A de novo approach to disentangle partner identity and function in holobiont systems

Arnaud Meng (1, 2) , Camille Marchet (3) , Erwan Corre (4, 5) , Pierre Peterlongo (3) , Adriana A. Alberti (6, 7) , Corinne da Silva (8) , Patrick Wincker (7) , Eric Pelletier (6, 7) , Ian Probert (4, 5) , Johan Decelle (9) , Stéphane Le Crom (1, 10) , Fabrice Not (4) , Lucie Bittner (1, 2)

1 SU - Sorbonne Université
2 UPMC - Université Pierre et Marie Curie - Paris 6 - UFR de Médecine Pierre et Marie Curie
3 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
4 SBR - Station biologique de Roscoff = Roscoff Marine Station
5 FR2424 - Fédération de recherche de Roscoff
6 GENOSCOPE - Genoscope - Centre national de séquençage [Evry]
7 UMR 8030 - Génomique métabolique
8 LBGB - Laboratoire de Bioinformatique pour la Génomique et la Biodiversité
9 UFZ - Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research
10 ADHDG - Analyse des Données à Haut Débit en Génomique

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. As the study of holobiont meta-transcriptomes is affected by challenges invoked above, we propose an innovative bioinformatic approach to tackle such difficulties and tested it on marine models as a proof of concept. Results: We considered three holobiont models, of which two transcriptomes were previously published and a yet unpublished transcriptome, to analyze and sort their raw reads using Short Read Connector, a k-mer based similarity method. Before assembly, we thus defined four distinct categories for each holobiont meta-transcriptome: host reads, symbiont reads, shared reads, and unassigned reads. Afterwards, we observed that independent de novo assemblies for each category led to a diminution of the number of chimeras compared to classical assembly methods. Moreover, the separation of each partner’ s transcriptome offered the independent and comparative exploration of their functional diversity in the holobiont. Finally, our strategy allowed to propose new functional annotations for two well-studied holobionts (a Cnidaria-Dinophyta, a Porifera-Bacteria) and a first meta-transcriptome from a planktonic Radiolaria-Dinophyta system forming widespread symbiotic association for which our knowledge is considerably limited. Conclusions: In contrast to classical assembly approaches, our bioinformatic strategy generates less de novo assembled chimera and allows biologists to study separately host and symbiont data from a holobiont mixture. The pre-assembly separation of reads using an efficient tool as Short Read Connector is an effective way to tackle meta-transcriptomic challenges and offers bright perpectives to study holobiont systems composed of either well-studied or poorly characterized symbiotic lineages and ultimately expand our knowledge about these associations.

Domains: Symbiosis; Bioinformatics [q-bio.QM]

Arnaud Meng, Camille Marchet, Erwan Corre, Pierre Peterlongo, Adriana A. Alberti, et al.. A de novo approach to disentangle partner identity and function in holobiont systems. Microbiome, 2018, pp.1-35. ⟨10.1186/s40168-018-0481-9⟩. ⟨hal-01643153v2⟩