Digital expression profiling of novel diatom transcripts provides insight into their biological functions
- Equal contributors
1 Institut de Biologie de l'Ecole Normale Supérieure, CNRS UMR 8197 INSERM U1024, Ecole Normale Supérieure, 46 rue d'Ulm, 75005 Paris, France
2 Current address: EMBL - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
3 CEA - Institut de Génomique, Genoscope and CNRS UMR 8030, 2 rue Gaston Crémieux CP5706, 91057 Evry, France
4 Current address: J Craig Venter Institute, 11149 N. Torrey Pines Rd, Suite 220, La Jolla, CA 92037, USA
5 Physiologie et Biotechnologie des Algues, IFREMER, BP 21105, 44311 Nantes, France
6 Marine Biogeochemistry, IFM-GEOMAR Leibniz-Institut für Meereswissenschaften, Düsternbrooker Weg 20, D-24105 Kiel, Germany
7 Université de Nantes, EA 2160, Laboratoire 'Mer, Molécule, Santé', Faculté des Sciences et Techniques, 2 rue de la Houssinière, 44322, BP 92208, 44322 Nantes Cedex 3, France
8 School of Oceanography, University of Washington, 616 NE Northlake Place, Seattle, WA 98105, USA
9 University of East Anglia, School of Environmental Sciences, Norwich Research Park, Norwich NR4 7TJ, UK
10 Department of Plant Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
Genome Biology 2010, 11:R85 doi:10.1186/gb-2010-11-8-r85Published: 25 August 2010
Diatoms represent the predominant group of eukaryotic phytoplankton in the oceans and are responsible for around 20% of global photosynthesis. Two whole genome sequences are now available. Notwithstanding, our knowledge of diatom biology remains limited because only around half of their genes can be ascribed a function based onhomology-based methods. High throughput tools are needed, therefore, to associate functions with diatom-specific genes.
We have performed a systematic analysis of 130,000 ESTs derived from Phaeodactylum tricornutum cells grown in 16 different conditions. These include different sources of nitrogen, different concentrations of carbon dioxide, silicate and iron, and abiotic stresses such as low temperature and low salinity. Based on unbiased statistical methods, we have catalogued transcripts with similar expression profiles and identified transcripts differentially expressed in response to specific treatments. Functional annotation of these transcripts provides insights into expression patterns of genes involved in various metabolic and regulatory pathways and into the roles of novel genes with unknown functions. Specific growth conditions could be associated with enhanced gene diversity, known gene product functions, and over-representation of novel transcripts. Comparative analysis of data from the other sequenced diatom, Thalassiosira pseudonana, helped identify several unique diatom genes that are specifically regulated under particular conditions, thus facilitating studies of gene function, genome annotation and the molecular basis of species diversity.
The digital gene expression database represents a new resource for identifying candidate diatom-specific genes involved in processes of major ecological relevance.