54 research outputs found

    Estimating the travel time and the most likely path from Lagrangian drifters

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    We provide a novel methodology for computing the most likely path taken by drifters between arbitrary fixed locations in the ocean. We also provide an estimate of the travel time associated with this path. Lagrangian pathways and travel times are of practical value not just in understanding surface velocities, but also in modelling the transport of ocean-borne species such as planktonic organisms, and floating debris such as plastics. In particular, the estimated travel time can be used to compute an estimated Lagrangian distance, which is often more informative than Euclidean distance in understanding connectivity between locations. Our methodology is purely data-driven, and requires no simulations of drifter trajectories, in contrast to existing approaches. Our method scales globally and can simultaneously handle multiple locations in the ocean. Furthermore, we provide estimates of the error and uncertainty associated with both the most likely path and the associated travel time

    Community-Level Responses to Iron Availability in Open Ocean Plankton Ecosystems

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    Predicting responses of plankton to variations in essential nutrients is hampered by limited in situ measurements, a poor understanding of community composition, and the lack of reference gene catalogs for key taxa. Iron is a key driver of plankton dynamics and, therefore, of global biogeochemical cycles and climate. To assess the impact of iron availability on plankton communities, we explored the comprehensive bio-oceanographic and bio-omics data sets from Tara Oceans in the context of the iron products from two state-of-the-art global scale biogeochemical models. We obtained novel information about adaptation and acclimation toward iron in a range of phytoplankton, including picocyanobacteria and diatoms, and identified whole subcommunities covarying with iron. Many of the observed global patterns were recapitulated in the Marquesas archipelago, where frequent plankton blooms are believed to be caused by natural iron fertilization, although they are not captured in large-scale biogeochemical models. This work provides a proof of concept that integrative analyses, spanning from genes to ecosystems and viruses to zooplankton, can disentangle the complexity of plankton communities and can lead to more accurate formulations of resource bioavailability in biogeochemical models, thus improving our understanding of plankton resilience in a changing environment

    Le génome du petit pois décrypté

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    National audienceLe génome du petit pois a été décrypté pour la première fois par huit équipes de chercheurs internationaux pilotées par l'INRA, ouvrant des perspectives pour l'alimentation de la planète, la transition agricole et la lutte contre le réchauffement climatique.Pisum sativum, une légumineuse plus connue sous le nom de petit pois, est une espèce fétiche pour les généticiens du monde entier, car c'est sur un pois que le père de la génétique moderne, le moine Gregor Mendel, s'était basé pour déterminer les premières lois de l'hérédité en 1866.Pour reconstituer la séquence de son génome, "il a fallu ordonner plusieurs milliards de courtes séquences d'ADN", a indiqué à l'AFP Judith Burstin de l'INRA-Dijon, qui a coordonné l'article publié lundi dans la revue Nature Genetics, par et avec Jonathan Kreplak (Inra) et Mohammed-Amin Madoui (CEA-CNRS).Alors que le premier séquençage du génome d'une plante a eu lieu en 2000, et que celui du blé est intervenu en 2018, celui du pois a pris plus de temps car "il s'agit d'un "génome très volumineux et très complexe, avec beaucoup de petites séquences qui se répètent", a indiqué Mme Burstin.Deux équipes françaises, de l'Institut national de la recherche agronomique(INRA) et du Commissariat à l'Energie Atomique (CEA) ont planché sur le sujet depuis 2013, ainsi que deux équipes tchèques, deux australiennes, une américaine, une canadienne et un chercheur néo-zélandais, avec aussi l'aide de financements privés, venant notamment du groupe agroalimentaire français Avril, spécialisé dans les oléagineux et légumineuses

    Whole-genome scanning reveals environmental selection mechanisms that shape diversity in populations of the epipelagic diatom Chaetoceros.

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    Diatoms form a diverse and abundant group of photosynthetic protists that are essential players in marine ecosystems. However, the microevolutionary structure of their populations remains poorly understood, particularly in polar regions. Exploring how closely related diatoms adapt to different environments is essential given their short generation times, which may allow rapid adaptations, and their prevalence in marine regions dramatically impacted by climate change, such as the Arctic and Southern Oceans. Here, we address genetic diversity patterns in Chaetoceros, the most abundant diatom genus and one of the most diverse, using 11 metagenome-assembled genomes (MAGs) reconstructed from Tara Oceans metagenomes. Genome-resolved metagenomics on these MAGs confirmed a prevalent distribution of Chaetoceros in the Arctic Ocean with lower dispersal in the Pacific and Southern Oceans as well as in the Mediterranean Sea. Single-nucleotide variants identified within the different MAG populations allowed us to draw a landscape of Chaetoceros genetic diversity and revealed an elevated genetic structure in some Arctic Ocean populations. Gene flow patterns of closely related Chaetoceros populations seemed to correlate with distinct abiotic factors rather than with geographic distance. We found clear positive selection of genes involved in nutrient availability responses, in particular for iron (e.g., ISIP2a, flavodoxin), silicate, and phosphate (e.g., polyamine synthase), that were further supported by analysis of Chaetoceros transcriptomes. Altogether, these results highlight the importance of environmental selection in shaping diatom diversity patterns and provide new insights into their metapopulation genomics through the integration of metagenomic and environmental data

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

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    International audienceMotivation: The availability of large metagenomic data offers great opportunities for the population geno-mic analysis of uncultured organisms, especially for small eukaryotes that represent an important part of the unexplored biosphere while playing a key ecological role. However, the majority of these species lacks reference genome or transcriptome which constitutes a technical barrier for classical population genomic analyses. Results: We introduce the metavariant species (MVS) model, a representation of the species 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 variant into MVS directly from multisample metagenomic raw reads without reference genome or reads 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 MVSs construction was tested on simulated and real metagenomic data. MVs showed the required quality for robust population genomics and allowed an accurate estimation of genomic differentiation (∆FST < 0.0001 and < 0.03 on simulated and real data respectively). Loci predicted under natural selection on real data were all found by MVSs. MVSs represent a new paradigm that may simplify and enhance holistic approaches for population genomics and evolution of microorganisms. Availability: The method was implemented in a R package, metaVaR. https://github.co

    How marine currents and environment shape plankton genomic differentiation: a mosaic view from Tara Oceans metagenomic data

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    Plankton seascape genomics show different trends from large-scale weak differentiation to micro-scale structures. Prior studies underlined the influence of environment and seascape on a few single species differentiation and adaptation. However, these works generally focused on few single species, sparse molecular markers, or local scales. Here, we investigate the genomic differentiation of plankton at macro-scale in a holistic approach using Tara Oceans metagenomic data together with a reference-free computational method to reconstruct the FST-based genomic differentiation of 113 marine planktonic species using metavariant species (MVS). These MVSs, modelling the species only by their polymorphism, include a wide range of taxonomic groups comprising notably 46 Maxillopoda/Copepoda, 24 Bacteria, 5 Dinoflagellates, 4 Haptophytes, 3 Cnidarians, 3 Mamiellales, 2 Ciliates, 1 Collodaria, 1 Echinoidea, 1 Pelagomonadaceae, 1 Cryptophyta and 1 Virus. The analyses showed that differentiation between populations was significantly lower within basins and higher in bacteria and unicellular eukaryotes compared to zooplantkon. By partitioning the variance of pairwise-FST matrices, we found that the main drivers of genomic differentiation were Lagrangian travel time, salinity and temperature. Furthermore, we classified MVSs into parameter-driven groups and showed that taxonomy poorly determines which environmental factor drives genomic differentiation. This holistic approach of plankton genomic differentiation for large geographic scales, a wide range of taxa and different oceanic basins, offers a systematic framework to analyse population genomics of non-model and undocumented marine organisms

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

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    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

    Chitin distribution in the Oithona digestive and reproductive systems revealed by fluorescence microscopy

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    Among copepods, which are the most abundant animals on Earth, the genus Oithona is described as one of the most numerous and plays a major role in the marine food chain and biogeochemical cycles, particularly through the excretion of chitin-coated fecal pellets. Despite the morphology of several Oithona species is well known, knowledge of its internal anatomy and chitin distribution is still limited. To answer this problem, Oithona nana and O. similis individuals were stained by Wheat Germ Agglutinin-Fluorescein IsoThioCyanate (WGA-FITC) and DiAmidino-2-PhenylIndole (DAPI) for fluorescence microscopy observations. The image analyses allowed a new description of the organization and chitin content of the digestive and reproductive systems of Oithona male and female. Chitin microfibrils were found all along the digestive system from the stomach to the hindgut with a higher concentration at the peritrophic membrane of the anterior midgut. Several midgut shrinkages were observed and proposed to be involved in faecal pellet shaping and motion. Amorphous chitin structures were also found to be a major component of the ducts and seminal vesicles and receptacles. The rapid staining protocol we proposed allowed a new insight into the Oithona internal anatomy and highlighted the role of chitin in the digestion and reproduction. This method could be applied to a wide range of copepods in order to perform comparative anatomy analyses

    Performance comparison of four exome capture systems for deep sequencing

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    Background Recent developments in deep (next-generation) sequencing technologies are significantly impacting medical research. The global analysis of protein coding regions in genomes of interest by whole exome sequencing is a widely used application. Many technologies for exome capture are commercially available; here we compare the performance of four of them: NimbleGen’s SeqCap EZ v3.0, Agilent’s SureSelect v4.0, Illumina’s TruSeq Exome, and Illumina’s Nextera Exome, all applied to the same human tumor DNA sample. Results Each capture technology was evaluated for its coverage of different exome databases, target coverage efficiency, GC bias, sensitivity in single nucleotide variant detection, sensitivity in small indel detection, and technical reproducibility. In general, all technologies performed well; however, our data demonstrated small, but consistent differences between the four capture technologies. Illumina technologies cover more bases in coding and untranslated regions. Furthermore, whereas most of the technologies provide reduced coverage in regions with low or high GC content, the Nextera technology tends to bias towards target regions with high GC content. Conclusions We show key differences in performance between the four technologies. Our data should help researchers who are planning exome sequencing to select appropriate exome capture technology for their particular application
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