Restriction Enzyme Based Enriched L1Hs Sequencing (REBELseq): A Scalable Technique for Detection of Ta Subfamily L1Hs in the Human Genome
Bibliographic record
Abstract
Long interspersed element-1 retrotransposons (LINE-1 or L1) are ∼6 kb mobile DNA elements implicated in the origins of many Mendelian and complex diseases. The actively retrotransposing L1s are mostly limited to the L1 human specific (L1Hs) transcriptional active (Ta) subfamily. In this manuscript, we present REBELseq as a method for the construction of Ta subfamily L1Hs-enriched next-generation sequencing libraries and bioinformatic identification. REBELseq was performed on DNA isolated from NeuN+ neuronal nuclei from postmortem brain samples of 177 individuals and empirically-driven bioinformatic and experimental cutoffs were established. Putative L1Hs insertions passing bioinformatics cutoffs were experimentally validated. REBELseq reliably identified both known and novel Ta subfamily L1Hs insertions distributed throughout the genome. Differences in the proportion of individuals possessing a given reference or non-reference retrotransposon insertion were identified. We conclude that REBELseq is an unbiased, whole genome approach to the amplification and detection of Ta subfamily L1Hs retrotransposons.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".