Background Bacterioplankton are main drivers of biogeochemical cycles and important components of aquatic food webs. However, difficulties in culturing the majority of aquatic prokaryotic species have complicated the study of their microdiversity. Here, we present POGENOM, a software that quantifies population genomic indices from metagenome data, enabling comparative analysis of genomic diversity and differentiation in multiple species in parallel. We demonstrate POGENOM on metagenome-assembled genomes from the Baltic Sea and investigate their genomic variation using metagenome data spanning a 1700 km transect and covering seasonal variation at one station.
ResultsThe majority of the investigated species, representing several major bacterioplankton clades, displayed population structure correlating significantly with environmental factors such as salinity, temperature, nutrients and oxygen, both over horizontal and vertical dimensions. Population differentiation was more pronounced over spatial than temporal scales, although some species displayed population structure correlating with season. We discovered genes that have undergone adaptation to different salinity regimes, potentially responsible for the populations' existence along the salinity range.
ConclusionsWe provide a new tool for high-throughput population genomics analysis based on metagenomics data. From an evolutionary point of view, our findings emphasize the importance of physiological barriers, and highlight the role of adaptive divergence as a structuring mechanism of bacterioplankton species, despite their seemingly unlimited dispersal potential. This is of central importance when learning about how species have adapted to new environmental conditions and what their adaptive potential is in the face of Global Change.
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