A chromosome-level reference genome for the common octopus, Octopus vulgaris (Cuvier, 1797)

Cephalopods are emerging animal models and include iconic species for studying the link between genomic innovations and physiological and behavioral complexities. Coleoid cephalopods possess the largest nervous system among invertebrates, both for cell counts and brain-to-body ratio. Octopus vulgaris has been at the center of a long-standing tradition of research into diverse aspects of cephalopod biology, including behavioral and neural plasticity, learning and memory recall, regeneration, and sophisticated cognition. However, no chromosome-scale genome assembly was available for O. vulgaris to aid in functional studies. To fill this gap, we sequenced and assembled a chromosome-scale genome of the common octopus, O. vulgaris. The final assembly spans 2.8 billion basepairs, 99.34% of which are in 30 chromosome-scale scaffolds. Hi-C heatmaps support a karyotype of 1n = 30 chromosomes. Comparisons with other octopus species' genomes show a conserved octopus karyotype and a pattern of local genome rearrangements between species. This new chromosome-scale genome of O. vulgaris will further facilitate research in all aspects of cephalopod biology, including various forms of plasticity and the neural machinery underlying sophisticated cognition, as well as an understanding of cephalopod evolution. ; sponsorship: The authors acknowledge that some of the computational results of this work have been achieved using the Life Science Compute Cluster (LiSC) of the University of Vienna. We also acknowledge support from the National Genomics Infrastructure in Stockholm funded by Science for Life Laboratory, the Knut and Alice Wallenberg Foundation and the Swedish Research Council, and NAISS/Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. (The authors acknowledge that some of the computational results of this work have been achieved using the Life Science Compute Cluster (LiSC) of the University of ...