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      Polydorid species (Annelida: Spionidae) associated with commercially important oyster shells and their shell infestation along the coast of Normandy, in the English Channel, France

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          Abstract

          Polydorid species (Annelida, Spionidae), which inhabit the shells of the commercially important oyster Crassostrea gigas, were investigated along the coast of Normandy, France. Eight species, including five new records for Normandy ( Polydora onagawaensis, Polydora websteri, Boccardia pseudonatrix, Boccardia proboscidea, and Boccardiella hamata) and two first records in European waters ( P. onagawaensis and B. pseudonatrix), were identified based on morphological, molecular biological, and ecological characteristics. Polydora onagawaensis, which belongs to the Polydora ciliata/ websteri complex, was discovered in the shells of wild and suspended cultured oysters, as well as in limestone substrates. In the phylogenetic analysis of mitochondrial COI gene sequences, specimens of P. onagawaensis collected from Normandy were grouped together with specimens from the USA into a single clade and were distinguished from the other three lineages that comprised Japanese and USA specimens. Polydora websteri inhabited shells of suspended cultured oysters. Polydora hoplura, Dipolydora giardi, and Dipolydora sp. were observed in shells from the sandy oyster culture grounds. Boccardiella hamata has been found in wild oyster shells from muddy oyster culture grounds. Boccardia pseudonatrix was observed in the shells of both the wild and cultured oysters. Adult and juvenile Boccardia proboscidea were observed in coralline algae, as well as in suspended cultured oysters. Mud tubes were observed to protrude from the outer surface of the shells, and abnormal black and calcareous deposits were secreted on the inner surface of the shells against polydorid penetration.

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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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            ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

            Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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              New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

              PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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                Author and article information

                Contributors
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                Journal
                Aquaculture International
                Aquacult Int
                Springer Science and Business Media LLC
                0967-6120
                1573-143X
                February 2023
                October 04 2022
                February 2023
                : 31
                : 1
                : 195-230
                Article
                10.1007/s10499-022-00971-y
                a24bcd5a-77eb-4185-a630-65d396e62091
                © 2023

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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