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<title lang=en>A transcriptomic approach to study marine plankton holobionts</title>
<creator>Meng, Arnaud</creator>
<creator>Corre, Erwan</creator>
<creator>Peterlongo, Pierre</creator>
<creator>Marchet, Camille</creator>
<creator>Alberti, Adriana</creator>
<creator>Silva, Corinne da</creator>
<creator>Wincker, Patrick</creator>
<creator>Probert, Ian</creator>
<creator>Suzuki, Noritoshi</creator>
<creator>Le Crom, Stéphane</creator>
<creator>Bittner, Lucie</creator>
<creator>Not, Fabrice</creator>
<contributor>Analyse des Données à Haut Débit en Génomique (ADHDG) ; Systématique, adaptation, évolution (SAE) ; Université Pierre et Marie Curie - Paris 6 (UPMC) - Centre National de la Recherche Scientifique (CNRS) - Université Pierre et Marie Curie - Paris 6 (UPMC) - Centre National de la Recherche Scientifique (CNRS) - Evolution Paris Seine ; Université Nice Sophia Antipolis (UNS) ; Université Côte d'Azur (UCA) - Université Côte d'Azur (UCA) - Centre National de la Recherche Scientifique (CNRS) - Université des Antilles et de la Guyane (UAG) - Université Pierre et Marie Curie - Paris 6 (UPMC) - Université Nice Sophia Antipolis (UNS) ; Université Côte d'Azur (UCA) - Université Côte d'Azur (UCA) - Université des Antilles et de la Guyane (UAG)</contributor>
<contributor>PRISMES - Langues, Textes, Arts et Cultures du Monde Anglophone - EA 4398 (PRISMES) ; Université Sorbonne Nouvelle - Paris 3</contributor>
<contributor>Scalable, Optimized and Parallel Algorithms for Genomics (GenScale) ; Inria Rennes – Bretagne Atlantique ; Institut National de Recherche en Informatique et en Automatique (Inria) - Institut National de Recherche en Informatique et en Automatique (Inria) - GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA_D7) ; Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) - Université de Bretagne Sud (UBS) - École normale supérieure - Rennes (ENS Rennes) - Institut National de Recherche en Informatique et en Automatique (Inria) - CentraleSupélec - Centre National de la Recherche Scientifique (CNRS) - IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique) - Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) - Université de Bretagne Sud (UBS) - École normale supérieure - Rennes (ENS Rennes) - Institut National de Recherche en Informatique et en Automatique (Inria) - CentraleSupélec - Centre National de la Recherche Scientifique (CNRS) - IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique) - Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA) ; Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) - Université de Bretagne Sud (UBS) - École normale supérieure - Rennes (ENS Rennes) - Institut National de Recherche en Informatique et en Automatique (Inria) - CentraleSupélec - Centre National de la Recherche Scientifique (CNRS) - IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique) - Université de Rennes 1 (UR1) - Institut National des Sciences Appliquées - Rennes (INSA Rennes) - Université de Bretagne Sud (UBS) - École normale supérieure - Rennes (ENS Rennes) - CentraleSupélec - Centre National de la Recherche Scientifique (CNRS) - IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique)</contributor>
<contributor>CNR IMM, 8 Str 5 Zona Ind, I-95121 Catania, Italy</contributor>
<contributor>Genoscope - Centre national de séquençage [Evry] (GENOSCOPE) ; Commissariat à l'énergie atomique et aux énergies alternatives (CEA)</contributor>
<contributor>Station biologique de Roscoff [Roscoff] (SBR) ; Université Pierre et Marie Curie - Paris 6 (UPMC) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Institute of Geology and Paleontology ; Tohoku University [Sendai]</contributor>
<description>International audience</description>
<source>International Conference on Holobionts</source>
<coverage>Paris, France</coverage>
<identifier>hal-01575069</identifier>
<identifier>https://hal.inria.fr/hal-01575069</identifier>
<source>https://hal.inria.fr/hal-01575069</source>
<source>International Conference on Holobionts, Apr 2017, Paris, France. 2017, 〈https://symposium.inra.fr/holobiont-paris2017〉</source>
<source>https://symposium.inra.fr/holobiont-paris2017</source>
<language>en</language>
<subject>[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]</subject>
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<type>Conference papers</type>
<description lang=en>Symbiosis is a widespread phenomenon in the biosphere. In marine benthic environments breakdown of symbiosis is responsible for coral bleaching and dramatically affects coral reef ecosystems functioning [1]. In the water column, planktonic organisms are key component of pelagic ecosystems and a number of species form mutualistic association with microalgae forming a photosymbiosis [2]. Here we intended to investigate the genetic basis of photosymbiosis, through a transcriptomic approach on marine plankton organisms. We focused more specifically on associations occurring between radiolarian host (protist, zooplankton) and dinoflagellates symbiont (protist, phytoplankton) living inside the host cell. It has recently been highlighted that these holobionts are widespread in oligotrophic open oceans and there are also evidences of their fundamental implication in biogeochemical carbon, silica and strontium cycles [3, 4, 5, 6]. RNA-seq technologies allow obtaining an unprecedented amount of data for unicellular organisms isolated from the environment [7]. The study of such non-model holobionts datasets requires de novo assembly, which implies considerable computational resources and the potential production of chimeric sequences [8, 9].We therefore developed an original strategy aiming at accelerating and improving de novo assembly for holobiont datasets. We chose SIMKA [10] a fast kmer-based method initially developed to estimate the similarity between numerous metagenomic datasets, and which has been recently adapted to extract their common sequences. As our symbionts are identified, we used SIMKA to compare our holobionts transcriptomes to publicly available dinoflagellates transcriptomes [11] generating two datasets, one composed of reads from the symbionts and another with reads from the host (for which no reference data are currently available). Independent assemblies were then performed in parallel, accelerating the study process, and minimizing the proportion of resulting chimeric sequences. Our strategy produced a unique and comprehensive genomic dataset for Radiolaria [12, 13], and offers a pragmatic, large scale, comparison strategy to assemble and study holobionts [9]. Our new sequences obtained from holobionts study will be used for phylogenomics investigation, as reference for environmental metagenomic studies and ultimately to understand and characterize the molecular basis of symbiotic relationships in the plankton.Bibliografic references :[1] Simon K. Davy, Denis Allemand, and Virginia M. Weis. “Cell Biology of Cnidarian-Dinoflagellate Symbiosis”. In: Microbiology and Molecular Biology Reviews 76.2 (June 1, 2012), pp. 229–261. issn: 1092-2172, 1098- 5557. doi: 10.1128/MMBR.05014-11.[2] Janouškovec, J. et al. “Major transitions in dinoflagellate evolution unveiled by phylotranscriptomics”. in: PNAS 201614842 (2016). doi:10.1073/pnas.1614842114[3] Tristan Biard et al. “In situ imaging reveals the biomass of giant protists in the global ocean”. In: Nature advance online publication (Apr. 20, 2016). issn: 0028-0836. doi: 10.1038/nature17652.[4] Lionel Guidi et al. “Plankton networks driving carbon export in the olig- otrophic ocean”. In: Nature 532.7600 (Apr. 28, 2016), pp. 465–470. issn: 0028-0836. doi: 10.1038/nature16942.[5] Diane K. Stoecker et al. “Acquired phototrophy in aquatic protists”. In: Aquatic Microbial Ecology 57.3 (Nov. 24, 2009), pp. 279–310. doi: 10.3354/ame01340.[6] Johan Decelle et al. “An original mode of symbiosis in open ocean plankton”. In: Proceedings of the National Academy of Sciences 109.44 (Oct. 30, 2012), pp. 18000–18005. issn: 0027-8424, 1091-6490. doi: 10. 1073/pnas.1212303109.[7] Sergio Balzano et al. “Transcriptome analyses to investigate symbiotic relationships between marine protists”. In: Frontiers in Microbiology 6 (Mar. 17, 2015). issn: 1664-302X. doi: 10.3389/fmicb.2015.00098.[8] Li, B. et al. “Evaluation of de novo transcriptome assemblies from RNA-Seq data”. In: Genome Biology 15, 553 (2014).[9] Sangwan, N., Xia, F. & Gilbert, J. A. “Recovering complete and draft population genomes from metagenome datasets”. In: Microbiome 4, 8 (2016).[10] Gaëtan Benoit et al. “Multiple comparative metagenomics using mul- tiset k -mer counting”. In: PeerJ Computer Science 2 (Nov. 14, 2016). doi: 10.7717/peerj-cs.94.[11] Patrick J. Keeling et al. “The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): Illuminating the Functional Diversity of Eukaryotic Life in the Oceans through Transcriptome Sequencing”. In: PLOS Biol 12.6 (June 2014), e1001889. issn: 1545-7885. doi: 10.1371/journal.pbio.1001889.[12] Burki, F. et al. “Evolution of Rhizaria: new insights from phylogenomic analysis of uncultured protists”. In BMC Evolutionary Biology 10, 377 (2010). </description>
<date>2017-04-19</date>
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