“Transcriptomics for the analysis of complex traits”
Rhode Island IDeA Network for Biomedical Research Excellence
With sequencing costs dipping below $7 per million reads, transcriptome analysis with next generation sequencing has become an attractive and accessible tool for molecular biologists. The volume of information produced per experiment is dizzying and necessitates a bioinformatic workflow to manage data. In addition, the analysis of data can be complicated when transcriptomics is used for discovery rather than for hypothesis testing. Our lab has recently identified a new gene that delays the rate of aging of the roundworm C. elegans. Aging is generally understood to be a multifactorial progressive decline in physiology that involves numerous cellular pathways from DNA damage repair and protein homeostasis to redox chemistry and adaptive metabolic responses. As a tool for discovery, we utilized RNA sequencing to gain insight into the molecular mechanism of longevity secondary to our discovered mutation. In this presentation, I will outline the various bioinformatic methods we used to validate our data, as well as tools to help us identify altered activity of cellular pathways based on our discovery of differentially expressed genes.
This project was supported in full by the RI-INBRE Subproject of Award NIH P20GM103430