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      The Complete Chloroplast Genomes of Echinacanthus Species (Acanthaceae): Phylogenetic Relationships, Adaptive Evolution, and Screening of Molecular Markers

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          Abstract

          Among the four species of Echinacanthus (Acanthaceae), one distributed in the West Himalayan region and three restricted to the Sino-Vietnamese karst region. Because of its ecological significance, molecular markers are necessary for proper assessment of its genetic diversity and phylogenetic relationships. Herein, the complete chloroplast genomes of four Echinacanthus species were determined for the first time. The results indicated that all the chloroplast genomes were mapped as a circular structure and each genomes included 113 unique genes, of which 80 were protein-coding, 29 were tRNAs, and 4 were rRNAs. However, the four cp genomes ranged from 151,333 to 152,672 bp in length. Comparison of the four cp genomes showed that the divergence level was greater between geographic groups. We also analyzed IR expansion or contraction in the four cp genomes and the fifth type of the large single copy/inverted repeat region in Lamiales was suggested. Furthermore, based on the analyses of comparison and nucleotide variability, six most divergent sequences ( rrn16, ycf1, ndhA, rps16- trnQ-UUG, trnS-GCU- trnG-UCC, and psaA- ycf3) were identified. A total of 37–45 simple sequence repeats were discovered in the four species and 22 SSRs were identified as candidate effective molecular markers for detecting interspecies polymorphisms. These SSRs and hotspot regions could be used as potential molecular markers for future study. Phylogenetic analysis based on Bayesian and parsimony methods did not support the monophyly of Echinacanthus. The phylogenetic relationships among the four species were clearly resolved and the results supported the recognition of the Sino-Vietnamese Echinacanthus species as a new genus. Based on the protein sequence evolution analysis, 12 genes ( rpl14, rpl16, rps4, rps15, rps18, rps19, psbK, psbN, ndhC, ndhJ, rpoB, and infA) were detected under positive selection in branch of Sino-Vietnamese Echinacanthus species. These genes will lead to understanding the adaptation of Echinacanthus species to karst environment. The study will help to resolve the phylogenetic relationship and understand the adaptive evolution of Echinacanthus. It will also provide genomic resources and potential markers suitable for future species identification and speciation studies of the genus.

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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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            Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.).

            A software tool was developed for the identification of simple sequence repeats (SSRs) in a barley ( Hordeum vulgare L.) EST (expressed sequence tag) database comprising 24,595 sequences. In total, 1,856 SSR-containing sequences were identified. Trimeric SSR repeat motifs appeared to be the most abundant type. A subset of 311 primer pairs flanking SSR loci have been used for screening polymorphisms among six barley cultivars, being parents of three mapping populations. As a result, 76 EST-derived SSR-markers were integrated into a barley genetic consensus map. A correlation between polymorphism and the number of repeats was observed for SSRs built of dimeric up to tetrameric units. 3'-ESTs yielded a higher portion of polymorphic SSRs (64%) than 5'-ESTs did. The estimated PIC (polymorphic information content) value was 0.45 +/- 0.03. Approximately 80% of the SSR-markers amplified DNA fragments in Hordeum bulbosum, followed by rye, wheat (both about 60%) and rice (40%). A subset of 38 EST-derived SSR-markers comprising 114 alleles were used to investigate genetic diversity among 54 barley cultivars. In accordance with a previous, RFLP-based, study, spring and winter cultivars, as well as two- and six-rowed barleys, formed separate clades upon PCoA analysis. The results show that: (1) with the software tool developed, EST databases can be efficiently exploited for the development of cDNA-SSRs, (2) EST-derived SSRs are significantly less polymorphic than those derived from genomic regions, (3) a considerable portion of the developed SSRs can be transferred to related species, and (4) compared to RFLP-markers, cDNA-SSRs yield similar patterns of genetic diversity.
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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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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                10 January 2019
                2018
                : 9
                : 1989
                Affiliations
                [1] 1College of Biological and Environmental Engineering, Binzhou University , Binzhou, China
                [2] 2Shandong Provincial Key Laboratory of Eco-Environmental Science for the Yellow River Delta, Binzhou University , Binzhou, China
                [3] 3Shandong Provincial Engineering and Technology Research Center for Wild Plant Resources Development and Application of Yellow River Delta, College of Biological and Environmental Engineering, Binzhou University , Binzhou, China
                [4] 4Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences , Guangzhou, China
                [5] 5Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences , Yezin, Myanmar
                Author notes

                Edited by: Fulvio Cruciani, Sapienza University of Rome, Italy

                Reviewed by: Marcelo R. S. Briones, Federal University of São Paulo, Brazil; Gaurav Sablok, Finnish Museum of Natural History, Finland; Piotr Androsiuk, University of Warmia and Mazury in Olsztyn, Poland

                *Correspondence: Yunfei Deng, yfdeng@ 123456scbg.ac.cn

                This article was submitted to Evolutionary and Population Genetics, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2018.01989
                6335349
                30687376
                0334b0de-f6a5-422b-808b-8276ef17bb04
                Copyright © 2019 Gao, Deng and Wang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 01 July 2018
                : 20 December 2018
                Page count
                Figures: 6, Tables: 3, Equations: 0, References: 67, Pages: 12, Words: 0
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                echinacanthus,chloroplast genome,sequence divergence,phylogeny,molecular marker,adaptive evolution

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