The genomics of wild yeast populations sheds light on the domestication of man's best (micro) friend
Bibliographic record
Abstract
The domestication of plants, animals and microbes by humans are the longest artificial evolution experiments ever performed. The study of these long-term experiments can teach us about the genomics of adaptation through the identification of the genetic bases underlying the traits favoured by humans. In laboratory evolution, the characterization of the molecular changes that evolved specifically in some lineages is straightforward because the ancestors are readily available, for instance in the freezer. However, in the case of domesticated species, the ancestor is often missing, which leads to the necessity of going back to nature in order to infer the most likely ancestral state. Significant and relatively recent examples of this approach include wolves as the closest wild relative to domestic dogs (Axelsson et al. 2013) and teosinte as the closest relative to maize (reviewed in Hake & Ross-Ibarra 2015). In both cases, the joint analysis of domesticated lineages and their wild cousins has been key in reconstructing the molecular history of their domestication. While the identification of closest wild relatives has been done for many plants and animals, these comparisons represent challenges for micro-organisms. This has been the case for the budding yeast Saccharomyces cerevisiae, whose natural ecological niche is particularly challenging to define. For centuries, this unicellular fungus has been the cellular factory for wine, beer and bread crafting, and currently for bioethanol and drug production. While the recent development of genomics has lead to the identification of many genetic elements associated with important wine characteristics, the historical origin of some of the domesticated wine strains has remained elusive due to the lack of knowledge of their close wild relatives. In this issue of Molecular Ecology, Almeida et al. (2015) identified what is to date the closest known wild population of the wine yeast. This population is found associated with oak trees in Europe, presumably its natural host. Using population genomics analyses, Almeida and colleagues discovered that the initial divergence between natural and domesticated wine yeasts in the Mediterranean region took place around the early days of wine production. Surprisingly, genomic regions that are key to wine production today appeared not to be derived from these natural populations but from genes gained from other yeast species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".