Identification of the Genes that Regulate Silk Production in Spiders: A Computational Biology Approach
Mark Alonzo
Abstract
Mark Alonzo
Abstract
The molecular basis of spider silk production is of broad interest because of its possible mechanical applications. For instance, dragline silk, which is produced in the major ampullate gland of certain spiders, has been found to be tougher than nylon and Kevlar??. However, even though there is research on the mechanical and structural properties of spider silk, the gene expression and regulation responsible for spider silk production remains largely unexplored. In this project, we tried to identify the genes that regulate spider silk production by analyzing 8 RNAseq libraries from silk glands of male and female Dysdera spiders. Using a reference transcriptome, a differential expression analysis is done to identify statistically relevant expressed genes. The programs BowTie2 and TopHat were used to perform alignment to the reference transcriptome. To perform differential expression analysis, tuxedo tool suite of programs (CuffLinks, CuffMerge, CuffCompare), HTSeq, and DESeq, were used to determine statistically significant differentially expressed genes. This analysis will provide insights regarding the genes that are either upregulated or downregulated during silk production in Dysdera spiders.
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The molecular basis of spider silk production is of broad interest because of its possible mechanical applications. For instance, dragline silk, which is produced in the major ampullate gland of certain spiders, has been found to be tougher than nylon and Kevlar??. However, even though there is research on the mechanical and structural properties of spider silk, the gene expression and regulation responsible for spider silk production remains largely unexplored. In this project, we tried to identify the genes that regulate spider silk production by analyzing 8 RNAseq libraries from silk glands of male and female Dysdera spiders. Using a reference transcriptome, a differential expression analysis is done to identify statistically relevant expressed genes. The programs BowTie2 and TopHat were used to perform alignment to the reference transcriptome. To perform differential expression analysis, tuxedo tool suite of programs (CuffLinks, CuffMerge, CuffCompare), HTSeq, and DESeq, were used to determine statistically significant differentially expressed genes. This analysis will provide insights regarding the genes that are either upregulated or downregulated during silk production in Dysdera spiders.
Key concepts: Identification (biology), Production (economics), Biology, Gene, SILK, Computational biology, Evolutionary biology, Genetics