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      Assessing the reliability of medicinal Dendrobium sequences in GenBank for botanical species identification

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          Abstract

          DNA-based method is a promising tool in species identification and is widely used in various fields. DNA barcoding method has already been included in different pharmacopoeias for identification of medicinal materials or botanicals. Accuracy and validity of DNA-based methods rely on the accuracy and taxonomic reliability of the DNA sequences in the database to be compared against. Here we evaluated the annotation quality and taxonomic reliability of selected barcode loci (rbcL, matK, psbA-trnH, trnL-trnF and ITS) of 41 medicinal Dendrobium species downloaded from GenBank. Annotations of most accessions are incomplete. Only 53.06% of the 2041 accessions downloaded contain a reference to a voucher specimen. Only 31.60% and 4.8% of the entries are annotated with country of origin and collector or assessor, respectively. Taxonomic reliability of the sequences was evaluated by a Megablast search based on similarity to sequences submitted by other research groups. A small number of sequences (211, 7.14%) was regarded as highly doubted. Moreover, 10 out of 60 complete chloroplast genomes contain highly doubted sequences. Our findings suggest that sequences of GenBank should be used with caution for species-level identification. The scientific community should provide more important information regarding identity and traceability of the sample when they deposit sequences to public databases.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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            Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

            S Altschul (1997)
            The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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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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                Author and article information

                Contributors
                pcshaw@cuhk.edu.hk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                9 February 2021
                9 February 2021
                2021
                : 11
                : 3439
                Affiliations
                [1 ]GRID grid.10784.3a, ISNI 0000 0004 1937 0482, Li Dak Sum Yip Yio Chin R&D Centre for Chinese Medicine, , The Chinese University of Hong Kong, ; Hong Kong, China
                [2 ]GRID grid.10784.3a, ISNI 0000 0004 1937 0482, State Key Laboratory of Research on Bioactivities and Clinical Applications of Medicinal Plants (The Chinese University of Hong Kong) and Institute of Chinese Medicine, , The Chinese University of Hong Kong, ; Hong Kong, China
                [3 ]GRID grid.10784.3a, ISNI 0000 0004 1937 0482, School of Life Sciences, , The Chinese University of Hong Kong, ; Hong Kong, China
                Article
                82385
                10.1038/s41598-021-82385-z
                7873228
                33564041
                9a991cef-7594-4c01-92b3-4e1537ec0b3e
                © 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
                : 21 July 2020
                : 19 January 2021
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                © The Author(s) 2021

                Uncategorized
                biological techniques,genetic techniques
                Uncategorized
                biological techniques, genetic techniques

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