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      Evolutionarily conserved odorant-binding proteins participate in establishing tritrophic interactions

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          Summary

          Attracting herbivores and their natural enemies is a standard method where plant volatiles mediate tritrophic interactions. However, it remains unknown whether the shared attraction has a shared chemosensory basis. Here we focus on the odorant-binding proteins (OBPs), a gene family integral to peripheral detection of odoriferous chemicals. Previous evidence suggests that the herbivorous beetle Monochamus alternatus and its parasitoid beetle Dastarcus helophoroides are attracted to stressed pines. In this study, (+)-fenchone, emitted by stressed pines, is found to be attracted to M. alternatus and D. helophoroides in behavioral assays. Meanwhile, two orthologous OBPs with a slower evolutionary rate, respectively, from the two insects are shown to bind with (+)-fenchone, and the attraction is abolished after RNAi. These results show the ability of evolutionarily conserved OBPs from herbivores and their enemies to detect the same plant volatiles, providing an olfactory mechanism of chemical signals–mediated tritrophic relationships.

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          Highlights

          • Monochamus alternatus and Dastarcus helophoroides are attracted to (+)-fenchone from host pines

          • They harbor evolutionarily conserved odorant-binding proteins (OBPs)

          • One pair of the conserved OBPs can bind with (+)-fenchone

          • The behavioral preference is lost upon RNAi knockdown of the OBPs

          Abstract

          Biochemistry; Evolutionary biology; Phylogenetics

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          Most cited references72

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

            Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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              PAML 4: phylogenetic analysis by maximum likelihood.

              PAML, currently in version 4, is a package of programs for phylogenetic analyses of DNA and protein sequences using maximum likelihood (ML). The programs may be used to compare and test phylogenetic trees, but their main strengths lie in the rich repertoire of evolutionary models implemented, which can be used to estimate parameters in models of sequence evolution and to test interesting biological hypotheses. Uses of the programs include estimation of synonymous and nonsynonymous rates (d(N) and d(S)) between two protein-coding DNA sequences, inference of positive Darwinian selection through phylogenetic comparison of protein-coding genes, reconstruction of ancestral genes and proteins for molecular restoration studies of extinct life forms, combined analysis of heterogeneous data sets from multiple gene loci, and estimation of species divergence times incorporating uncertainties in fossil calibrations. This note discusses some of the major applications of the package, which includes example data sets to demonstrate their use. The package is written in ANSI C, and runs under Windows, Mac OSX, and UNIX systems. It is available at -- (http://abacus.gene.ucl.ac.uk/software/paml.html).
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                Author and article information

                Contributors
                Journal
                iScience
                iScience
                iScience
                Elsevier
                2589-0042
                23 June 2022
                15 July 2022
                23 June 2022
                : 25
                : 7
                : 104664
                Affiliations
                [1 ]Hubei Insect Resources Utilization and Sustainable Pest Management Key Laboratory, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
                [2 ]Key Laboratory of Forest Protection of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
                Author notes
                []Corresponding author mqwang@ 123456mail.hzau.edu.cn
                [3]

                Lead contact

                Article
                S2589-0042(22)00936-1 104664
                10.1016/j.isci.2022.104664
                9263996
                35811847
                dd664053-35ca-4365-bb86-5f6709c290f7
                © 2022 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 4 January 2022
                : 6 May 2022
                : 20 June 2022
                Categories
                Article

                biochemistry,evolutionary biology,phylogenetics
                biochemistry, evolutionary biology, phylogenetics

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