Candidate adaptive genes associated with lineage divergence: identifying <scp>SNP</scp>s via next‐generation targeted resequencing in mule deer (<i>Odocoileus hemionus</i>)
Bibliographic record
Abstract
Mule deer (Odocoileus hemionus) are an excellent nonmodel species for empirically testing hypotheses in landscape and population genomics due to their large population sizes (low genetic drift), relatively continuous distribution, diversity of occupied habitats and phenotypic variation. Because few genomic resources are currently available for this species, we used exon data from a cattle (Bos taurus) reference genome to direct targeted resequencing of 5935 genes in mule deer. We sequenced approximately 3.75 Mbp at minimum 20X coverage in each of the seven mule deer, identifying 23 204 single nucleotide polymorphisms (SNPs) within, or adjacent to, 6886 exons in 3559 genes. We found 91 SNP loci (from 69 genes) with putatively fixed allele frequency differences between the two major lineages of mule deer (mule deer and black-tailed deer), and our estimate of mean genetic divergence (genome-wide FST = 0.123) between these lineages was consistent with previous findings using microsatellite loci. We detected an over-representation of gamete generation and amino acid transport genes among the genes with SNPs exhibiting potentially fixed allele frequency differences between lineages. This targeted resequencing approach using exon capture techniques has identified a suite of loci that can be used in future research to investigate the genomic basis of adaptation and differentiation between black-tailed deer and mule deer. This study also highlights techniques (and an exon capture array) that will facilitate population genomic research in other cervids and nonmodel organisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".