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      Description of a new species of Aplectana (Nematoda: Ascaridomorpha: Cosmocercidae) using an integrative approach and preliminary phylogenetic study of Cosmocercidae and related taxa

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          Abstract

          Background

          Nematodes of the family Cosmocercidae (Ascaridomorpha: Cosmocercoidea) are mainly parasitic in the digestive tract of various amphibians and reptiles worldwide. However, our knowledge of the molecular phylogeny of the Cosmocercidae is still far from comprehensive. The phylogenetic relationships between Cosmocercidae and the other two families, Atractidae and Kathlaniidae, in the superfamily Cosmocercoidea are still under debate. Moreover, the systematic position of some genera within Cosmocercidae remains unclear.

          Methods

          Nematodes collected from Polypedates megacephalus (Hallowell) (Anura: Rhacophoridae) were identified using morphological (light and scanning electron microscopy) and molecular methods [sequencing the small ribosomal DNA (18S), internal transcribed spacer 1 (ITS-1), large ribosomal DNA (28S) and mitochondrial cytochrome c oxidase subunit 1 ( cox1) target regions]. Phylogenetic analyses of cosmocercoid nematodes using 18S + 28S sequence data were performed to clarify the phylogenetic relationships of the Cosmocercidae, Atractidae and Kathlaniidae in the Cosmocercoidea and the systematic position of the genus Aplectana in Cosmocercidae.

          Results

          Morphological and genetic evidence supported the hypothesis that the nematode specimens collected from P. megacephalus represent a new species of Aplectana (Cosmocercoidea: Cosmocercidae). Our phylogenetic results revealed that the Cosmocercidae is a monophyletic group, but not the basal group in Cosmocercoidea as in the traditional classification. The Kathlaniidae is a paraphyletic group because the subfamily Cruziinae within Kathlaniidae (including only the genus Cruzia) formed a seperate lineage. Phylogenetic analyses also showed that the genus Aplectana has a closer relationship to the genus Cosmocerca in Cosmocercidae.

          Conclusions

          Our phylogenetic results suggested that the subfamily Cruziinae should be moved from the hitherto-defined family Kathlaniidae and elevated as a separate family, and the genus Cosmocerca is closely related to the genus Aplectana in the family Cosmocercidae. The present study provided a basic molecular phylogenetic framework for the superfamily Cosmocercoidea based on 18S + 28S sequence data for the first time to our knowledge. Moreover, a new species, A. xishuangbannaensis n. sp., was described using integrative approach.

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

          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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            MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

            Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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              Nematode-specific PCR primers for the 18S small subunit rRNA gene

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                Author and article information

                Contributors
                liangliangex369@126.com
                Journal
                Parasit Vectors
                Parasit Vectors
                Parasites & Vectors
                BioMed Central (London )
                1756-3305
                18 March 2021
                18 March 2021
                2021
                : 14
                : 165
                Affiliations
                GRID grid.256884.5, ISNI 0000 0004 0605 1239, Key Laboratory of Animal Physiology, Biochemistry and Molecular Biology of Hebei Province, College of Life Sciences, , Hebei Normal University, ; 20 East Road of 2nd South Ring, Yuhua District, 050024 Shijiazhuang, Hebei Province People’s Republic of China
                Article
                4667
                10.1186/s13071-021-04667-9
                7977297
                33736693
                9fd3bfc5-de58-42fd-841a-7175b0b27e01
                © The Author(s) 2021

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 26 December 2020
                : 1 March 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003787, Natural Science Foundation of Hebei Province;
                Award ID: C2019205094
                Award Recipient :
                Funded by: Support Program for 100 Excellent Innovative Talents of Hebei Province
                Award ID: SLRC2019033
                Award Recipient :
                Funded by: Strategic Priority Research Program of the Chinese Academy of Sciences
                Award ID: XDB26000000
                Award Recipient :
                Funded by: Youth Top Talent Support Program of Hebei Province
                Funded by: Natural Science Foundation of Hebei Normal University
                Award ID: L2020B15
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Parasitology
                nematoda,ascaridomorpha,systematics,genetic data,molecular phylogeny,new species
                Parasitology
                nematoda, ascaridomorpha, systematics, genetic data, molecular phylogeny, new species

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