Engineering of glucosinolate biosynthesis: candidate gene identification and validation.

The diverse biological roles of glucosinolates as plant defense metabolites and anticancer compounds have spurred a strong interest in their biosynthetic pathways. Since the completion of the Arabidopsis genome, functional genomics approaches have enabled significant progress on the elucidation of glucosinolate biosynthesis, although in planta validation of candidate gene function often is hampered by time-consuming generation of knockout and overexpression lines in Arabidopsis. To better exploit the increasing amount of data available from genomic sequencing, microarray database and RNAseq, time-efficient methods for identification and validation of candidate genes are needed. This chapter covers the methodology we are using for gene discovery in glucosinolate engineering, namely, guilt-by-association-based in silico methods and fast proof-of-function screens by transient expression in Nicotiana benthamiana. Moreover, the lessons learned in the rapid, transient tobacco system are readily translated to our robust, versatile yeast expression platform, where additional genes critical for large-scale microbial production of glucosinolates can be identified. We anticipate that the methodology presented here will be beneficial to elucidate and engineer other plant biosynthetic pathways.