Development of a Novel Mule Deer Genomic Assembly and Species-Diagnostic SNP Panel for Assessing Introgression in Mule Deer, White-Tailed Deer, and Their Interspecific Hybrids
Bibliographic record
Abstract
Abstract Mule deer (Odocoileus hemionus) are endemic to a wide variety of habitats in western North America, many of which are shared in sympatry with their closely related sister-species white-tailed deer (Odocoileus virginianus), whom they hybridize with in wild populations. Although mule deer meet many ideal conditions for a molecular ecological research species, such as high abundance, ecological importance, and broad dispersal and gene flow, conservation genetic studies have been limited by a relative lack of existing genomic resources and inherent difficulties caused by introgression with white-tailed deer. Many molecular tools currently available for the study of cervids were designed using reference assemblies of divergent model species, specifically cattle (Bos taurus). Bovidae and Cervidae diverged approximately 28 million years ago, therefore, we sought to ameliorate the available resources by contributing the first mule deer whole genome sequence draft assembly with an average genome-wide read depth of 25X, using the white-tailed genome assembly (Ovir.te_1.0) as a reference. Comparing the two assemblies, we identified ∼33 million single nucleotide polymorphisms (SNPs) and insertion/deletion variants. We then verified fixed SNP differences between the two species and developed a 40-loci SNP assay capable of identifying pure mule deer, white-tailed deer, and interspecific hybrids. Assignment capacity of the panel, which was tested on simulated datasets, is reliable up to and including the third backcross hybrid generation. Identification of post-F1 hybrids will be necessary for hybrid zone population studies going forward, and the new mule deer assembly will be a valuable resource for genetic and comparative genomics studies.
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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".