The complete chloroplast genome of  Tainia dunnii  (Orchidaceae): genome structure and evolution

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Abstract

Tainia dunnii is a terrestrial orchid with high ornamental value. Herein, we assembled the complete chloroplast genome of Tainia dunnii by next-generation sequencing technologies. The complete chloroplast genome sequence of Tainia dunnii is 158,305 base pairs (bp) in length, including a pair of inverted repeat regions (IRs, 25,244 bp), one large single-copy region (LSC, 86,819 bp), one small single-copy region (SSC, 20,998 bp). Besides, the complete chloroplast genome contains 136 genes in total, including 88 protein-coding genes, 38 tRNA genes, and 8 rRNA genes. Phylogenetic analysis showed that Tainia dunnii has the closest relationship with Calanthe davidii and Calanthe triplicata. Our study lay a foundation for further research of Tainia dunnii.

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MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.

Koichiro Tamura, Glen Stecher, Daniel Walter Peterson … (2013)

We announce the release of an advanced version of the Molecular Evolutionary Genetics Analysis (MEGA) software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis. In version 6.0, MEGA now enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny. A new Timetree Wizard in MEGA6 facilitates this timetree inference by providing a graphical user interface (GUI) to specify the phylogeny and calibration constraints step-by-step. This version also contains enhanced algorithms to search for the optimal trees under evolutionary criteria and implements a more advanced memory management that can double the size of sequence data sets to which MEGA can be applied. Both GUI and command-line versions of MEGA6 can be downloaded from www.megasoftware.net free of charge.

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Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

Matthew Kearse, Richard Moir, Amy Wilson … (2012)

Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com

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Ultrafast Approximation for Phylogenetic Bootstrap

Bui Minh, Minh Nguyen, Arndt von Haeseler (2013)

Nonparametric bootstrap has been a widely used tool in phylogenetic analysis to assess the clade support of phylogenetic trees. However, with the rapidly growing amount of data, this task remains a computational bottleneck. Recently, approximation methods such as the RAxML rapid bootstrap (RBS) and the Shimodaira–Hasegawa-like approximate likelihood ratio test have been introduced to speed up the bootstrap. Here, we suggest an ultrafast bootstrap approximation approach (UFBoot) to compute the support of phylogenetic groups in maximum likelihood (ML) based trees. To achieve this, we combine the resampling estimated log-likelihood method with a simple but effective collection scheme of candidate trees. We also propose a stopping rule that assesses the convergence of branch support values to automatically determine when to stop collecting candidate trees. UFBoot achieves a median speed up of 3.1 (range: 0.66–33.3) to 10.2 (range: 1.32–41.4) compared with RAxML RBS for real DNA and amino acid alignments, respectively. Moreover, our extensive simulations show that UFBoot is robust against moderate model violations and the support values obtained appear to be relatively unbiased compared with the conservative standard bootstrap. This provides a more direct interpretation of the bootstrap support. We offer an efficient and easy-to-use software (available at http://www.cibiv.at/software/iqtree) to perform the UFBoot analysis with ML tree inference.

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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): 10 December 2019

Publication date (Electronic, collection): 2020

Volume: 5

Issue: 1

Pages: 3-4

Affiliations

Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture, Fujian Agriculture and Forestry University , Fuzhou, China

Author notes

CONTACT Ye Ai aiyefafu@ 123456163.com Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture, Fujian Agriculture and Forestry University , Fuzhou350002, China

Article

Publisher ID: 1693935

DOI: 10.1080/23802359.2019.1693935

PMC ID: 7720984

PubMed ID: 33366394

SO-VID: 4f76e331-9a08-4296-9294-e8f3d45e4c67

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.

The complete chloroplast genome of Tainia dunnii (Orchidaceae): genome structure and evolution

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Genome Integrity

Most cited references 5

MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.

Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

Ultrafast Approximation for Phylogenetic Bootstrap

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