Classifying a yeast strain into a recognized species is not always straightforward. Currently, the taxonomic delineation of yeast strains involves multiple approaches covering phenotypic characteristics and molecular methodologies, including genome-based analysis. The aim of this study was to evaluate the suitability of the Average Nucleotide Identity (ANI) calculation through FastANI, a tool created for bacterial species identification, for the assignment of strains to some yeast species. FastANI, the alignment of in silico-extracted D1/D2 sequences of LSU rRNA, and multiple alignments of orthologous genes (MAOG) were employed to analyze 644 assemblies from 12 yeast genera, encompassing various species, and on a dataset of hybrid Saccharomyces species. Overall, the analysis showed high consistency between results obtained with FastANI and MAOG, although, FastANI proved to be more discriminating than the other two methods applied to genomic sequences. In particular, FastANI was effective in distinguishing between strains belonging to different species, defining clear boundaries between them (cutoff: 94-96%). Our results show that FastANI is a reliable method for attributing a known yeast species to a particular strain. Moreover, although hybridization events make species discrimination more complex, it was revealed to be useful in the identification of these cases. We suggest its inclusion as a key component in a comprehensive approach to species delineation. Using this approach with a larger number of yeasts would validate it as a rapid technique to identify yeasts based on whole genome sequences.

Cortimiglia, C., Alonso-Del-Real, J., Belloso Daza, M. V., Querol, A., Iacono, G., Cocconcelli, P. S., Evaluating the Genome-Based Average Nucleotide Identity Calculation for Identification of Twelve Yeast Species, <<JOURNAL OF FUNGI>>, 2024; 10 (9): N/A-N/A. [doi:10.3390/jof10090646] [https://hdl.handle.net/10807/293036]

Evaluating the Genome-Based Average Nucleotide Identity Calculation for Identification of Twelve Yeast Species

Cortimiglia, Claudia;Belloso Daza, Mireya Viviana;Cocconcelli, Pier Sandro
2024

Abstract

Classifying a yeast strain into a recognized species is not always straightforward. Currently, the taxonomic delineation of yeast strains involves multiple approaches covering phenotypic characteristics and molecular methodologies, including genome-based analysis. The aim of this study was to evaluate the suitability of the Average Nucleotide Identity (ANI) calculation through FastANI, a tool created for bacterial species identification, for the assignment of strains to some yeast species. FastANI, the alignment of in silico-extracted D1/D2 sequences of LSU rRNA, and multiple alignments of orthologous genes (MAOG) were employed to analyze 644 assemblies from 12 yeast genera, encompassing various species, and on a dataset of hybrid Saccharomyces species. Overall, the analysis showed high consistency between results obtained with FastANI and MAOG, although, FastANI proved to be more discriminating than the other two methods applied to genomic sequences. In particular, FastANI was effective in distinguishing between strains belonging to different species, defining clear boundaries between them (cutoff: 94-96%). Our results show that FastANI is a reliable method for attributing a known yeast species to a particular strain. Moreover, although hybridization events make species discrimination more complex, it was revealed to be useful in the identification of these cases. We suggest its inclusion as a key component in a comprehensive approach to species delineation. Using this approach with a larger number of yeasts would validate it as a rapid technique to identify yeasts based on whole genome sequences.
2024
Inglese
Cortimiglia, C., Alonso-Del-Real, J., Belloso Daza, M. V., Querol, A., Iacono, G., Cocconcelli, P. S., Evaluating the Genome-Based Average Nucleotide Identity Calculation for Identification of Twelve Yeast Species, <<JOURNAL OF FUNGI>>, 2024; 10 (9): N/A-N/A. [doi:10.3390/jof10090646] [https://hdl.handle.net/10807/293036]
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