Abstract
The cannabis community typically uses the terms “Sativa” and “Indica” to characterize drug strains with high tetrahydrocannabinol (THC) levels. Due to large scale, extensive, and unrecorded hybridization in the past 40 years, this vernacular naming convention has become unreliable and inadequate for identifying or selecting strains for clinical research and medicinal production. Additionally, cannabidiol (CBD) dominant strains and balanced strains (or intermediate strains, which have intermediate levels of THC and CBD), are not included in the current classification studies despite the increasing research interest in the therapeutic potential of CBD. This paper is the first in a series of studies proposing that a new classification system be established based on genome-wide variation and supplemented by data on secondary metabolites and morphological characteristics. This study performed a whole-genome sequencing of 23 cannabis strains marketed in Canada, aligned sequences to a reference genome, and, after filtering for minor allele frequency of 10%, identified 137,858 single nucleotide polymorphisms (SNPs). Discriminant analysis of principal components (DAPC) was applied to these SNPs and further identified 344 structural SNPs, which classified individual strains into five chemotype-aligned groups: one CBD dominant, one balanced, and three THC dominant clusters. These structural SNPs were all multiallelic and were predominantly tri-allelic (339/344). The largest portion of these SNPs (37%) occurred on the same chromosome containing genes for CBD acid synthases (CBDAS) and THC acid synthases (THCAS). The remainder (63%) were located on the other nine chromosomes. These results showed that the genetic differences between modern cannabis strains were at a whole-genome level and not limited to THC or CBD production. These SNPs contained enough genetic variation for classifying individual strains into corresponding chemotypes. In an effort to elucidate the confused genetic backgrounds of commercially available cannabis strains, this classification attempt investigated the utility of DAPC for classifying modern cannabis strains and for identifying structural SNPs.
Highlights
The grouping assignment for individual strains by Discriminant analysis of principal components (DAPC) is listed in Table 1
principal component analysis (PCA) was carried out on the same set of single nucleotide polymorphisms (SNPs) and results are shown in S1 Fig. Twenty-three cannabis strains are plotted along pair-wise principal components (PC) of the first 4 PCs, which account for 18.4%, 11.5%, 9.5%, and 8.7% of the total variance, respectively
The cannabis industry is rapidly advancing after the relaxation of legal restrictions in North America, the increasing number of THC dominant strains, CBD dominant strains, and balanced strains only adds confusion to the currently poorly understood genetic background of the thousands of varieties already in existence
Summary
Since the 1980s, breeding for high psychoactive THC content has occurred very aggressively in North America [2]. Most drug-type cannabis currently cultivated in the USA, Canada, and Europe are hybridized, resulting in thousands of strains [3]. Recent genetic studies focused on validating the vernacular classification of “Sativa” and “Indica” [4,5,6,7]. This terminology is inadequate for identifying or selecting strains for clinical research and medicinal production due to the misuse of the botanical nomenclature, extensive cross-breeding, and unreliable labelling during unrecorded hybridization [2]. CBD dominant strains and balanced strains (THC CBD), which have gained increasing attention due to CBD’s use as a therapeutic [8,9,10,11,12], have been omitted in recent classification studies
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