<i>De Novo</i>Genome and Transcriptome Assembly of the Canadian Beaver (<i>Castor canadensis</i>)
Bibliographic record
Abstract
) is the largest indigenous rodent in North America. We report a draft annotated assembly of the beaver genome, the first for a large rodent and the first mammalian genome assembled directly from uncorrected and moderate coverage (< 30 ×) long reads generated by single-molecule sequencing. The genome size is 2.7 Gb estimated by k-mer analysis. We assembled the beaver genome using the new Canu assembler optimized for noisy reads. The resulting assembly was refined using Pilon supported by short reads (80 ×) and checked for accuracy by congruency against an independent short read assembly. We scaffolded the assembly using the exon-gene models derived from 9805 full-length open reading frames (FL-ORFs) constructed from the beaver leukocyte and muscle transcriptomes. The final assembly comprised 22,515 contigs with an N50 of 278,680 bp and an N50-scaffold of 317,558 bp. Maximum contig and scaffold lengths were 3.3 and 4.2 Mb, respectively, with a combined scaffold length representing 92% of the estimated genome size. The completeness and accuracy of the scaffold assembly was demonstrated by the precise exon placement for 91.1% of the 9805 assembled FL-ORFs and 83.1% of the BUSCO (Benchmarking Universal Single-Copy Orthologs) gene set used to assess the quality of genome assemblies. Well-represented were genes involved in dentition and enamel deposition, defining characteristics of rodents with which the beaver is well-endowed. The study provides insights for genome assembly and an important genomics resource for Castoridae and rodent evolutionary biology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".