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      Epidemiology, Biotic Interactions and Biological Control of Armillarioids in the Northern Hemisphere

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          Abstract

          Armillarioids, including the genera Armillaria, Desarmillaria and Guyanagaster, represent white-rot specific fungal saprotrophs with soilborne pathogenic potentials on woody hosts. They propagate in the soil by root-like rhizomorphs, connecting between susceptible root sections of their hosts, and often forming extended colonies in native forests. Pathogenic abilities of Armillaria and Desarmillaria genets can readily manifest in compromised hosts, or hosts with full vigour can be invaded by virulent mycelia when exposed to a larger number of newly formed genets. Armillaria root rot-related symptoms are indicators of ecological imbalances in native forests and plantations at the rhizosphere levels, often related to abiotic environmental threats, and most likely unfavourable changes in the microbiome compositions in the interactive zone of the roots. The less-studied biotic impacts that contribute to armillarioid host infection include fungi and insects, as well as forest conditions. On the other hand, negative biotic impactors, like bacterial communities, antagonistic fungi, nematodes and plant-derived substances may find applications in the environment-friendly, biological control of armillarioid root diseases, which can be used instead of, or in combination with the classical, but frequently problematic silvicultural and chemical control measures.

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          Most cited references322

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          FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments

          Background We recently described FastTree, a tool for inferring phylogenies for alignments with up to hundreds of thousands of sequences. Here, we describe improvements to FastTree that improve its accuracy without sacrificing scalability. Methodology/Principal Findings Where FastTree 1 used nearest-neighbor interchanges (NNIs) and the minimum-evolution criterion to improve the tree, FastTree 2 adds minimum-evolution subtree-pruning-regrafting (SPRs) and maximum-likelihood NNIs. FastTree 2 uses heuristics to restrict the search for better trees and estimates a rate of evolution for each site (the “CAT” approximation). Nevertheless, for both simulated and genuine alignments, FastTree 2 is slightly more accurate than a standard implementation of maximum-likelihood NNIs (PhyML 3 with default settings). Although FastTree 2 is not quite as accurate as methods that use maximum-likelihood SPRs, most of the splits that disagree are poorly supported, and for large alignments, FastTree 2 is 100–1,000 times faster. FastTree 2 inferred a topology and likelihood-based local support values for 237,882 distinct 16S ribosomal RNAs on a desktop computer in 22 hours and 5.8 gigabytes of memory. Conclusions/Significance FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments. FastTree 2 is freely available at http://www.microbesonline.org/fasttree.
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            MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform.

            K Katoh (2002)
            A multiple sequence alignment program, MAFFT, has been developed. The CPU time is drastically reduced as compared with existing methods. MAFFT includes two novel techniques. (i) Homo logous regions are rapidly identified by the fast Fourier transform (FFT), in which an amino acid sequence is converted to a sequence composed of volume and polarity values of each amino acid residue. (ii) We propose a simplified scoring system that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length. Two different heuristics, the progressive method (FFT-NS-2) and the iterative refinement method (FFT-NS-i), are implemented in MAFFT. The performances of FFT-NS-2 and FFT-NS-i were compared with other methods by computer simulations and benchmark tests; the CPU time of FFT-NS-2 is drastically reduced as compared with CLUSTALW with comparable accuracy. FFT-NS-i is over 100 times faster than T-COFFEE, when the number of input sequences exceeds 60, without sacrificing the accuracy.
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              OrthoFinder: phylogenetic orthology inference for comparative genomics

              Here, we present a major advance of the OrthoFinder method. This extends OrthoFinder’s high accuracy orthogroup inference to provide phylogenetic inference of orthologs, rooted gene trees, gene duplication events, the rooted species tree, and comparative genomics statistics. Each output is benchmarked on appropriate real or simulated datasets, and where comparable methods exist, OrthoFinder is equivalent to or outperforms these methods. Furthermore, OrthoFinder is the most accurate ortholog inference method on the Quest for Orthologs benchmark test. Finally, OrthoFinder’s comprehensive phylogenetic analysis is achieved with equivalent speed and scalability to the fastest, score-based heuristic methods. OrthoFinder is available at https://github.com/davidemms/OrthoFinder.
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                Author and article information

                Journal
                Pathogens
                Pathogens
                pathogens
                Pathogens
                MDPI
                2076-0817
                16 January 2021
                January 2021
                : 10
                : 1
                : 76
                Affiliations
                [1 ]Department of Microbiology, Faculty of Science and Informatics, University of Szeged, Szeged, Közép fasor 52, H-6726 Szeged, Hungary; kedvesorsolya91@ 123456gmail.com (O.K.); danish18581@ 123456yahoo.co.in (D.S.); simang5c@ 123456uni-sopron.hu (S.C.); liqiongchen2016@ 123456163.com (L.C.); boka.tina@ 123456gmail.com (B.B.); viktor.david.nagy@ 123456gmail.com (V.D.N.); csaba@ 123456bio.u-szeged.hu (C.V.)
                [2 ]Functional Genomics and Bioinformatics Group, Research Center for Forestry and Wood Industry, University of Sopron, Bajcsy-Zsilinszky str. 4., H-9400 Sopron, Hungary; boris.indjic@ 123456phd.uni-sopron.hu
                Author notes
                [* ]Correspondence: kredics@ 123456bio.u-szeged.hu (L.K.); sipos.gyorgy@ 123456uni-sopron.hu (G.S.); Tel.: +36-62-544516 (L.K.); +36-99-518769 (G.S.)
                [†]

                Equal contribution.

                Author information
                https://orcid.org/0000-0003-0009-7773
                https://orcid.org/0000-0002-8837-3973
                https://orcid.org/0000-0002-6666-1384
                Article
                pathogens-10-00076
                10.3390/pathogens10010076
                7830283
                33467216
                b9a19829-2fa6-48e3-a01a-19f94460174d
                © 2021 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 November 2020
                : 14 January 2021
                Categories
                Review

                armillaria,biocontrol,epidemiology,management
                armillaria, biocontrol, epidemiology, management

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