A phylogenetic approach uncovers cryptic endogenous retrovirus subfamilies in the primate lineage
Bibliographic record
Abstract
Current approaches for classifying and annotating endogenous retroviruses (ERVs) and their long terminal repeats (LTRs) have limited resolution and are inaccurate. Here, we developed an annotation approach based on phylogenetic analysis and cross-species conservation. Focusing on the evolutionarily young LTR subfamilies known as MER11A/B/C, we revealed the presence of four "new subfamilies," suggesting a new annotation for 412 (19.8%) of these repeat elements. We then validated their regulatory potential using a massively parallel reporter assay. We further identified motifs associated with their differential activities including an ape-specific gain of SOX-related motifs through a single-nucleotide deletion. By applying our approach across 53 simian-enriched LTR subfamilies, we defined 75 new subfamilies and found a novel annotation for a total of 3807 (30.0%) instances from 26 subfamilies. With this refined annotation of simian-enriched LTRs, it will be possible to better understand the evolution in primate genomes and potentially identify critical roles for ERVs and their LTRs in the hosts.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".