Exploring Saccharomycotina Yeast Ecology Through an Ecological Ontology Framework.

Autor: Harrison MC; Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, USA.; Evolutionary Studies Initiative, Vanderbilt University, Nashville, Tennessee, USA., Opulente DA; Department of Biology, Villanova University, Villanova, Pennsylvania, USA.; Laboratory of Genetics, DOE Great Lakes Bioenergy Research Center, Center for Genomic Science Innovation, Wisconsin Energy Institute, J. F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, Madison, Wisconsin, USA., Wolters JF; Laboratory of Genetics, DOE Great Lakes Bioenergy Research Center, Center for Genomic Science Innovation, Wisconsin Energy Institute, J. F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, Madison, Wisconsin, USA., Shen XX; Centre for Evolutionary and Organismal Biology, Institute of Insect Sciences, Zhejiang University, Hangzhou, China., Zhou X; Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Center, South China Agricultural University, Guangzhou, China., Groenewald M; Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands., Hittinger CT; Laboratory of Genetics, DOE Great Lakes Bioenergy Research Center, Center for Genomic Science Innovation, Wisconsin Energy Institute, J. F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, Madison, Wisconsin, USA., Rokas A; Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, USA.; Evolutionary Studies Initiative, Vanderbilt University, Nashville, Tennessee, USA., LaBella AL; Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Kannapolis, North Carolina, USA.; Center for Computational Intelligence to Predict Health and Environmental Risks (CIPHER), University of North Carolina at Charlotte, Charlotte, North Carolina, USA.
Jazyk: angličtina
Zdroj: Yeast (Chichester, England) [Yeast] 2024 Oct; Vol. 41 (10), pp. 615-628. Date of Electronic Publication: 2024 Sep 18.
DOI: 10.1002/yea.3981
Abstrakt: Yeasts in the subphylum Saccharomycotina are found across the globe in disparate ecosystems. A major aim of yeast research is to understand the diversity and evolution of ecological traits, such as carbon metabolic breadth, insect association, and cactophily. This includes studying aspects of ecological traits like genetic architecture or association with other phenotypic traits. Genomic resources in the Saccharomycotina have grown rapidly. Ecological data, however, are still limited for many species, especially those only known from species descriptions where usually only a limited number of strains are studied. Moreover, ecological information is recorded in natural language format limiting high throughput computational analysis. To address these limitations, we developed an ontological framework for the analysis of yeast ecology. A total of 1,088 yeast strains were added to the Ontology of Yeast Environments (OYE) and analyzed in a machine-learning framework to connect genotype to ecology. This framework is flexible and can be extended to additional isolates, species, or environmental sequencing data. Widespread adoption of OYE would greatly aid the study of macroecology in the Saccharomycotina subphylum.
(© 2024 The Author(s). Yeast published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
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