Investigating population-scale allelic differential expression in wild populations of Oithona similis (Cyclopoida, Claus, 1866)

Holistic view of the seascape dynamics and environment impact on macro-scale genetic connectivity of marine plankton populations

BACKGROUND

Plankton seascape genomics studies have revealed different trends from large-scale weak differentiation to microscale structures. Previous studies have underlined the influence of the environment and seascape on species differentiation and adaptation. However, these studies have generally focused on a few single species, sparse molecular markers, or local scales. Here, we investigated the genomic differentiation of plankton at the macro-scale in a holistic approach using Tara Oceans metagenomic data together with a reference-free computational method.

RESULTS

We reconstructed the FST-based genomic differentiation of 113 marine planktonic taxa occurring in the North and South Atlantic Oceans, Southern Ocean, and Mediterranean Sea. These taxa belong to various taxonomic clades spanning Metazoa, Chromista, Chlorophyta, Bacteria, and viruses. Globally, population genetic connectivity was significantly higher within oceanic basins and lower in bacteria and unicellular eukaryotes than in zooplankton. Using mixed linear models, we tested six abiotic factors influencing connectivity, including Lagrangian travel time, as proxies of oceanic current effects. We found that oceanic currents were the main population genetic connectivity drivers, together with temperature and salinity. Finally, we classified the 113 taxa into parameter-driven groups and showed that plankton taxa belonging to the same taxonomic rank such as phylum, class or order presented genomic differentiation driven by different environmental factors.

CONCLUSION

Our results validate the isolation-by-current hypothesis for a non-negligible proportion of taxa and highlight the role of other physicochemical parameters in large-scale plankton genetic connectivity. The reference-free approach used in this study offers a new systematic framework to analyse the population genomics of non-model and undocumented marine organisms from a large-scale and holistic point of view.

Genomic differentiation of three pico-phytoplankton species in the Mediterranean Sea

For more than a decade, high-throughput sequencing has transformed the study of marine planktonic communities and has highlighted the extent of protist diversity in these ecosystems. Nevertheless, little is known relative to their genomic diversity at the species-scale as well as their major speciation mechanisms. An increasing number of data obtained from global scale sampling campaigns is becoming publicly available, and we postulate that metagenomic data could contribute to deciphering the processes shaping protist genomic differentiation in the marine realm. As a proof of concept, we developed a findable, accessible, interoperable and reusable (FAIR) pipeline and focused on the Mediterranean Sea to study three a priori abundant protist species: Bathycoccus prasinos, Pelagomonas calceolata and Phaeocystis cordata. We compared the genomic differentiation of each species in light of geographic, environmental and oceanographic distances. We highlighted that isolation-by-environment shapes the genomic differentiation of B. prasinos, whereas P. cordata is impacted by geographic distance (i.e. isolation-by-distance). At present time, the use of metagenomics to accurately estimate the genomic differentiation of protists remains challenging since coverages are lower compared to traditional population surveys. However, our approach sheds light on ecological and evolutionary processes occurring within natural marine populations and paves the way for future protist population metagenomic studies.

metaVaR: Introducing metavariant species models for reference-free metagenomic-based population genomics

The availability of large metagenomic data offers great opportunities for the population genomic analysis of uncultured organisms, which represent a large part of the unexplored biosphere and play a key ecological role. However, the majority of these organisms lack a reference genome or transcriptome, which constitutes a technical obstacle for classical population genomic analyses. We introduce the metavariant species (MVS) model, in which a species is represented only by intra-species nucleotide polymorphism. We designed a method combining reference-free variant calling, multiple density-based clustering and maximum-weighted independent set algorithms to cluster intra-species variants into MVSs directly from multisample metagenomic raw reads without a reference genome or read assembly. The frequencies of the MVS variants are then used to compute population genomic statistics such as FST, in order to estimate genomic differentiation between populations and to identify loci under natural selection. The MVS construction was tested on simulated and real metagenomic data. MVSs showed the required quality for robust population genomics and allowed an accurate estimation of genomic differentiation (ΔFST < 0.0001 and <0.03 on simulated and real data respectively). Loci predicted under natural selection on real data were all detected by MVSs. MVSs represent a new paradigm that may simplify and enhance holistic approaches for population genomics and the evolution of microorganisms.