One hundred million years history of bornavirus infections hidden in vertebrate genomes
Bibliographic record
Abstract
Abstract Although viruses have threatened our ancestors for millions of years, prehistoric epidemics of viruses are largely unknown. Endogenous bornavirus-like elements (EBLs) are ancient viral sequences that have been integrated into animal genomes. These elements can be used as molecular fossil records to trace past bornaviral infections. In this study, we systematically identified EBLs in vertebrate genomes and revealed the history of bornavirus infections over nearly 100 million years. We found that ancient bornaviral infections have occurred in diverse vertebrate lineages, especially in primate ancestors. Phylogenetic analyses indicated that primate ancestors had been infected with various bornaviral lineages during evolution. Moreover, EBLs in primate genomes formed clades according to their integration ages, suggesting that epidemic lineages of bornaviruses had changed chronologically. However, we found that some bornaviral lineages coexisted with primate ancestors and underwent repeated endogenizations for tens of millions of years. Furthermore, this viral lineage that coexisted with primate ancestors was also endogenized in some ancestral bats. Notably, the geographic distributions of these bat ancestors have been reported to overlap with the migration route of primate ancestors, suggesting that long-term virus-host coexistence could have expanded the geographic distributions of the viral lineage and might have spread their infections to new hosts. Thus, our findings describe hidden virus-host co-evolutionary history over geological timescales, including chronological change in epidemic bornaviral lineages, long-term virus-host coexistence, and expansion of viral infections.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".