Diversity of human tRNA genes from the 1000-genomes project
Why this work is in the frame
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Bibliographic record
Abstract
The sequence diversity of individual human genomes has been extensively analyzed for variations and phenotypic implications for mRNA, miRNA, and long non-coding RNA genes. TRNA (tRNA) also exhibits large sequence diversity in the human genome, but tRNA gene sequence variation and potential functional implications in individual human genomes have not been investigated. Here we capitalize on the sequencing data from the 1000-genomes project to examine the diversity of tRNA genes in the human population. Previous analysis of the reference human genome indicated an unexpected large number of diverse tRNA genes beyond the necessity of translation, suggesting that some tRNA transcripts may perform non-canonical functions. We found 24 new tRNA sequences in>1% and 76 new tRNA sequences in>0.2% of all individuals, indicating that tRNA genes are also subject to evolutionary changes in the human population. Unexpectedly, two abundant new tRNA genes contain base-pair mismatches in the anticodon stem. We experimentally determined that these two new tRNAs have altered structures in vitro; however, one new tRNA is not aminoacylated but extremely stable in HeLa cells, suggesting that this new tRNA can be used for non-canonical function. Our results show that at the scale of human population, tRNA genes are more diverse than conventionally understood, and some new tRNAs may perform non-canonical, extra-translational functions that may be linked to human health and disease.
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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 it