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      Rediscovery of Mazus lanceifolius reveals a new genus and a new species in Mazaceae

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          Abstract

          Mazus lanceifolius ( Mazaceae ) is a perennial herb with opposite leaves and endemic to central China that has not been collected for 130 years. Rediscovery of this enigmatic species in the wild allows for determination of its phylogenetic position within Mazaceae . Phylogenetic reconstruction of Mazaceae based on DNA sequences from four plastid markers ( matK, rbcL, rps16 and trnL- trnF) and nuclear ribosome ITS consistently showed that Mazus was not monophyletic. Mazus lanceifolius is in the most basal clade within Mazaceae , as sister to the remaining species of three recognized genera Dodartia , Lancea and Mazus . These results support the separation of M. lanceifolius from Mazus as a new genus, which was established here as Puchiumazus Bo Li, D.G. Zhang & C.L. Xiang. Meanwhile, a collection from Shennongjia Forestry District of Hubei Province, China, misidentified as “ M. lanceifolius ” in previous molecular study, is here revealed to represent an undescribed species of Mazus , i.e., M. fruticosus Bo Li, D.G. Zhang & C.L. Xiang, sp. nov. Morphologically, Puchiumazus is clearly distinct from the other three genera by having quadrangular to somewhat ribbed stems, and obviously opposite leaves. In addition, we provide a taxonomic key to the four genera of Mazaceae .

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          RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

          Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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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
                PhytoKeys
                PhytoKeys
                3
                urn:lsid:arphahub.com:pub:F7FCE910-8E78-573F-9C77-7788555F8AAD
                PhytoKeys
                Pensoft Publishers
                1314-2011
                1314-2003
                2021
                06 January 2021
                : 171
                : 1-24
                Affiliations
                [1 ] CAS Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, Yunnan, China Kunming Institute of Botany, Chinese Academy of Sciences Kunming China
                [2 ] Sichuan Academy of Forestry, Chengdu 610081, Sichuan, China Sichuan Academy of Forestry Chengdu China
                [3 ] Research Centre of Ecological Sciences, College of Agronomy, Jiangxi Agricultural University, Nanchang 330045, China Jiangxi Agricultural University Nanchang China
                [4 ] Key Laboratory of Plant Resources Conservation and Utilization, Jishou University, Jishou 416000, China Jishou University Jishou China
                [5 ] State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China Institute of Botany, Chinese Academy of Sciences Beijing China
                [6 ] Sino-African Joint Research Center, Chinese Academy of Sciences, Wuhan 430074, China Sino-African Joint Research Center, Chinese Academy of Sciences Wuhan China
                Author notes
                Corresponding author: Bo Li ( hanbolijx@ 123456163.com )

                Academic editor: A. Paton

                Author information
                https://orcid.org/0000-0001-8775-6967
                https://orcid.org/0000-0002-6086-253X
                https://orcid.org/0000-0003-1628-8128
                Article
                61926
                10.3897/phytokeys.171.61926
                7806577
                33510572
                adbc00a6-a251-45d1-954f-976a5ae4c8a7
                Chun-Lei Xiang, Hong-Li Pan, Dao-Zhang Min, Dai-Gui Zhang, Fei Zhao, Bing Liu, Bo Li

                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
                : 11 December 2020
                : 15 December 2020
                Categories
                Research Article
                Lamiales
                Taxonomy
                Asia

                Plant science & Botany
                dodartia , lamiales , lancea ,new genus, puchiumazus
                Plant science & Botany
                dodartia , lamiales , lancea , new genus, puchiumazus

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