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      • Record: found
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      First national record of Microhylahmongorum Hoang, Nguyen, Phan, Pham, Ninh, Wang, Jiang, Ziegler and Nguyen, 2022 (Anura, Microhylidae, Microhyla) in China

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          Abstract

          Background

          To date, 10 species of the genus Microhyla have been recorded in China, of which six were distributed in Yunnan Province. Microhyla hmongorum Hoang, Nguyen, Phan, Pham, Ninh, Wang, Jiang, Ziegler, and Nguyen, 2022 was also speculated to be distributed in Xishuangbana, Yunnan Province, China. However, there is no evidence of documentation of M. hmongorum .

          New information

          We report the first country record of Microhyla hmongorum , based on specimens collected from Yunnan border region. Morphologically, the specimen was consistent with the original descriptions of M. hmongorum . Phylogenetically, the sequences of the specimens from China clustered with the sequence of type specimens of M. hmongorum from Vietnam, with uncorrected pairwise distances of 0.9% at the 16S gene fragment analysed. Therefore, we report M. hmongorum as a new record species in China.

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

          Alexandros Stamatakis (2014)
          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.

            R. C. Edgar (2004)
            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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              MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.

              Koichiro Tamura, Glen Stecher, Daniel Walter Peterson … (2013)
              We announce the release of an advanced version of the Molecular Evolutionary Genetics Analysis (MEGA) software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis. In version 6.0, MEGA now enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny. A new Timetree Wizard in MEGA6 facilitates this timetree inference by providing a graphical user interface (GUI) to specify the phylogeny and calibration constraints step-by-step. This version also contains enhanced algorithms to search for the optimal trees under evolutionary criteria and implements a more advanced memory management that can double the size of sequence data sets to which MEGA can be applied. Both GUI and command-line versions of MEGA6 can be downloaded from www.megasoftware.net free of charge.
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                Author and article information

                Contributors
                Jing Che
                Journal
                Journal ID (nlm-ta): Biodivers Data J
                Journal ID (iso-abbrev): Biodivers Data J
                Journal ID (publisher-id): 1
                Journal ID (index): urn:lsid:arphahub.com:pub:F9B2E808-C883-5F47-B276-6D62129E4FF4
                Journal ID (aggregator): urn:lsid:zoobank.org:pub:245B00E9-BFE5-4B4F-B76E-15C30BA74C02
                Title: Biodiversity Data Journal
                Publisher: Pensoft Publishers
                ISSN (Print): 1314-2836
                ISSN (Electronic): 1314-2828
                Publication date Collection: 2023
                Publication date (Electronic): 10 April 2023
                Volume: 11
                Electronic Location Identifier: e103580
                Affiliations
                [1 ] Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences, 05282, Yezin, Nay Pyi Taw, Myanmar Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences, 05282 Yezin, Nay Pyi Taw Myanmar
                [2 ] State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of biodiversity and ecological conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, Yunnan, China State Key Laboratory of Genetic Resources and Evolution & Yunnan key laboratory of biodiversity and ecological conservation of Gaoligong Mountain, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223 Kunming, Yunnan China
                [3 ] Kunming College of Life Science, University of the Chinese Academy of Sciences, 650204, Kunming, Yunnan, China Kunming College of Life Science, University of the Chinese Academy of Sciences, 650204 Kunming, Yunnan China
                [4 ] Key Laboratory of Conserving Wildlife with Small Populations in Yunnan, Southwest Forestry University, 650224, Kunming, Yunnan, China Key Laboratory of Conserving Wildlife with Small Populations in Yunnan, Southwest Forestry University, 650224 Kunming, Yunnan China
                Author notes
                Corresponding author: Jing Che ( chej@ 123456mail.kiz.ac.cn ).

                Academic editor: Truong Nguyen

                Author information
                https://orcid.org/0000-0001-6432-7721
                https://orcid.org/0000-0001-5991-3021
                Article
                Publisher ID: 103580 Publisher-manuscript ID: 21890
                DOI: 10.3897/BDJ.11.e103580
                PMC ID: 10848633
                PubMed ID: 38327331
                SO-VID: e598bcbd-be3b-417c-b042-1d10f19deb2d
                Copyright © Yun-He Wu, Zhong-Bin Yu, Chen-Qi Lu, Kasyoka Kilunda Felista, Shao-bing Hou, Jie-Qiong Jin, Jin-Min Chen, Dong-Ru Zhang, Zhi-Yong Yuan, Jing Che
                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 : 16 March 2023
                Date accepted : 01 April 2023
                Page count
                Figures: 3, Tables: 1, References: 25
                Funding
                This work was supported by the National Key R&D Program of China (Grant No. 2022YFC2602500); National Natural Science Foundation of China (NSFC 32100371, 32001222); Major Science and Technique Program (202102AA310055), Key R & D program (202103AC100003), and the Digitalization, Development and Application of Biotic Resource (202002AA100007) in Yunnan Province; China's Biodiversity Observation Network (Sino-BON), and the Animal Branch of the Germplasm Bank of Wild Species, CAS (Large Research Infrastructure Funding).
                Categories
                Subject: Taxonomy & Inventories
                Subject: Animalia
                Subject: Amphibia
                Subject: Vertebrata
                Subject: Biodiversity & Conservation
                Subject: Asia

                Keywords: amphibia, microhylahmongorum ,new record,china
                Data availability:
                Keywords: amphibia, microhylahmongorum , new record, china

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