Complete mitochondrial sequence of  Auricularia heimuer , one of the most popular edible fungus in China

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Abstract

Auricularia heimuer is one of the most popular edible fungi in China. It has high economic and medicinal value. The complete mitochondrial genome of A. heimuer is 40586 bp. It contains 48 genes, including 25 protein-coding genes, 22 tRNA genes, and 1 gene coding RNase P RNA. The G + C content is 37.92%. The phylogenetic relationships were constructed on the Bayesian inference method. It showed that A. heimuer was in distance to other species of Russulales, Polyporales, and Agaricales. The complete genome sequence of A. heimuer will provide a useful resource for the genetic and systematics studies.

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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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SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

Anton Bankevich, Sergey Nurk, Dmitry Antipov … (2012)

The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

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MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

Fredrik Ronquist, Maxim Teslenko, Paul van der Mark … (2012)

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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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): 13 November 2019

Publication date (Electronic, collection): 2019

Volume: 4

Issue: 2

Pages: 4029-4030

Affiliations

[a ]College of Horticulture, Jilin Agricultural University , Changchun, P. R. China;

[b ]Engineering Research Centre of Chinese Ministry of Education for Edible and Medicinal Fungi, Jilin Agricultural University , Changchun, P. R. China

Author notes

CONTACT Fangjie Yao yaofj@ 123456aliyun.com College of Horticulture, Jilin Agricultural University , Changchun, P. R. China

Article

Publisher ID: 1688717

DOI: 10.1080/23802359.2019.1688717

PMC ID: 7707809

PubMed ID: 33366302

SO-VID: e466293a-ac69-4c0a-abb7-1ff3d7d59c64

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

Complete mitochondrial sequence of Auricularia heimuer, one of the most popular edible fungus in China

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Coleoptera

Most cited references 8

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

SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

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