Horizontal transfer of a retrotransposon between parasitic nematodes and the common shrew
Bibliographic record
Abstract
As the genomes of more metazoan species are sequenced, reports of horizontal transposon transfers (HTT) have increased. Our understanding of the mechanisms of such events is at an early stage. The close physical relationship between a parasite and its host could facilitate horizontal transfer. To date, two studies have identified horizontal transfer of RTEs, a class of retrotransposable elements, involving parasites: ticks might act as vector for BovB between ruminants and squamates, and AviRTE was transferred between birds and parasitic nematodes. We searched for RTEs shared between nematode and mammalian genomes. Given their physical proximity, it was necessary to detect and remove sequence contamination from the genome datasets, which would otherwise distort the signal of horizontal transfer. We developed an approach that is based on reads instead of genomic sequences to reliably detect contamination. From comparison of 43 RTEs across 197 genomes, we identified a single putative case of horizontal transfer: we detected RTE1_Sar from Sorex araneus , the common shrew, in parasitic nematodes. From the taxonomic distribution and evolutionary analysis, we show that RTE1_Sar was horizontally transferred. We identified a new horizontal RTE transfer in host-parasite interactions, which suggests that it is not uncommon. Further, we present and provide the workflow a read-based method to distinguish between contamination and horizontal transfer.
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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".