Digital expression profiling of novel diatom transcripts provides insight into their biological functions View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-08

AUTHORS

Uma Maheswari, Kamel Jabbari, Jean-Louis Petit, Betina M Porcel, Andrew E Allen, Jean-Paul Cadoret, Alessandra De Martino, Marc Heijde, Raymond Kaas, Julie La Roche, Pascal J Lopez, Véronique Martin-Jézéquel, Agnès Meichenin, Thomas Mock, Micaela Schnitzler Parker, Assaf Vardi, E Virginia Armbrust, Jean Weissenbach, Michaël Katinka, Chris Bowler

ABSTRACT

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. More... »

PAGES

r85

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/gb-2010-11-8-r85

DOI

http://dx.doi.org/10.1186/gb-2010-11-8-r85

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1041617129

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20738856


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