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      The complete chloroplast genome sequence of Altingia excelsa

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      Author(s): a , b , a , a , a , a , b
      Publication date (Electronic, pub):
      Publication date (Electronic, collection):
      Journal: Mitochondrial DNA. Part B, Resources
      Publisher: Taylor & Francis
      Keywords: Altingia excelsa, chloroplast, Illumina sequencing, phylogenetic analysis

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          Abstract

          The first complete chloroplast genome (cpDNA) sequence of Altingia excelsa was determined from Illumina HiSeq pair-end sequencing data in this study. The cpDNA is 160,861 bp in length, contains a large single copy region (LSC) of 89,126 bp and a small single copy region (SSC) of 19,011 bp, which were separated by a pair of inverted repeats (IR) regions of 26,362 bp each. The genome contains 127 genes, including 82 protein-coding genes, 8 ribosomal RNA genes, and 37 transfer RNA genes. Phylogenomic analysis showed that A. excelsa and Liquidambar formosana clustered in a clade in Saxifragales order.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          Kazutaka Katoh, Daron Standley (2013)
          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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            RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

            Alexandros Stamatakis (2006)
            RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Gamma yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets > or =4000 taxa it also runs 2-3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25,057 (1463 bp) and 2182 (51,089 bp) taxa, respectively. icwww.epfl.ch/~stamatak
            Article 0 comments Cited 1507 times – based on 0 reviews     Review now
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              GeSeq – versatile and accurate annotation of organelle genomes

              Michael Tillich, Pascal Lehwark, Tommaso Pellizzer … (2017)
              Abstract We have developed the web application GeSeq (https://chlorobox.mpimp-golm.mpg.de/geseq.html) for the rapid and accurate annotation of organellar genome sequences, in particular chloroplast genomes. In contrast to existing tools, GeSeq combines batch processing with a fully customizable reference sequence selection of organellar genome records from NCBI and/or references uploaded by the user. For the annotation of chloroplast genomes, the application additionally provides an integrated database of manually curated reference sequences. GeSeq identifies genes or other feature-encoding regions by BLAT-based homology searches and additionally, by profile HMM searches for protein and rRNA coding genes and two de novo predictors for tRNA genes. These unique features enable the user to conveniently compare the annotations of different state-of-the-art methods, thus supporting high-quality annotations. The main output of GeSeq is a GenBank file that usually requires only little curation and is instantly visualized by OGDRAW. GeSeq also offers a variety of optional additional outputs that facilitate downstream analyzes, for example comparative genomic or phylogenetic studies.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Mitochondrial DNA B Resour
                Journal ID (iso-abbrev): Mitochondrial DNA B Resour
                Title: Mitochondrial DNA. Part B, Resources
                Publisher: Taylor & Francis
                ISSN (Electronic): 2380-2359
                Publication date (Electronic, pub): 14 January 2020
                Publication date (Electronic, collection): 2020
                Volume: 5
                Issue: 1
                Pages: 534-535
                Affiliations
                [a ]Institute of Tropical Forestry, Yunnan Academy of Forestry , Puwen, Yunnan, People’s Republic of China;
                [b ]Laboratory of Forest Plant Cultivation and Utilization, Yunnan Academy of Forestry , Kunming, Yunnan, People’s Republic of China
                Author notes
                CONTACT Yi Wang 22825818@ 123456qq.com Laboratory of Forest Plant Cultivation and Utilization, Yunnan Academy of Forestry , Kunming650204, Yunnan, People’s Republic of China
                Author information
                https://orcid.org/0000-0003-3089-8184
                Article
                Publisher ID: 1710277
                DOI: 10.1080/23802359.2019.1710277
                PMC ID: 7748526
                SO-VID: 468ab78e-fd93-4aa3-b936-016ad3992881
                Copyright © © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Figures: 1, Tables: 0, Pages: 2, Words: 970
                Categories
                Subject: Research Article
                Subject: Mitogenome Announcement

                Keywords: altingia excelsa,chloroplast,illumina sequencing,phylogenetic analysis
                Data availability:
                Keywords: altingia excelsa, chloroplast, illumina sequencing, phylogenetic analysis

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