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dc.contributor.authorPronzato, R.
dc.contributor.authorRuthensteiner, B.
dc.contributor.authorVandenspiegel, D.
dc.contributor.authorvan Soest, R.
dc.date2018
dc.date.accessioned2024-03-14T13:15:37Z
dc.date.available2024-03-14T13:15:37Z
dc.identifier.urihttps://orfeo.belnet.be/handle/internal/12043
dc.descriptionAfrican sponges, particularly freshwater sponges, are understudied relative to demosponges in most other geographical regions. Freshwater sponges (Spongillida) likely share a common ancestor; however, their evolutionary history, particularly during their radiation into endemic and allegedly cosmopolitan groups, is unclear. Freshwater sponges of at least 58 species of 17 genera and four families are described from Central and Eastern Africa, but the diversity is underestimated due to limited distinguishable morphological features. The discovery of additional cryptic species is very likely with the use of molecular techniques such as DNA barcoding. The Royal Museum of Central Africa (MRAC, Tervuren, Belgium) hosts one of the largest collections of (Central) African freshwater sponge type material. Type specimens in theory constitute ideal targets for molecular taxonomy; however, the success is frequently hampered by DNA degradation and deamination, which are a consequence of suboptimal preservation techniques. Therefore, we genotyped African demosponge holotype material of the MRAC with specific short primers suitable for degenerated tissue and compare the results with the current, morphology-based classification. Our results demonstrate the utility of minimalistic barcodes for identification of sponges, potentially enabling efficient identification of individuals in taxonomic or metabarcoding studies, and highlight inconsistencies in the current freshwater sponge classification.
dc.languageeng
dc.titleMinimalist barcodes for sponges - A case study classifying African freshwater Spongillida.
dc.typeArticle
dc.subject.frascatiBiological sciences
dc.audienceScientific
dc.subject.freeBiological collection and data management
dc.source.titleGenome
dc.source.volume62
dc.source.page1-28
Orfeo.peerreviewedYes
dc.identifier.rmca5895


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