A Histone Methyltransferase ESET Is Critical for T Cell Development
Bibliographic record
Abstract
ESET/SETDB1, one of the major histone methyltransferases, catalyzes histone 3 lysine 9 (H3K9) trimethylation. ESET is critical for suppressing expression of retroviral elements in embryonic stem cells; however, its role in the immune system is not known. We found that thymocyte-specific deletion of ESET caused impaired T cell development, with CD8 lineage cells being most severely affected. Increased apoptosis of CD8 single-positive cells was observed, and TCR-induced ERK activation was severely inhibited in ESET(-/-) thymocytes. Genome-wide comprehensive analysis of mRNA expression and H3K9 trimethylation revealed that ESET regulates expression of numerous genes in thymocytes. Among them, FcγRIIB, whose signaling can inhibit ERK activation, was strongly and ectopically expressed in ESET(-/-) thymocytes. Indeed, genetic depletion of FcγRIIB in ESET(-/-) thymocytes rescued impaired ERK activation and partially restored defective positive selection in ESET(-/-) mice. Therefore, impaired T cell development in ESET(-/-) mice is partly due to the aberrant expression of FcγRIIB. Collectively, to our knowledge, we identify ESET as the first trimethylated H3K9 histone methyltransferase playing a crucial role in T cell development.
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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 | 0.000 | 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) | 0.002 | 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".