Exploring Saccharomycotina Yeast Ecology Through an Ecological Ontology Framework

Marie Claire Harrison, Dana A. Opulente, John F. Wolters, Xing Xing Shen, Xiaofan Zhou, Marizeth Groenewald, Chris Todd Hittinger, Antonis Rokas, Abigail Leavitt LaBella*

*Bijbehorende auteur voor dit werk

Onderzoeksoutput: Bijdrage aan wetenschappelijk tijdschrift/periodieke uitgaveBoek/film/artikelrecensieWetenschappelijk

Samenvatting

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.

Originele taal-2Engels
Pagina's (van-tot)615-628
Aantal pagina's14
TijdschriftYeast
Volume41
Nummer van het tijdschrift10
DOI's
StatusGepubliceerd - okt. 2024

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