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  • 1
    Publication Date: 2024-02-15
    Description: With declining biodiversity worldwide, a better understanding of species diversity and their relationships is imperative for conservation and management efforts. Marine sponges are species-rich ecological key players on coral reefs, but their species diversity is still poorly understood. This is particularly true for the demosponge order Haplosclerida, whose systematic relationships are contentious due to the incongruencies between morphological and molecular phylogenetic hypotheses. The single gene markers applied in previous studies did not resolve these discrepancies. Hence, there is a high need for a genome-wide approach to derive a phylogenetically robust classification and understand this group\'s evolutionary relationships. To this end, we developed a target enrichment-based multilocus probe assay for the order Haplosclerida using transcriptomic data. This probe assay consists of 20,000 enrichment probes targeting 2956 ultraconserved elements in coding (i.e. exon) regions across the genome and was tested on 26 haplosclerid specimens from the Red Sea. Our target-enrichment approach correctly placed our samples in a well-supported phylogeny, in agreement with previous haplosclerid molecular phylogenies. Our results demonstrate the applicability of high-resolution genomic methods in a systematically complex marine invertebrate group and provide a promising approach for robust phylogenies of Haplosclerida. Subsequently, this will lead to biologically unambiguous taxonomic revisions, better interpretations of biological and ecological observations and new avenues for applied research, conservation and managing declining marine diversity.
    Keywords: bait design ; exon ; phylogenetic markers ; target capture ; ultraconserved element
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
    Format: application/pdf
    Format: application/pdf
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  • 2
    Publication Date: 2020-02-06
    Description: The dichotomy between high microbial abundance (HMA) and low microbial abundance (LMA) sponges has been observed in sponge-microbe symbiosis, although the extent of this pattern remains poorly unknown. We characterized the differences between the microbiomes of HMA (n=19) and LMA (n=17) sponges (575 specimens) present in the Sponge Microbiome Project. HMA sponges were associated with richer and more diverse microbiomes than LMA sponges, as indicated by the comparison of alpha diversity metrics. Microbial community structures differed between HMA and LMA sponges considering Operational Taxonomic Units (OTU) abundances and across microbial taxonomic levels, from phylum to species. The largest proportion of microbiome variation was explained by the host identity. Several phyla, classes, and OTUs were found differentially abundant in either group, which were considered “HMA indicators” and “LMA indicators”. Machine learning algorithms (classifiers) were trained to predict the HMA-LMA status of sponges. Among nine different classifiers, higher performances were achieved by Random Forest trained with phylum and class abundances. Random Forest with optimized parameters predicted the HMA-LMA status of additional 135 sponge species (1,232 specimens) without a priori knowledge. These sponges were grouped in four clusters, from which the largest two were composed of species consistently predicted as HMA (n=44) and LMA (n=74). In summary, our analyses shown distinct features of the microbial communities associated with HMA and LMA sponges. The prediction of the HMA-LMA status based on the microbiome profiles of sponges demonstrates the application of machine learning to explore patterns of host-associated microbial communities.
    Type: Article , PeerReviewed
    Format: text
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