On the way to specificity - Microbiome reflects sponge genetic cluster primarily in highly structured populations

Abstract

ABSTRACT Most animals, including sponges (Porifera), have species‐specific microbiomes. Which genetic or environmental factors play major roles structuring the microbial community at the intraspecific level in sponges is, however, largely unknown. In this study, we tested whether geographic location or genetic structure of conspecific sponges influences their microbial assembly. For that, we used three sponge species with different rates of gene flow, and collected samples along their entire distribution range (two from the Mediterranean and one from the Southern Ocean) yielding a total of 393 samples. These three sponge species have been previously analysed by microsatellites or single nucleotide polymorphisms, and here we investigate their microbiomes by amplicon sequencing of the microbial 16S rRNA gene. The sponge Petrosia ficiformis, with highly isolated populations (low gene flow), showed a stronger influence of the host genetic distance on the microbial composition than the spatial distance. Host‐specificity was therefore detected at the genotypic level, with individuals belonging to the same host genetic cluster harbouring more similar microbiomes than distant ones. On the contrary, the microbiome of Ircinia fasciculata and Dendrilla antarctica ‐ both with weak population structure (high gene flow) ‐ seemed influenced by location rather than by host genetic distance. Our results suggest that in sponge species with high population structure, the host genetic cluster influence the microbial community more than the geographic location. ; ACKNOWLEDGEMENTS This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under the Marie Skłodowska‐Curie Individual Fellowships Grant Agreement No. 796011 ('DeepSym'), and Grant Agreement No. 679849 ('SponGES'). We thank the team around Andre Franke at the Institute of Clinical Molecular Biology, Kiel, for sequencing support. We also want to thank Shaun Nielsen for support and guidance through data analysis. Finally, we ...