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      Genetic Diversity and Population Structure of the Slender Racer (Orientocoluber spinalis) in South Korea

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          Abstract

          The slender racer, Orientocoluber spinalis, is a monotypic species found in northeast Asia. We collected 67 O. spinalis samples from the Republic of Korea (hereafter, South Korea) and 7 from China and Mongolia and investigated their genetic diversity and population structure. In South Korea, O. spinalis populations were mainly found on Oeyeondo, Uido, and Udo islands and Woraksan Mountain and showed low genetic diversity in the analysis of concatenated mitochondrial sequences of the cytochrome b (Cytb) and NADH dehydrogenase subunit 4 (ND4) genes. Orientocoluber spinalis populations in South Korea showed low differentiation and likely diverged recently. Orientocoluber spinalis may have colonized the Korean Peninsula from China and Mongolia, but this route is not confirmed due to the lack of samples from the Democratic People’s Republic of Korea and middle eastern China. Considering its extreme rarity, low population density, and low genetic diversity, O. spinalis should be designated an endangered species in South Korea, as it is in Russia, Mongolia, and Kazakhstan.

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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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
                DIVEC6
                Diversity
                Diversity
                MDPI AG
                1424-2818
                April 2023
                April 09 2023
                : 15
                : 4
                : 543
                Article
                10.3390/d15040543
                bc1b38a5-a6a8-4a43-a45b-b6d95763a441
                © 2023

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

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