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      Convergent evolution of

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      Invertebrate Systematics
      CSIRO Publishing

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          Abstract

          East Asian terrestrial snails of the family Camaenidae Pilsbry, 1895a are diverse in terms of genus and species numbers, shell morphology and mode of living. This family also includes colourful conical arboreal snails that traditionally have been assigned to the genus Amphidromus Albers, 1850. Yet, the present study shows that, despite their deceiving conchological similarity, some of these East Asian arboreal snails do not belong to the genus Amphidromus or the subfamily Camaeninae Pilsbry, 1895a. The presence of a dart complex comprising a mucous gland, a dart sac, an accessory sac and a proximal accessory sac, along with a pronounced penial caecum and molecular phylogenetic analyses revealed that former ‘Amphidromus’ dautzenbergi, ‘A.’ roemeri and ‘Camaena’ mirifica, and one additional new species belong to Aegistohadra Wu, 2004 (subfamily Bradybaeninae Pilsbry, 1934). Aegistohadra dautzenbergi, comb. nov. and Aegistohadra roemeri, comb. nov. are conical with colourful spiral bands, whereas Aegistohadra mirifica, comb. nov. and Aegistohadra zhangdanae, sp. nov. are heliciform to conical with colourful, variegated spiral and transverse banding patterns. DNA sequence analyses also revealed that each variety of Aegistohadra dautzenbergi could not be differentiated by mitochondrial (cytochrome c oxidase subunit I and 16S rRNA) gene fragments. The phylogenetic position of Aegistohadra within the East Asian camaenids revealed that the similar appearance in shell morphology, microhabitat use and diet to arboreal snails in the genus Amphidromus is homoplastic. Moreover, the presence or absence of a dart complex is also homoplastic and is unsuitable for suprageneric classification. By contrast, the presence of a flagellum and a penial caecum is useful for the suprageneric classification.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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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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                Author and article information

                Contributors
                Journal
                Invertebrate Systematics
                Invertebr. Syst.
                CSIRO Publishing
                1445-5226
                1447-2600
                2022
                April 8 2022
                : 36
                : 3
                : 244-290
                Article
                10.1071/IS21015
                172a7cb7-42f2-4ff9-9cdc-641a3a3ae6dc
                © 2022
                History

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