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      RNAi-Mediated Silencing of the Chitinase 5 Gene for Fall Webworm ( Hyphantria cunea) Can Inhibit Larval Molting Depending on the Timing of dsRNA Injection

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          Abstract

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          The fall webworm, Hyphantria cunea, is a worldwide invasive pest causing serious ecological and economic damage. The use of RNAi is a feasible strategy for controlling this pest. In this study, we evaluated the importance of the chitinase 5 gene ( HcCht5) in the development of H. cunea larvae. We found that the RNAi-mediated silencing of HcCht5 arrested molting and caused larval mortality depending on the dsRNA injection time. The silencing of HcCht5 down-regulated genes that were related to chitin metabolism, molting hormone signaling, and detoxification metabolism. Our findings indicate that HcCht5 is an important gene in regulating larval development and a promising target for RNAi-mediated pest management of the pest H. cunea.

          Abstract

          Chitinases, which are crucial enzymes required for chitin degradation and reconstruction, are often selectively considered to be effective molecular targets for pest control due to their critical roles in insect development. Although the Hyphantria cunea chitinase gene has been reported previously, its sequence characteristics, gene function, and feasibility as a potential target for pest management were absent. In the present study, we characterized the H. cunea chitinase gene and designated it HcCht5. Phylogenic and domain structure analysis suggested that HcCht5 contained the typical chitinase features and was clustered into chitinase group I. Tissue-specific and developmental expression pattern analysis with Real-Time Quantitative PCR (RT-qPCR) showed that HcCht5 was mainly expressed in the integument tissues and that the transcript levels peaked during molting. RNA interference (RNAi)-mediated silencing of HcCht5 caused 33.3% (2 ug) and 66.7% (4 ug) mortality rates after double-stranded RNA (dsRNA) injection. Importantly, the interference efficiency of HcCht5 depended on the injection time of double-stranded RNA (dsRNA), as the pre-molting treatment achieved molt arrest more effectively. In addition, transcriptome sequencing (RNA-seq) analysis of RNAi samples demonstrated silencing of the down-regulated HcCht5 genes related to chitin metabolism and molting hormone signaling, as well as genes related to detoxification metabolism. Our results indicate the essential role of HcCht5 in H. cunea development and detail the involvement of its gene function in the larval molting process.

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          RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

          Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
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            Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data

            Massively-parallel cDNA sequencing has opened the way to deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here, we present the Trinity methodology for de novo full-length transcriptome reconstruction, and evaluate it on samples from fission yeast, mouse, and whitefly – an insect whose genome has not yet been sequenced. Trinity fully reconstructs a large fraction of the transcripts present in the data, also reporting alternative splice isoforms and transcripts from recently duplicated genes. In all cases, Trinity performs better than other available de novo transcriptome assembly programs, and its sensitivity is comparable to methods relying on genome alignments. Our approach provides a unified and general solution for transcriptome reconstruction in any sample, especially in the complete absence of a reference genome.
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              Multiple sequence alignment with the Clustal series of programs.

              R Chenna (2003)
              The Clustal series of programs are widely used in molecular biology for the multiple alignment of both nucleic acid and protein sequences and for preparing phylogenetic trees. The popularity of the programs depends on a number of factors, including not only the accuracy of the results, but also the robustness, portability and user-friendliness of the programs. New features include NEXUS and FASTA format output, printing range numbers and faster tree calculation. Although, Clustal was originally developed to run on a local computer, numerous Web servers have been set up, notably at the EBI (European Bioinformatics Institute) (http://www.ebi.ac.uk/clustalw/).
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Insects
                Insects
                insects
                Insects
                MDPI
                2075-4450
                30 April 2021
                May 2021
                : 12
                : 5
                : 406
                Affiliations
                Key Laboratory of Forest Protection of National Forestry and Grassland Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China; zhx3355@ 123456126.com (X.Z.); cafwy1016@ 123456163.com (Y.W.); Zhangsf@ 123456caf.ac.cn (S.Z.); xbkong@ 123456sina.com (X.K.); liufu@ 123456sina.com (F.L.)
                Author notes
                [* ]Correspondence: zhangzhen@ 123456caf.ac.cn
                Article
                insects-12-00406
                10.3390/insects12050406
                8147239
                33946562
                3923811c-a4fd-472d-b3f5-0fcdffb618f5
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 01 March 2021
                : 29 April 2021
                Categories
                Article

                hyphantria cunea,chitinase,molting,rnai efficiency,transcriptome analysis

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