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      Chloroplast Genomic Resource of Paris for Species Discrimination

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          Abstract

          Paris is famous in China for its medicinal value and has been included in the Chinese Pharmacopoeia. Inaccurate identification of these species could confound their effective exploration, conservation, and domestication. Due to the plasticity of the morphological characteristics, correct identification among Paris species remains problematic. In this regard, we report the complete chloroplast genome of P. thibetica and P. rugosa to develop highly variable molecular markers. Comparing three chloroplast genomes, we sought out the most variable regions to develop the best cpDNA barcodes for Paris. The size of Paris chloroplast genome ranged from 162,708 to 163,200 bp. A total of 134 genes comprising 81 protein coding genes, 45 tRNA genes and 8 rRNA genes were observed in all three chloroplast genomes. Eight rapidly evolving regions were detected, as well as the difference of simple sequence repeats (SSR) and repeat sequence. Two regions of the coding gene ycf1, ycf1a and ycf1b, evolved the quickest and were proposed as core barcodes for Paris. The complete chloroplast genome sequences provide more integrated and adequate information for better understanding the phylogenetic pattern and improving efficient discrimination during species identification.

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          Highly Variable Chloroplast Markers for Evaluating Plant Phylogeny at Low Taxonomic Levels and for DNA Barcoding

          Background At present, plant molecular systematics and DNA barcoding techniques rely heavily on the use of chloroplast gene sequences. Because of the relatively low evolutionary rates of chloroplast genes, there are very few choices suitable for molecular studies on angiosperms at low taxonomic levels, and for DNA barcoding of species. Methodology/Principal Findings We scanned the entire chloroplast genomes of 12 genera to search for highly variable regions. The sequence data of 9 genera were from GenBank and 3 genera were of our own. We identified nearly 5% of the most variable loci from all variable loci in the chloroplast genomes of each genus, and then selected 23 loci that were present in at least three genera. The 23 loci included 4 coding regions, 2 introns, and 17 intergenic spacers. Of the 23 loci, the most variable (in order from highest variability to lowest) were intergenic regions ycf1-a, trnK, rpl32-trnL, and trnH-psbA, followed by trnSUGA-trnGUCC , petA-psbJ, rps16-trnQ, ndhC-trnV, ycf1-b, ndhF, rpoB-trnC, psbE-petL, and rbcL-accD. Three loci, trnSUGA-trnGUCC , trnT-psbD, and trnW-psaJ, showed very high nucleotide diversity per site (π values) across three genera. Other loci may have strong potential for resolving phylogenetic and species identification problems at the species level. The loci accD-psaI, rbcL-accD, rpl32-trnL, rps16-trnQ, and ycf1 are absent from some genera. To amplify and sequence the highly variable loci identified in this study, we designed primers from their conserved flanking regions. We tested the applicability of the primers to amplify target sequences in eight species representing basal angiosperms, monocots, eudicots, rosids, and asterids, and confirmed that the primers amplified the desired sequences of these species. Significance/Conclusions Chloroplast genome sequences contain regions that are highly variable. Such regions are the first consideration when screening the suitable loci to resolve closely related species or genera in phylogenetic analyses, and for DNA barcoding.
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            Spider: an R package for the analysis of species identity and evolution, with particular reference to DNA barcoding.

            Spider: SPecies IDentity and Evolution in R is a new R package implementing a number of useful analyses for DNA barcoding studies and associated research into species delimitation and speciation. Included are functions essential for generating important summary statistics from DNA barcode data, assessing specimen identification efficacy, and for testing and optimizing divergence threshold limits. In terms of investigating evolutionary and taxonomic questions, techniques for assessing diagnostic nucleotides and probability of reciprocal monophyly are also provided. Additionally, a sliding window function offers opportunities to analyse information across a gene, essential for marker design in degraded DNA studies. Spider capitalizes on R's extensible ethos and offers an integrated platform ideal for the analysis of both nucleotide and morphological data. The program can be obtained from the comprehensive R archive network (CRAN, http://cran.r-project.org) and from the R-Forge package development site (http://spider.r-forge.r-project.org/). © 2012 Blackwell Publishing Ltd.
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              Methods for obtaining and analyzing whole chloroplast genome sequences.

              During the past decade, there has been a rapid increase in our understanding of plastid genome organization and evolution due to the availability of many new completely sequenced genomes. There are 45 complete genomes published and ongoing projects are likely to increase this sampling to nearly 200 genomes during the next 5 years. Several groups of researchers including ours have been developing new techniques for gathering and analyzing entire plastid genome sequences and details of these developments are summarized in this chapter. The most important developments that enhance our ability to generate whole chloroplast genome sequences involve the generation of pure fractions of chloroplast genomes by whole genome amplification using rolling circle amplification, cloning genomes into Fosmid or bacterial artificial chromosome (BAC) vectors, and the development of an organellar annotation program (Dual Organellar GenoMe Annotator [DOGMA]). In addition to providing details of these methods, we provide an overview of methods for analyzing complete plastid genome sequences for repeats and gene content, as well as approaches for using gene order and sequence data for phylogeny reconstruction. This explosive increase in the number of sequenced plastid genomes and improved computational tools will provide many insights into the evolution of these genomes and much new data for assessing relationships at deep nodes in plants and other photosynthetic organisms.
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                Author and article information

                Contributors
                chennz@263.net.cn
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                13 June 2017
                13 June 2017
                2017
                : 7
                : 3427
                Affiliations
                [1 ]ISNI 0000 0004 1756 5008, GRID grid.418544.8, Institute of Plant Quarantine, , Chinese Academy of Inspection and Quarantine, ; Beijing, 100176 China
                [2 ]Biological Germplasm Resources Identification Center of AQSIQ, Beijing, 100176 China
                [3 ]Inspection and Quarantine Technology Center of Yunnan entry-exit inspection and Quarantine Bureau, Kunming, 650228 Yunnan China
                Article
                2083
                10.1038/s41598-017-02083-7
                5469780
                28611359
                8015ae31-cc06-45c2-a80e-d89796acf0c7
                © The Author(s) 2017

                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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                : 27 February 2017
                : 6 April 2017
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