By Philippe Henry

Genomic technologies have revolutionized the fields of evolutionary biology and genetics, bringing with it the promise of our understanding of the functional basis and inheritance of key traits of interest. On the other hand, the stupendous amount of data generated by such means have not been matched by computer power and as such, many genomic studies use quality control measures to reduce the number of marker retained in analyses, resulting in most studies retaining bi-allelic Single Nucleotide Polymorphisms (SNPs) Henry 2018.

We set out to compare the utility of a select tri-allelic SNPs panel against three functionally validated bi-allelic SNPs underlying monoterpene, sesquiterpene and cannabinoid expression Watts et al 2021. We leveraged data from Jin et al 2021 containing genotypes from 23 cannabis accessions with associated chemotypic profiles, which clustered into THC, CBD and intermediate (THC/CBD) categories. Low sesquiterpene content was noted in the CBD and intermediate groups. An independent compilation of data from the public domain available from the International Cannabis Research Consortium was used to demonstrate the power of the tri-allelic panel.

We show near perfect assignment to the predefined chemotype groups, and demonstrate that the three tri-allelic markers can be used in combination as predictors of biochemical makeup in Cannabis, providing a simple means to categorize cannabis into groups based on their monoterpene, sesquiterpene and cannabinoid content.

Attachment: Henry2022JBriefIdeas.pdf (3.32 MB)

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Authors

Philippe Henry

Metadata

Zenodo.6643865

Published: 18 Apr, 2022

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