bioRxivGenomicsPreprint
Pervasive tandem duplications and convergent evolution shape coral genomes
Benjamin NoëliD, France DenœudiD, Alice RouaniD, Carol Buitrago‐LópeziD, Laura CapassoiD, Julie PoulainiD, Émilie BoissiniD, Mélanie Pousse, Corinne Da SilvaiD, Arnaud CoulouxiD, Eric J. ArmstrongiD, Quentin CarradeciD, Corinne CruaudiD, Karine LabadieiD, Julie Lê-HoangiD, Sylvie TambuttéiD, Valérie BarbeiD, Clémentine MouliniD, Guillaume BourdiniD, Guillaume IwankowiD, Sarah RomaciD, Denis AllemandiD, Serge PlanesiD, Éric GilsoniD, Didier ZoccolaiD, , Jean‐Marc AuryiD
Abstract
Over the last decade, several coral genomes have been sequenced allowing a better understanding of these symbiotic organisms threatened by climate change. Scleractinian corals are reef builders and are central to these ecosystems, providing habitat and food to a great diversity of species. In the frame of the Tara Pacific expedition, we generated two coral genomes, Porites lobata and Pocillopora meandrina with vastly improved contiguity that allowed us to study the functional organisation of these genomes. We annotated their gene catalog and report a relatively higher gene number (43,000 and 32,000 genes respectively) than that found in other public coral genome sequences. This finding is explained by a high number of tandemly duplicated genes (almost a third of the predicted genes). We show that these duplicated genes originate from multiple and distinct duplication events throughout the coral lineage. They contribute to the amplification of gene families, mostly related to immune system and disease-resistance, which we suggest to be functionally linked to coral host resilience. At large, we show the importance of duplicated genes to inform the biology of reef-building corals and provide novel avenues to understand and screen for differences in stress resilience.
- organism: non-human primate
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: variant calling
- approach: statistical model
- Citations
- 2
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