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      Widely used, short 16S rRNA mitochondrial gene fragments yield poor and erratic results in phylogenetic estimation and species delimitation of amphibians

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          Abstract

          Background

          The 16S mitochondrial rRNA gene is the most widely sequenced molecular marker in amphibian systematic studies, making it comparable to the universal CO1 barcode that is more commonly used in other animal groups. However, studies employ different primer combinations that target different lengths/regions of the 16S gene ranging from complete gene sequences (~ 1500 bp) to short fragments (~ 500 bp), the latter of which is the most ubiquitously used. Sequences of different lengths are often concatenated, compared, and/or jointly analyzed to infer phylogenetic relationships, estimate genetic divergence ( p-distances), and justify the recognition of new species (species delimitation), making the 16S gene region, by far, the most influential molecular marker in amphibian systematics. Despite their ubiquitous and multifarious use, no studies have ever been conducted to evaluate the congruence and performance among the different fragment lengths.

          Results

          Using empirical data derived from both Sanger-based and genomic approaches, we show that full-length 16S sequences recover the most accurate phylogenetic relationships, highest branch support, lowest variation in genetic distances (pairwise p-distances), and best-scoring species delimitation partitions. In contrast, widely used short fragments produce inaccurate phylogenetic reconstructions, lower and more variable branch support, erratic genetic distances, and low-scoring species delimitation partitions, the numbers of which are vastly overestimated. The relatively poor performance of short 16S fragments is likely due to insufficient phylogenetic information content.

          Conclusions

          Taken together, our results demonstrate that short 16S fragments are unable to match the efficacy achieved by full-length sequences in terms of topological accuracy, heuristic branch support, genetic divergences, and species delimitation partitions, and thus, phylogenetic and taxonomic inferences that are predicated on short 16S fragments should be interpreted with caution. However, short 16S fragments can still be useful for species identification, rapid assessments, or definitively coupling complex life stages in natural history studies and faunal inventories. While the full 16S sequence performs best, it requires the use of several primer pairs that increases cost, time, and effort. As a compromise, our results demonstrate that practitioners should utilize medium-length primers in favor of the short-fragment primers because they have the potential to markedly improve phylogenetic inference and species delimitation without additional cost.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12862-022-01994-y.

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          Most cited references69

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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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            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            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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              Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

              Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
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                Author and article information

                Contributors
                cko@nus.edu.sg
                Journal
                BMC Ecol Evol
                BMC Ecol Evol
                BMC Ecology and Evolution
                BioMed Central (London )
                2730-7182
                28 March 2022
                28 March 2022
                2022
                : 22
                : 37
                Affiliations
                [1 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, Lee Kong Chian Natural History Museum, Faculty of Science, , National University of Singapore, ; 2 Conservatory Drive, Singapore, 117377 Singapore
                [2 ]Naturhistorisches Museum der Burgergemeinde Bern, Bernastrasse 15, 3005 Bern, Switzerland
                [3 ]GRID grid.5734.5, ISNI 0000 0001 0726 5157, Institute of Ecology and Evolution, , University of Bern, ; Baltzerstrasse 6, 3012 Bern, Switzerland
                [4 ]GRID grid.452935.c, ISNI 0000 0001 2216 5875, Leibniz-Institute for the Analysis of Biodiversity Change, Zoological Research Museum Alexander Koenig, ; Adenauerallee 160, 53113 Bonn, Germany
                [5 ]GRID grid.266515.3, ISNI 0000 0001 2106 0692, Department of Ecology and Evolutionary Biology, Biodiversity Institute, , University of Kansas, ; 1345 Jayhawk Blvd, Dyche Hall, Lawrence, KS 66045 USA
                Article
                1994
                10.1186/s12862-022-01994-y
                8959075
                35346025
                bcace13b-0a6a-4826-9051-a211b485cca0
                © The Author(s) 2022

                Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 20 December 2021
                : 10 March 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                branch support,genetic distance,p-distance,missing data,phylogenetics,species delimitation,systematics

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