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      Notes on four species of Russula subgenus Heterophyllidiae (Russulaceae, Russulales) from southern China

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          Abstract

          Heterophyllidiae, one of the main subgenus of Russula (Russulaceae, Russulales), is both ecologically and economically important. Although many studies have focused on subgenus Heterophyllidiae in China, the diversity, taxonomy, and molecular phylogeny still remained incompletely understood. In the present study, two new species, R. discoidea and R. niveopicta, and two known taxa, R. xanthovirens and R. subatropurpurea, were described based on morphology and molecular phylogenetic analyses of ITS and 28S DNA sequences with new collections of subgenus Heterophyllidiae from southern China. Both morphological and phylogenetic analyses consistently confirmed that R. niveopicta and R. xanthovirens belong to the subsect. Virescentinae, R. discoidea and R. subatropurpurea come under subsect. Heterophyllae, and R. prasina is synonymized with R. xanthovirens.

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          MUSCLE: multiple sequence alignment with high accuracy and high throughput.

          R. C. Edgar (2004)
          We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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            AMPLIFICATION AND DIRECT SEQUENCING OF FUNGAL RIBOSOMAL RNA GENES FOR PHYLOGENETICS

            T.J White, T. Bruns, S. Lee … (1990)
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              RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

              Alexandros Stamatakis (2006)
              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
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                Author and article information

                Contributors
                Journal
                Journal ID (nlm-ta): Front Microbiol
                Journal ID (iso-abbrev): Front Microbiol
                Journal ID (publisher-id): Front. Microbiol.
                Title: Frontiers in Microbiology
                Publisher: Frontiers Media S.A.
                ISSN (Electronic): 1664-302X
                Publication date (Electronic): 21 March 2023
                Publication date Collection: 2023
                Volume: 14
                Electronic Location Identifier: 1140127
                Affiliations
                [1] 1Key Laboratory of Tropical Translational Medicine of Ministry of Education, School of Pharmacy, Hainan Medical University , Haikou, China
                [2] 2College of Science, Hainan University , Haikou, China
                Author notes

                Edited by: Yong-Zhong Lu, Guizhou Institute of Technology, China

                Reviewed by: Fang Wu, Beijing Forestry University, China; Chang-lin Zhao, Southwest Forestry University, China

                *Correspondence: Zhi-Qun Liang, lizhqu1980@ 123456126.com

                This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                DOI: 10.3389/fmicb.2023.1140127
                PMC ID: 10072125
                SO-VID: bdc9df30-a2fb-4bfb-9a6a-20c55432704a
                Copyright © Copyright © 2023 Han, Liang and Zeng.
                License:

                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
                Date received : 08 January 2023
                Date accepted : 23 February 2023
                Page count
                Figures: 11, Tables: 7, Equations: 0, References: 85, Pages: 18, Words: 12144
                Funding
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Award ID: 32160001
                Funded by: Natural Science Foundation of Hainan Medical University
                Award ID: JBGS202112
                Funded by: Hainan Institute of National Park
                Categories
                Subject: Microbiology
                Subject: Original Research

                ScienceOpen disciplines: Microbiology & Virology
                Keywords: ectomycorrhizal fungi,molecular phylogeny,morphology,new taxa,taxonomy
                Data availability:
                ScienceOpen disciplines: Microbiology & Virology
                Keywords: ectomycorrhizal fungi, molecular phylogeny, morphology, new taxa, taxonomy

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