PT - JOURNAL ARTICLE AU - Arnaud Meng AU - Camille Marchet AU - Erwan Corre AU - Pierre Peterlongo AU - Adriana Alberti AU - Corinne Da Silva AU - Patrick Wincker AU - Eric Pelletier AU - Ian Probert AU - Johan Decelle AU - Stéphane Le Crom AU - Fabrice Not AU - Lucie Bittner TI - A <em>de novo</em> approach to disentangle partner identity and function in holobiont systems AID - 10.1101/221424 DP - 2017 Jan 01 TA - bioRxiv PG - 221424 4099 - http://biorxiv.org/content/early/2017/11/17/221424.short 4100 - http://biorxiv.org/content/early/2017/11/17/221424.full AB - Background Study of meta-transcriptomic datasets involving non-model organisms represents bioinformatic challenges. The production of chimeric sequences and our inability to distinguish the taxonomic origins of the sequences produced are inherent and recurrent difficulties in de novo assembly analyses. The study of holobiont transcriptomes shares similarities with meta-transcriptomic, and hence, is also affected by challenges invoked above. Here we propose an innovative approach to tackle such difficulties which was applied to the study of marine holobiont models as a proof of concept.Results We considered three holobionts models, of which two transcriptomes were previously assembled and published, and a yet unpublished transcriptome, to analyze their raw reads and assign them to the host and/or to the symbiont(s) using Short Read Connector, a k-mer based similarity method. We were able to define four distinct categories of reads for each holobiont transcriptome: host reads, symbiont reads, shared reads and unassigned reads. The result of the independent assemblies for each category within a transcriptome led to a significant diminution of de novo assembled chimeras compared to classical assembly methods. Combining independent functional and taxonomic annotations of each partner’s transcriptome is particularly convenient to explore the functional diversity of an holobiont. Finally, our strategy allowed to propose new functional annotations for two well-studied holobionts and a first transcriptome from a planktonic Radiolaria-Dinophyta system forming widespread symbiotic association for which our knowledge is limited. ConclusionsIn contrast to classical assembly approaches, our bioinformatic strategy not only allows biologists to studying separately host and symbiont data from a holobiont mixture, but also generates improved transcriptome assemblies. The use of Short Read Connector has proven to be an effective way to tackle meta-transcriptomic challenges to study holobiont systems composed of either well-studied or poorly characterized symbiotic lineages such as the newly sequenced marine plankton Radiolaria-Dinophyta symbiosis and ultimately expand our knowledge about these marine symbiotic associations.