Philippe Henry

Philippe Henry, Ph.D. / CSO

Abstract Presenter

Philippe Henry is a population geneticist and cannabis enthusiast who uses genomic data to advance our understanding of the genetic basis of key traits of the cannabis plant and its therapeutic potential. He holds a BSc and MSc In Biology from the University of Lausanne, Switzerland and a PhD from the University of British Columbia. For the past five years, Philippe has focused on the development of statistical approaches to model the chemotypic variation in elite cannabis cultivars and correlate that information with genomic data. His long term goal is to use sound science to objectively guide cannabis breeding efforts and the product development. Philippe is Chief Scientific Office with VSSL, director of R&D with the Flowr Corporation and adjunct professor at the University of Northern British Columbia.

On the Classification of Cannabis Chemovars Using Targeted Single Nucleotide Polymorphism Assays

The classification of Cannabis varieties has been increasingly discussed in the past years, particularly in the wake of emerging legal markets, with implications for intellectual property development, marketing and improvement of the scientific understanding of this contentious plant. While the concept of chemovars has been proposed and has gained popularity of late, the lack of guidance in introducing this concept and the fact that chemovars are based on indirectly assessed traits with a heritable basis has likely impeded the implementation of the concept to a broader audience. Here, we validate a previously proposed classification scheme derived from chemotype profiles from over 5000 individual accessions from Nevada. The resulting chemovar classification model was then applied to a sub-set of 70 samples sequenced using the Strainseek V2 protocol typed at about 10,000 locations in the genome. Using loading extraction from multivartiate analyses, we identify 21 highly informative Single Nucleotide Polymorphisms (SNPs) associated with the most parsimonious chemovar classification model based on terpene expression, with three major groups including myrcene, limonene and terpinolene dominant accessions. These highly informative genetic markers were then developed in target specific primers using the KASP assay chemistry, a competitive allele-specific PCR that enables bi-allelic scoring of SNPs and insertions and deletions (Indels) at specific loci based on dual FRET (Fluorescent Resonance Energy Transfer). The 21 novel assays were validated in 120 accessions from the west coast to assess amplification success and polymorphism. We propose using the validated assays as a simple tool for chemovar classification in drug type I cannabis in an accessible, rapid and cost effective means to classify cannabis by their respective chemovars.