High nucleotide similarity of three <i>Copia</i> lineage LTR retrotransposons among plant genomes
Bibliographic record
Abstract
Transposable elements (TEs) are mobile elements found in the majority of eukaryotic genomes. TEs deeply impact the structure and evolution of chromosomes and can induce mutations affecting coding genes. In plants, the major group of TEs is long terminal repeat retrotransposons (LTR-RTs). They are classified into superfamilies ( Gypsy, Copia) and subclassified into lineages. Horizontal transfer (HT), defined as the nonsexual transmission of genetic material between species, is a process allowing LTR-RTs to invade a new genome. Although this phenomenon was considered rare, recent studies demonstrate numerous transfers of LTR-RTs. This study aims to determine which LTR-RT lineages are shared with high similarity among 69 plant genomes. We identified and classified 88 450 LTR-RTs and determined 143 cases of high similarities between pairs of genomes. Most of them involved three Copia lineages ( Oryco/ Ivana, Retrofit/ Ale, and Tork/ Tar/ Ikeros). A detailed analysis of three cases of high similarities involving Tork/ Tar/ Ikeros group shows an uneven distribution in the phylogeny of the elements and incongruence with between phylogenetic trees topologies, indicating they could be originated from HTs. Overall, our results suggest that LTR-RT Copia lineages share outstanding similarity between distant species and may likely be involved in HT mechanisms more frequent than initially estimated.
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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 | 0.001 | 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".