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      Comparative Mitogenomic Analysis Reveals Dynamics of Intron Within and Between Tricholoma Species and Phylogeny of Basidiomycota

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          Abstract

          The genus of Tricholoma is a group of important ectomycorrhizal fungi. The overlapping of morphological characteristics often leads to the confusion of Tricholoma species classification. In this study, the mitogenomes of five Tricholoma species were sequenced based on the next-generation sequencing technology, including T. matsutake SCYJ1, T. bakamatsutake, T. terreum, T. flavovirens, and T. saponaceum. These five mitogenomes were all composed of circular DNA molecules, with sizes ranging from 49,480 to 103,090 bp. Intergenic sequences were considered to be the main factor contributing to size variations of Tricholoma mitogenomes. Comparative mitogenomic analysis showed that the introns of the Agaricales mitogenome experienced frequent loss/gain events. In addition, potential gene transfer was detected between the mitochondrial and nuclear genomes of the five species of Tricholoma. Evolutionary analysis showed that the rps3 gene of the Tricholoma species was under positive selection or relaxed selection in the evolutionary process. In addition, large-scale gene rearrangements were detected between some Tricholoma species. Phylogenetic analysis using the Bayesian inference and maximum likelihood methods based on a combined mitochondrial gene set yielded identical and well-supported tree topologies. This study promoted the understanding of the genetics, evolution, and phylogeny of the Tricholoma genus and related species.

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          RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

          Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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            SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

            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

              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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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                15 February 2021
                2021
                : 12
                : 534871
                Affiliations
                [1] 1Biotechnology and Nuclear Technology Research Institute, Sichuan Academy of Agricultural Sciences , Chengdu, China
                [2] 2Key Laboratory of Coarse Cereal Processing, Ministry of Agriculture and Rural Affairs, School of Food and Biological Engineering, Chengdu University , Chengdu, China
                [3] 3College of Life Sciences, Henan Agricultural University , Zhengzhou, China
                Author notes

                Edited by: Denis Baurain, University of Liège, Belgium

                Reviewed by: Baojun Wu, Clark University, United States; Gerard Barroso, Université de Bordeaux, France

                *Correspondence: Qiang Li leeq110@ 123456126.com

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

                †Present address: Xu Wang and Qiang Li, School of Food and Biological Engineering, Chengdu University, Chengdu, China

                Article
                10.3389/fgene.2021.534871
                7917209
                33659021
                f609bb00-91d1-4802-9cfb-9c7e71f1f162
                Copyright © 2021 Huang, Feng, Tu, Xiong, Jin, Li, Wang and Li.

                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
                : 03 June 2020
                : 18 January 2021
                Page count
                Figures: 8, Tables: 0, Equations: 0, References: 79, Pages: 15, Words: 9015
                Categories
                Genetics
                Original Research

                Genetics
                tricholoma,mitochondrial genome,intron,gene rearrangement,evolution,phylogenetic analysis
                Genetics
                tricholoma, mitochondrial genome, intron, gene rearrangement, evolution, phylogenetic analysis

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