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      The evolving species concepts used for yeasts: from phenotypes and genomes to speciation networks

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          Abstract

          Here we review how evolving species concepts have been applied to understand yeast diversity. Initially, a phenotypic species concept was utilized taking into consideration morphological aspects of colonies and cells, and growth profiles. Later the biological species concept was added, which applied data from mating experiments. Biophysical measurements of DNA similarity between isolates were an early measure that became more broadly applied with the advent of sequencing technology, leading to a sequence-based species concept using comparisons of parts of the ribosomal DNA. At present phylogenetic species concepts that employ sequence data of rDNA and other genes are universally applied in fungal taxonomy, including yeasts, because various studies revealed a relatively good correlation between the biological species concept and sequence divergence. The application of genome information is becoming increasingly common, and we strongly recommend the use of complete, rather than draft genomes to improve our understanding of species and their genome and genetic dynamics. Complete genomes allow in-depth comparisons on the evolvability of genomes and, consequently, of the species to which they belong. Hybridization seems a relatively common phenomenon and has been observed in all major fungal lineages that contain yeasts. Note that hybrids may greatly differ in their post-hybridization development. Future in-depth studies, initially using some model species or complexes may shift the traditional species concept as isolated clusters of genetically compatible isolates to a cohesive speciation network in which such clusters are interconnected by genetic processes, such as hybridization.

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          Most cited references230

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          Basic local alignment search tool.

          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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            Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

            S Altschul (1997)
            The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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              Hybridization and speciation.

              Hybridization has many and varied impacts on the process of speciation. Hybridization may slow or reverse differentiation by allowing gene flow and recombination. It may accelerate speciation via adaptive introgression or cause near-instantaneous speciation by allopolyploidization. It may have multiple effects at different stages and in different spatial contexts within a single speciation event. We offer a perspective on the context and evolutionary significance of hybridization during speciation, highlighting issues of current interest and debate. In secondary contact zones, it is uncertain if barriers to gene flow will be strengthened or broken down due to recombination and gene flow. Theory and empirical evidence suggest the latter is more likely, except within and around strongly selected genomic regions. Hybridization may contribute to speciation through the formation of new hybrid taxa, whereas introgression of a few loci may promote adaptive divergence and so facilitate speciation. Gene regulatory networks, epigenetic effects and the evolution of selfish genetic material in the genome suggest that the Dobzhansky-Muller model of hybrid incompatibilities requires a broader interpretation. Finally, although the incidence of reinforcement remains uncertain, this and other interactions in areas of sympatry may have knock-on effects on speciation both within and outside regions of hybridization. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.
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                Author and article information

                Contributors
                t.boekhout@wi.knaw.nl
                Journal
                Fungal Divers
                Fungal Divers
                Fungal Diversity
                Springer Netherlands (Dordrecht )
                1560-2745
                1878-9129
                26 June 2021
                26 June 2021
                2021
                : 109
                : 1
                : 27-55
                Affiliations
                [1 ]GRID grid.418704.e, ISNI 0000 0004 0368 8584, Westerdijk Fungal Biodiversity Institute, ; Utrecht, The Netherlands
                [2 ]GRID grid.7177.6, ISNI 0000000084992262, Institute of Biodiversity and Ecosystem Dynamics (IBED), , University of Amsterdam, ; Amsterdam, The Netherlands
                [3 ]GRID grid.169077.e, ISNI 0000 0004 1937 2197, Dept Botany and Plant Pathology, College of Agriculture, , Purdue University, ; West Lafayette, IN 47907 USA
                [4 ]GRID grid.5570.7, ISNI 0000 0004 0490 981X, Evolution of Plants and Fungi, Ruhr-University Bochum, ; 44801 Bochum, Germany
                [5 ]GRID grid.10097.3f, ISNI 0000 0004 0387 1602, Barcelona Supercomputing Centre (BSC–CNS), Jordi Girona, ; 29, 08034 Barcelona, Spain
                [6 ]GRID grid.7722.0, ISNI 0000 0001 1811 6966, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, ; 10, 08028 Barcelona, Spain
                [7 ]GRID grid.425902.8, ISNI 0000 0000 9601 989X, Catalan Institution for Research and Advanced Studies (ICREA), ; Barcelona, Spain
                [8 ]GRID grid.189509.c, ISNI 0000000100241216, Department of Molecular Genetics and Microbiology, , Duke University Medical Center, ; Durham, NC 27710 USA
                [9 ]GRID grid.412996.1, ISNI 0000 0004 0625 2209, Department of Microbiology and Parasitology, Faculty of Medical Sciences, , University of Phayao, ; Phayao, 56000 Thailand
                [10 ]GRID grid.39381.30, ISNI 0000 0004 1936 8884, Department of Biology, , University of Western Ontario, ; London, ON N6A 5B7 Canada
                [11 ]GRID grid.9918.9, ISNI 0000 0004 1936 8411, Department of Genetics and Genome Biology, Genetic Architecture of Complex Traits, , University of Leicester, ; Leicester, LE1 7RH UK
                [12 ]GRID grid.420081.f, ISNI 0000 0000 9247 8466, German Collection of Microorganisms and Cell Cultures, Leibniz Institute DSMZ, ; Brunswick, Germany
                Author notes

                Handling editor: Jian-Kui Liu

                Author information
                http://orcid.org/0000-0002-0476-3609
                http://orcid.org/0000-0001-8742-6685
                http://orcid.org/0000-0002-8286-1597
                http://orcid.org/0000-0003-0019-1735
                http://orcid.org/0000-0001-6369-5995
                http://orcid.org/0000-0002-0738-4233
                http://orcid.org/0000-0002-9867-8324
                http://orcid.org/0000-0001-9139-3935
                http://orcid.org/0000-0003-1157-3608
                http://orcid.org/0000-0002-2895-1153
                http://orcid.org/0000-0001-7960-2765
                http://orcid.org/0000-0002-1072-5166
                Article
                475
                10.1007/s13225-021-00475-9
                8550739
                34720775
                edf2f31a-04eb-4873-a51d-26ad84b4f83b
                © The Author(s) 2021, corrected publication 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 November 2020
                : 31 May 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: Award AI39115-23
                Award ID: Award AI39115-23
                Award ID: Award AI50113-16
                Award ID: Award AI50113-16
                Award ID: Award AI133654-03
                Award ID: Award AI133654-03
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000268, Biotechnology and Biological Sciences Research Council;
                Award ID: BB/L022508/1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: BE 2201/23-1
                Award ID: BE 2201/28-1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100007917, Agricultural Research Service;
                Award ID: USDA Hatch 1010662
                Award Recipient :
                Categories
                Review
                Custom metadata
                © MUSHROOM RESEARCH FOUNDATION 2021

                fungi,species concepts,comparative genomics,hybrids,nomenclature,taxonomy

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