Development and Analyses of Expressed Sequence Tags from Gracilaria Changii for Functional Genomic Studies

Macroalgae from the genus Gracilaria is the most common agarophytic genus in Malaysia (Phang et al., 1996). This wild population of seaweed has been identified as an important source of raw material for the agar industry. Despite its potential to produce good gel strength agar, Gracilaria sp. was genetically less studied. The aims of this study are to generate and sequence a thousand Expressed Sequence Tag (EST) sequences from G. changii for further cDNA microarray to facilitate functional genomic research. RNA extraction from G. changii is difficult due to poor yield, polysaccharide contamination and gel formation. To circumvent these problems the RNA isolation procedure was modified and repeated more than 150 times (more than 10 kg of fresh samples were used) to obtain high quality RNA for further studies. From the three modified RNA extraction methods, the modified method of Kim et al. (1997) was chosen for rapid RNA isolation from G. changii. This method can be completed within 1 day and many samples can be processed at the same time. The yield was increased from 0.018 μg/g to 1.14 μg/g of tissue with an average purity measured as A(260/280) of 1.90. After the modification, the mRNA was recovered from the total RNA of G. changii at a ratio of 0.5 – 1.0%. Starting from 5 μg of mRNA, a primary cDNA library of 1.14 x 106 clones was constructed and 1.375 x 1010 pfu/mL plaques were established for the amplified library. A total of 1854 cDNA clones were successfully sequenced. The database consists of ESTs with putative functions in protein synthesis (6%), energy (4%), protein destination and storage (3%), metabolism (3%), transportation (2%), transcription (2%), signal transduction (1%), cell structure/maintenance (1%), disease and defence (1%), cell growth and division (1%), intracellular traffic (1%) and other miscellaneous functions (2%). Putative proteins with unknown functions (67%), and novel sequences (6%) that do not show significant matches to the existing sequence databases are also present. Among the ESTs, 1342 sequences (72.38%) were clustered as singleton, and the remaining 512 were clustered into 168 contigs