Recombination, admixture and genome instability shape the genomic landscape of Saccharomyces cerevisiae derived from spontaneous grape ferments
Bibliographic record
Abstract
Cultural exchange of fermentation techniques has driven the spread of Saccharomyces cerevisiae across the globe, establishing natural populations in many countries. Despite this, Oceania is thought to lack native populations of S. cerevisiae, only being introduced after colonisation. Here we investigate the genomic landscape of 411 S. cerevisiae isolated from spontaneous grape fermentations in Australia across multiple locations, years, and grape cultivars. Spontaneous fermentations contained highly recombined mosaic strains that exhibited high levels of genome instability. Assigning genomic windows to putative ancestral origin revealed that few closely related starter lineages have come to dominate the genetic landscape, contributing most of the genetic variation. Fine-scale phylogenetic analysis of loci not observed in strains of commercial wine origin identified widespread admixture with European derived beer yeast along with three independent admixture events from potentially endemic Oceanic lineages that was associated with genome instability. Finally, we investigated Australian ecological niches for basal isolates, identifying phylogenetically distinct S. cerevisiae of non-European, non-domesticated origin associated with admixture loci. Our results illustrate the effect commercial use of microbes may have on local microorganism genetic diversity and demonstrates the presence of non-domesticated, potentially endemic lineages of S. cerevisiae in Australian niches that are actively admixing.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".