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      Grunts (Actinopterygii: Perciformes: Haemulidae) of Bangladesh with two new distributional records from the northern Bay of Bengal assessed by morphometric characters and DNA barcoding

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      Acta Ichthyologica et Piscatoria
      Pensoft Publishers

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          Abstract

          Grunts (family Haemulidae) are among the most commercially important fish in Bangladesh. This paper provides brief diagnostic characters of five previously reported grunt species: Plectorhinchus pictus (Thunberg, 1792); Pomadasys andamanensis McKay et Satapoomin, 1994; Pomadasys argenteus (Forsskål, 1775); Pomadasys argyreus (Valenciennes, 1833); Pomadasys maculatus (Bloch, 1793) and two new distributional records: Pomadasys guoraca (Cuvier, 1829) and Plectorhinchus macrospilus Satapoomin et Randall, 2000. The fishes were collected from the Saint Martin’s Island coral reef-like ecosystem and the adjacent sea of the Sundarbans mangrove forest of Bangladesh. The examined specimens were identified and diagnosed based on their morphometric characters and DNA barcoding COI gene. The new records of Pomadasys guoraca and Plectorhinchus macrospilus from Bangladesh greatly extend their distributional range in the Bay of Bengal. An updated checklist of grunts of Bangladesh is provided.

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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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              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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                Author and article information

                Contributors
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                Journal
                Acta Ichthyologica et Piscatoria
                AIeP
                Pensoft Publishers
                1734-1515
                0137-1592
                September 13 2021
                September 13 2021
                : 51
                : 3
                : 299-309
                Article
                10.3897/aiep.51.67043
                bbd7c58f-418f-4156-b175-611502a84bdd
                © 2021

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

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