High-throughput sequencing studies generate vast amounts of taxonomic data.Evolutionary ecological hypotheses of the recovered taxa and Species Hypotheses are difficult to test due to problems with alignments and the ...High-throughput sequencing studies generate vast amounts of taxonomic data.Evolutionary ecological hypotheses of the recovered taxa and Species Hypotheses are difficult to test due to problems with alignments and the lack of a phylogenetic backbone.We propose an updated phylum-and class-level fungal classification accounting for monophyly and divergence time so that the main taxonomic ranks are more informative.Based on phylogenies and divergence time estimates,we adopt phylum rank to Aphelidiomycota,Basidiobolomycota,Calcarisporiellomycota,Glomeromycota,Entomophthoromycota,Entorrhizomycota,Kickxellomycota,Monoblepharomycota,Mortierellomycota and Olpidiomycota.We accept nine subkingdoms to accommodate these 18 phyla.We consider the kingdom Nucleariae(phyla Nuclearida and Fonticulida)as a sister group to the Fungi.We also introduce a perl script and a newick-formatted classification backbone for assigning Species Hypotheses into a hierarchical taxonomic framework,using this or any other classification system.We provide an example of testing evolutionary ecological hypotheses based on a global soil fungal data set.展开更多
The cryptic lifestyle of most fungi necessitates molecular identification of the guild in environmental studies.Over the past decades,rapid development and affordability of molecular tools have tremendously improved i...The cryptic lifestyle of most fungi necessitates molecular identification of the guild in environmental studies.Over the past decades,rapid development and affordability of molecular tools have tremendously improved insights of the fungal diversity in all ecosystems and habitats.Yet,in spite of the progress of molecular methods,knowledge about functional properties of the fungal taxa is vague and interpretation of environmental studies in an ecologically meaningful manner remains challenging.In order to facilitate functional assignments and ecological interpretation of environmental studies we introduce a user friendly traits and character database FungalTraits operating at genus and species hypothesis levels.Combining the information from previous efforts such as FUNGuild and FunFun together with involvement of expert knowledge,we reannotated 10,210 and 151 fungal and Stramenopila genera,respectively.This resulted in a stand-alone spreadsheet dataset covering 17 lifestyle related traits of fungal and Stramenopila genera,designed for rapid functional assignments of environmental stud-ies.In order to assign the trait states to fungal species hypotheses,the scientific community of experts manually categorised and assigned available trait information to 697,413 fungal ITS sequences.On the basis of those sequences we were able to summarise trait and host information into 92,623 fungal species hypotheses at 1%dissimilarity threshold.展开更多
Correction to:Fungal Diversity(2020)105:116 https://doi.org/10.1007/s13225-020-00466-2 There were errors in the name of author LászlóG.Nagy and in affiliation no.31 in the original publication.The original a...Correction to:Fungal Diversity(2020)105:116 https://doi.org/10.1007/s13225-020-00466-2 There were errors in the name of author LászlóG.Nagy and in affiliation no.31 in the original publication.The original article has been corrected.展开更多
基金LT acknowledges funding from the Estonian Science Foundation(1399PUT,IUT20-30),MOBERC and ECOLCHANGE.
文摘High-throughput sequencing studies generate vast amounts of taxonomic data.Evolutionary ecological hypotheses of the recovered taxa and Species Hypotheses are difficult to test due to problems with alignments and the lack of a phylogenetic backbone.We propose an updated phylum-and class-level fungal classification accounting for monophyly and divergence time so that the main taxonomic ranks are more informative.Based on phylogenies and divergence time estimates,we adopt phylum rank to Aphelidiomycota,Basidiobolomycota,Calcarisporiellomycota,Glomeromycota,Entomophthoromycota,Entorrhizomycota,Kickxellomycota,Monoblepharomycota,Mortierellomycota and Olpidiomycota.We accept nine subkingdoms to accommodate these 18 phyla.We consider the kingdom Nucleariae(phyla Nuclearida and Fonticulida)as a sister group to the Fungi.We also introduce a perl script and a newick-formatted classification backbone for assigning Species Hypotheses into a hierarchical taxonomic framework,using this or any other classification system.We provide an example of testing evolutionary ecological hypotheses based on a global soil fungal data set.
基金Estonian Science Foundation grants PSG136,PRG632,PUT1170the University of Tartu(PLTOM20903)the European Regional Development Fund(Centre of Excellence EcolChange).
文摘The cryptic lifestyle of most fungi necessitates molecular identification of the guild in environmental studies.Over the past decades,rapid development and affordability of molecular tools have tremendously improved insights of the fungal diversity in all ecosystems and habitats.Yet,in spite of the progress of molecular methods,knowledge about functional properties of the fungal taxa is vague and interpretation of environmental studies in an ecologically meaningful manner remains challenging.In order to facilitate functional assignments and ecological interpretation of environmental studies we introduce a user friendly traits and character database FungalTraits operating at genus and species hypothesis levels.Combining the information from previous efforts such as FUNGuild and FunFun together with involvement of expert knowledge,we reannotated 10,210 and 151 fungal and Stramenopila genera,respectively.This resulted in a stand-alone spreadsheet dataset covering 17 lifestyle related traits of fungal and Stramenopila genera,designed for rapid functional assignments of environmental stud-ies.In order to assign the trait states to fungal species hypotheses,the scientific community of experts manually categorised and assigned available trait information to 697,413 fungal ITS sequences.On the basis of those sequences we were able to summarise trait and host information into 92,623 fungal species hypotheses at 1%dissimilarity threshold.
文摘Correction to:Fungal Diversity(2020)105:116 https://doi.org/10.1007/s13225-020-00466-2 There were errors in the name of author LászlóG.Nagy and in affiliation no.31 in the original publication.The original article has been corrected.
