Uncovering hidden diversity within the <i>Euwallacea fornicatus</i> species complex in China

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Abstract

Accurate species delimitation is an important component of pest management. The Euwallacea fornicatus species complex (Coleoptera: Curculionidae: Scolytinae) includes a series of morphologically similar forest pests that cause huge economic losses both in invaded regions and in the native region. The current hypothesis about the species complex postulates the existence of four species: E. fornicatus (Eichhoff), E. fornicatior (Eggers), E. kuroshio Gomez and Hulcr, and E. perbrevis (Schedl). To test the current hypothesis and reveal the diversity in China, we explored the genetic diversity of the Euwallacea fornicatus complex using molecular approaches. Species and clades were delimited (using ABGD, bGMYC, mPTP and BP&P approaches) based on mitochondrial COI and 16S, and nuclear 18S-ITS1-5. 8S, 28S and CAD. All specimens from continental China were E. fornicatus, consistently separating into three molecular taxonomic. Of the other species, E. perbrevis was recovered from Hainan. The distribution pattern and genetic diversity of these species contributes to the development of adequate control strategies since different species can cause different damage.

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MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

Kazutaka Katoh, Daron Standley (2013)

We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.

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MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

Sudhir Kumar, Glen Stecher, Michael KaWah Li … (2018)

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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IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

Lam-Tung Nguyen, Heiko Schmidt, Arndt von Haeseler … (2014)

Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.

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Author and article information

Journal

Journal ID (publisher): entomologia

Title: Entomologia Generalis

Subtitle: Journal of General and Applied Entomology - Zeitschrift für Allgemeine und Angewandte Entomologie

Abbreviated Title: entomologia

Publisher: Schweizerbart Science Publishers (Stuttgart, Germany http://www.schweizerbart.com/ mail@ 123456schweizerbart.de )

ISSN: 0171-8177

Publication date (Electronic): 04 February 2022

Publication date (Print): 11 July 2022

Volume: 42

Issue: 4

Pages: 631-639

Affiliations

¹ College of Advanced Agricultural Sciences, Zhejiang Agriculture and Forestry University, Hangzhou, Zhejiang, 311300, PRC

² Shanghai Academy of Landscape Architecture Science and Planning, Key Laboratory of National Forestry and Grassland Administration on Ecological Landscaping of Challenging Urban Sites, Shanghai, 200232, PRC

³ College of Forestry and Biotechnology, Zhejiang Agriculture and Forestry University, Hangzhou, Zhejiang, 311300, PRC

⁴ School of Forestry, Fisheries and Geomatics Sciences, University of Florida, Gainesville, Florida, 32611, USA

⁵ Vector-borne Virus Research Center, Fujian Province Key Laboratory of Plant Virology, Fujian Agriculture and Forestry University, Fuzhou, Fujian, 350002, PRC