Complete Genome Sequencing and Comparative Phylogenomics of Nine African Swine Fever Virus (ASFV) Isolates of the Virulent East African p72 Genotype IX without Viral Sequence Enrichment
Bibliographic record
Abstract
). While Sub-Saharan Africa is believed to be the original home of ASFV, publicly available whole-genome ASFV sequences show a strong bias towards p72 Genotypes I and II, which are responsible for domestic pig pandemics outside Africa. To reduce this bias, we hereby describe nine novel East African complete genomes in p72 Genotype IX and present the phylogenetic analysis of all 16 available Genotype IX genomes compared with other ASFV p72 clades. We also document genome-level differences between one specific novel Genotype IX genome sequence (KE/2013/Busia.3) and a wild boar cell-passaged derivative. The Genotype IX genomes clustered with the five available Genotype X genomes. By contrast, Genotype IX and X genomes were strongly phylogenetically differentiated from all other ASFV genomes. The p72 gene region, on which the p72-based virus detection primers are derived, contains consistent SNPs in Genotype IX, potentially resulting in reduced sensitivity of detection. In addition to the abovementioned cell-adapted variant, eight novel ASFV Genotype IX genomes were determined: five from viruses passaged once in primary porcine peripheral blood monocytes and three generated from DNA isolated directly from field-sampled kidney tissues. Based on this methodological simplification, genome sequencing of ASFV field isolates should become increasingly routine and result in a rapid expansion of knowledge pertaining to the diversity of African ASFV at the whole-genome level.
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 | 0.001 |
| 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".