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      Two novel venom proteins underlie divergent parasitic strategies between a generalist and a specialist parasite

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          Abstract

          Parasitoids are ubiquitous in natural ecosystems. Parasitic strategies are highly diverse among parasitoid species, yet their underlying genetic bases are poorly understood. Here, we focus on the divergent adaptation of a specialist and a generalist drosophilid parasitoids. We find that a novel protein (Lar) enables active immune suppression by lysing the host lymph glands, eventually leading to successful parasitism by the generalist. Meanwhile, another novel protein (Warm) contributes to a passive strategy by attaching the laid eggs to the gut and other organs of the host, leading to incomplete encapsulation and helping the specialist escape the host immune response. We find that these diverse parasitic strategies both originated from lateral gene transfer, followed with duplication and specialization, and that they might contribute to the shift in host ranges between parasitoids. Our results increase our understanding of how novel gene functions originate and how they contribute to host adaptation.

          Abstract

          Parasitism is a widespread evolutionary strategy. A study that spans functional and evolutionary genomics identifies the molecular basis and history underlying two genes that have mediated divergent parasitic strategies (specialist vs generalist) between two sister species of parasitoid wasp.

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          Most cited references97

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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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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              MUSCLE: multiple sequence alignment with high accuracy and high throughput.

              We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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                Author and article information

                Contributors
                jhhuang@zju.edu.cn
                xxchen@zju.edu.cn
                szhan@sibs.ac.cn
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                11 January 2021
                11 January 2021
                2021
                : 12
                : 234
                Affiliations
                [1 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, Institute of Insect Sciences, Ministry of Agriculture Key Lab of Molecular Biology of Crop Pathogens and Insect Pests, College of Agriculture and Biotechnology, , Zhejiang University, ; 310058 Hangzhou, China
                [2 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, , Zhejiang University, ; 310058 Hangzhou, China
                [3 ]GRID grid.9227.e, ISNI 0000000119573309, CAS Key Laboratory of Insect Developmental and Evolutionary Biology, CAS Center for Excellence in Molecular Plant Sciences, , Chinese Academy of Sciences, ; Shanghai, China
                [4 ]GRID grid.410726.6, ISNI 0000 0004 1797 8419, CAS Center for Excellence in Biotic Interactions, , University of Chinese Academy of Sciences, ; Beijing, China
                [5 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, State Key Lab of Rice Biology, , Zhejiang University, ; 310058 Hangzhou, China
                Author information
                http://orcid.org/0000-0001-6509-1765
                http://orcid.org/0000-0003-4546-061X
                http://orcid.org/0000-0002-2237-6848
                http://orcid.org/0000-0002-9109-8853
                http://orcid.org/0000-0002-1378-6765
                Article
                20332
                10.1038/s41467-020-20332-8
                7801585
                33431897
                8f43c8aa-e202-4160-9e55-1cf28847623a
                © The Author(s) 2021

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 June 2020
                : 25 November 2020
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                © The Author(s) 2021

                Uncategorized
                behavioural ecology,evolutionary genetics,rnai,entomology
                Uncategorized
                behavioural ecology, evolutionary genetics, rnai, entomology

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