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      Terpenes and Terpenoids in Plants: Interactions with Environment and Insects

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          Abstract

          The interactions of plants with environment and insects are bi-directional and dynamic. Consequently, a myriad of mechanisms has evolved to engage organisms in different types of interactions. These interactions can be mediated by allelochemicals known as volatile organic compounds (VOCs) which include volatile terpenes (VTs). The emission of VTs provides a way for plants to communicate with the environment, including neighboring plants, beneficiaries (e.g., pollinators, seed dispersers), predators, parasitoids, and herbivores, by sending enticing or deterring signals. Understanding terpenoid distribution, biogenesis, and function provides an opportunity for the design and implementation of effective and efficient environmental calamity and pest management strategies. This review provides an overview of plant–environment and plant–insect interactions in the context of terpenes and terpenoids as important chemical mediators of these abiotic and biotic interactions.

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          Most cited references115

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          New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

          PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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            Abiotic Stress Signaling and Responses in Plants.

            As sessile organisms, plants must cope with abiotic stress such as soil salinity, drought, and extreme temperatures. Core stress-signaling pathways involve protein kinases related to the yeast SNF1 and mammalian AMPK, suggesting that stress signaling in plants evolved from energy sensing. Stress signaling regulates proteins critical for ion and water transport and for metabolic and gene-expression reprogramming to bring about ionic and water homeostasis and cellular stability under stress conditions. Understanding stress signaling and responses will increase our ability to improve stress resistance in crops to achieve agricultural sustainability and food security for a growing world population.
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              Pfam: the protein families database

              Pfam, available via servers in the UK (http://pfam.sanger.ac.uk/) and the USA (http://pfam.janelia.org/), is a widely used database of protein families, containing 14 831 manually curated entries in the current release, version 27.0. Since the last update article 2 years ago, we have generated 1182 new families and maintained sequence coverage of the UniProt Knowledgebase (UniProtKB) at nearly 80%, despite a 50% increase in the size of the underlying sequence database. Since our 2012 article describing Pfam, we have also undertaken a comprehensive review of the features that are provided by Pfam over and above the basic family data. For each feature, we determined the relevance, computational burden, usage statistics and the functionality of the feature in a website context. As a consequence of this review, we have removed some features, enhanced others and developed new ones to meet the changing demands of computational biology. Here, we describe the changes to Pfam content. Notably, we now provide family alignments based on four different representative proteome sequence data sets and a new interactive DNA search interface. We also discuss the mapping between Pfam and known 3D structures.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                06 October 2020
                October 2020
                : 21
                : 19
                : 7382
                Affiliations
                [1 ]School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong; delboncan@ 123456gmail.com
                [2 ]Center for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong
                [3 ]Simon F.S. Li Marine Science Laboratory, The Chinese University of Hong Kong, Shatin, Hong Kong; stacey.tsang@ 123456link.cuhk.edu.hk (S.S.K.T.); R21381184@ 123456link.cuhk.edu.hk (C.L.); ivyleeting@ 123456yahoo.com.hk (I.H.T.L.)
                Author notes
                [†]

                Contributed equally.

                Author information
                https://orcid.org/0000-0002-6673-8740
                https://orcid.org/0000-0002-0489-3884
                https://orcid.org/0000-0003-1355-8495
                Article
                ijms-21-07382
                10.3390/ijms21197382
                7583029
                33036280
                3869e733-c14b-4502-8047-84d3bb093e8d
                © 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
                : 23 September 2020
                : 01 October 2020
                Categories
                Review

                Molecular biology
                terpenes,terpenoids,plants,insect,abiotic,biotic,interaction,environment
                Molecular biology
                terpenes, terpenoids, plants, insect, abiotic, biotic, interaction, environment

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