Signatures of selection in mammalian clock genes with coding trinucleotide repeats: Implications for studying the genomics of high‐pace adaptation
Bibliographic record
Abstract
Abstract Climate change is predicted to affect the reproductive ecology of wildlife; however, we have yet to understand if and how species can adapt to the rapid pace of change. Clock genes are functional genes likely critical for adaptation to shifting seasonal conditions through shifts in timing cues. Many of these genes contain coding trinucleotide repeats, which offer the potential for higher rates of change than single nucleotide polymorphisms (SNPs) at coding sites, and, thus, may translate to faster rates of adaptation in changing environments. We characterized repeats in 22 clock genes across all annotated mammal species and evaluated the potential for selection on repeat motifs in three clock genes (NR1D1, CLOCK, and PER1) in three congeneric species pairs with different latitudinal range limits: Canada lynx and bobcat (Lynx canadensis and L. rufus), northern and southern flying squirrels (Glaucomys sabrinus and G. volans), and white‐footed and deer mouse (Peromyscus leucopus and P. maniculatus). Signatures of positive selection were found in both the interspecific comparison of Canada lynx and bobcat, and intraspecific analyses in Canada lynx. Northern and southern flying squirrels showed differing frequencies at common CLOCK alleles and a signature of balancing selection. Regional excess homozygosity was found in the deer mouse at PER1 suggesting disruptive selection, and further analyses suggested balancing selection in the white‐footed mouse. These preliminary signatures of selection and the presence of trinucleotide repeats within many clock genes warrant further consideration of the importance of candidate gene motifs for adaptation to climate change.
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 | 0.000 | 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".