Literature DB >> 29624751

Analysis of the genomic basis of functional diversity in dinoflagellates using a transcriptome-based sequence similarity network.

Arnaud Meng1, Erwan Corre2, Ian Probert3, Andres Gutierrez-Rodriguez4, Raffaele Siano5, Anita Annamale6,7,8, Adriana Alberti6,7,8, Corinne Da Silva6,7,8, Patrick Wincker6,7,8, Stéphane Le Crom1, Fabrice Not9, Lucie Bittner1.   

Abstract

Dinoflagellates are one of the most abundant and functionally diverse groups of eukaryotes. Despite an overall scarcity of genomic information for dinoflagellates, constantly emerging high-throughput sequencing resources can be used to characterize and compare these organisms. We assembled de novo and processed 46 dinoflagellate transcriptomes and used a sequence similarity network (SSN) to compare the underlying genomic basis of functional features within the group. This approach constitutes the most comprehensive picture to date of the genomic potential of dinoflagellates. A core-predicted proteome composed of 252 connected components (CCs) of putative conserved protein domains (pCDs) was identified. Of these, 206 were novel and 16 lacked any functional annotation in public databases. Integration of functional information in our network analyses allowed investigation of pCDs specifically associated with functional traits. With respect to toxicity, sequences homologous to those of proteins found in species with toxicity potential (e.g., sxtA4 and sxtG) were not specific to known toxin-producing species. Although not fully specific to symbiosis, the most represented functions associated with proteins involved in the symbiotic trait were related to membrane processes and ion transport. Overall, our SSN approach led to identification of 45,207 and 90,794 specific and constitutive pCDs of, respectively, the toxic and symbiotic species represented in our analyses. Of these, 56% and 57%, respectively (i.e., 25,393 and 52,193 pCDs), completely lacked annotation in public databases. This stresses the extent of our lack of knowledge, while emphasizing the potential of SSNs to identify candidate pCDs for further functional genomic characterization.
© 2018 John Wiley & Sons Ltd.

Entities:  

Keywords:  genomics/proteomics; microbial biology; molecular evolution; protists; transcriptomics

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Year:  2018        PMID: 29624751     DOI: 10.1111/mec.14579

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  4 in total

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

Authors:  Arnaud Meng; Camille Marchet; Erwan Corre; Pierre Peterlongo; Adriana Alberti; Corinne Da Silva; Patrick Wincker; Eric Pelletier; Ian Probert; Johan Decelle; Stéphane Le Crom; Fabrice Not; Lucie Bittner
Journal:  Microbiome       Date:  2018-06-09       Impact factor: 14.650

2.  Core genes in diverse dinoflagellate lineages include a wealth of conserved dark genes with unknown functions.

Authors:  Timothy G Stephens; Mark A Ragan; Debashish Bhattacharya; Cheong Xin Chan
Journal:  Sci Rep       Date:  2018-11-21       Impact factor: 4.379

3.  Species specific gene expression dynamics during harmful algal blooms.

Authors:  Gabriel Metegnier; Sauvann Paulino; Pierre Ramond; Raffaele Siano; Marc Sourisseau; Christophe Destombe; Mickael Le Gac
Journal:  Sci Rep       Date:  2020-04-10       Impact factor: 4.379

4.  Towards omics-based predictions of planktonic functional composition from environmental data.

Authors:  Sakina-Dorothée Ayata; Lucie Bittner; Emile Faure
Journal:  Nat Commun       Date:  2021-07-16       Impact factor: 14.919

  4 in total

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