Comparative genomic analysis of the family Iridoviridae: re-annotating and defining the core set of iridovirus genes
Bibliographic record
Abstract
BACKGROUND: Members of the family Iridoviridae can cause severe diseases resulting in significant economic and environmental losses. Very little is known about how iridoviruses cause disease in their host. In the present study, we describe the re-analysis of the Iridoviridae family of complex DNA viruses using a variety of comparative genomic tools to yield a greater consensus among the annotated sequences of its members. RESULTS: A series of genomic sequence comparisons were made among, and between the Ranavirus and Megalocytivirus genera in order to identify novel conserved ORFs. Of these two genera, the Megalocytivirus genomes required the greatest number of altered annotations. Prior to our re-analysis, the Megalocytivirus species orange-spotted grouper iridovirus and rock bream iridovirus shared 99% sequence identity, but only 82 out of 118 potential ORFs were annotated; in contrast, we predict that these species share an identical complement of genes. These annotation changes allowed the redefinition of the group of core genes shared by all iridoviruses. Seven new core genes were identified, bringing the total number to 26. CONCLUSION: Our re-analysis of genomes within the Iridoviridae family provides a unifying framework to understand the biology of these viruses. Further re-defining the core set of iridovirus genes will continue to lead us to a better understanding of the phylogenetic relationships between individual iridoviruses as well as giving us a much deeper understanding of iridovirus replication. In addition, this analysis will provide a better framework for characterizing and annotating currently unclassified iridoviruses.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".