TY - JOUR
T1 - Digital expression profiling of novel diatom transcripts provides insight into their biological functions
AU - Maheswari, Uma
AU - Jabbari, Kamel
AU - Petit, Jean Louis
AU - Porcel, Betina M.
AU - Allen, Andrew E.
AU - Cadoret, Jean Paul
AU - De Martino, Alessandra
AU - Heijde, Marc
AU - Kaas, Raymond
AU - La Roche, Julie
AU - Lopez, Pascal J.
AU - Martin-Jézéquel, Véronique
AU - Meichenin, Agnès
AU - Mock, Thomas
AU - Schnitzler Parker, Micaela
AU - Vardi, Assaf
AU - Armbrust, E. Virginia
AU - Weissenbach, Jean
AU - Katinka, Michaël
AU - Bowler, Chris
N1 - Funding Information:
Funding for the Diatom Digital Gene Expression Database was from the European Union-funded Diatomics project and the Agence Nationale de la Recherche (France). cDNA construction and DNA sequencing was funded by Genoscope (France). We are grateful to Pierre Vincens, Jean-Pierre Roux and Edouard Bray for managing the server and the software and for their help in web interface creation, Ikhlak Ahmed for his help with statistical analysis using R statistical language, as well as Igor Grigoriev and Alan Kuo from JGI. We would also like to thank Patrick Wincker, Julie Poulain and the technical staff of Genoscope for their essential contribution to the experimental part of the work, as well as Franck Anière and the entire system network team at Genoscope. The database is freely available on the web at [48]. The P. tricornutum cDNAs have been submitted to the NCBI dbEST (GenBank accession numbers [GenBank:CD374840] to [GenBank:CD384835] and [GenBank:BI306757] to [GenBank:BI307753]).
PY - 2010/8/25
Y1 - 2010/8/25
N2 - Background: 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.Results: 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.Conclusions: The digital gene expression database represents a new resource for identifying candidate diatom-specific genes involved in processes of major ecological relevance.
AB - Background: 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.Results: 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.Conclusions: The digital gene expression database represents a new resource for identifying candidate diatom-specific genes involved in processes of major ecological relevance.
UR - http://www.scopus.com/inward/record.url?scp=77955821696&partnerID=8YFLogxK
U2 - 10.1186/gb-2010-11-8-r85
DO - 10.1186/gb-2010-11-8-r85
M3 - Article
C2 - 20738856
AN - SCOPUS:77955821696
VL - 11
JO - Genome Biology
JF - Genome Biology
SN - 1474-760X
IS - 8
M1 - R85
ER -