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      Large number of putative chemoreception and pheromone biosynthesis genes revealed by analyzing transcriptome from ovipositor-pheromone glands of Chilo suppressalis

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          Abstract

          The chemoreception role of moth ovipositor has long been suggested, but its molecular mechanism is mostly unknown. By transcriptomic analysis of the female ovipositor-pheromone glands (OV-PG) of Chilo suppressalis, we obtained 31 putative chemoreception genes (9 OBPs, 10 CSPs, 2 ORs, 1 SNMP, 8 CXEs and 1 AOX), in addition to 32 genes related to sex pheromone biosynthesis (1 FAS, 6 Dess, 10 FARs, 2 ACOs, 1 ACC, 4 FATPs, 3 ACBPs and 5 ELOs). Tissue expression profiles further revealed that CsupCSP2 and CsupCSP10 were OV-PG biased, while most chemoreception genes were highly and preferably expressed in antennae. This suggests that OV-PG employs mostly the same chemoreception proteins as in antennae, although the physiological roles of these proteins might be different in OV-PG. Of the 32 pheromone biosynthesis related genes, CsupDes4, CsupDes5 and CsupFAR2 are strongly OV-PG biased, and clustered with functionally validated genes from other moths, strongly indicating their involvement in specific step of the pheromone biosynthesis. Our study for the first time identified a large number of putative chemoreception genes, and provided an important basis for exploring the chemoreception mechanisms of OV-PG in C. suppressalis, as well as other moth species.

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          Insect olfactory receptors are heteromeric ligand-gated ion channels.

          Koji Sato, Maurizio Pellegrino, Takao Nakagawa … (2008)
          In insects, each olfactory sensory neuron expresses between one and three ligand-binding members of the olfactory receptor (OR) gene family, along with the highly conserved and broadly expressed Or83b co-receptor. The functional insect OR consists of a heteromeric complex of unknown stoichiometry but comprising at least one variable odorant-binding subunit and one constant Or83b family subunit. Insect ORs lack homology to G-protein-coupled chemosensory receptors in vertebrates and possess a distinct seven-transmembrane topology with the amino terminus located intracellularly. Here we provide evidence that heteromeric insect ORs comprise a new class of ligand-activated non-selective cation channels. Heterologous cells expressing silkmoth, fruitfly or mosquito heteromeric OR complexes showed extracellular Ca2+ influx and cation-non-selective ion conductance on stimulation with odorant. Odour-evoked OR currents are independent of known G-protein-coupled second messenger pathways. The fast response kinetics and OR-subunit-dependent K+ ion selectivity of the insect OR complex support the hypothesis that the complex between OR and Or83b itself confers channel activity. Direct evidence for odorant-gated channels was obtained by outside-out patch-clamp recording of Xenopus oocyte and HEK293T cell membranes expressing insect OR complexes. The ligand-gated ion channel formed by an insect OR complex seems to be the basis for a unique strategy that insects have acquired to respond to the olfactory environment.
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            Processing of gene expression data generated by quantitative real-time RT-PCR.

            Patrick Y Muller, Harald Janovjak, André Miserez … (2002)
            Quantitative real-time PCR represents a highly sensitive and powerful technique for the quantitation of nucleic acids. It has a tremendous potential for the high-throughput analysis of gene expression in research and routine diagnostics. However, the major hurdle is not the practical performance of the experiments themselves but rather the efficient evaluation and the mathematical and statistical analysis of the enormous amount of data gained by this technology, as these functions are not included in the software provided by the manufacturers of the detection systems. In this work, we focus on the mathematical evaluation and analysis of the data generated by quantitative real-time PCR, the calculation of the final results, the propagation of experimental variation of the measured values to the final results, and the statistical analysis. We developed a Microsoft Excel-based software application coded in Visual Basic for Applications, called Q-Gene, which addresses these points. Q-Gene manages and expedites the planning, performance, and evaluation of quantitative real-time PCR experiments, as well as the mathematical and statistical analysis, storage, and graphical presentation of the data. The Q-Gene software application is a tool to cope with complex quantitative real-time PCR experiments at a high-throughput scale and considerably expedites and rationalizes the experimental setup, data analysis, and data management while ensuring highest reproducibility.
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              Q-Gene: processing quantitative real-time RT-PCR data.

              Perikles Simon (2003)
              Q-Gene is an application for the processing of quantitative real-time RT-PCR data. It offers the user the possibility to freely choose between two principally different procedures to calculate normalized gene expressions as either means of Normalized Expressions or Mean Normalized Expressions. In this contribution it will be shown that the calculation of Mean Normalized Expressions has to be used for processing simplex PCR data, while multiplex PCR data should preferably be processed by calculating Normalized Expressions. The two procedures, which are currently in widespread use and regarded as more or less equivalent alternatives, should therefore specifically be applied according to the quantification procedure used. Web access to this program is provided at http://www.biotechniques.com/softlib/qgene.html
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                Author and article information

                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 20 January 2015
                Publication date Collection: 2015
                Volume: 5
                Electronic Location Identifier: 7888
                Affiliations
                [1 ]Education Ministry Key Laboratory of Integrated Management of Crop Diseases and Pests, College of Plant Protection, Nanjing Agricultural University , Nanjing, China
                [2 ]College of Life Sciences, Huaibei Normal University , Huaibei, China
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                Publisher Item ID: srep07888
                DOI: 10.1038/srep07888
                PMC ID: 5379011
                PubMed ID: 25601555
                SO-VID: 84e1daf2-09ed-4165-8937-4b03b3b851d6
                Copyright © Copyright © 2015, Macmillan Publishers Limited. All rights reserved
                License:

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/

                History
                Date received : 03 July 2014
                Date accepted : 04 December 2014
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                Subject: Article

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