Modeling cannabinoids from a large-scale sample of Cannabis sativa chemotypes.

The widespread legalization of Cannabis has opened the industry to using contemporary analytical techniques for chemotype analysis. Chemotypic data has been collected on a large variety of oil profiles inherent to the cultivars that are commercially available. The unknown gene regulation and pharmacokinetics of dozens of cannabinoids offer opportunities of high interest in pharmacology research. Retailers in many medical and recreational jurisdictions are typically required to report chemical concentrations of at least some cannabinoids. Commercial cannabis laboratories have collected large chemotype datasets of diverse Cannabis cultivars. In this work a data set of 17,600 cultivars tested by Steep Hill Inc., is examined using machine learning techniques to interpolate missing chemotype observations and cluster cultivars into groups based on chemotype similarity. The results indicate cultivars cluster based on their chemotypes, and that some imputation methods work better than others at grouping these cultivars based on chemotypic identity. Due to the missing data and to the low signal to noise ratio for some less common cannabinoids, their behavior could not be accurately predicted. These findings have implications for characterizing complex interactions in cannabinoid biosynthesis and improving phenotypical classification of Cannabis cultivars.

Genomic characterization of the complete terpene synthase gene family from Cannabis sativa.

Terpenes are responsible for most or all of the odor and flavor properties of Cannabis sativa, and may also impact effects users experience either directly or indirectly. We report the diversity of terpene profiles across samples bound for the Washington dispensary market. The remarkable degree of variation in terpene profiles ultimately results from action of a family of terpene synthase genes, only some of which have been described. Using a recently available genome assembly we describe 55 terpene synthases with genomic context, and tissue specific expression. The family is quite diverse from a protein similarity perspective, and subsets of the family are expressed in all tissues in the plant, including a set of root specific monoterpene synthases that could well have agronomic importance. Ultimately understanding and breeding for specific terpene profiles will require a good understanding of the gene family that underlies it. We intend for this work to serve as a foundation for that.

Gene copy number is associated with phytochemistry in Cannabis sativa.

Gene copy number (CN) variation is known to be important in nearly every species where it has been examined. Alterations in gene CN may provide a fast way of acquiring diversity, allowing rapid adaptation under strong selective pressures, and may also be a key component of standing genetic variation within species. Cannabis sativa plants produce a distinguishing set of secondary metabolites, the cannabinoids, many of which have medicinal utility. Two major cannabinoids-THCA (delta-9-tetrahydrocannabinolic acid) and CBDA (cannabidiolic acid)-are products of a three-step biochemical pathway. Using whole-genome shotgun sequence data for 69 Cannabis cultivars from diverse lineages within the species, we found that genes encoding the synthases in this pathway vary in CN. Transcriptome sequence data show that the cannabinoid paralogs are differentially expressed among lineages within the species. We also found that CN partially explains variation in cannabinoid content levels among Cannabis plants. Our results demonstrate that biosynthetic genes found at multiple points in the pathway could be useful for breeding purposes, and suggest that natural and artificial selection have shaped CN variation. Truncations in specific paralogs are associated with lack of production of particular cannabinoids, showing how phytochemical diversity can evolve through a complex combination of processes.

Compromised External Validity: Federally Produced Cannabis Does Not Reflect Legal Markets.

As the most widely used illicit drug worldwide, and as a source of numerous under-studied pharmacologically-active compounds, a precise understanding of variability in psychological and physiological effects of Cannabis varieties is essential. The National Institute on Drug Abuse (NIDA) is designated as the sole legal producer of Cannabis for use in US research studies. We sought to compare the chemical profiles of Cannabis varieties that are available to consumers in states that have state-legalized use versus what is available to researchers interested in studying the plant and its effects. Our results demonstrate that the federally-produced Cannabis has significantly less variety and lower concentrations of cannabinoids than are observed in state-legal U.S. dispensaries. Most dramatically, NIDA's varieties contain only 27% of the THC levels and as much as 11-23 times the Cannabinol (CBN) content compared to what is available in the state-legal markets. Research restricted to using the current range of federally-produced Cannabis thus may yield limited insights into the chemical, biological and pharmacological properties, and medical potential of material that is available in the state markets. Investigation is urgently needed on the full diversity of Cannabis chemotypes known to be available to the public.