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      Analysis of Acanthamoeba genotypes from public freshwater sources in Thailand reveals a new genotype, T23 Acanthamoeba bangkokensis sp. nov.

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          Abstract

          A survey of Acanthamoeba in 100 public freshwater sources in 28 provinces across Thailand has identified 9 genotypes comprising T2/6, T3-T5, T9, T11, T12, T18 and a novel ‘T23’ among 131 isolates. Sequencing of the near complete 18S rRNA gene of Acanthamoeba of all isolates has shown that the most predominant genotype T4 found in 87 isolates (66.4%) contained 4 subtypes, i.e. T4A, T4B, T4C and T4F, while all isolates assigned to genotype T2/6 belonged to subtype B. Among intron-bearing genotypes, most isolates harbouring genotype T3 contained S516 introns, characterised by 3 distinct variants whilst all genotypes T4A and T5 were intronless. Identical 18S rRNA sequences of Acanthamoeba were identified across regions of the country and four isolates in this study shared the same sequences with those from remote nations, suggesting that some strains have reproductive success in diverse ecological niche. Nucleotide diversity of genotypes T2/6B, T3, T4, T9 and T11 in this study was significantly less than that among global isolates outside Thailand, implying that limited sequence diversity occurred within local populations. A remarkably higher level of nucleotide diversity in genotype T11 than those of other genotypes (0.041 vs. 0.012–0.024) could be due to cryptic subtypes. Recombination breakpoints have been detected within genotypes and subtypes as well as within isolates despite no evidence for sexual and parasexual cycles in the genus Acanthamoeba. Tajima’s D, Fu & Li’s D* and F* statistics revealed significantly negative deviation from neutrality across genotypes and subtypes, implying purifying selection in this locus. The 18S rRNA gene of the novel genotype ‘T23’ displayed 7.82% to 28.44% sequence differences in comparison with all known genotypes. Both Bayesian and maximum likelihood phylogenetic trees have placed genotype T23 as sister to the clade comprising genotypes T10, T12 and T14, all of these possess cyst structure belonging to morphological group III. Hence, Acanthamoeba bangkokensis sp. nov. is proposed for this novel genotype. It is likely that more genotypes of Acanthamoeba remain to be discovered while the evolution of the 18S rRNA gene of this pathogenic-free living amoeba seems to be ongoing.

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          MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.

          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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            MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization

            Abstract This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and the need for MSAs with large numbers of sequences is increasing. To extract biologically relevant information from such data, sophistication of algorithms is necessary but not sufficient. Intuitive and interactive tools for experimental biologists to semiautomatically handle large data are becoming important. We are working on development of MAFFT toward these two directions. Here, we explain (i) the Web interface for recently developed options for large data and (ii) interactive usage to refine sequence data sets and MSAs.
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              BEAST 2: A Software Platform for Bayesian Evolutionary Analysis

              We present a new open source, extensible and flexible software platform for Bayesian evolutionary analysis called BEAST 2. This software platform is a re-design of the popular BEAST 1 platform to correct structural deficiencies that became evident as the BEAST 1 software evolved. Key among those deficiencies was the lack of post-deployment extensibility. BEAST 2 now has a fully developed package management system that allows third party developers to write additional functionality that can be directly installed to the BEAST 2 analysis platform via a package manager without requiring a new software release of the platform. This package architecture is showcased with a number of recently published new models encompassing birth-death-sampling tree priors, phylodynamics and model averaging for substitution models and site partitioning. A second major improvement is the ability to read/write the entire state of the MCMC chain to/from disk allowing it to be easily shared between multiple instances of the BEAST software. This facilitates checkpointing and better support for multi-processor and high-end computing extensions. Finally, the functionality in new packages can be easily added to the user interface (BEAUti 2) by a simple XML template-based mechanism because BEAST 2 has been re-designed to provide greater integration between the analysis engine and the user interface so that, for example BEAST and BEAUti use exactly the same XML file format.
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                Author and article information

                Contributors
                jongwutiwes@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 August 2021
                27 August 2021
                2021
                : 11
                : 17290
                Affiliations
                GRID grid.7922.e, ISNI 0000 0001 0244 7875, Molecular Biology of Malaria and Opportunistic Parasites Research Unit, Department of Parasitology, Faculty of Medicine, , Chulalongkorn University, ; Bangkok, Thailand
                Article
                96690
                10.1038/s41598-021-96690-0
                8397737
                34453084
                176a0339-3789-41e4-b307-19d9ebacceab
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 26 May 2021
                : 11 August 2021
                Funding
                Funded by: Ratchadapiseksompotch Fund (special project), Chulalongkorn University
                Award ID: IGB-CU-61-23-30-13
                Award ID: IGB-CU-61-23-30-13
                Award ID: IGB-CU-61-23-30-13
                Award ID: IGB-CU-61-23-30-13
                Award ID: IGB-CU-61-23-30-13
                Award Recipient :
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                © The Author(s) 2021

                Uncategorized
                parasitology,parasite genetics
                Uncategorized
                parasitology, parasite genetics

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