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Saccharomycotina yeasts defy longstanding macroecological patterns.
David, Kyle T; Harrison, Marie-Claire; Opulente, Dana A; LaBella, Abigail L; Wolters, John F; Zhou, Xiaofan; Shen, Xing-Xing; Groenewald, Marizeth; Pennell, Matt; Hittinger, Chris Todd; Rokas, Antonis.
Affiliation
  • David KT; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA; Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA.
  • Harrison MC; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA; Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA.
  • Opulente DA; Laboratory of Genetics, J. F. Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, DOE Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI 53726, USA.
  • LaBella AL; Department of Biology, Villanova University, Villanova PA 19085, USA.
  • Wolters JF; Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA; Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN 37235, USA.
  • Zhou X; Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte NC 28223, USA.
  • Shen XX; Laboratory of Genetics, J. F. Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, DOE Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI 53726, USA.
  • Groenewald M; Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Province Key Laboratory of Microbial Signals and Disease Control, Integrative Microbiology Research Center, South China Agricultural University, Guangzhou 510642, China.
  • Pennell M; Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Insect Sciences, Zhejiang University, Hangzhou 310058, China.
  • Hittinger CT; Westerdijk Fungal Biodiversity Institute, 3584 Utrecht, The Netherlands.
  • Rokas A; Department of Quantitative and Computational Biology and Biological Sciences, University of Southern California, Los Angeles CA 90089, USA.
bioRxiv ; 2023 Aug 31.
Article in En | MEDLINE | ID: mdl-37693602
ABSTRACT
The Saccharomycotina yeasts ("yeasts" hereafter) are a fungal clade of scientific, economic, and medical significance. Yeasts are highly ecologically diverse, found across a broad range of environments in every biome and continent on earth1; however, little is known about what rules govern the macroecology of yeast species and their range limits in the wild2. Here, we trained machine learning models on 12,221 occurrence records and 96 environmental variables to infer global distribution maps for 186 yeast species (~15% of described species from 75% of orders) and to test environmental drivers of yeast biogeography and macroecology. We found that predicted yeast diversity hotspots occur in mixed montane forests in temperate climates. Diversity in vegetation type and topography were some of the greatest predictors of yeast species richness, suggesting that microhabitats and environmental clines are key to yeast diversification. We further found that range limits in yeasts are significantly influenced by carbon niche breadth and range overlap with other yeast species, with carbon specialists and species in high diversity environments exhibiting reduced geographic ranges. Finally, yeasts contravene many longstanding macroecological principles, including the latitudinal diversity gradient, temperature-dependent species richness, and latitude-dependent range size (Rapoport's rule). These results unveil how the environment governs the global diversity and distribution of species in the yeast subphylum. These high-resolution models of yeast species distributions will facilitate the prediction of economically relevant and emerging pathogenic species under current and future climate scenarios.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: BioRxiv Year: 2023 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: BioRxiv Year: 2023 Document type: Article Affiliation country: United States
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