Philippe Henry, Surender Khatodia, Karan Kapoor, Britni Gonzales, Alexis Middleton, Kevin Hong, Aaron Hilyard, Steve Johnson, Davis Allen, Zachary Chester, Dan Jin, José Carlos Rodriguez Jule, Iain Wilson, Manu Gangola, Jason Broome, Deron Caplan, Dinesh Adhikary, Michael K. Deyholos, Michael Morgan, Oliver W. Hall, Brent J. Guppy & Cindy Orser
Journal of Cannabis Research
Background
The taxonomic classification of Cannabis genus has been delineated through three main types: sativa (tall and less branched plant with long and narrow leaves), indica (short and highly branched plant with broader leaves) and ruderalis (heirloom type with short stature, less branching and small thick leaves). While still under discussion, particularly whether the genus is polytypic or monotypic, this broad classification reflects the putative geographical origins of each group and putative chemotype and pharmacologic effect.
Kovalchuk I, Pellino M, Rigault P, van Velzen R, Ebersbach J, Ashnest JR, Mau M, Schranz ME, Alcorn J, Laprairie RB, McKay JK, Burbridge C, Schneider D, Vergara D, Kane NC, Sharbel TF. The Genomics of Cannabis and Its Close Relatives. Annu Rev Plant Biol. 2020 Apr 29;71:713-739. doi: 10.1146/annurev-arplant-081519-040203. Epub 2020 Mar 10. PMID: 32155342.
A major analysis of statistical data and studies has highlighted the importance of mapping the cannabis genome for unlocking the full potential of the plant.
The international study, led by University of Saskatchewan researchers and published in the Annual Review of Plant Biology, says that mapping the cannabis genome will require a co-ordinated scientific effort, and will benefit applications of cannabis in both health and agriculture.
The authors of the review conclude that there are large gaps in the scientific knowledge of this high-demand, multi-purpose crop. The team, which includes scientists in The Netherlands, Germany, and the US, found that less than 50% of the cannabis genome is accurately mapped, with about 10% of the genome missing and another 10 to 25% unmapped.
Lead Author: Prof. Dr. Tim Sharbel
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