Genetic and phenotypic diversity of wine-associated <i>Hanseniaspora</i> species
Bibliographic record
Abstract
The genus Hanseniaspora includes apiculate yeasts commonly found in fruit- and fermentation-associated environments. Their genetic diversity and evolutionary adaptations remain largely unexplored despite their ecological and oenological significance. This study investigated the phylogenetic relationships, genome structure, selection patterns, and phenotypic diversity of Hanseniaspora species isolated primarily from Australian wine environments, focusing on Hanseniaspora uvarum, the most abundant non-Saccharomyces yeast in wine fermentation. A total of 151 isolates were sequenced, including long-read genomes for representatives of the main phylogenetic clades. Comparative genomics revealed ancestral chromosomal rearrangements between the slow-evolving lineage (SEL) and fast-evolving lineage (FEL) that could have contributed to their evolutionary split, as well as significant loss of genes associated with mRNA splicing, chromatid segregation and signal recognition particle protein targeting in the FEL. Pangenome analysis within H. uvarum identified extensive copy number variation, particularly in genes related to xenobiotic tolerance and nutrient transport. Investigation into the selective landscape following the FEL/SEL divergence identified diversifying selection in 229 genes in the FEL, with significant enrichment in genes within the lysine biosynthetic pathway. Furthermore, phenotypic screening of 116 isolates revealed substantial intraspecific diversity, with specific species exhibiting enhanced ethanol, osmotic, copper, SO₂, and cold tolerance.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".