A SNP resource for studying North American moose
Bibliographic record
Abstract
<ns4:p> <ns4:bold>Background</ns4:bold> : Moose ( <ns4:italic>Alces alces</ns4:italic> ) colonized the North American continent from Asia less than 15,000 years ago, and spread across the boreal forest regions of Canada and the northern United States (US). Contemporary populations have low genetic diversity, due either to low number of individuals in the original migration (founder effect), and/or subsequent population bottlenecks in North America. Genetic tests based on informative single nucleotide polymorphism (SNP) markers are helpful in forensic and wildlife conservation activities, but have been difficult to develop for moose, due to the lack of a reference genome assembly and whole genome sequence (WGS) data. </ns4:p> <ns4:p> <ns4:bold>Methods</ns4:bold> : WGS data were generated for four individual moose from the US states of Alaska, Idaho, Wyoming, and Vermont with minimum and average genome coverage depths of 14- and 19-fold, respectively. Cattle and sheep reference genomes were used for aligning sequence reads and identifying moose SNPs. </ns4:p> <ns4:p> <ns4:bold>Results</ns4:bold> : Approximately 11% and 9% of moose WGS reads aligned to cattle and sheep genomes, respectively. The reads clustered at genomic segments, where sequence identity between these species was greater than 95%. In these segments, average mapped read depth was approximately 19-fold. Sets of 46,005 and 36,934 high-confidence SNPs were identified from cattle and sheep comparisons, respectively, with 773 and 552 of those having minor allele frequency of 0.5 and conserved flanking sequences in all three species. Among the four moose, heterozygosity and allele sharing of SNP genotypes were consistent with decreasing levels of moose genetic diversity from west to east. A minimum set of 317 SNPs, informative across all four moose, was selected as a resource for future SNP assay design. </ns4:p> <ns4:p> <ns4:bold>Conclusions</ns4:bold> : All SNPs and associated information are available, without restriction, to support development of SNP-based tests for animal identification, parentage determination, and estimating relatedness in North American moose. </ns4:p>
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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 | 0.001 | 0.002 |
| 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".