Repeated Recruitment of LTR Retrotransposons as Promoters by the Anti-Apoptotic Locus NAIP during Mammalian Evolution
Bibliographic record
Abstract
Neuronal apoptosis inhibitory protein (NAIP, also known as BIRC1) is a member of the conserved inhibitor of apoptosis protein (IAP) family. Lineage-specific rearrangements and expansions of this locus have yielded different copy numbers among primates and rodents, with human retaining a single functional copy and mouse possessing several copies, depending on the strain. Roles for this gene in disease have been documented, but little is known about transcriptional regulation of NAIP. We show here that NAIP has multiple promoters sharing no similarity between human and rodents. Moreover, we demonstrate that multiple, domesticated long terminal repeats (LTRs) of endogenous retroviral elements provide NAIP promoter function in human, mouse, and rat. In human, an LTR serves as a tissue-specific promoter, active primarily in testis. However, in rodents, our evidence indicates that an ancestral LTR common to all rodent genes is the major, constitutive promoter for these genes, and that a second LTR found in two of the mouse genes is a minor promoter. Thus, independently acquired LTRs have assumed regulatory roles for orthologous genes, a remarkable evolutionary scenario. We also demonstrate that 5' flanking regions of IAP family genes as a group, in both human and mouse are enriched for LTR insertions compared to average genes. We propose several potential explanations for these findings, including a hypothesis that recruitment of LTRs near NAIP or other IAP genes may represent a host-cell adaptation to modulate apoptotic responses.
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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 | 0.000 |
| 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 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".