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      New estimates of genome size in Orthoptera and their evolutionary implications

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          Abstract

          Animal genomes vary widely in size, and much of their architecture and content remains poorly understood. Even among related groups, such as orders of insects, genomes may vary in size by orders of magnitude–for reasons unknown. The largest known insect genomes were repeatedly found in Orthoptera, e.g., Podisma pedestris (1C = 16.93 pg), Stethophyma grossum (1C = 18.48 pg) and Bryodemella holdereri (1C = 18.64 pg). While all these species belong to the suborder of Caelifera, the ensiferan Deracantha onos (1C = 19.60 pg) was recently found to have the largest genome. Here, we present new genome size estimates of 50 further species of Ensifera (superfamilies Gryllidea, Tettigoniidea) and Caelifera (Acrididae, Tetrigidae) based on flow cytometric measurements. We found that Bryodemella tuberculata (Caelifera: Acrididae) has the so far largest measured genome of all insects with 1C = 21.96 pg (21.48 gBp). Species of Orthoptera with 2n = 16 and 2n = 22 chromosomes have significantly larger genomes than species with other chromosome counts. Gryllidea genomes vary between 1C = 0.95 and 2.88 pg, and Tetrigidae between 1C = 2.18 and 2.41, while the genomes of all other studied Orthoptera range in size from 1C = 1.37 to 21.96 pg. Reconstructing ancestral genome sizes based on a phylogenetic tree of mitochondrial genomic data, we found genome size values of >15.84 pg only for the nodes of Bryodemella holdereri / B. tuberculata and Chrysochraon dispar / Euthystira brachyptera. The predicted values of ancestral genome sizes are 6.19 pg for Orthoptera, 5.37 pg for Ensifera, and 7.28 pg for Caelifera. The reasons for the large genomes in Orthoptera remain largely unknown, but a duplication or polyploidization seems unlikely as chromosome numbers do not differ much. Sequence-based genomic studies may shed light on the underlying evolutionary mechanisms.

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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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            Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

            Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
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              IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

              Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: InvestigationRole: ValidationRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 March 2023
                2023
                : 18
                : 3
                : e0275551
                Affiliations
                [1 ] Leibniz Institute for the Analysis of Biodiversity Change (LIB), Museum of Nature, Hamburg, Germany
                [2 ] Institute of Medical Biochemistry and Laboratory Diagnostics, Centre of Oncocytogenomics, General University Hospital in Prague, Prague, Czech Republic
                [3 ] Department of Biology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
                [4 ] Staatliches Museum für Naturkunde Stuttgart, Stuttgart, Germany
                [5 ] Leibniz Institute for the Analysis of Biodiversity Change (LIB), Museum Koenig, Bonn, Germany
                [6 ] Zoologische Staatssammlung München (ZSM-SNSB), München, Germany
                [7 ] Czech Academy of Sciences, Institute of Botany, Průhonice, Czech Republic
                [8 ] Naturhistorisches Museum Wien, Wien, Austria
                Laboratoire de Biologie du Développement de Villefranche-sur-Mer, FRANCE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-8010-4157
                Article
                PONE-D-22-25859
                10.1371/journal.pone.0275551
                10016648
                36920952
                baf8c26e-d938-49ec-8dd0-e992cd304a0a
                © 2023 Hawlitschek et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 September 2022
                : 24 February 2023
                Page count
                Figures: 4, Tables: 5, Pages: 20
                Funding
                Funded by: Czech Academy of Sciences
                Award ID: RVO 67985939
                Award Recipient :
                Funding was provided by a grant from the Czech Academy of Sciences (RVO 67985939) to Pavel Trávníček. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Genomics
                Animal Genomics
                Invertebrate Genomics
                Biology and Life Sciences
                Genetics
                Genomics
                Animal Genomics
                Biology and Life Sciences
                Genetics
                Genomics
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Biology and Life Sciences
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Computer and Information Sciences
                Data Management
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Biology and Life Sciences
                Genetics
                Genomics
                Human Genomics
                Biology and Life Sciences
                Zoology
                Entomology
                Insects
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Arthropoda
                Insects
                Biology and Life Sciences
                Biochemistry
                Bioenergetics
                Energy-Producing Organelles
                Mitochondria
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                Cell Biology
                Cellular Structures and Organelles
                Energy-Producing Organelles
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                Computational Biology
                Genome Evolution
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                Genetics
                Genomics
                Genome Evolution
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                Evolutionary Biology
                Molecular Evolution
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                Custom metadata
                All relevant data are within the paper and its Supporting Information files. All measurement values will be provided to the Animal Genome Size Database.

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