A Single Nucleotide Polymorphism assay sheds light on the extent and distribution of genetic diversity, population structure and functional basis of key traits in cultivated North American Cannabis
Bibliographic record
Abstract
Abstract Background The taxonomic classification of the Cannabis genus has been delineated through three main types: sativa (long and less branched plant with long and narrow leaves), indica (short but highly branched plant with broader leaves) and ruderalis (wild 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 putative geographical origin of each group and putative chemotypic and pharmacology. Methods Here we describe a thorough investigation of cannabis accessions using a set of 22 highly informative and polymorphic SNP markers associated with important traits such as cannabinoid and terpenoid expression as well as fibre and resin production. The assay offers insight into cannabis population structure, phylogenetic relationship, population genetics and correlation to secondary metabolite concentrations and demonstrate the utility of this assay for rapid, repeatable and cost-efficient genotyping of commercial and industrial cannabis accessions for use in product traceability, breeding programs, regulatory compliance and consumer education. Results The main outcomes are the identification of 5 clusters in the sample set available, including industrial hemp, resin hemp which likely underwent a bottleneck to stabilize CBDA accumulation (Type II & III). THC resin (type I) make up the other three clusters with terpinolene (colloquial “sativa” or “NLD”), myrcene/pinene and myrcene/limonene (colloquial “indica”, “BLD”), which also putatively harbour an active CBCAS. Conclusion The functional basis of key traits is also discussed as recently enabled by the NCBI Cannabis sativa Annotation Release 100, allowing for hypothesis testing with regards to secondary metabolite production as well as other key traits of importance for adaptable and compliant large-scale seed production under the new US Domestic Hemp Production Program.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".