Navigating uncertainty in museum workflows: Genomic data mining and curation of the RMCA Diptera collections

Esselens Lore, Addison Pia, Bakengesa Jacqueline, Bota Luis, Canhanga Laura, Cugala Domingos, Daniel Beatriz, De Meyer Marc, Delatte Hélène, Herpers Jean-Marc, Jordaens Kurt, Kabota Sija, Kudra Abdul B., Majubwa Ramadhani, Manrakhan Aruna, Mussumbe Mirene, Mwatawala Maulid W., Theeten Franck, Van den Spiegel Didier, Vanbergen Sam, Vangestel Carl, Virgilio Massimiliano. 2025. Navigating uncertainty in museum workflows: Genomic data mining and curation of the RMCA Diptera collections. Biodiversity Data Journal, 13:e157274, 19 p.

https://doi.org/10.3897/BDJ.13.e157274

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Url - jeu de données - Entrepôt autre : https://darwin.naturalsciences.be/ / Url - jeu de données - Entrepôt autre : https://darwinweb.africamuseum.be/ / Url - jeu de données - Entrepôt autre : https://github.com/naturalsciences/Darwin

Résumé : 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.

Mots-clés Agrovoc : Tephritidae, génomique, fouille de données, génome, Syrphidae, adn, taxonomie, histoire naturelle, gestion des ressources naturelles, Dacus, Bactrocera, collections du musée, collecte de données, Diptera

Mots-clés géographiques Agrovoc : Afrique centrale

Mots-clés libres : Natural history collections, Museomics, Whole Genome Sequencing, True fruit flies, Hoverflies

Agences de financement européennes : European Commission

Agences de financement hors UE : Directorate General for Development Cooperation and Humanitarian Aid

Programme de financement européen : H2020

Projets sur financement : (EU) In-silico boosted, pest prevention and off-season focused IPM against new and emerging fruit flies ('OFF-Season' FF-IPM), (EU) Rapid elimination of invasive insect agricultural pest outbreaks by tackling them with Sterile Insect Technique programs, (EU) SYNTHESYS PLUS

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