Introduction: Cannabis is a plant with high potential for use in several sectors of the industry; however, it is also a controversial crop due to its tetrahydrocannabinol (THC) content. Moreover, the plant has a rather unclarified classification. Traditionally, two types of Cannabis have been distinguished, hemp as a source of fiber and low THC content, and marijuana with high THC levels, which is used as a drug. With the increasing use of CBD strains and wide range of commercially used THC strains, it is becoming paramount to be able to develop an easy and reliable method for Cannabis strain differentiation. The use of simple sequence repeat markers, or microsatellites, seems to be an applicable choice. Materials and Methods: In this study, 52 strains of Cannabis with variable cannabinoid content were collected from growers from different geographical regions and analyzed using 17 different microsatellite markers. For more precise differentiation, five strains were selected and a higher number of individuals of each were analyzed. Results: Fragment analysis and cluster analysis showed that when one to three individual plants per strain were analyzed, the method was able to classify these samples into distinguishable groups with similar gene structure. They also revealed that when a larger sample set was used (10 individual plants per strain), highly specific strain clusters could be fully discriminated. Conclusion: Our study involved the highest number of cannabinoid-rich strains up to now and showed that the microsatellite method can be used to reliably differentiate Cannabis strains and show their relationships.
Keywords: Cannabis; cannabinoid rich; clustering; microsatellite method; strain identification.