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      Comparative transcriptome analysis reveals differences in gene expression in whitefly following individual or combined applications of Akanthomyces attenuatus (Zare & Gams) and matrine

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          Abstract

          Background

          Bemisia tabaci Gennadius (Hemiptera: Aleyrodidae) is a serious pest of crops in different regions of the world. Our recent studies on the joint application of Akanthomyces attenuatus (a pathogenic insect fungus) and matrine (a botanical insecticide) against B. tabaci have shown promising results. Using RNA sequencing (RNA-Seq), we identified differentially expressed genes involved in whitefly responses to single or mixed applications of A. attenuatus and matrine.

          Methods

          In this study, we compared the transcriptome profiles of B. tabaci treated with individual and combined treatments of A. attenuatus and matrine to determine variations in gene expression among whiteflies in response to different treatments.

          Results

          Transcriptomic data analysis showed differential expression of 71, 1194, and 51 genes in response to A. attenuatus (BtA), matrine (BtM), and A. attenuatus + matrine (BtAM) treatment, respectively. A total of 65 common differentially expressed genes (DEGs) were identified between whiteflies treated with A. attenuatus (BtA) and matrine (BtM). A comparison of DEGs across the three treatments (BtA, BtM, and BtAM) revealed two common DEGs. The results also revealed that AMPK signaling, apoptosis, and drug metabolism pathways are likely involved in whitefly defense responses against A. attenuatus and matrine infection. Furthermore, a notable suppression of general metabolism and immune response genes was observed in whiteflies treated with A. attenuatus + matrine (BtAM) compared to whiteflies treated with individual A. attenuatus (BtA) or matrine (BtM) treatments.

          Conclusion

          Dynamic changes in the number of differentially expressed genes were observed in B. tabaci subjected to different treatments (BtA, BtM, and BtAM). To the best of our knowledge, this is the first report on the molecular interactions between whitefly and individual or combined treatments of A. attenuatus and matrine. These results will further improve our knowledge of the infection mechanism and complex biochemical processes involved in the synergistic action of A. attenuatus and matrine against B. tabaci.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-022-09048-9.

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          KEGG: kyoto encyclopedia of genes and genomes.

          M Kanehisa (2000)
          KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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            RNA-Seq: a revolutionary tool for transcriptomics.

            Zhong Wang, Mark Gerstein, Michael Snyder (2009)
            RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.
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              RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays.

              John Marioni, Christopher E Mason, Shrikant Mane … (2008)
              Ultra-high-throughput sequencing is emerging as an attractive alternative to microarrays for genotyping, analysis of methylation patterns, and identification of transcription factor binding sites. Here, we describe an application of the Illumina sequencing (formerly Solexa sequencing) platform to study mRNA expression levels. Our goals were to estimate technical variance associated with Illumina sequencing in this context and to compare its ability to identify differentially expressed genes with existing array technologies. To do so, we estimated gene expression differences between liver and kidney RNA samples using multiple sequencing replicates, and compared the sequencing data to results obtained from Affymetrix arrays using the same RNA samples. We find that the Illumina sequencing data are highly replicable, with relatively little technical variation, and thus, for many purposes, it may suffice to sequence each mRNA sample only once (i.e., using one lane). The information in a single lane of Illumina sequencing data appears comparable to that in a single array in enabling identification of differentially expressed genes, while allowing for additional analyses such as detection of low-expressed genes, alternative splice variants, and novel transcripts. Based on our observations, we propose an empirical protocol and a statistical framework for the analysis of gene expression using ultra-high-throughput sequencing technology.
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                Author and article information

                Contributors
                Jianhui Wu: jhw@scau.edu.cn
                Tingfei Sun: suntingfei@stu.scau.edu.cn
                Muhammad Hamid Bashir: hamid_uaf@yahoo.com
                Baoli Qiu: baoliqiu@cqun.edu.cn
                Xingmin Wang: wangxmcn@scau.edu.cn
                Shaukat Ali: aliscau@scau.edu.cn
                Journal
                Journal ID (nlm-ta): BMC Genomics
                Journal ID (iso-abbrev): BMC Genomics
                Title: BMC Genomics
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1471-2164
                Publication date (Electronic): 6 December 2022
                Publication date PMC-release: 6 December 2022
                Publication date Collection: 2022
                Volume: 23
                Electronic Location Identifier: 808
                Affiliations
                [1 ]GRID grid.20561.30, ISNI 0000 0000 9546 5767, Key Laboratory of Bio-Pesticide Innovation and Application, Engineering Research Centre of Biological Control, , South China Agricultural University, ; Guangzhou, 510642 China
                [2 ]GRID grid.20561.30, ISNI 0000 0000 9546 5767, Engineering Research Center of Biological Control, Ministry of Education and Guangdong Province, , South China Agricultural University, ; Guangzhou, 510642 China
                [3 ]GRID grid.413016.1, ISNI 0000 0004 0607 1563, Department of Entomology, , University of Agriculture, ; Faisalabad, Pakistan
                [4 ]GRID grid.411575.3, ISNI 0000 0001 0345 927X, Chongqing Key Laboratory of Vector Insects, College of Life Sciences, , Chongqing Normal University, ; Chongqing, 401331 China
                Article
                Publisher ID: 9048
                DOI: 10.1186/s12864-022-09048-9
                PMC ID: 9727895
                PubMed ID: 36474158
                SO-VID: b32af59c-9879-4b70-89f0-fb0c9c1ef2c0
                Copyright © © The Author(s) 2022
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                Date received : 29 April 2022
                Date accepted : 25 November 2022
                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © The Author(s) 2022

                ScienceOpen disciplines: Genetics
                Keywords: bemisia tabaci,akanthomyces attenuatus,matrine,synergistic action,immune response
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: bemisia tabaci, akanthomyces attenuatus, matrine, synergistic action, immune response

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