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

82Citations
Citations of this article
168Readers
Mendeley users who have this article in their library.

This article is free to access.

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. © 2010 Maheswari et al; licensee BioMed Central Ltd.

Cite

CITATION STYLE

APA

Maheswari, U., Jabbari, K., Petit, J. L., Porcel, B. M., Allen, A. E., Cadoret, J. P., … Bowler, C. (2010). Digital expression profiling of novel diatom transcripts provides insight into their biological functions. Genome Biology, 11(8). https://doi.org/10.1186/gb-2010-11-8-r85

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free