Gene Properties and Chromatin State Influence the Accumulation of Transposable Elements in Genes
Bibliographic record
Abstract
Transposable elements (TEs) are mobile DNA sequences found in the genomes of almost all species. By measuring the normalized coverage of TE sequences within genes, we identified sets of genes with conserved extremes of high/low TE density in the genomes of human, mouse and cow and denoted them as 'shared upper/lower outliers (SUOs/SLOs)'. By comparing these outlier genes to the genomic background, we show that a large proportion of SUOs are involved in metabolic pathways and tend to be mammal-specific, whereas many SLOs are related to developmental processes and have more ancient origins. Furthermore, the proportions of different types of TEs within human and mouse orthologous SUOs showed high similarity, even though most detectable TEs in these two genomes inserted after their divergence. Interestingly, our computational analysis of polymerase-II (Pol-II) occupancy at gene promoters in different mouse tissues showed that 60% of tissue-specific SUOs show strong Pol-II binding only in embryonic stem cells (ESCs), a proportion significantly higher than the genomic background (37%). In addition, our analysis of histone marks such as H3K4me3 and H3K27me3 in mouse ESCs also suggest a strong association between TE-rich genes and open-chromatin at promoters. Finally, two independent whole-transcriptome datasets show a positive association between TE density and gene expression level in ESCs. While this study focuses on genes with extreme TE densities, the above results clearly show that the probability of TE accumulation/fixation in mammalian genes is not random and is likely associated with different factors/gene properties and, most importantly, an association between the TE insertion/fixation rate and gene activity status in ES cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".