Contribution of local recombination and AT-biased mutations to differentiated region formation along a speciation continuum
Bibliographic record
Abstract
Genome features can interact with evolutionary processes and involve in the formation of differentiated regions potentially containing adaptation and speciation loci. However, GC content that can elevate regional mutation rate and is positively correlated with recombination has not been investigated in evolving lineages. Here, we employed 499 genomes of Apis cerana, with a widely distributed Central lineage diverged with its peripheral lineages at both population genetic and phylogenetic timescales, to investigate mutation accumulation and lineage divergence along the speciation continuum. We found differentiated regions are generally with lower recombination and GC compared with the rest of the genome, and with lower divergence (dxy) initially to higher ones at deeper timescale. Higher mutation load in low-GC regions in all A. cerana lineages suggest the important role of restricted recombination instead of selection on differentiated region formation. In addition, most mutations are AT-biased that derived from GC, resulting in lower mutation rate and nucleotide diversity in low-GC regions. AT-biased mutations can be counteracted by GC-biased gene conversion (fixation of GC alleles). While in low-GC regions, we found higher percentage of nearly fixed AT alleles in all peripheral lineages compared with Central lineage, supporting the contribution of AT-biased mutations to lineage divergence. Finally, low-GC regions possess higher proportion of lineage-specific polymorphisms than high-GC regions, and reconciliate discordance between mitochondrial and nuclear phylogenies in A. cerana. Our results shed light on the contribution of polymorphisms in low-GC regions to differentiated region formation along the speciation continuum and their application in reconstruction of intraspecific phylogeny.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".