The distribution and dispersal of large haploblocks in a superspecies
Bibliographic record
Abstract
Haploblocks are regions of the genome that coalesce to an ancestor as a single unit. Differentiated haplotypes in these regions can result from the accumulation of mutational differences in low-recombination chromosomal regions, especially when selective sweeps occur within geographically structured populations. We introduce a method to identify large well-differentiated haploblock regions (LHBRs), based on the variance in standardized heterozygosity (ViSHet) of single nucleotide polymorphism (SNP) genotypes among individuals, calculated across a genomic region (500 SNPs in our case). We apply this method to the greenish warbler ( Phylloscopus trochiloides ) ring species, using a newly assembled reference genome and genotypes at more than 1 million SNPs among 257 individuals. Most chromosomes carry a single distinctive LHBR, containing 4-6 distinct haplotypes that are associated with geography, enabling detection of hybridization events and transition zones between taxa. LHBRs have exceptionally low within-haplotype nucleotide variation and moderately low between-haplotype nucleotide distance, suggesting their establishment through recurrent selective sweeps at varying geographic scales. Meiotic drive is potentially a powerful mechanism of producing such selective sweeps, and the LHBRs are likely to often represent centromeric regions where recombination is restricted. Links between populations enable introgression of favored haplotypes and we identify one haploblock showing a highly discordant distribution compared to the rest of the genome, being present in two distantly separated geographic regions that are at similar latitudes in both east and west Asia. Our results set the stage for detailed studies of haploblocks, including their genomic location, gene content, and contribution to reproductive isolation.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".