One new species and one new record of  Zasmidium  in China

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Abstract

Background

Two hyphomycetous species were collected from leaves of Smilax china ( Liliales , Smilacaceae ) and Cremastra appendiculata ( Asparagales , Orchidaceae ). ITS barcoding indicated that they belong to the genus Zasmidium .

New information

Morphological data in combination with molecular phylogenetic analyses based on ITS, LSU and rpb2 confirmed that our Chinese strains represented a new species, Zasmidium liboense and a new record of Z. citri-griseum .

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Most cited references 33

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IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

Lam-Tung Nguyen, Heiko Schmidt, Arndt von Haeseler … (2014)

Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.

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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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ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

Subha Kalyaanamoorthy, Bui Minh, Thomas Wong … (2017)

Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.

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Author and article information

Contributors

Yong Wang

Journal

Journal ID (nlm-ta): Biodivers Data J

Journal ID (iso-abbrev): Biodivers Data J

Journal ID (publisher-id): 1

Journal ID (index): urn:lsid:arphahub.com:pub:F9B2E808-C883-5F47-B276-6D62129E4FF4

Journal ID (aggregator): urn:lsid:zoobank.org:pub:245B00E9-BFE5-4B4F-B76E-15C30BA74C02

Title: Biodiversity Data Journal

Publisher: Pensoft Publishers

ISSN (Print): 1314-2836

ISSN (Electronic): 1314-2828

Publication date Collection: 2021

Publication date (Electronic): 07 January 2021

Volume: 9

Electronic Location Identifier: e59001

Affiliations

[1 ] Department of Plant Pathology, Agriculture College, Guizhou University, Guiyang, China Department of Plant Pathology, Agriculture College, Guizhou University Guiyang China

[2 ] Center of Excellence in Fungal Research, Mae Fah Luang University, Chiang Rai, Thailand Center of Excellence in Fungal Research, Mae Fah Luang University Chiang Rai Thailand

[3 ] School of Science, Mae Fah Luang University, Chiang Rai, Thailand School of Science, Mae Fah Luang University Chiang Rai Thailand

[4 ] Guiyang plant protection and inspection station, Guiyang, China Guiyang plant protection and inspection station Guiyang China

Author notes

Corresponding author: Yong Wang ( yongwangbis@ 123456aliyun.com ).

Academic editor: Danny Haelewaters

Author information

Yuan-Yan An https://orcid.org/0000-0001-5549-1028

Article

Publisher ID: 59001 Publisher-manuscript ID: 14840

DOI: 10.3897/BDJ.9.e59001

PMC ID: 7809012

SO-VID: 07ad3638-9c8d-4880-b3ba-9496bb68710b

License:

This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 26 September 2020

Date accepted : 08 December 2020

Page count

Figures: 3, Tables: 2, References: 32

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One new species and one new record of Zasmidium in China

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Abstract

Background

New information

Related collections

Pensoft Biodiversity

Most cited references 33

IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

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

ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

Author and article information

Contributors

Journal

Affiliations

Author notes

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Article

History

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Cited by 2

Most referenced authors 2,145