Evolutionary dynamics and molecular epidemiology of West Nile virus in New York State: 1999–2015
Bibliographic record
Abstract
) underwent a rapid expansion throughout the USA and into Canada and Latin America. WNV has been characterized as being evolutionarily stable, with weak geographic structure, a dominance of purifying selection and limited adaptive change. We analyzed all available full-genome WNV sequences, focusing on the 543 available sequences from NYS, which included 495 newly sequenced 2000-15 isolates. In addition, we analyzed deep-sequencing data from 317 of these isolates. While our data are generally in agreement with the limited pace of evolutionary change and broad geographic and temporal mixing identified in other studies, we have identified some important exceptions. Most notably, there are 14 codons which demonstrated evidence of positive selection as determined by multiple models, including some positions with evidence of selection in NYS exclusively. Coincident with increased WNV activity, genotypes possessing one or more of these mutations, designated NY01, NY07, and NY10, have increased in prevalence in recent years and displaced historic strains. In addition, we have found a geographical bias with many of these mutations, which suggests selective pressures and adaptations could be regional. Lastly, our deep-sequencing data suggest both increased overall diversity in avian tissue isolates relative to mosquito isolates and multiple non-synonymous minority variants that are both host-specific and retained over time and space. Together, these data provide novel insight into the evolutionary pressures on WNV and the need for continued genetic surveillance and characterization of emergent strains.
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 | 0.000 |
| 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) | 0.001 | 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".