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      Two new species of freshwater crabs of the genera Eosamon Yeo & Ng, 2007 and Indochinamon Yeo & Ng, 2007 (Crustacea, Brachyura, Potamidae) from southern Yunnan, China

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          Abstract

          Two new species of potamid crabs, Eosamon daiae sp. nov. and Indochinamon malipoense sp. nov. are described from the Sino-Burmese border, southwestern Yunnan and from the Sino-Vietnamese border, southeastern Yunnan, China. The two new species can be distinguished from their closest congeners by several characters, among which is the form of the first gonopod structures. Molecular analyses based on partial mitochondrial 16S rDNA sequences also support the systematic status of these new taxa.

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

              Fredrik Ronquist, Maxim Teslenko, Paul van der Mark … (2012)
              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
                Hongying Sun:
                ORCID: https://orcid.org/0000-0003-2311-1814
                Journal
                Journal ID (nlm-ta): Zookeys
                Journal ID (iso-abbrev): Zookeys
                Journal ID (publisher-id): 2
                Journal ID (index): urn:lsid:arphahub.com:pub:45048D35-BB1D-5CE8-9668-537E44BD4C7E
                Journal ID (aggregator): urn:lsid:zoobank.org:pub:91BD42D4-90F1-4B45-9350-EEF175B1727A
                Title: ZooKeys
                Publisher: Pensoft Publishers
                ISSN (Print): 1313-2989
                ISSN (Electronic): 1313-2970
                Publication date Collection: 2020
                Publication date (Electronic): 28 October 2020
                Volume: 980
                Pages: 1-21
                Affiliations
                [1 ] Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, 1 Wenyuan Rd, Nanjing 210023, China Nanjing Normal University Nanjing China
                Author notes
                Corresponding author: Hongying Sun ( sunhongying@ 123456njnu.edu.cn )

                Academic editor: K. Van Damme

                Author information
                https://orcid.org/0000-0003-2311-1814
                Article
                Publisher ID: 52186
                DOI: 10.3897/zookeys.980.52186
                PMC ID: 7642192
                PubMed ID: 33192135
                SO-VID: 2c02d530-9e85-4e7c-ae25-504d58accabd
                Copyright © Zewei Zhang, Da Pan, Xiyang Hao, Hongying Sun
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 18 March 2020
                Date accepted : 14 September 2020
                Funding
                Funded by: National Natural Science Foundation of China 501100001809 http://doi.org/10.13039/501100001809
                Categories
                Subject: Research Article
                Subject: Crustacea
                Subject: Decapoda
                Subject: Potamidae
                Subject: Potamoidea
                Subject: Biodiversity & Conservation
                Subject: Molecular systematics
                Subject: Taxonomy
                Subject: Asia
                Subject: China

                ScienceOpen disciplines: Animal science & Zoology
                Keywords: 16s rdna,eosamon daiae sp. nov.,indochinamon malipoense sp. nov.,new species, potamidae , potamiscinae ,taxonomy
                Data availability:
                ScienceOpen disciplines: Animal science & Zoology
                Keywords: 16s rdna, eosamon daiae sp. nov., indochinamon malipoense sp. nov., new species, potamidae , potamiscinae , taxonomy

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