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Microbiome. 2018 Jun 9;6(1):105. doi: 10.1186/s40168-018-0481-9.

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

Author information

1
Sorbonne Université, Univ Antilles, CNRS, Evolution Paris Seine - Institut de Biologie Paris Seine (EPS - IBPS), F-75005, Paris, France. arnaud.meng@etu.upmc.fr.
2
Univ Rennes, CNRS, Inria, IRISA - UMR 6074, F-35000, Rennes, France.
3
Sorbonne Universités, CNRS - FR2424, ABiMS, Station biologique de Roscoff, Place Georges Teissier, 29680, Roscoff, France.
4
Institut de biologie François Jacob, GENOSCOPE, 2 rue Gaston Crémieux, 91057, Evry, France.
5
UMR8030, CNRS, Evry, France.
6
Sorbonne Université, CNRS - FR2424, Roscoff Culture Collection, Station Biologique de Roscoff, Place Georges Teissier, 29682, Roscoff, France.
7
Helmholtz Centre for Environmental Research - UFZ, Department of Isotope Biogeochemistry, Permoserstraße 15, 04318, Leipzig, Germany.
8
Sorbonne Université, Univ Antilles, CNRS, Evolution Paris Seine - Institut de Biologie Paris Seine (EPS - IBPS), F-75005, Paris, France.
9
Sorbonne Université, CNRS - UMR7144 - Ecology of Marine Plankton Group, Station Biologique de Roscoff, Place Georges Teissier, 29680, Roscoff, France.
10
Sorbonne Université, Univ Antilles, CNRS, Evolution Paris Seine - Institut de Biologie Paris Seine (EPS - IBPS), F-75005, Paris, France. lucie.bittner@upmc.fr.

Abstract

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We considered three holobiont models, of which two transcriptomes were previously published and a yet unpublished transcriptome, to analyze and sort their raw reads using Short Read Connector, a k-mer based similarity method.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.

KEYWORDS:

De novo assembly; Holobiont; Marine; Meta-transcriptomic; Plankton; k-mer based similarity

PMID:
29885666
PMCID:
PMC5994019
DOI:
10.1186/s40168-018-0481-9
[Indexed for MEDLINE]
Free PMC Article

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