Abstract
The fungal kingdom represents a greatly untapped resource to produce a wide range of bioactive secondary metabolites, including antibiotics, anticancer agents, industrially significant dyes and enzymes. To-date, it is estimated only less than 5% of all fungi have been characterised, a deficit that is especially pronounced in tropical regions like Singapore, where fungal diversity remains underexplored compared to northern hemisphere counterparts. This underlines the urgency and importance of our research which motivated the creation of our curated dataset, aiming to address this gap and contribute to understanding the broader ecosystem. We developed a generalisable cultivation workflow that enables systematic strain preparation, supports high-resolution imaging, and yields sufficient fungal biomass amenable for genomic analyses. This resulted in a diverse collection of 518 phylogenetically and ecologically varied fungal strains from both terrestrial and marine environments in biodiverse Singapore. The curated dataset from this project captures both taxonomic identity and colony-level morphological traits serving as a foundation for visual phenotype to taxonomy mapping through the integration of computer vision.
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Data availability
All dataset components have been made publicly available on Figshare33. The 18S sequences have also been deposited to the NCBI SRA under the accession number SRP647581 (https://identifiers.org/ncbi/insdc.sra:SRP647581)34.
Code availability
Scripts for (1) 18S rRNA prediction with Barrnap, (2) MAFFT alignment, (3) FastTree maximum-likelihood tree inference, (4) consensus tree construction and (5) ResNet-50 embedding generation are available on the GitHub repository (https://github.com/twxdarren/fungal-trove.git) and Figshare33.
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Acknowledgements
This work is supported by the Agency for Science, Technology and Research (A*STAR) under C233017006, and the Singapore Integrative Biosystems and Engineering Research Strategic Research & Translational Thrust (SIBER SRTT, A*STAR). The authors extend their gratitude towards Dr. Siew Bee Ng (SIFBI, A*STAR) for her support on strains retrieval.
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F.T.W., Y.H.L. and W.K. conceptualised, designed and coordinated the study. D.W.X.T conducted the experiments and data acquisition. D.W.X.T. wrote the manuscript along with inputs from all the authors.
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Ten, D.W.X., Wong, F.T., Lim, Y.H. et al. A Singapore-centric Fungal Dataset of 518 Cultivated Strains with Visual Phenotypes and Taxonomic Identity. Sci Data (2026). https://doi.org/10.1038/s41597-025-06532-1
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DOI: https://doi.org/10.1038/s41597-025-06532-1
