MétaCan
Menu
Back to cohort
Record W4365504760 · doi:10.1139/cjb-2022-0140

Genomic description of critical cannabinoid biosynthesis genes

2023· article· en· W4365504760 on OpenAlexvenueno aff
Peter A. Innes, Daniela Vergara

Bibliographic record

VenueBotany · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyGeneCannabinoidGenomeGeneticsCannabidiolPhylogenetic treeComputational biologyCannabis

Abstract

fetched live from OpenAlex

Cannabinoid production is a key attribute of the plant Can nabis sativa and characterizing the genes involved is an essential first step to develop tools for their optimization. We used bioinformatic approaches to annotate and explore variation in the genes coding for enzymes comprising the cannabinoid pathway: olivetol synthase (OLS), olivetolic acid cyclase (OAC), cannabigerolic acid synthase (CBGAS), and the cannabinoid oxidocyclases (THCAS, CBDAS, CBCAS) in multiple C. sativa genome assemblies from diverse lineages. The former three enzymes generate the precursor molecules for the oxidocyclases to produce cannabinoids tetrahydrocannabinol (THC) and cannabidiol (CBD). We show that duplications of OLS and OAC are consistent across varieties, and that OAC has the least amount of sequence diversity based on phylogenetic comparisons. We also found that one CBGAS-like gene exhibits copy number variation among varieties. We discuss implications of these genes existing on separate chromosomes (with homologs of each found in close proximity), and the significance of CBGAS being located on the X chromosome for cannabinoid production in female plants. This study provides valuable insight on the genomic identity and variation of cannabinoid biosynthesis genes that will benefit future research on the origin and evolution of this pathway, a driver of economic, social, and medicinal value.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.248
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBotanySame topicLipid metabolism and biosynthesisFrench-language works237,207