Comparative analysis of the paired immunoglobulin-like receptor (<i>PILR</i>) locus in six mammalian genomes: duplication, conversion, and the birth of new genes
Bibliographic record
Abstract
Manyaspects of the immune system are controlled by homologous cell surface receptors that mediate inhibitory and activating pathways. The paired immunoglobulin-like receptor (PILR) locus at 7q22 encodes both PILRA, an inhibitory receptor, and PILRB, its activating counterpart. Mouse Pilrb1 is a novel immune system regulator, and its ligand Cd99 participates in the recruitment of T-cells to inflamed tissue. We characterized the PILR locus in six mammalian genomes and investigated the structure and mRNA expression of human PILRB. Synteny at the PILR locus is conserved in the human, chimpanzee, dog, mouse and rat genomes. The absence of the PILR locus in opossum and chicken genomes suggests it arose after the divergence of placental and nonplacental mammals. In humans, a Williams-Beuren syndrome-related segmental duplication has created a complex chimeric transcript representing the predominantly expressed form of PILRB. Unlike PILRA, PILRB transcripts were detected in a wide variety of tissues including cells of the lymphoid lineage. In the mouse genome, a second activating gene, Pilrb2, and six pseudogenes were found. Extensive gene duplications in the rat genome have resulted in at least 27 Pilrb genes and or pseudogenes. Abundant gene duplication events involving novel CD99-related genes were also detected in the rat genome. In addition to duplication, we show that gene conversion has played a persistent role in the evolution of the PILR genes. Overall, we demonstrate that the PILR locus is dynamically evolving via multiple evolutionary mechanisms in several mammalian genomes.
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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 | 0.001 | 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) | 0.001 | 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".