Human SNPs resulting in premature stop codons and protein truncation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Single nucleotide polymorphisms (SNPs) constitute the most common type of genetic variation in humans. SNPs introducing premature termination codons (PTCs), herein called X-SNPs, can alter the stability and function of transcripts and proteins and thus are considered to be biologically important. Initial studies suggested a strong selection against such variations/mutations. In this study, we undertook a genome-wide systematic screening to identify human X-SNPs using the dbSNP database. Our results demonstrated the presence of 28 X-SNPs from 28 genes with known minor allele frequencies. Eight X-SNPs (28.6 per cent) were predicted to cause transcript degradation by nonsense-mediated mRNA decay. Seventeen X-SNPs (60.7 per cent) resulted in moderate to severe truncation at the C-terminus of the proteins (deletion of >50 per cent of the amino acids). The majority of the X-SNPs (78.6 per cent) represent commonly occurring SNPs, by contrast with the rarely occurring disease-causing PTC mutations. Interestingly, X-SNPs displayed a non-uniform distribution across human populations: eight X-SNPs were reported to be prevalent across three different human populations, whereas six X-SNPs were found exclusively in one or two population(s). In conclusion, we have systematically investigated human SNPs introducing PTCs with respect to their possible biological consequences, distributions across different human populations and evolutionary aspects. We believe that the SNPs reported here are likely to affect gene/protein function, although their biological and evolutionary roles need to be further investigated.
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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