Whole-Genome Sequencing of Porcine Reproductive and Respiratory Syndrome Virus from Field Clinical Samples Improves the Genomic Surveillance of the Virus
Bibliographic record
Abstract
Porcine reproductive and respiratory syndrome virus (PRRSV) is a major economic concern worldwide. There are currently large data sets available about the ORF5 gene of the virus, with thousands of sequences available, but little data are currently available on the full-length genome of PRRSV. We hypothesized that whole-genome sequencing (WGS) of the PRRSV genome would allow better epidemiological monitoring than ORF5 gene sequencing. PRRSV PCR-positive serum, oral fluid, and tissue clinical samples submitted to the diagnostic laboratory for routine surveillance or diagnosis of PRRSV infection in Québec, Canada, swine herds were used. The PRRSV reverse transcription-quantitative PCR Cq values of the processed samples varied between 11.5 and 34.34. PRRSV strain genomes were isolated using a poly (A)-tail method and were sequenced with a MiSeq Illumina sequencer. Ninety-two full-length PRRSV genomes were obtained from 88 clinical samples out of 132 tested samples, resulting in a PRRSV WGS success rate of 66.67%. Three important deletions in ORF1a were found in most wild-type (i.e., not vaccine-like) strains. The importance of these deletions remains undetermined. Two different full-length PRRSV genomes were found in four different samples (three serum samples and one pool of tissues), suggesting a 4.55% PRRSV strain coinfection prevalence in swine. Moreover, six PRRSV whole genomes (6.52% of PRRSV strains) were found to cluster differently than they did under the ORF5 classification method. Overall, WGS of PRRSV enables better strain classification and/or interpretation of results in 9.10% of clinical samples than ORF5 sequencing, as well as allowing interesting research avenues.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".