eLife Assessment: Transposable elements regulate thymus development and function
Bibliographic record
Abstract
Transposable elements (TE) are repetitive sequences representing ∼45% of the human and mouse genomes and are highly expressed by medullary thymic epithelial cells (mTEC). In this study, we investigated the role of transposable elements (TE), which are highly expressed by medullary thymic epithelial cells (mTEC), on T-cell development in the thymus. We performed multi-omic analyses of TEs in human and mouse thymic cells to elucidate their role in T cell development. We report that TE expression in the human thymus is high and shows extensive age- and cell lineage-related variations. TEs interact with multiple transcription factors in all cell types of the human thymus. Two cell types express particularly broad TE repertoires: mTECs and plasmacytoid dendritic cells (pDC). In mTECs, TEs interact with transcription factors essential for mTEC development and function (e.g., PAX1 and RELB) and generate MHC-I-associated peptides implicated in thymocyte education. Notably, AIRE, FEZF2, and CHD4 regulate non-redundant sets of TEs in murine mTECs. Human thymic pDCs homogenously express large numbers of TEs that lead to the formation of dsRNA, triggering RIG-I and MDA5 signaling and explaining why thymic pDCs constitutively secrete IFN ɑ/β. This study illustrates the diversity of interactions between TEs and the adaptive immune system. TEs are genetic parasites, and the two thymic cell types most affected by TEs (mTEcs and pDCs) are essential to establishing central T-cell tolerance. Therefore, we propose that the orchestration of TE expression in thymic cells is critical to prevent autoimmunity in vertebrates.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.014 |
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".