Meta-Omics Reveals Genetic Flexibility of Diatom Nitrogen Transporters in Response to Environmental Changes.

diatoms machine learning meta-omics nitrogen transporters

Journal

Molecular biology and evolution
ISSN: 1537-1719
Titre abrégé: Mol Biol Evol
Pays: United States
ID NLM: 8501455

Informations de publication

Date de publication:
01 Nov 2019
Historique:
medline: 2 7 2019
pubmed: 2 7 2019
entrez: 2 7 2019
Statut: ppublish

Résumé

Diatoms (Bacillariophyta), one of the most abundant and diverse groups of marine phytoplankton, respond rapidly to the supply of new nutrients, often out-competing other phytoplankton. Herein, we integrated analyses of the evolution, distribution, and expression modulation of two gene families involved in diatom nitrogen uptake (DiAMT1 and DiNRT2), in order to infer the main drivers of divergence in a key functional trait of phytoplankton. Our results suggest that major steps in the evolution of the two gene families reflected key events triggering diatom radiation and diversification. Their expression is modulated in the contemporary ocean by seawater temperature, nitrate, and iron concentrations. Moreover, the differences in diversity and expression of these gene families throughout the water column hint at a possible link with bacterial activity. This study represents a proof-of-concept of how a holistic approach may shed light on the functional biology of organisms in their natural environment.

Identifiants

pubmed: 31259367
pii: 5525704
doi: 10.1093/molbev/msz157
pmc: PMC6805229
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2522-2535

Informations de copyright

© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Auteurs

Greta Busseni (G)

Stazione Zoologica Anton Dohrn, Naples, Italy.

Fabio Rocha Jimenez Vieira (F)

Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Université Paris, Paris, France.

Alberto Amato (A)

Laboratoire de Physiologie Cellulaire et Végétale, Univ. Grenoble Alpes, CEA, INRA, CNRS. BIG, Grenoble Cedex 9, France.

Eric Pelletier (E)

Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, France.
FR2022/Tara Oceans-GOSEE, Paris, France.

Juan J Pierella Karlusich (JJ)

Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Université Paris, Paris, France.

Maria I Ferrante (MI)

Stazione Zoologica Anton Dohrn, Naples, Italy.

Patrick Wincker (P)

Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, France.
FR2022/Tara Oceans-GOSEE, Paris, France.

Alessandra Rogato (A)

Stazione Zoologica Anton Dohrn, Naples, Italy.
Institute of Biosciences and BioResources, CNR, Naples, Italy.

Chris Bowler (C)

Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Université Paris, Paris, France.

Remo Sanges (R)

Stazione Zoologica Anton Dohrn, Naples, Italy.
Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy.

Luigi Maiorano (L)

Stazione Zoologica Anton Dohrn, Naples, Italy.
Dipartimento di Biologia e Biotecnologie "Charles Darwin", Università di Roma "La Sapienza", Roma, Italy.

Maurizio Chiurazzi (M)

Institute of Biosciences and BioResources, CNR, Naples, Italy.

Maurizio Ribera d'Alcalà (M)

Stazione Zoologica Anton Dohrn, Naples, Italy.

Luigi Caputi (L)

Stazione Zoologica Anton Dohrn, Naples, Italy.

Daniele Iudicone (D)

Stazione Zoologica Anton Dohrn, Naples, Italy.

Classifications MeSH