Transposable Elements Are a Significant Contributor to Tandem Repeats in the Human Genome
Bibliographic record
Abstract
Sequence repeats are an important phenomenon in the human genome, playing important roles in genomic alteration often with phenotypic consequences. The two major types of repeat elements in the human genome are tandem repeats (TRs) including microsatellites, minisatellites, and satellites and transposable elements (TEs). So far, very little has been known about the relationship between these two types of repeats. In this study, we identified TRs that are derived from TEs either based on sequence similarity or overlapping genomic positions. We then analyzed the distribution of these TRs among TE families/subfamilies. Our study shows that at least 7,276 TRs or 23% of all minisatellites/satellites is derived from TEs, contributing ∼0.32% of the human genome. TRs seem to be generated more likely from younger/more active TEs, and once initiated they are expanded with time via local duplication of the repeat units. The currently postulated mechanisms for origin of TRs can explain only 6% of all TE-derived TRs, indicating the presence of one or more yet to be identified mechanisms for the initiation of such repeats. Our result suggests that TEs are contributing to genome expansion and alteration not only by transposition but also by generating tandem repeats.
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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) | 0.003 | 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".