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Record W2974934997 · doi:10.1101/gr.245605.118

Fitness benefits of loss of heterozygosity in <i>Saccharomyces</i> hybrids

2019· article· en· W2974934997 on OpenAlexfundno aff
Samuel M. Lancaster, Célia Payen, Caiti Smukowski Heil, Maitreya J. Dunham

Bibliographic record

VenueGenome Research · 2019
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 heterozygosityGeneticsHybridSaccharomyces cerevisiaeAlleleContext (archaeology)Adaptation (eye)ChromosomeGenomePhenotypeEvolutionary biologyYeastGene

Abstract

fetched live from OpenAlex

With two genomes in the same organism, interspecific hybrids have unique fitness opportunities and costs. In both plants and yeasts, wild, pathogenic, and domesticated hybrids may eliminate portions of one parental genome, a phenomenon known as loss of heterozygosity (LOH). Laboratory evolution of hybrid yeast recapitulates these results, with LOH occurring in just a few hundred generations of propagation. In this study, we systematically looked for alleles that are beneficial when lost in order to determine how prevalent this mode of adaptation may be and to determine candidate loci that might underlie the benefits of larger-scale chromosome rearrangements. These aims were accomplished by mating Saccharomyces uvarum with the S. cerevisiae deletion collection to create hybrids such that each nonessential S. cerevisiae allele is deleted. Competitive fitness assays of these pooled, barcoded, hemizygous strains, and accompanying controls, revealed a large number of loci for which LOH is beneficial. We found that the fitness effects of hemizygosity are dependent on the species context, the selective environment, and the species origin of the deleted allele. Further, we found that hybrids have a wider distribution of fitness consequences versus matched S. cerevisiae hemizygous diploids. Our results suggest that LOH can be a successful strategy for adaptation of hybrids to new environments, and we identify candidate loci that drive the chromosomal rearrangements observed in evolution of yeast hybrids.

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)0.001
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 score0.021
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
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 head0.032
GPT teacher head0.320
Teacher spread0.288 · 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

Citations70
Published2019
Admission routes1
Has abstractyes

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