Next-generation sequencing approach to investigate genome variability of Parapoxvirus in Canadian muskoxen (Ovibos moschatus)
Bibliographic record
Abstract
In 2016, the first orf virus, a double-stranded DNA (dsDNA) virus of the genus parapoxvirus, from a muskox was isolated on Victoria Island, Nunavut (NU), Canada. We used deep sequencing on DNA extracted from orf virus-positive tissues from wild muskoxen from locations on Victoria Island and the adjacent mainland. Orf virus sequence reads derived from four samples were nearly identical. The consensus sequences generated from pooled reads of MxOV comprises of a large contiguous sequence (contig) of 131,759 bp and a smaller right terminal contig of 3552 bp, containing all coding sequences identified as Parapoxvirus. Individual gene comparisons reveal that MxOV shares genetic characteristics with reference strains from both sheep and goat origin. Recombination analysis using Bootscan, MAXCHI, GENECONV, CHIMAERA, SISCAN, and RDP algorithms within the RDP4 software predicted recombination events in two virulence factors, and a large 3000 bp segment of the MxOV genome. Partial B2L nucleotide sequences from strains around the world and other North American isolates were compared to MxOV using MUSCLE alignments and RAxML phylogenetic trees. MxOV was identical to our previously characterized isolate, and shared similarity with orf virus isolated from sheep and goats. The phylogenetic grouping of partial B2L nucleotide sequences did not follow the sample geographic distribution. More full genomes of orf virus, or at least full B2L gene squences, in wildlife are needed especially in North America to better understand the epidemiology of the disease in muskoxen.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".