Detection of long terminal repeat loci derived from endogenous retrovirus in junglefowl using whole-genome sequencing
Bibliographic record
Abstract
Endogenous retroviruses (ERVs) are genetic elements present in the genome that retain traces of past viral infections. Characterization of ERVs can provide crucial insights into avian evolution. This study aimed to identify novel long terminal repeat (LTR) loci derived from ERVs (ERV-LTRs) absent in the reference genome using whole-genome sequencing data of red junglefowl, gray junglefowl, Ceylon junglefowl, and green junglefowl. In total, 835 ERV-LTR loci were identified across the four Gallus species. The numbers of ERV-LTRs loci detected in red junglefowl and its subspecies gray junglefowl, Ceylon junglefowl, and green junglefowl were 362, 216, 193, and 128, respectively. The phylogenetic tree was congruent with previously reported trees, suggesting the potential for inferring relationships among past junglefowl populations from the identified ERV-LTR loci. Of the detected loci, 306 ERV-LTRs were identified near or within the genes, and some were associated with cell adhesion. The detected ERV-LTR sequences were classified as endogenous avian retrovirus family, avian leukosis virus subgroup E, Ovex-1, and murine leukemia virus-related ERVs. In addition, the sequence of the EAV family was divided into four patterns by combining the U3, R, and U5 regions. These findings contribute to a more comprehensive understanding of the characteristics of junglefowl ERVs.
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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 | 0.000 |
| 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) | 0.000 | 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".