The Genome Sequence of the Jean-Talon Strain, an Archeological Beer Yeast from Québec, Reveals Traces of Adaptation to Specific Brewing Conditions
Bibliographic record
Abstract
Abstract The genome sequences of archeological Saccharomyces cerevisiae isolates can reveal insights about the history of human baking, brewing and winemaking activities. A yeast strain called Jean-Talon was recently isolated from the vaults of the Intendant’s Palace of Nouvelle France on a historical site in Québec City. This site was occupied by breweries from the end of the 17th century until the middle of the 20th century when poisoning caused by cobalt added to the beer led to a shutdown of brewing activities. We sequenced the genome of the Jean-Talon strain and reanalyzed the genomes of hundreds of strains to determine how it relates to other domesticated and wild strains. The Jean-Talon strain is most closely related to industrial beer strains from the beer and bakery genetic groups from the United Kingdom and Belgium. It has numerous aneuploidies and Copy Number Variants (CNVs), including the main gene conferring cobalt resistance in yeast. The Jean-Talon strain has indeed higher tolerance to cobalt compared to other yeast strains, consistent with adaptation to the most recent brewing activities on the site. We conclude from this that the Jean-Talon strain most likely derives from recent brewing activities and not from the original breweries of Nouvelle France on the site.
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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 | 0.001 | 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".