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      Plastid super-barcodes as a tool for species discrimination in feather grasses (Poaceae: Stipa)

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          Abstract

          Present study was designed to verify which or if any of plastome loci is a hotspot region for mutations and hence might be useful for molecular species identification in feather grasses. 21 newly sequenced complete plastid genomes representing 19 taxa from the genus of Stipa were analyzed in search of the most variable and the most discriminative loci within Stipa. The results showed that the problem with selecting a good barcode locus for feather grasses lies in the very low level of genetic diversity within its plastome. None of the single chloroplast loci is polymorphic enough to play a role of a barcode or a phylogenetic marker for Stipa. The biggest number of taxa was successfully identified by the analysis of 600 bp long DNA fragment comprising a part of rbcL gene, the complete rbcL-rpl23 spacer and a part of rpl23 gene. The effectiveness of multi-locus barcode composed of six best-performing loci for Stipa ( ndhH, rpl23, ndhF- rpl32, rpl32-ccsA, psbK-psbI and petA-psbJ) didn’t reach 70% of analyzed taxa. The analysis of complete plastome sequences as a super-barcode for Stipa although much more effective, still didn’t allow for discrimination of all the analyzed taxa of feather grasses.

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          A DNA barcode for land plants.

          DNA barcoding involves sequencing a standard region of DNA as a tool for species identification. However, there has been no agreement on which region(s) should be used for barcoding land plants. To provide a community recommendation on a standard plant barcode, we have compared the performance of 7 leading candidate plastid DNA regions (atpF-atpH spacer, matK gene, rbcL gene, rpoB gene, rpoC1 gene, psbK-psbI spacer, and trnH-psbA spacer). Based on assessments of recoverability, sequence quality, and levels of species discrimination, we recommend the 2-locus combination of rbcL+matK as the plant barcode. This core 2-locus barcode will provide a universal framework for the routine use of DNA sequence data to identify specimens and contribute toward the discovery of overlooked species of land plants.
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            OrganellarGenomeDRAW—a suite of tools for generating physical maps of plastid and mitochondrial genomes and visualizing expression data sets

            Mitochondria and plastids (chloroplasts) are cell organelles of endosymbiotic origin that possess their own genetic information. Most organellar DNAs map as circular double-stranded genomes. Across the eukaryotic kingdom, organellar genomes display great size variation, ranging from ∼15 to 20 kb (the size of the mitochondrial genome in most animals) to >10 Mb (the size of the mitochondrial genome in some lineages of flowering plants). We have developed OrganellarGenomeDraw (OGDRAW), a suite of software tools that enable users to create high-quality visual representations of both circular and linear annotated genome sequences provided as GenBank files or accession numbers. Although all types of DNA sequences are accepted as input, the software has been specifically optimized to properly depict features of organellar genomes. A recent extension facilitates the plotting of quantitative gene expression data, such as transcript or protein abundance data, directly onto the genome map. OGDRAW has already become widely used and is available as a free web tool (http://ogdraw.mpimp-golm.mpg.de/). The core processing components can be downloaded as a Perl module, thus also allowing for convenient integration into custom processing pipelines.
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              Use of DNA barcodes to identify flowering plants.

              Methods for identifying species by using short orthologous DNA sequences, known as "DNA barcodes," have been proposed and initiated to facilitate biodiversity studies, identify juveniles, associate sexes, and enhance forensic analyses. The cytochrome c oxidase 1 sequence, which has been found to be widely applicable in animal barcoding, is not appropriate for most species of plants because of a much slower rate of cytochrome c oxidase 1 gene evolution in higher plants than in animals. We therefore propose the nuclear internal transcribed spacer region and the plastid trnH-psbA intergenic spacer as potentially usable DNA regions for applying barcoding to flowering plants. The internal transcribed spacer is the most commonly sequenced locus used in plant phylogenetic investigations at the species level and shows high levels of interspecific divergence. The trnH-psbA spacer, although short ( approximately 450-bp), is the most variable plastid region in angiosperms and is easily amplified across a broad range of land plants. Comparison of the total plastid genomes of tobacco and deadly nightshade enhanced with trials on widely divergent angiosperm taxa, including closely related species in seven plant families and a group of species sampled from a local flora encompassing 50 plant families (for a total of 99 species, 80 genera, and 53 families), suggest that the sequences in this pair of loci have the potential to discriminate among the largest number of plant species for barcoding purposes.
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                Author and article information

                Contributors
                katarzyna.krawczyk@uwm.edu.pl
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                31 January 2018
                31 January 2018
                2018
                : 8
                : 1924
                Affiliations
                [1 ]ISNI 0000 0001 2149 6795, GRID grid.412607.6, Department of Botany and Nature Protection, Faculty of Biology and Biotechnology, , University of Warmia and Mazury in Olsztyn, ; Olsztyn, Poland
                [2 ]ISNI 0000 0001 2162 9631, GRID grid.5522.0, Institute of Botany, Faculty of Biology, , Jagiellonian University, ; Kraków, Poland
                Article
                20399
                10.1038/s41598-018-20399-w
                5792575
                29386579
                922af287-8f57-4f54-a220-93617c5e697b
                © The Author(s) 2018

                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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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                : 19 October 2017
                : 17 January 2018
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