Citation
Teo, Swee Sen
(2004)
Development and Analyses of Expressed Sequence Tags from Gracilaria Changii for Functional Genomic Studies.
Masters thesis, Universiti Putra Malaysia.
Abstract
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.
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