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      Diversity of Plectosphaerella within aquatic plants from southwest China, with P. endophytica and P. sichuanensis spp. nov.

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          Members of Plectosphaerella inhabit different substrates, including plants, soil and insects, and most species are pathogens causing large losses in agriculture. During a survey of endophytic fungi in aquatic plants in southwest China, 112 strains of Plectosphaerella were isolated, representing two new species, P. endophytica sp. nov. and P. sichuanensis sp. nov., as well as two known species, P. cucumerina and P. pauciseptata . The novel taxa are described and illustrated here using combined morphological and multi-locus phylogenetic (LSU-ITS-TEF-1α-TUB2) analyses. Our result revealed Plectosphaerella species inhabiting within aquatic plants in southwest China, and the separation frequency of each species was presented.

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          Most cited references 33

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          MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.

          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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            MrBayes 3: Bayesian phylogenetic inference under mixed models.

            MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types-e.g. morphological, nucleotide, and protein-and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.
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              RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

              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

                Author and article information

                Pensoft Publishers
                11 May 2021
                : 80
                : 57-75
                [1 ] Laboratory for Conservation and Utilization of Bio-resources, Key Laboratory for Microbial Resources of the Ministry of Education, Yunnan University, Kunming, Yunnan, 650091, China Yunnan University Kunming China
                [2 ] Tianma development office of Yiliang county, Yunnan Province, China Tianma development office of Yiliang county Zhaotong China
                Author notes
                Corresponding author: Zefen Yu ( zfyuqm@ 123456hotmail.com )

                Academic editor: R. Phookamsak

                Xiao Qian Yang, Shi Yun Ma, Ze Xiang Peng, Zhong Qiao Wang, Min Qiao, Zefen Yu

                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.

                Laboratory for Conservation and Utilization of Bio-resources, Key Laboratory for Microbial Resources of the Ministry of Education, Yunnan University, Kunming, Yunnan, P. R. China. Tianma development office of Yiliang county, Yunnan province, P. R. China
                Research Article
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