Haplotype-resolved de novo assembly of the Vero cell line genome
Bibliographic record
Abstract
The Vero cell line is the most used continuous cell line for viral vaccine manufacturing with more than 40 years of accumulated experience in the vaccine industry. Additionally, the Vero cell line has shown a high affinity for infection by MERS-CoV, SARS-CoV, and recently SARS-CoV-2, emerging as an important discovery and screening tool to support the global research and development efforts in this COVID-19 pandemic. However, the lack of a reference genome for the Vero cell line has limited our understanding of host-virus interactions underlying such affinity of the Vero cell towards key emerging pathogens, and more importantly our ability to redesign high-yield vaccine production processes using Vero genome editing. In this paper, we present an annotated highly contiguous 2.9 Gb assembly of the Vero cell genome. In addition, several viral genome insertions, including Adeno-associated virus serotypes 3, 4, 7, and 8, have been identified, giving valuable insights into quality control considerations for cell-based vaccine production systems. Variant calling revealed that, in addition to interferon, chemokines, and caspases-related genes lost their functions. Surprisingly, the ACE2 gene, which was previously identified as the host cell entry receptor for SARS-CoV and SARS-CoV-2, also lost function in the Vero genome due to structural variations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".