Tissue-specific expression of histone H3 variants diversified after species separation
Bibliographic record
Abstract
BACKGROUND: The selective incorporation of appropriate histone variants into chromatin is critical for the regulation of genome function. Although many histone variants have been identified, a complete list has not been compiled. RESULTS: We screened mouse, rat and human genomes by in silico hybridization using canonical histone sequences. In the mouse genome, we identified 14 uncharacterized H3 genes, among which 13 are similar to H3.3 and do not have human or rat counterparts, and one is similar to human testis-specific H3 variant, H3T/H3.4, and had a rat paralog. Although some of these genes were previously annotated as pseudogenes, their tissue-specific expression was confirmed by sequencing the 3'-UTR regions of the transcripts. Certain new variants were also detected at the protein level by mass spectrometry. When expressed as GFP-tagged versions in mouse C2C12 cells, some variants were stably incorporated into chromatin and the genome-wide distributions of most variants were similar to that of H3.3. Moreover, forced expression of H3 variants in chromatin resulted in alternate gene expression patterns after cell differentiation. CONCLUSIONS: We comprehensively identified and characterized novel mouse H3 variant genes that encoded highly conserved amino acid sequences compared to known histone H3. We speculated that the diversity of H3 variants acquired after species separation played a role in regulating tissue-specific gene expression in individual species. Their biological relevance and evolutionary aspect involving pseudogene diversification will be addressed by further functional analysis.
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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) | 0.001 | 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 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".