Signatures of mitonuclear coevolution in a warbler species complex
Bibliographic record
Abstract
Abstract Mitochondrial (mtDNA) and nuclear (nDNA) genes interact to govern metabolic pathways of mitochondria. When differentiated populations interbreed at secondary contact, incompatibilities between mtDNA of one population and nDNA of the other could result in low fitness of hybrids. In northwestern North America, two hybridizing species of warblers, Setophaga occidentalis (abbreviated as SOCC) and S. townsendi (STOW), provide an excellent system to investigate the potential co-adaptation of mitochondrial and nuclear DNA. The inland population of STOW (inland STOW) harbors mtDNA haplotype that is half a million years divergent from the SOCC mtDNA, and these populations also differ strongly in a few nDNA regions. Coastal populations of STOW (coastal STOW) have mixed ancestry, consistent with ancient hybridization of SOCC and inland STOW-like population. Of the few highly-differentiated nDNA regions between inland STOW and SOCC, one of these regions (on chromosome 5) is also differentiated between coastal STOW and inland STOW, and covaries with mtDNA among coastal STOW populations. Genes in this 1.2Mb region of chromosome 5 are associated with fatty acid oxidation and energy-related signaling transduction, both of which are closely associated with mitochondrial function. This chromosome 5 region is correlated with mtDNA haplotypes both within and across sampling sites, a pattern consistent with mitonuclear co-adaptation. We show that such mitonuclear coevolution might be maintained by climate-related selection, because mitonuclear ancestry is correlated with climatic conditions among sampling sites. Together, our observation suggests climatic-associated adaptation shaping mitonuclear differentiation and introgression in this species complex.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".