31
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Transcriptomics-Based Approach Identifies Spinosad-Associated Targets in the Colorado Potato Beetle, Leptinotarsa decemlineata

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Simple Summary

          The Colorado potato beetle Leptinotarsa decemlineata is a potato pest that can cause substantial damages to potato crops worldwide. Multiple approaches have been leveraged to control this pest including the use of a variety of insecticides. Resistance to different insecticides aimed at controlling this insect has been reported and much work has been conducted in recent years to elucidate the underlying molecular changes associated with insecticide resistance in L. decemlineata. However, information is sparse regarding the molecular impact associated with spinosad treatment in this insect pest. The current study thus explores transcriptional changes associated with spinosad response in L. decemlineata exposed to this compound using high-throughput sequencing. Results presented show multiple transcripts of interest that exhibit differential expression in spinosad-treated L. decemlineata and provide a preliminary footprint of transcripts affected by this insecticide in this potato pest. Select targets identified in this signature should be further explored in follow-up studies to better characterize their contribution, if any, in the process of spinosad resistance.

          Abstract

          The Colorado potato beetle Leptinotarsa decemlineata is an insect pest that threatens potato crops globally. The primary method to control its damage on potato plants is the use of insecticides, including imidacloprid, chlorantraniliprole and spinosad. However, insecticide resistance has been frequently observed in Colorado potato beetles. The molecular targets and the basis of resistance to imidacloprid and chlorantraniliprole have both been previously quantified. This work was undertaken with the overarching goal of better characterizing the molecular changes associated with spinosad exposure in this insect pest. Next-generation sequencing was conducted to identify transcripts that were differentially expressed between Colorado potato beetles exposed to spinosad versus control insects. Results showed several transcripts that exhibit different expression levels between the two conditions, including ones coding for venom carboxylesterase-6, chitinase 10, juvenile hormone esterase and multidrug resistance-associated protein 4. In addition, several microRNAs, such as miR-12-3p and miR-750-3p, were also modulated in the investigated conditions. Overall, this work reveals a molecular footprint underlying spinosad response in Colorado potato beetles and provides novel leads that could be targeted as part of RNAi-based approaches to control this insect pest.

          Related collections

          Most cited references63

          • Record: found
          • Abstract: found
          • Article: not found

          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

              Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
                Bookmark

                Author and article information

                Journal
                Insects
                Insects
                insects
                Insects
                MDPI
                2075-4450
                21 November 2020
                November 2020
                : 11
                : 11
                : 820
                Affiliations
                [1 ]Department of Chemistry and Biochemistry, Université de Moncton, 18 Antonine-Maillet Avenue, Moncton, NB E1A 3E9, Canada; epb6696@ 123456umoncton.ca (P.B.); epd3362@ 123456umoncton.ca (P.D.)
                [2 ]Atlantic Cancer Research Institute, Pavillon Hôtel-Dieu 35 Providence Street, Moncton, NB E1C 8X3, Canada; Gabrielw@ 123456canceratl.ca (G.W.); simic@ 123456canceratl.ca (S.C.); jacynthe.lacroix@ 123456canceratl.ca (J.L.); nicolas.crapoulet@ 123456vitalitenb.ca (N.C.)
                [3 ]Fredericton Research and Development Centre, Agriculture and Agri-Food Canada, 850 Lincoln Road, Fredericton, NB E3B 4Z7, Canada; chandra.moffat@ 123456canada.ca
                Author notes
                [* ]Correspondence: pier.morin@ 123456umoncton.ca ; Tel.: +1-(506)-858-4355; Fax: +1-(506)-858-4541
                Author information
                https://orcid.org/0000-0002-6244-9191
                Article
                insects-11-00820
                10.3390/insects11110820
                7700309
                33233355
                3aff102a-56ec-49d9-a141-4a9b89cd3f07
                © 2020 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 ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 30 October 2020
                : 19 November 2020
                Categories
                Article

                colorado potato beetle,insecticides,micrornas,next-generation sequencing,non-coding rnas,spinosad,transcriptomics

                Comments

                Comment on this article