RNA-seq Analysis of Monoterpene Indole Alkaloid Biosynthetic Pathway Elucidation in Catharanthus roseus.

Abstract

Increased affordability and availability of high-throughput next-generation sequencing (NGS) technologies have resulted in an explosion of available RNA-seq data, igniting a variety of data-mining methodologies, valuable for plant-specialized biosynthetic pathway discovery. When combined with traditional homology-based annotations, these methods can facilitate short-listing candidate genes for downstream functional validation screenings. Genes related to common pathways often display homogenous expression patterns across different tissue types and experimental conditions. Here, we describe bioinformatic protocols for exploiting such coexpression to shortlist candidate genes of the well-described monoterpene indole alkaloid (MIA) pathway of Catharanthus roseus. These methods aim to inspire researchers to utilize this publicly available RNA-seq treasure trove to guide their own endeavors in the characterization of missing steps in plant metabolic pathways.