Genomic Motifs as a Novel Indicator of the Relationship between Strains Isolated from the Epidemic of Porcine Epidemic Diarrhea in 2013-2014
Bibliographic record
Abstract
Porcine epidemic diarrhea virus (PEDV) is a positive-sense RNA virus that causes infectious gastroenteritis in pigs. Following a PED outbreak that occurred in China in 2010, the disease was identified for the first time in the United States in April 2013, and was reported in many other countries worldwide from 2013 to 2014. As a novel approach to elucidate the epidemiological relationship between PEDV strains, we explored their genome sequences to identify the motifs that were shared within related strains. Of PED outbreaks reported in many countries during 2013-2014, 119 PEDV strains in Japan, USA, Canada, Mexico, Germany, and Korea were selected and used in this study. We developed a motif mining program, which aimed to identify a specific region of the genome that was exclusively shared by a group of PEDV strains. Eight motifs were identified (M1-M8) and they were observed in 41, 9, 18, 6, 10, 14, 2, and 2 strains, respectively. Motifs M1-M6 were shared by strains from more than two countries, and seemed to originate from one PEDV strain, Indiana12.83/USA/2013, among the 119 strains studied. BLAST search for motifs M1-M6 revealed that M3-M5 were almost identical to the strain ZMDZY identified in 2011 in China, while M1 and M2 were similar to other Chinese strains isolated in 2011-2012. Consequently, the PED outbreaks in these six countries may be closely related, and multiple transmissions of PEDV strains between these countries may have occurred during 2013-2014. Although tools such as phylogenetic tree analysis with whole genome sequences are increasingly applied to reveal the connection between isolates, its interpretation is sometimes inconclusive. Application of motifs as a tool to examine the whole genome sequences of causative agents will be more objective and will be an explicit indicator of their relationship.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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".