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      Fungal Endophytic Community Associated with Guarana ( Paullinia cupana Var. Sorbilis): Diversity Driver by Genotypes in the Centre of Origin

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          Abstract

          Guarana plant is a native of the Amazon region. Due to its high amount of caffeine and tannins, the seed has medicinal and stimulating properties. The guarana industry has grown exponentially in recent years; however, little information is available about associated mycobiota, particularly endophytic fungi. The present study aimed to compare the distribution and diversity of endophytic fungi associated with the leaves and seeds of anthracnose-resistant and susceptible guarana plants produced in Maués and Manaus, Amazonas State, Brazil. A total of 7514 endophytic fungi were isolated on Potato Dextrose Agar, Sabouraud and Czapek media, and grouped into 77 morphological groups. Overall, fungal communities in guarana leaves and seeds were mainly composed by Colletotrichum and Fusarium genera, but also by Chondrostereum, Clonostachys, Curvularia, Hypomontagnella, Lentinus, Neopestalotiopsis, Nigrospora, Peroneutypa, Phyllosticta, Simplicillium and Tinctoporellus. Obtained results indicate that some members of Colletotrichum and Fusarium genera may have experienced dysbiosis during the guarana domestication process, suggesting that some individuals may behave as latent pathogens. The susceptible guarana genotype cultivated in Manaus presented higher fungal diversity. The relative abundance of taxa and diversity among samples suggests that communities are structured by genotype and geographic location. This is the first report of mycobiota in both guarana leaves and seeds.

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            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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              phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

              Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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                Author and article information

                Journal
                J Fungi (Basel)
                J Fungi (Basel)
                jof
                Journal of Fungi
                MDPI
                2309-608X
                31 July 2020
                September 2020
                : 6
                : 3
                : 123
                Affiliations
                [1 ]CEB-Centre of Biological Engineering, Micoteca da Universidade do Minho, University of Minho, 4710-057 Braga, Portugal; carla.santos@ 123456ceb.uminho.pt (C.S.); nelson@ 123456ie.uminho.pt (N.L.)
                [2 ]Postgraduate Program in Tropical Agronomy, Federal University of Amazonas, Manaus-AM 69067-005, Brazil; blenda.naara@ 123456gmail.com (B.N.S.d.S.); ana.tiburcia@ 123456gmail.com (A.F.T.A.F.eF.); jlbentes@ 123456ufam.edu.br (J.L.d.S.B.)
                [3 ]Department of Chemical Sciences and Natural Resources, BIOREN-UFRO, Universidad de La Frontera, Temuco 4811-230, Chile
                Author notes
                [* ]Correspondence: cledir.santos@ 123456ufrontera.cl ; Tel.: +56-452-596-726
                Author information
                https://orcid.org/0000-0002-4575-1807
                https://orcid.org/0000-0002-7484-8106
                https://orcid.org/0000-0003-4681-0941
                https://orcid.org/0000-0003-2185-0613
                https://orcid.org/0000-0001-7302-5661
                Article
                jof-06-00123
                10.3390/jof6030123
                7558939
                32751796
                14cb8fdc-860d-4f57-a228-8ebb689404e9
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 30 June 2020
                : 28 July 2020
                Categories
                Article

                mycobiota,composition,diversity,genotypes,plant organs,geographical location

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