Alternative start codon selection shapes mitochondrial function and rare human diseases
Bibliographic record
Abstract
Rare genetic diseases collectively affect millions of individuals. A common target of many rare diseases is the mitochondria, intracellular organelles that originated through endosymbiosis. Eukaryotic cells require related proteins to function both within the mitochondria and in the host cell. By analyzing N-terminal protein isoforms generated through alternative start codon selection, we identify hundreds of differentially localized isoform pairs, including dual-localized isoforms that are essential for both mitochondrial and host cell function. Subsets of dual mitochondria-localized isoforms emerged during early eukaryotic evolution, coinciding with mitochondrial endosymbiosis. Importantly, we identify dozens of rare disease alleles that affect these alternative protein variants with unique molecular and clinical consequences. Alternative start codon selection can bypass pathogenic nonsense and frameshift mutations, thereby selectively eliminating specific isoforms, which we term isoform-selective alleles (ISAs). Together, our findings illuminate the evolutionary and pathological relevance of alternative translation, offering insights into the molecular basis of rare human diseases. • Alternate N-terminal isoforms diversify the mitochondrial proteome and its function • N-terminal masking regulates the localization of alternative N-terminal isoforms • TRNT1 alternative start codons coincide with mitochondrial endosymbiosis • Alternative N-terminal “isoform-selective alleles” shape rare human diseases Ly et al. demonstrate that alternative start codon selection generates distinct N-terminal isoforms from a single mRNA, influencing mitochondrial function, evolution, and rare diseases. They uncover mechanisms controlling alternative N-terminal isoform localization and show that disease alleles can selectively disrupt specific isoforms, terming these mutations as “isoform-selective alleles.”
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".