Signatures of directional selection in a hybrid yeast population
Bibliographic record
Abstract
Meiotic recombination is a fundamental biological process that leads to crossover and gene conversion. High resolution maps of meiotic recombination have been reported in several model organisms. However, few studies have studied how rapidly selection affects the products of meiotic recombination. Here we constructed and sequenced a yeast population of 38 haploid strains derived from hybridizations of two common used strains S288c and YJM789. We identified 20 regions with strong biased allele frequency across the genome, revealing signatures of selection in a rather short period. These regions harbor ample crossovers and gene conversions, which enable us to trace how selection works on the genomic fragments after meiosis. The total length of such regions under selection accounts for 5% of the entire genome, and those regions contain many functional-related genes. In addition, recombination breaks down linkage disequilibrium to half of its maximum within 42 kb and reduces nucleotide diversity significantly in selected regions. Our study thus provides details of directional selection on the outcomes of meiotic recombination using experimental approaches, and will shed light on our understanding of the fast reshaping of population structure by selection, as well as the important roles of recombination.
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 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 | 0.000 | 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".