Genomic profiling used to identify genes associated with calcification in the marine coccolithophorid, Emiliania huxleyi

The major goal of this study was to identify genes involved in the calcification and coccolithogenesis in the marine alga, Emiliania huxleyi using microarray analysis. Previous Suppressive Subtractive Hybridization (SSH) identified 168 differentially expressed transcripts between calcifying and non-calcifying cultures, and an earlier eDNA microarray analysis identified 188 differentially expressed genes using Expressed Sequence Tag's (EST's) as targets. To this point, E. huxleyi, strain 1516 has been used in all experiments, including the construction of both the SSH libraries and the EST libraries. The trigger for calcification had been phosphate stress. In strain 1516, calcification occurs in phosphate deplete media (1.67 [!M) and is inhibited in phosphate replete media (41.7 [!M). E. huxleyi, strain B39 recently was adopted in our lab as an experimental culture to compare to 1516 as it tends to calcify in phosphate replete media. A time course study was designed to compare gene expression profiles in a calcifying strain (B39) and a non-calcifying strain (1516) following the dissolution of calcite coccoliths with a dilute acid treatment. A eDNA microarray was constructed with a total of 368 elements printed in triplicate on glass slides. Target elements originated from both SSH and EST libraries. Total RNA was isolated from 12 L ofB39 cells and 12 L of 1516 cells. RNA was reverse transcribed and differentially labeled with Cy3 and Cy5 fluorescent dyes using Invotrogen's Superscript direct labeling system. Following the hybridizations, 60 genes were selected for further analysis based on exhibiting fluorescence intensities above two times the background fluorescence for at least two of the six time points. A repeated measures ANOV A was performed using these 60 clones to determine if there was an overall treatment effect over time. Of the 60 clones, 44 (73%) had a significant overall treatment effect. These 44 clones were then analyzed further using a factorial ANOVA to determine significant gene expression changes between time points of a single treatment.