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      Prevalence of transcription factors in ascomycete and basidiomycete fungi

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          Abstract

          Background

          Gene regulation underlies fungal physiology and therefore is a major factor in fungal biodiversity. Analysis of genome sequences has revealed a large number of putative transcription factors in most fungal genomes. The presence of fungal orthologs for individual regulators has been analysed and appears to be highly variable with some regulators widely conserved and others showing narrow distribution. Although genome-scale transcription factor surveys have been performed before, no global study into the prevalence of specific regulators across the fungal kingdom has been presented.

          Results

          In this study we have analysed the number of members for 37 regulator classes in 77 ascomycete and 31 basidiomycete fungal genomes and revealed significant differences between ascomycetes and basidiomycetes. In addition, we determined the presence of 64 regulators characterised in ascomycetes across these 108 genomes. This demonstrated that overall the highest presence of orthologs is in the filamentous ascomycetes. A significant number of regulators lacked orthologs in the ascomycete yeasts and the basidiomycetes. Conversely, of seven basidiomycete regulators included in the study, only one had orthologs in ascomycetes.

          Conclusions

          This study demonstrates a significant difference in the regulatory repertoire of ascomycete and basidiomycete fungi, at the level of both regulator class and individual regulator. This suggests that the current regulatory systems of these fungi have been mainly developed after the two phyla diverged. Most regulators detected in both phyla are involved in central functions of fungal physiology and therefore were likely already present in the ancestor of the two phyla.

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          Most cited references114

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          Genome sequencing and analysis of the biomass-degrading fungus Trichoderma reesei (syn. Hypocrea jecorina).

          Trichoderma reesei is the main industrial source of cellulases and hemicellulases used to depolymerize biomass to simple sugars that are converted to chemical intermediates and biofuels, such as ethanol. We assembled 89 scaffolds (sets of ordered and oriented contigs) to generate 34 Mbp of nearly contiguous T. reesei genome sequence comprising 9,129 predicted gene models. Unexpectedly, considering the industrial utility and effectiveness of the carbohydrate-active enzymes of T. reesei, its genome encodes fewer cellulases and hemicellulases than any other sequenced fungus able to hydrolyze plant cell wall polysaccharides. Many T. reesei genes encoding carbohydrate-active enzymes are distributed nonrandomly in clusters that lie between regions of synteny with other Sordariomycetes. Numerous genes encoding biosynthetic pathways for secondary metabolites may promote survival of T. reesei in its competitive soil habitat, but genome analysis provided little mechanistic insight into its extraordinary capacity for protein secretion. Our analysis, coupled with the genome sequence data, provides a roadmap for constructing enhanced T. reesei strains for industrial applications such as biofuel production.
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            Insights from the genome of the biotrophic fungal plant pathogen Ustilago maydis.

            Ustilago maydis is a ubiquitous pathogen of maize and a well-established model organism for the study of plant-microbe interactions. This basidiomycete fungus does not use aggressive virulence strategies to kill its host. U. maydis belongs to the group of biotrophic parasites (the smuts) that depend on living tissue for proliferation and development. Here we report the genome sequence for a member of this economically important group of biotrophic fungi. The 20.5-million-base U. maydis genome assembly contains 6,902 predicted protein-encoding genes and lacks pathogenicity signatures found in the genomes of aggressive pathogenic fungi, for example a battery of cell-wall-degrading enzymes. However, we detected unexpected genomic features responsible for the pathogenicity of this organism. Specifically, we found 12 clusters of genes encoding small secreted proteins with unknown function. A significant fraction of these genes exists in small gene families. Expression analysis showed that most of the genes contained in these clusters are regulated together and induced in infected tissue. Deletion of individual clusters altered the virulence of U. maydis in five cases, ranging from a complete lack of symptoms to hypervirulence. Despite years of research into the mechanism of pathogenicity in U. maydis, no 'true' virulence factors had been previously identified. Thus, the discovery of the secreted protein gene clusters and the functional demonstration of their decisive role in the infection process illuminate previously unknown mechanisms of pathogenicity operating in biotrophic fungi. Genomic analysis is, similarly, likely to open up new avenues for the discovery of virulence determinants in other pathogens.
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              Multiple alignment of DNA sequences with MAFFT.

              Multiple alignment of DNA sequences is an important step in various molecular biological analyses. As a large amount of sequence data is becoming available through genome and other large-scale sequencing projects, scalability, as well as accuracy, is currently required for a multiple sequence alignment (MSA) program. In this chapter, we outline the algorithms of an MSA program MAFFT and provide practical advice, focusing on several typical situations a biologist sometimes faces. For genome alignment, which is beyond the scope of MAFFT, we introduce two tools: TBA and MAUVE.
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                Author and article information

                Contributors
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2014
                20 March 2014
                : 15
                : 214
                Affiliations
                [1 ]Department of Plant Pathology, Kansas State University, 4024 Throckmorton Plant Sciences Center, Manhattan, KS 66506, USA
                [2 ]Fungal Physiology, CBS-KNAW, Uppsalalaan 8, 3584 CT Utrecht, The Netherlands
                [3 ]Microbiology & Kluyver Centre for Genomics of Industrial Fermentations, Utrecht University, Uppsalalaan 8, 3584 CT Utrecht, The Netherlands
                [4 ]Current address: US Department of Energy (DOE) Joint Genome Institute (JGI), 2800 Mitchell Drive, Walnut Creek, CA 94598, USA
                [5 ]Current address: Department of Plant Physiology, Wageningen University, Droevendaalsesteeg 1, 6708 PA, Wageningen, The Netherlands
                Article
                1471-2164-15-214
                10.1186/1471-2164-15-214
                3998117
                24650355
                14c21410-bc04-417f-ae6e-2e31e2732e92
                Copyright © 2014 Todd et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

                History
                : 17 August 2013
                : 11 March 2014
                Categories
                Research Article

                Genetics
                transcription factor,ascomycete,basidiomycete,gene regulation,fungal genomes,evolution,zinc binuclear cluster,zinc finger,dna binding domain,aspergillus

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