Thesis

TOWARDS AN UNDERSTANDING OF BIOMINERALIZATION USING COMPARATIVE TRANSCRIPTOMICS IN THREE SISTER SPECIES OF COCCOLITHOPHORIDS

In this study, we aimed to identify the genes related to biomineralization of coccolithophorid using a comparative transcriptomic analysis.
 
 We started with 50 million paired-end Solexa short reads of two calcifying species of coccolithophorid, E. huxleyi and G. oceanica, and one non-calcifying species, I. galbana. By using de-novo assembly tools such as Trinity, we assembled transcriptomes of roughly 60,000 sequences for each species. Using the transcriptome, we identified the expression level of each gene using digital counting of reads aligning to individual transcript via an alignment tool Bowtie. We were interested in the amount of calcification under the ambient seawater growth condition with 9 mM calcium and another growth condition with 0 mM calcium. Thus, we identified the combined total across the three species about 4000 differentially expressed genes between the two growth conditions by comparing the expressed genes in each condition through an analysis tool such as RSEM (RNA-Seq by Expectation Maximization).
 
 Once we identified the differentially expressed genes between growth conditions for a single organism, we extended our work to cross-species analysis. By creating BLAST database from the differentially expressed genes of a single species and using tblastx to compare the differentially expressed genes of another species. A total of 399 gene sequences were differentially expressed in both E. huxleyi and G. oceanica and not in I. galbana when comparing calcifying versus non-calcifying growth conditions.
 
 Finally, the function of candidate genes related to biomineralization was predicted by
 using the Blast2GO annotation tool.

In this study, we aimed to identify the genes related to biomineralization of coccolithophorid using a comparative transcriptomic analysis. We started with 50 million paired-end Solexa short reads of two calcifying species of coccolithophorid, E. huxleyi and G. oceanica, and one non-calcifying species, I. galbana. By using de-novo assembly tools such as Trinity, we assembled transcriptomes of roughly 60,000 sequences for each species. Using the transcriptome, we identified the expression level of each gene using digital counting of reads aligning to individual transcript via an alignment tool Bowtie. We were interested in the amount of calcification under the ambient seawater growth condition with 9 mM calcium and another growth condition with 0 mM calcium. Thus, we identified the combined total across the three species about 4000 differentially expressed genes between the two growth conditions by comparing the expressed genes in each condition through an analysis tool such as RSEM (RNA-Seq by Expectation Maximization). Once we identified the differentially expressed genes between growth conditions for a single organism, we extended our work to cross-species analysis. By creating BLAST database from the differentially expressed genes of a single species and using tblastx to compare the differentially expressed genes of another species. A total of 399 gene sequences were differentially expressed in both E. huxleyi and G. oceanica and not in I. galbana when comparing calcifying versus non-calcifying growth conditions. Finally, the function of candidate genes related to biomineralization was predicted by using the Blast2GO annotation tool.

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