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Record W2598419373 · doi:10.1093/molbev/msx098

Loss of Heterozygosity Drives Adaptation in Hybrid Yeast

2017· article· en· W2598419373 on OpenAlexfundno aff
Caiti Smukowski Heil, Christopher DeSevo, Dave A. Pai, Cheryl M. Tucker, Margaret L. Hoang, Maitreya J. Dunham

Bibliographic record

VenueMolecular Biology and Evolution · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFungal and yeast genetics research
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesCanadian Institute for Advanced ResearchNational Human Genome Research InstituteHoward Hughes Medical InstituteNational Institutes of HealthNational Science Foundation
KeywordsBiologyLoss of heterozygosityGeneticsSaccharomyces cerevisiaeAdaptation (eye)Experimental evolutionGenomeAlleleGenome evolutionGeneEvolutionary biology

Abstract

fetched live from OpenAlex

Hybridization is often considered maladaptive, but sometimes hybrids can invade new ecological niches and adapt to novel or stressful environments better than their parents. The genomic changes that occur following hybridization that facilitate genome resolution and/or adaptation are not well understood. Here, we examine hybrid genome evolution using experimental evolution of de novo interspecific hybrid yeast Saccharomyces cerevisiae × Saccharomyces uvarum and their parentals. We evolved these strains in nutrient-limited conditions for hundreds of generations and sequenced the resulting cultures identifying numerous point mutations, copy number changes, and loss of heterozygosity (LOH) events, including species-biased amplification of nutrient transporters. We focused on a particularly interesting example, in which we saw repeated LOH at the high-affinity phosphate transporter gene PHO84 in both intra- and interspecific hybrids. Using allele replacement methods, we tested the fitness of different alleles in hybrid and S. cerevisiae strain backgrounds and found that the LOH is indeed the result of selection on one allele over the other in both S. cerevisiae and the hybrids. This is an example where hybrid genome resolution is driven by positive selection on existing heterozygosity and demonstrates that even infrequent outcrossing may have lasting impacts on adaptation.

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 score0.349
Threshold uncertainty score0.300

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 head0.012
GPT teacher head0.289
Teacher spread0.277 · 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

Citations154
Published2017
Admission routes1
Has abstractyes

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