title: Leveraging metabolomics for functional investigations in sequenced marine diatoms.
abstract: Recent years have witnessed the genomic decoding of a wide range of photosynthetic organisms from the model plant Arabidopsis thaliana and the complex genomes of important crop species to single-celled marine phytoplankton. The comparative sequencing of green, red and brown algae has provided considerable insight into a number of important questions concerning their evolution, physiology and metabolism. The combinatorial application of metabolomics has further deepened our understanding both of the function of individual genes and of metabolic processes. Here we discuss the power of utilising metabolomics in conjunction with sequencing data to gain greater insight into the metabolic hierarchies underpinning the function of individual organisms, using unicellular marine diatoms as a case study to exemplify the advantages of this approach.
authors.affiliation: Max-Planck-Institut für Molekulare Pflanzenphysiologie, Potsdam-Golm, Germany. fernie@mpimp-golm.mpg.de
authors.forename: Alisdair R
authors.initials: AR
authors.lastname: Fernie
authors.forename: Toshihiro
authors.initials: T
authors.lastname: Obata
authors.forename: Andrew E
authors.initials: AE
authors.lastname: Allen
authors.forename: Wagner L
authors.initials: WL
authors.lastname: Araújo
authors.forename: Chris
authors.initials: C
authors.lastname: Bowler
mesh_terms: D000220:Adaptation, Biological; D005075:Biological Evolution; D017377:Diatoms / Q000235:genetics* / Q000378:metabolism; D022761:Gene Transfer, Horizontal; D016678:Genome; D007501:Iron / Q000378:metabolism; D053858:Metabolic Networks and Pathways; D055432:Metabolomics; D009952:Ornithine / Q000378:metabolism; D013559:Symbiosis; D014508:Urea / Q000378:metabolism
chemical_list: D014508:Urea; D007501:Iron; D009952:Ornithine