Evolutionary plasticity of zoonotic porcine Deltacoronavirus (PDCoV): genetic characteristics and geographic distribution
Bibliographic record
Abstract
Abstract The emergence and rapid spread of the acute respiratory syndrome coronavirus-2 have confirmed that animal coronaviruses represent a potential zoonotic source. Porcine deltacoronavirus is a worldwide evolving enteropathogen of swine, detected first in Hong Kong, China, before its global identification. Following the recent detection of PDCoV in humans, we attempted in this report to re-examine the status of PDCoV phylogenetic classification and evolutionary characteristics. A dataset of 166 complete PDCoV genomes was analyzed using the Maximum Likelihood method in IQ-TREE with the best-fitting model GTR + F + I + G4, revealing two major genogroups (GI and GII), with further seven and two sub-genogroups, (GI a-g) and (GII a-b), respectively. PDCoV strains collected in China exhibited the broadest genetic diversity, distributed in all subgenotypes. Thirty-one potential natural recombination events were identified, 19 of which occurred between China strains, and seven involved at least one China strain as a parental sequence. Importantly, we identified a human Haiti PDCoV strain as recombinant, alarming a possible future spillover that could become a critical threat to human health. The similarity and recombination analysis showed that PDCoV spike ORF is highly variable compared to ORFs encoding other structural proteins. Prediction of linear B cell epitopes of the spike glycoprotein and the 3D structural mapping of amino acid variations of two representative strains of GI and GII showed that the receptor-binding domain (RBD) of spike glycoprotein underwent a significant antigenic drift, suggesting its contribution in the genetic diversity and the wider spread of PDCoV.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".