Polymorphism Analysis Reveals Reduced Negative Selection and Elevated Rate of Insertions and Deletions in Intrinsically Disordered Protein Regions
Bibliographic record
Abstract
Intrinsically disordered protein regions are abundant in eukaryotic proteins and lack stable tertiary structures and enzymatic functions. Previous studies of disordered region evolution based on interspecific alignments have revealed an increased propensity for indels and rapid rates of amino acid substitution. How disordered regions are maintained at high abundance in the proteome and across taxa, despite apparently weak evolutionary constraints, remains unclear. Here, we use single nucleotide and indel polymorphism data in yeast and human populations to survey the population variation within disordered regions. First, we show that single nucleotide polymorphisms in disordered regions are under weaker negative selection compared with more structured protein regions and have a higher proportion of neutral non-synonymous sites. We also confirm previous findings that nonframeshifting indels are much more abundant in disordered regions relative to structured regions. We find that the rate of nonframeshifting indel polymorphism in intrinsically disordered regions resembles that of noncoding DNA and pseudogenes, and that large indels segregate in disordered regions in the human population. Our survey of polymorphism confirms patterns of evolution in disordered regions inferred based on longer evolutionary comparisons.
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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".