Genomic evidence for non-random endemic populations of decaying exons from mammalian genes
Bibliographic record
Abstract
BACKGROUND: Functional diversification of genes in mammalian genomes is engendered by a number of processes, e.g., gene duplication and alternative splicing. Gene duplication is classically discussed as leading to neofunctionalization (generation of new functions), subfunctionalization (generation of a varied function), or pseudogenization (loss of the gene and its function). RESULTS: Here, we focus on the process of pseudogenization, but specifically for individual exons from genes. It is at present unclear to what extent pseudogenization of individual exon duplications affects gene evolution, i.e., is it a random phenomenon, or is it associated with specific types of genes and encoded proteins, and positions in gene structures? We gathered genomic evidence for pseudogenic exons (PsiEs, i.e., exons disabled by frameshifts and premature stop codons), to examine for significant trends in their distribution across four mammalian genomes (specifically human, cow, mouse and rat). Across these four genomes, we observed a consistent population of PsiEs, associated with 0.4-1.0% of genes. These PsiE populations exhibit codon substitution patterns that are typical of an endemic population of decaying sequences. In human, PsiEs have significant over-representation for functional categories related to 'ion binding' and 'nucleic-acid binding', compared to duplicated exons in general. Also, PsiEs tend to be associated with some protein domains that are abundant generally, e.g., Zinc-finger and immunoglobulin protein domains, but not others, e.g., EGF-like domains. Positionally, PsiEs are also significantly associated with the 5' end of genes, but despite this, individual stop codons are positioned so that there is significant avoidance of potential targeting to nonsense-mediated decay. In human, PsiEs are often associated with alternative splicing (in 22 out of 284 genes with PsiEs in their milieu), and can have different parts of their sequence differentially spliced in alternative transcripts. Some unusual cases of PsiEs embedded within 5' and 3' non-coding exons are observed. CONCLUSION: Our results indicate the types of genes that harbour PsiEs, and demonstrate that PsiEs have non-random distribution within gene structures. These PsiEs may function in gene regulation through generation of transcribed pseudogenes, or regulatory alternate transcripts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".