• Data Descriptor

• Open access

• Published: 22 January 2026

• Darren Wei Xian Ten1,2,

• Fong Tian Wong1,2,3,

• Yee Hwee Lim1,2 &

• …

• Winston Koh1,2,4

Scientific Data , Article number: (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

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.

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.

References

Case, N. T. et al. The future of fungi: threats and opportunities. G3 Genes|Genomes|Genetics 12, jkac224 (2022).

Google Scholar 1.

Peay, K. G., Kennedy, P. G. & Talbot, J. M. Dimensions of biodiversity in the Earth mycobiome. Nat Rev Microbiol 14, 434–447 (2016).

Google Scholar 1.

Tedersoo, L. et al. Global diversity and geography of soil fungi. Science 346, 1256688 (2014).

Google Scholar 1.

Bhattarai, K., Bhattarai, K., Kabir, M. E., Bastola, R. & Baral, B. Fungal natural products galaxy: Biochemistry and molecular genetics toward blockbuster drugs discovery. in Advances in Genetics vol. 107 193–284 (Elsevier, 2021). 1.

Danner, C., Mach, R. L. & Mach-Aigner, A. R. The phenomenon of strain degeneration in biotechnologically relevant fungi. Appl Microbiol Biotechnol 107, 4745–4758 (2023).

Google Scholar 1.

Hyde, K. D. et al. Current trends, limitations and future research in the fungi? Fungal Diversity 125, 1–71 (2024).

Google Scholar 1.

Pye, C. R., Bertin, M. J., Lokey, R. S., Gerwick, W. H. & Linington, R. G. Retrospective analysis of natural products provides insights for future discovery trends. Proc. Natl. Acad. Sci. U.S.A. 114, 5601–5606 (2017).

Google Scholar 1.

Ahrendt, S. R., Mondo, S. J., Haridas, S. & Grigoriev, I. V. MycoCosm, the JGI’s Fungal Genome Portal for Comparative Genomic and Multiomics Data Analyses. in Microbial Environmental Genomics (MEG) (eds. Martin, F. & Uroz, S.) vol. 2605 271–291 (Springer US, New York, NY, 2023). 1.

Grigoriev, I. V. et al. MycoCosm portal: gearing up for 1000 fungal genomes. Nucl. Acids Res. 42, D699–D704 (2014).

Google Scholar 1.

Crous, P. W., Grams, W., Stalpers, J. A., Robert, V. & Stegehuis, G. MycoBank: an online initiative to launch mycology into the 21st century. Studies in Mycology 50, 19–22 (2004).

Google Scholar 1.

Robert, V. et al. MycoBank gearing up for new horizons. IMA Fungus 4, 371–379 (2013).

Google Scholar 1.

Huberman, L. B. Developing Functional Genomics Platforms for Fungi. mSystems 6, https://doi.org/10.1128/msystems.00730-21 (2021). 1.

Hyde, K. D. The numbers of fungi. Fungal Diversity 114, 1–1 (2022).

Google Scholar 1.

Paterson, R. R. M., Solaiman, Z. & Santamaria, O. Guest edited collection: fungal evolution and diversity. Sci Rep 13, 21438, s41598-023-48471–0 (2023). 1.

Wu, B. et al. Current insights into fungal species diversity and perspective on naming the environmental DNA sequences of fungi. Mycology 10, 127–140 (2019).

Google Scholar 1.

Aime, M. C. & Brearley, F. Q. Tropical fungal diversity: closing the gap between species estimates and species discovery. Biodivers Conserv 21, 2177–2180 (2012).

Google Scholar 1.

Stallman, J. K. et al. The contribution of tropical long-term studies to mycology. IMA Fungus 15, 35 (2024).

Google Scholar 1.

Chisholm, R. A. et al. Two centuries of biodiversity discovery and loss in Singapore. Proc. Natl. Acad. Sci. USA 120, e2309034120 (2023).

Google Scholar 1.

Davison, G. Special Ecology Feature: Biodiversity’s Crucial Role in the Modern Singapore City. CITYGREEN 01, 102 (2012).

Google Scholar 1.

Choong, M. F. A. Education on plants and fungi in Singapore: an urgent call. Nature in Singapore Supplement 1, 279286 (2022).

Google Scholar 1.

Lee, S. & Choong, A. Checklist of Fungi Species with their Category of Threat Status for Singapore. in The Singapore red data book: red lists of Singapore biodiversity 515–518 (National Parks Board, Singapore, 2024). 1.

Weerakoon, G., Ngo, K. M., Lum, S., Lumbsch, H. T. & Lücking, R. On time or fashionably late for lichen discoveries in Singapore? Seven new species and nineteen new records of Graphidaceae from the Bukit Timah Nature Reserve, a highly urbanized tropical environment in South-East Asia. The Lichenologist 47, 157–166 (2015).

Google Scholar 1.

Katoh, K. & Standley, D. M. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Molecular Biology and Evolution 30, 772–780 (2013).

Google Scholar 1.

Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments. PLoS ONE 5, e9490 (2010).

Google Scholar 1.

Yu, G., Smith, D. K., Zhu, H., Guan, Y. & Lam, T. T. ggtree: an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol Evol 8, 28–36 (2017).

Google Scholar 1.

He, K., Zhang, X., Ren, S. & Sun, J. Deep Residual Learning for Image Recognition. in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 770–778, https://doi.org/10.1109/CVPR.2016.90 (IEEE, Las Vegas, NV, USA, 2016). 1.

Zhou, X. et al. EAST: An Efficient and Accurate Scene Text Detector. in 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR*)* 2642–2651, https://doi.org/10.1109/CVPR.2017.283 (IEEE, Honolulu, HI, 2017). 1.

Eliahu, N., Igbaria, A., Rose, M. S., Horwitz, B. A. & Lev, S. Melanin Biosynthesis in the Maize Pathogen Cochliobolus heterostrophus Depends on Two Mitogen-Activated Protein Kinases, Chk1 and Mps1, and the Transcription Factor Cmr1. Eukaryot Cell 6, 421–429 (2007).

Google Scholar 1.

Plemenitaš, A., Vaupotič, T., Lenassi, M., Kogej, T. & Gunde-Cimerman, N. Adaptation of extremely halotolerant black yeast Hortaea werneckii to increased osmolarity: a molecular perspective at a glance. Studies in Mycology 61, 67–75 (2008).

Google Scholar 1.

Ng, S. B. et al. The 160K Natural Organism Library, a unique resource for natural products research. Nat Biotechnol 36, 570–573 (2018).

Google Scholar 1.

Seemann, T. barrnap 0.9: rapid ribosomal RNA prediction. https://github.com/tseemann/barrnap (2013). 1.

Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2019).

Google Scholar 1.

Ten, D. W. X., Wong, F. T., Lim, Y. H. & Koh, L. C. W. A Singapore-centric Fungal Dataset of 518 Cultivated Strains with Visual Phenotypes and Taxonomic Identity. figshare https://doi.org/10.6084/m9.figshare.29434469 (2025). 1.

NCBI Sequence Read Archive https://identifiers.org/ncbi/insdc.sra:SRP647581 (2025).

Download references

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.

Author information

Authors and Affiliations

Institute of Sustainability for Chemicals, Energy and Environment (ISCE2), Agency for Science, Technology and Research (A*STAR), 8 Biomedical Grove, #07-01 Neuros Building, Singapore, 138665, Republic of Singapore

Darren Wei Xian Ten, Fong Tian Wong, Yee Hwee Lim & Winston Koh 1.

Singapore Integrative Biosystems and Engineering Research, Biosystems and Engineering (SIBER), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-01 Innovis, Singapore, 138634, Republic of Singapore

Darren Wei Xian Ten, Fong Tian Wong, Yee Hwee Lim & Winston Koh 1.

Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), 61 Biopolis Drive, #07-06, Proteos, Singapore, 138673, Republic of Singapore

Fong Tian Wong 1.

Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Republic of Singapore

Winston Koh

Authors

1. Darren Wei Xian Ten
2. Fong Tian Wong
3. Yee Hwee Lim
4. Winston Koh

Contributions

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.

Corresponding author

Correspondence to Winston Koh.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Cite this article

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

Download citation

Received: 04 July 2025

Accepted: 24 December 2025

Published: 22 January 2026

DOI: https://doi.org/10.1038/s41597-025-06532-1