Biological and genomic resources for the cosmopolitan phytoplankton Bathycoccus: insights into genetic diversity and function of outlier chromosomes.

Population-scale genome sequencing has become essential for exploring genetic diversity and adaptation, particularly in land plants. In contrast, eukaryotic phytoplankton resources remain limited to model reference genomes or community-level metagenomics, leaving a gap in understanding intraspecific variation and evolutionary processes. To address this, we developed a comprehensive biological and genomic resource for the cosmopolitan and ecologically important genus Bathycoccus. Extensive metagenomic data from across the world Ocean are available for this genus, and previous studies have identified four Bathycoccus species and reconstructed 34 metagenome-assembled genomes (MAGs). Here we report 28 high-quality strain genome sequences using a combination of Oxford Nanopore Technologies long reads and Illumina short reads and associated biological resources. These include 24 Bathycoccus prasinos strains spanning a latitudinal gradient from 40° to 78° N, a reference genome for Bathycoccus calidus, and three genomes of the recently identified B3 clade, which we propose as the Bathycoccus catiminus species. Comparative analyses of sequenced genomes with MAGs highlight the complementarity between resources: While MAGs capture environmental diversity and uncover uncultured taxa, the cultured strain genomes provide complete, non-chimeric high-quality assemblies that resolve structural variations and haplotype-level diversity not detected in MAGs. These include the big outlier chromosome, a putative sexual chromosome revealing a second mating type, and extensive variability in the small outlier chromosome, associated with viral resistance and genome plasticity. Together, these biological and genomic resources establish B. prasinos as a powerful model for studying diversity, adaptation, and evolution of eukaryotic phytoplankton in the ocean, complementing existing global metagenomic datasets.