factors to process dsRNA into small RNAs. Both Dicers were also found in D. melanogaster, Dm-Dicer-1 and Dm-Dicer-2, responsible for the miRNA and siRNA pathway, respectively [39]. In T. castaneum, Dicer-2 (Tc-Dcr-2) has been found to play an important role in systemic RNAi, while Dicer1 (Tc-Dcr-1) is not involved. In C. elegans, a single Dicer was found to govern both pathways [40]. The presence of Dicer-1 and Dicer-2 as well as their cofactors in C. puncticollis, suggests that they could have a role in the miRNA and siRNA pathway, respectively.

Another crucial RNAi-related gene is Argonaute, which is a component of the RISC complex and is involved in post-transcriptional silencing. A contig containing the main domains (PAZ domain and PIWI domain) usually found in Argonaute (Ago) proteins, is also present in C. puncticollis (Table 1, S1 Supporting Information). Five types of Ago were found in T. castaneum and D. melanogaster and 27 in C. elegans [22, 41]. Ago1 and Ago2 are critical in the miRNA and siRNA pathway, respectively [42]. In the present study, we have identified 5 members of the Argonaute protein family: Ago1, Ago2, which belong to Argonaute subfamily and Ago3, Aubergine (Aub) and Piwi, which belong to the Piwi subfamily [43].

Aub and Piwi, as well as Zucchini are proteins involved in the third pathway of piRNA [37]. Searching Aub and Piwi from T. castaneum resulted in two protein sequences that matched the same contig in C. puncticollis. This result suggests that either Aub or Piwi is present in C. puncticollis (Table 1, S1 Supporting Information). For Zucchini, which is an endoribonuclease with a role in piRNA maturation, a 61% of similarity was observed with two analyzed sequences (bitscore >150). Even though the observed similarity for Zucchini was slightly lower than for the other blasted sequences (bitscore >200), the full conserved domain could be identified, suggesting that Zucchini is present in C. puncticollis, (Table 1, S1 Supporting Information).

Auxiliary factors (RISC). The presence of auxiliary factors to the RNAi machinery was also examined in the C. puncticollis transcriptome (Table 2, S2 Supporting Information). These included 19 intracellular factors that are associated with (or regulate) the activity of the RISC complex. The protein sequences for Tudor-SN (TSN), Vasa-intronic gene (VIG), fragile X related protein 1 (FXMR1) and p68 RNA helicase, that are present in the holo-RISC complex as found in D. melanogaster [44, 45], were identified in C. puncticollis, all with conserved main domains.

The two conserved subunits of the C3PO (component 3 promoter of RISC), Translin and Translin-associated factor X, which were characterized to promote RISC activation [46], were also identified in C. puncticollis. The nucleases involved in piRNA biogenesis, Armitage (Armi), spindle-E (Spn-E) and Maelstrom, as well as Hen-1 were present in C. puncticollis with all conserved domains. Armi, Spn-E and Maelstrom are required for piRNA production and/or stability. Mutation of these genes showed depletion of piRNAs in fly ovaries [47, 48]. Hen-1 is a methyltransferase associated with Piwi proteins in ovaries. This protein methylates small RNAs through a 2’-O-methyl modification at their 3’ ends, playing a critical role in gene silencing suppression. [49, 50].

Full-length fragments were found for the DEAD-box RNA helicases, Belle and PRP16 in C. puncticollis. Belle has a function in the endo-siRNA pathway, interacting with Ago2 and endo-siRNA-generating loci and is localized in condensing chromosomes in a dcr-2- and ago2-dependent manner [51]. PRP16 has an important role in the pre-mRNA splicing [52] with activity in RNAi, and it is a homologous protein to Mut6 in Chlamydomonas [53]. For another DEAD-box RNA helicase, Gemin3 homolog [54], a partial fragment is present in C. puncticollis, only covering 50% of the full sequence; however the main domains are present.

The proteins Gawky, localized in GW-bodies in D. melanogaster and required for miRNA function [55], Staufen (STAU1), a dsRNA-binding protein, and Clp-1, a RNA kinase able to phosphorylate siRNAs, were all present in C. puncticollis. Elp-1, a component of the pol II core elongator complex involved in the RNAi silencing, was also identified in C. puncticollis. Two fragments covered the full-length sequence of this protein [56]. A full-length sequence is also present for the protein GLD-1 homolog, a KH motif containing RNA-binding protein of the GSG/STAR subfamily, involved in different aspects of germline development. It is known to prevent translation of mRNA into proteins through target mRNA binding [57]. For ACO-1, an RNAi-binding protein involved in translational inhibition, a partial fragment was identified in C. puncticollis [58].

dsRNA uptake. The proteins sequences for SID1, FBX011, Scavenger receptor SR-C-like protein and Eater were searched in the C. puncticollis transcriptome as well (Table 3, S3 Supporting Information). SilC and SilB were found in C. puncticollis as a first and second hit, respectively; whereas SilA and SID1 were not. The sid1 gene in C. elegans encodes a multi-transmembrane domain protein, which is essential for uptake of dsRNAs into cells and for the spreading of the RNAi signal in C. elegans [59]. Three sid1-like genes were found in T. castaneum (SilA, SilB and SilC) [60], while in D. melanogaster no homologs for Sid proteins were found. Initially, it was thought that the presence or absence of these genes explained the robust and systemic RNAi response in T. castaneum and the lack of systemic RNAi in D. melanogaster, respectively. However, later research has shown that these Sils in T. castaneum are not critical for the systemic RNAi response, as silencing these genes did not affect the systemic RNAi response [58]. Furthermore, other mechanisms, including endocytosis, have been shown to be involved in dsRNA-uptake in certain insects as well [61, 62]. Whether or not these Sils play a role in dsRNA uptake in insects from other orders remains unclear.

FBX011 was found in C. puncticollis with a conserved F-box domain and three beta-helices. Scavenger receptors, such as Eater and SR-CI, were found to be important for dsRNA uptake [63]. Scavenger receptors are known to act as receptors for large molecules and/or microbes and play a role in phagocytosis. Eater encodes a Nimrod family protein that contains multiple NIN-type EGF domains. All these protein sequences are present in the C. puncticollis transcriptome.

Antiviral RNAi. Four protein sequences involved in antiviral RNAi found in D. melanogaster, were searched in C. puncticollis: Ars2, a regulator of the RISC complex, CG4572, a protein with an unknown function, Egghead (egh), a seven transmembrane-domain glycosyltransferase and ninaC, a protein involved in vesicle transport [64, 65] (Table 3, S4 Supporting Information). In C. puncticollis, full-length sequences were identified for CG4572 and ninaC, but only partial fragments for both Ars2 and Egghead proteins.

Nucleases. Little is known about the nucleases that interact in RNAi. Six nucleases believed to have RNAi-related activity were found present in the C. puncticollis transcriptome: Eri-1 like, Nibbler, Sdn1-like, the homolog of the B. mori DNA/RNA non-specific alkaline nuclease, Exosome and Poly(A) polymerase (Table 3, S5 Supporting Information). A full-length sequence of the Eri-1 protein is present in C. puncticollis. Eri-1 is an evolutionary conserved protein involved in intracellular siRNA degradation, and of which the SAP/SAF-box domain and DEDDh family exonuclease domain [66] are conserved in C. puncticollis. For the small RNA-degrading nuclease Sdn1-like, which has a 3’ to 5’ exonuclease activity, and which can degrade mature miRNAs in plants [67], a full-length sequence with conserved domains was identified. For the nucleases, Nibbler, which processes 3’-ends of miRNAs [68], dsRNAse, a dsRNA-degrading enzyme [69]. Exosome, which has a 3’ to 5’ exonuclease activity [70] and Poly(A) polymerase, which is involved in the mRNA degradation [71], partial sequences with conservation of the main domains also are present in C. puncticollis.

In summary, these results revealed the presence of 47 known RNAi-related genes in C. puncticollis, which is a first condition for the use of RNAi-based pest control methods for this weevil. Furthermore, our results confirmed the conservation of these RNAi-related genes among coleopteran species as T. castaneum, which show a very robust RNAi system [22, 72].

Silencing of laccase2 gene

To demonstrate the functionality of the RNAi pathway in C. puncticollis, dsRNA targeting laccase2 was synthetized. This gene is involved in insect cuticle sclerotization and provides a rapid and clear phenotypic evidence for gene silencing in T. castaneum [29]. Prior research showed that a high concentration and longer fragments of dsRNA (>300 bp) are critical for an efficient inhibition of laccase2 expression and longer duration of the RNAi effect [72]. Therefore, we injected a 362 bp-long dsRNA molecule targeting laccase2 into the hemocoel of second-instar larvae with a final dsRNA concentration of 0.2 µg/mg of body weight. The control group was injected with the same concentration of a 495 bp-long dsRNA molecule targeting the gfp gene being absent in C. puncticollis.

Inhibition of laccase2 expression could be observed phenotypically in 21 of 25 (84%) individuals as early as 3 days following injection. Treated larvae exhibited lack of sclerotization in the head capsule resulting in an untanned cuticle (Fig. 3C.1) compared to the control larvae injected with gfp dsRNA (Fig. 3B.1). Injection trauma in the control resulted in 8% of mortality. Suppression of laccase2 expression can be detected after 24 h when tested by qPCR (Fig. 4). These results demonstrate that laccase2 mRNA levels were reduced 91.7% compared to the control injected with gfp dsRNA (p-value 0.0193) after 24 h. This reduction was also observed at the other two time points, where the expression levels on day 3 and day 5 showed a reduction of 92.9% (p-value 0.0107) and 93% (p-value 0.001), respectively. Interestingly, expression of laccase2 was found to be variable between different larval stages and even within a certain stage. Possibly, laccase2 expression only exhibits a peak at a certain time after the molt, given its role in the cuticle tanning. However, further studies should be conducted in order to confirm this. Nevertheless, despite this natural variability, the silencing we observed was strong when compared to the control for each time point. and consistent in all experiments and repetitions.

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Figure 3. Effect of inhibition of laccase2 expression after injection with dsRNA in second-instar larvae of Cylas puncticollis.

(A) Mortality after injection with dsRNA targeting laccase2 (dslac2) (day 14–20) expressed in percentage. Mortality in larvae injected with dsRNA targeting gfp (dsgfp) (control) was only 8% (B) Larvae injected with dsgfp as a control and (C) treated larvae after 3 days; (D) Pupa development 6 days after injection with dsgfp as a control and (E) dslac2; (F) Adult development injected 10 days after injection with dsgfp as a control (G) dslac2 (H) Surviving individual 13 days after injection with dslac2. Larvae were injected with the dsRNA solution into the hemocoel at a concentration of 0.2 µg/mg body weight. The insects were kept in sweetpotato roots after injection for the duration of the experiment.

https://doi.org/10.1371/journal.pone.0115336.g003

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Figure 4. Inhibition of laccase2 expression in second-instar larvae of Cylas puncticollis at 1, 3, 5 and 10 days after injection with dsRNA targeting laccase2 at 0.2 µg/mg of body weight.

Injection with dsRNA targeting gfp was used as a control. As internal controls, ribosomal protein L32 and Actin were used. Values are based on two repetitions of three biological samples and expressed as mean ± SEM. Each sample contains 5 pooled insects. The p-values were calculated by unpaired t-test.

https://doi.org/10.1371/journal.pone.0115336.g004

At 5–6 days post-injection, the pupal stages showed no tanning in cuticular structures as pronotum, prothoracic, mesothoracic and metathoracic legs, elytral and wing sheath and urogomphi (Fig. 3E) whereas an initiation of tanning for these structures was obvious in the control (Fig. 3D). In adults, a complete inhibition of the cuticular sclerotization in the exoskeleton was observed (Fig. 3G) compared to the control (Fig. 3F). Moreover, they exhibited a malformed and soft cuticle with no pigmentation, which complicated their normal mobilization. Additionally, a partial recovery of the cuticle tanning of adults was observed at 13 days post-injection (Fig. 3H). On transcript level, the gradual recovery could already be shown after 10 days, where a smaller difference (34%) in transcript levels between control and treatment could be observed (p-value 0.0170) (Fig. 4). The evaluation of treated insects at 15 to 20 days post-injection showed no survival of adults (Fig. 3A), which could be due to the difficulty of feeding as a result of the malformed and soft cuticle in the mouthparts.

These results clearly demonstrate that an RNAi response is activated in C. puncticollis to laccase2; furthermore, the lack of cuticle tanning suggests that the RNAi activity is systemic with a persistence of the RNAi signal for at least 10 days. Similar results were also demonstrated by [73], who determined that RNAi in T. castaneum is systemic by injecting dsRNA targeting Tc-achaete-scute in larvae. Our results demonstrate that targeting C. puncticollis using RNAi as a pest control agent has a clear potential, given the strong and systemic RNAi effect shown here.

Conclusions

Our data demonstrate that the necessary components of the three major RNAi-related pathways described in insects are present and expressed in C. puncticollis. The presence of the core RNAi machinery genes in the transcriptome indicates the potential to initiate an RNAi response in this weevil. Direct injection of dsRNA targeting laccase2 into the larvae efficiently downregulated gene expression, occurring after 24 h and lasting for at least 10 days after a single injection. This result demonstrated that C. puncticollis exhibits a strong and systemic RNAi effect, suggesting the potential of RNAi as a future strategy to control SPW. Furthermore, our research provides valuable sequence data on this important pest insect that will be useful for further research on this economically important weevil.

Supporting Information

S1 Supporting Information. Sequences of C. puncticollis core machinery proteins.

https://doi.org/10.1371/journal.pone.0115336.s001

(DOCX)

S2 Supporting Information. Sequences of C. puncticollis RISC-associated auxiliary factors.

https://doi.org/10.1371/journal.pone.0115336.s002

(DOCX)

S3 Supporting Information. Sequences of C. puncticollis proteins involved in dsRNA uptake.

https://doi.org/10.1371/journal.pone.0115336.s003

(DOCX)

S4 Supporting Information. Sequences of C. puncticollis proteins involved in antiviral RNAi.

https://doi.org/10.1371/journal.pone.0115336.s004

(DOCX)

Acknowledgments

The authors thank Jenn Schaff and Elizabeth Scholl from North Carolina State University, Genomic Sciences Laboratory for their support in this paper. Katterinne Prentice is recipient of a doctoral grant by the Special Research Fund of Ghent University and the International Potato Center.

Author Contributions

Conceived and designed the experiments: KP IP OC MG GG GS. Performed the experiments: KP IP OC. Analyzed the data: KP IP OC LB GG GS. Contributed reagents/materials/analysis tools: MG GG GS. Wrote the paper: KP IP OC AB CN MG GG GS.

References

  1. 1. FAOSTAT (2012) Available:http://faostat.fao.org/. Accessed 3 May 2014.
  2. 2. Fuglie KO (2007) Priorities for sweetpotato research in developing countries: Results of a survey. HortScience 42: 1200–1206.
  3. 3. Mwanga ROM, Ghislain M, Kreuze J, Ssemakula GN, Yencho C (2011) Exploiting the use of biotechnology in sweetpotato for improved nutrition and food security: progress and future outlook. Proc Intl Conf Agbiotech, Biosafety & Seed Systems (2011) 25–31.
  4. 4. Wolfe GW (1991) The origin and dispersal of the pest species of Cylas with a key to the pest species groups of the world, pp 13–44. In Sweet potato Pest Management. A global Perspective. (Edited by Jansson R.K. and Raman K.V.) Westview Press, Boulder, Colorado, USA.
  5. 5. Skoglund L G, Smit NEJM (1994) Major diseases and pest of sweetpotato in Eastern Africa. International Potato Center (CIP) Lima, Peru. 67p.
  6. 6. Stathers TE, Rees D, Kabi S, Mbilinyi L, Smit N, et al. (2003) Sweetpotato infestation by Cylas spp. in East Africa: I. Cultivar differences in field infestation and the role of plant factors. Int J Pest Manag 49:131–140.
  7. 7. Chalfant RB, Jansson R K, Seal DR, Schalk JM (1990) Ecology and management of sweetpotato insects. Annu Rev Entomol 35: 157–180.
  8. 8. Stevenson PC, Muyinza H, Hall DR, Porter EA, Farman DI (2009) Chemical basis for resistance in sweetpotato Ipomoea batatas to the sweetpotato weevil Cylas puncticollis. Pure Appl Chem 81: 141–151.
  9. 9. Andrade M, Barker I, Cole D, Dapaah H, Elliott H, et al. (2009). Unleashing the potential of sweetpotato in Sub-Saharan Africa: Current challenges and way forward. International potato Center (CIP), Lima, Peru. Working Paper 2009–1. 197 p.
  10. 10. Smit NEJM (1997) The effect of the indigenous cultural practices of in-ground storage and piecemeal harvesting of sweetpotato on yield and quality losses caused by sweetpotato weevil in Uganda. Agr Ecosyst Environ 64: 191–200.
  11. 11. Smit NEJM, Downham MCA, Laboke PO, Hall DR, Odongo B (2001) Mass-trapping male Cylas spp. With sex pheromones: a potential IPM component in sweetpotato production in Uganda. Crop Protect 20: 643–651.
  12. 12. Baum JA, Bogaert T, Clinton W, Heck GR, Feldmann P, et al. (2007). Control of coleopteran insect pests through RNA interference. Nature Biotechnol 25: 1322–1326.
  13. 13. Yu N, Christiaens O, Liu J, Niu J, Cappelle K, et al. (2013) Delivery of dsRNA for RNAi in insects: an overview and future directions. Insect Sci 20: 4–14. pmid:23955821
  14. 14. Price DRG, Gatehouse JA (2008) RNAi-mediated crop protection against insects. Trend Biotechnol 26: 393–400.
  15. 15. Kim VN, Han J, Siomi MC (2009) Biogenesis of small RNAs in animals. Nature 10: 126–139.
  16. 16. Ghildiyal M, Zamore PD (2009) Small silencing RNAs: an expanding universe. Nature 10: 94–108.
  17. 17. Gaynor JW, Campbell BJ, Cosstick R (2010) RNA interference: a chemist’s perspective. Chem Soc Rev 39: 4169–4184. pmid:20717561
  18. 18. Shabalina SA, Koonin EV (2008) Origins and evolution of eukaryotic RNA interference. Trends in Ecol Evol 23: 578–587.
  19. 19. Bachman PM, Bolognesi R, Moar WJ, Mueller GM, Paradise MS, et al. (2013) Characterization of the spectrum of insecticidal activity of a double-stranded RNA with targeted activity against Western Corn Rootworm (Diabrotica virgifera virgifera LeConte). Transgen Res 22: 1207–1222.
  20. 20. Katoch R, Sethi A, Thakur N (2013) RNAi for insect control: Current perspective and future challenges. Appl Biochem Biotechnol 171: 847–873. pmid:23904259
  21. 21. Busher G, Scholten J, Klingler M (2002) Parental RNAi in Tribolium (Coleoptera). Curr Biol 12: R85–86.
  22. 22. Tomoyasu Y, Miller S, Tomita S, Schoppmeier M, Grossmann D, et al. (2008) Exploring systemic RNA interference in insects: a genome-wide survey for RNAi genes in Tribolium. Genome Biol 9:R10. pmid:18201385
  23. 23. Terenius O, Papanicolaou A, Garbutt JS, Eleftherianos L, Huvenne H, et al. (2011) RNA intereference in Lepidoptera: an overview of successful and unsuccessful studies and implications for experimental design. J Insect Physiol 57: 231–245. pmid:21078327
  24. 24. Huvenne H, Smagghe G (2010) Mechanisms of dsRNA uptake in insects and potential of RNAi for pest control: A review. J Insect Physiol 56: 226–235.
  25. 25. Scott JG, Michel K, Bartholomay LC, Siegfried BD, Hunter WB et al. (2013) Toward the elements of successful insect RNAi. J Insect Physiol 59: 1212–1221. pmid:24041495
  26. 26. Crawford JE, Guelbeogo WM, Sanou A, Traoré A, Vernick KD, et al. (2010) De novo transcriptome sequencing in Anopheles funestus using Illumina RNA-seq technology. PLoS ONE 5(12): e14202.. pmid:21151993
  27. 27. Xue J, Bao YY, Li BL, Cheng YB, Peng ZY et al. (2010) Transcriptome Analysis of the brown planthopper Nilaparvata lugens. PLoS ONE 5(12): e14233. pmid:21151909
  28. 28. Li H, Jiang W, Zhang Z, Xing Y, Li F (2013) Transcriptome analysis and screening for potential target genes for RNAi–mediated pest control of the beet armyworm, Spodoptera exigua. PLoS ONE 8: e65931. pmid:23823756
  29. 29. Arakane Y, Muthukrishnan S, Beeman RW, Kanost M R, Kramer KJ (2005) Laccase 2 is the phenoloxidase gene required for beetle cuticle tanning. Proc Natl Acad Sci U S A 102: 11337–11342. pmid:16076951
  30. 30. Swevers L, Huvenne H, Menschaert G, Kontogiannatos D, Kourti A, et al. (2013) Colorado potato beetle (Coleoptera) gut transcriptome analysis: expression of RNA interference-related genes. Insect Mol Biol 22: 668–684. pmid:24580832
  31. 31. Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCt method. Methods 25:402–408. pmid:11846609
  32. 32. Keeling C, Henderson H, Li M, Yuen M, Clark EL, et al. (2012) Transcriptome and full-length cDNA resources for the mountain pine beetle Dendroctonus ponderosae Hopkins, a major insect pest of pine forests. Insect Biochem Mol Biol 42: 525–536. pmid:22516182
  33. 33. Scully ED, Hoover K, Carlson JE, Tien M, Geib S (2013) Midgut transcriptome profiling of Anoplophora glabripennis, a lignocellulose degrading cerambycid beetle. BMC Genom 14:850 http://www.biomedcentral.com/1471–2164/14/850. .
  34. 34. Tribolium Genome Sequencing Consortium: The genome of the developmental model beetle and pest Tribolium castaneum. Nature 452:
  35. 35. Liu Q, Paroo Z (2010) Biochemical principles of small RNA pathways. Annu Rev Biochem 79:295–319. pmid:20205586
  36. 36. Bartel DP (2009) MicroRNAs: Target recognition and regulatory functions. Cell 136:215–239. pmid:19167326
  37. 37. Hartig JV, Tomari Y, Forsteman K (2007) piRNAs—The ancient hunter of genome invaders. Genes Dev 21:1707–1713. pmid:17639076
  38. 38. Carmell M, Hannon G J (2004) RNase III enzymes and the initiation of gene silencing. Nat Struct Mol Biol 11:214–218. pmid:14983173
  39. 39. Lee YS, Nakahara K, Pham JW, Kim K, He Z, et al. (2004) Distinct roles for Drosophila Dicer-1 and Dicer-2 in the siRNA/miRNA silencing pathways. Cell 17:69–81.
  40. 40. Keeting RF, Fischer SEJ, Bernstein E, Sijen T, Hannon GJ, et al. (2001) Dicer functions in RNA interference and in synthesis of small RNA involved in developmental timing in C. elegans. Genes Dev 15:2654–2659.
  41. 41. Yigit E, Batista PJ, Bei Y, Pang KM, Chen CC, et al. (2006) Analysis of the C. elegans Argonaute family reveals that distinct Argonautes act sequentially during RNAi. Cell 127:747–757. pmid:17110334
  42. 42. Okamura K, Ishizuka A, Siomi H, Siomi MC (2004) Distinct roles for Argonaute proteins in small RNA-directed RNA cleavage pathways. Genes Dev 18:1655–1666. pmid:15231716
  43. 43. Lin H (2007) piRNAs in the germ lines. Science 316:397. pmid:17446387
  44. 44. Ishizuka A, Siomi MC, Siomi H (2002) A Drosophila fragile X protein interacts with components of RNAi and ribosomal proteins. Genes Dev 16:2497–2508. pmid:12368261
  45. 45. Tomari Y, Zamore P (2005) Perspective: machines for RNAi. Genes Dev 19:517–529. pmid:15741316
  46. 46. Liu Y, Ye X, Jiang F, Liang C, Chen D, et al. (2009) C3PO, an endoribonuclease that promotes RNAi by facilitating RISC activation. Science 325:750–753. pmid:19661431
  47. 47. Vagin VV, Sigova A, Li C, Seitz, Gvozdev V, Zamore P (2006) A distinct small RNA pathway silences selfish genetic elements in the germline. Science 313:320–324. pmid:16809489
  48. 48. Findley SD, Tamanaha M, Clegg NJ, Ruohola-Baker H (2003) Maelstrom, a Drosophila spindle-class gene, encodes a protein that colocalizes with Vasa and RDE1/AGO1 homolog, Aubergine, in nuage. Development 130:859–871. pmid:12538514
  49. 49. Saito K, Sakaguchi Y, Suzuki T, Suzuki T, Siomi H et al. (2007) Pimet, the Drosophila homolog of HEN1, mediates 2’-O-methylation of Piwi-interacting RNAs at their 3’ ends. Genes Dev 21:1603–1608. pmid:17606638
  50. 50. Billi AC, Alessi AF, Khivansara V, Han T, Freeberg M, et al. (2012) the Caenorhabditis elegans HEN1 ortholog, HENN-1, methylates and stabilizes select subclasses of germline small RNAs. PLoS Genet 8(4): e1002617.. pmid:22548001
  51. 51. Pek JW, Kai T (2011) DEAD-box RNA helicase Belle/DDX3 and the RNA interference pathway promote mitotic chromosome segregation. Proc Natl Acad Sci USA 108:12007–12012. pmid:21730191
  52. 52. Ansari A, Schwer B (1995) SLU7 and a novel activity, SSF1, act during the PRP16-dependent step of yeast pre-mRNA splicing. EMBO J 14:4001–4009. pmid:7664739
  53. 53. Wu-Scharf D, Jeong B, Zhang C, Cerutti H (2000) Transgene and transposon silencing in Chlamydomonas reinhardtii by a DEAH-Box RNA helicase. Science 290:1159–1162. pmid:11073454
  54. 54. Cauchi RJ, Davies KE, Liu JL (2008) A motor function for the DEAD-Box RNA helicase, Gemin3, in Drosophila. PLoS Genet 4(11): e1000265.. pmid:19023405
  55. 55. Schneider MD, Najand N, Chaker S, Pare JM, Hakins J, et al. (2006) Gawky is a component of cytoplasmic mRNA processing bodies required for early Drosophila development. J Cell Biol 174:349–358. pmid:16880270
  56. 56. Lipardi C, Paterson BM (2010) Identification of an RNA-dependent RNA polymerase in Drosophila establishes a common theme in RNA silencing. Fly 4:30–35. pmid:20023402
  57. 57. Lee MH, Schedl T (2001) Identification of in vivo mRNA targets of GLD-1, a maxi-KH motif containing protein required for C. elegans germ cell development. Genes Dev 15:2408–2420. pmid:11562350
  58. 58. Gourley BL, Parker SB, Jones BJ, Zumbrennen B, Leibold EA (2003) Cytosolic Aconitase and Ferritin are regulated by iron in Caenorhabditis elegans. J Biol Chem 278:3227–3234. pmid:12438312
  59. 59. Hunter CP, Winston WM, Molodowith C, Feinberg EH, Shih J, et al. (2006) Systemic RNAi in Caenorhabditis elegans. Cold Spring Harb Symp Quant Biol 71:95–100. pmid:17381285
  60. 60. Tomoyasu Y, Miller SC, Tomita S, Schoppmeier M, Grossman D, et al. (2008) Exploring systemic RNA interference in insects: a genome-wide survey for RNAi genes in Tribolium. Genome Biol 9:R10. pmid:18201385
  61. 61. Saleh MC, Van Rij RP, Hekele A, Gillis A, Foley E, et al. (2006) The endocytic pathway mediates cell entry of dsRNA to induce RNAi silencing. Nat Cell Biol Huvenne H, Smagghe G (2010) Mechanisms of dsRNA uptake in insects and potential of RNAi for pest control: A review. J Insect Physiol 56:227–235.
  62. 62. Ulvila J, Parikka M, Kleino A, Sormunen R, Ezekowitz A, et al. (2006) Double-stranded RNA is internalized by Scavenger receptor-mediated endocytosis in Drosophila S2 cells. J Biol Chem 281:14370–14375. pmid:16531407
  63. 63. Sabin LR, Zhou R, Gruber J, Lukinova N, Bambina S, et al. (2009) Ars2 regulates both miRNA- and siRNA-dependent silencing and suppresses RNA virus infection in Drosophila. Cell 138:340–351. pmid:19632183
  64. 64. Saleh MC, Tassetto M, van Rij R, Goic B, Gausson V et al. (2009) Antiviral immunity in Drosophila requires systemic RNA interference spread. Nature 458:346–351. pmid:19204732
  65. 65. Kennedy S, Wang D, Ruvkun G (2004) A conserved siRNA-degrading RNase negatively regulates RNA interference in C. elegans. Nature 427: 645–649.
  66. 66. Ramachandran V, Chen X (2008) Degradation of microRNAs by a family of exoribonuclease in Arabidopsis. Science 321:1490–1492. pmid:18787168
  67. 67. Han BW, Hung JH, Weng Z, Zamore PD, Ameres S (2011) The 3’-to-5’ exoribonuclease Nibbler shapes the 3’ ends of microRNAs bound to Drosophila Argonaute1. Curr Biol 27:1878–1887.
  68. 68. Liu J, Swevers L, Latrou K, Huvenne H, Smagghe G (2012) Bombyx mori DNA/RNA non-specific nuclease: Expression of isoforms in insect culture cells, subcellular localization and functional assays. J Insect Physiol 58:1166–1176. pmid:22709524
  69. 69. Morlando M, Ballarino M, Gromak N, Pagano F, Bozzoni I, et al. (2008) Primary microRNA transcripts are processed co-transcriptionally. Nat Struct Mol Biol 15:902–909. pmid:19172742
  70. 70. Yamanaka S, Mehta S, Reyes-Turcu FE, Zhuang F, Fuchs RT, et al. (2013) RNAi triggered by specialized machinery silences developmental genes and retrotransposons. Nature 493:557–561. pmid:23151475
  71. 71. Miller SC, Miyata K, Brown SJ, Tomoyasu Y (2012) Dissecting systemic RNA interference in the Red Flour Beetle Tribolium castaneum; Parameters affecting the Efficiency of RNAi. PLoS ONE 7(10): e47431.. pmid:23133513
  72. 72. Tomoyasu Y, Denell RE (2004) Larval RNAi in Tribolium (Coleoptera) for analyzing adult development. Dev Gene Evol 214:575–578.