Navigating uncertainty in museum workflows: genomic data mining and curation of the Diptera collections hosted at RMCA
Authors/Creators
- Esselens, Lore1
- Addison, Pia2
- Bakengesa, Jacqueline3
- Bota, Luis4
- Canhanga, Laura5
- Cugala, Domingos5
- Daniel, Beatriz5
- De Meyer, Marc1
- Delatte, Hélène6
- Herpers, Jean-Marc7
- Jordaens, Kurt1
- Kabota, Sija8
- Kudra, Abdul8
- Majubwa, Ramadhani8
- Manrakhan, Aruna9
- Mussumbe, Mirene5
- Mwatawala, Maulid8
- Theeten, Franck1
- Van den Spiegel, Didier1
- Vanbergen, Sam10
- Vangestel, Carl11
- Virgilio, Massimiliano1
- 1. Royal Museum for Central Africa, Tervuren, Belgium
- 2. University of Stellenbosch, Stellenbosch, South Africa
- 3. Sokoine University of Agriculture, Morogoro, Tanzania|The University of Dodoma, Dodoma, Tanzania
- 4. National Fruit Fly Laboratory, Chimoio, Mozambique|Eduardo Mondlane University, Maputo, Mozambique|Centre of Excellence in Agri-Food Systems and Nutrition, Maputo, Mozambique
- 5. Eduardo Mondlane University, Maputo, Mozambique|Centre of Excellence in Agri-Food Systems and Nutrition, Maputo, Mozambique
- 6. Centre de Coopération Internationale en Recherche Agronomique pour le Développement, La Réunion, France
- 7. Royal Belgian Institute of Natural Sciences, Brussels, Belgium
- 8. Sokoine University of Agriculture, Morogoro, Tanzania
- 9. Citrus Research International, Nelspruit, South Africa
- 10. Royal Museum for Central Africa, Tervuren, Belgium|University of Leuven, Leuven, Belgium
- 11. Royal Belgian Institute of Natural Sciences, Brussels, Belgium|University of Ghent, Ghent, Belgium
Description
As part of its extensive Diptera holdings, the Royal Museum for Central Africa (RMCA) houses over 100,000 specimens of Tephritidae and Syrphidae, which represent a critical resource for taxonomic and systematic research. Here, we present a feasibility study evaluating streamlined workflows for genomic data mining and archiving in museum collections. We analysed DNA yield, quality and sequencing performance from more than 1,400 insect vouchers and found few predictable trends, reflecting the nature of heterogeneous and skewed groups of samples collected under largely unknown field conditions. Regardless, our results show that Illumina short read whole genome sequencing can work well even with degraded insect material. In this context, routine short-read sequencing offers a practical first step for genomic data mining, particularly for large collections. It enables us to reserve more complex and resource-intensive methods for the subset of samples that fail initial sequencing (7% of specimens, in our case). As an outcome of this work, RMCA's archiving system has been adapted to integrate genomic data and metadata alongside traditional specimen records. We argue that genomic data should be treated as an integral component of collection management, enhancing scientific value, supporting long term preservation and improving traceability of genetic resources in natural history collections.
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