Genome-wide methylation patterns from canine nanopore assemblies
Bibliographic record
Abstract
Recent advances in long-read sequencing have enabled the creation of reference-quality genome assemblies for multiple individuals within a species. In particular, 8 long-read genome assemblies have recently been published for the canine model (dogs and wolves). These assemblies were created using a range of sequencing and computational approaches, with only limited comparisons described among subsets of the assemblies. Here we present 3 high-quality de novo reference assemblies based upon Oxford Nanopore long-read sequencing: 2 Bernese Mountain Dogs (BD & OD) and a Cairn terrier (CA611). These breeds are of particular interest due to the enrichment of unresolved genetic disorders. Leveraging advancement in software technologies, we utilized published data of Labrador Retriever (Yella) to generate a new assembly, resulting in a ∼280-fold increase in continuity (N50 size of 91 kbp vs 25.75 Mbp). In conjunction with these 4 new assemblies, we uniformly assessed 8 existing assemblies for generalized quality metrics, sequence divergence, and a detailed BUSCO assessment. We identified a set of ∼400 conserved genes during the BUSCO analysis missing in all assemblies. Genome-wide methylation profiles were generated from the nanopore sequencing, resulting in broad concordance with existing whole-genome and reduced-representation bisulfite sequencing, while highlighting superior overage of mobile elements. These analyses demonstrate the ability of Nanopore sequencing to resolve the sequence and epigenetic profile of canine genomes.
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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 | 0.001 |
| 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".