A Comprehensive Study of Polymorphic Sites along the HLA-G Gene: Implication for Gene Regulation and Evolution
Bibliographic record
Abstract
HLA-G molecule plays an important role on immune response regulation and has been implicated on the inhibition of T and natural killer cell cytolytic function and inhibition of allogeneic T-cell proliferation. Due to its immune-modulator properties, the HLA-G gene expression has been associated with the outcome of allograft and of autoimmune, infectious, and malignant disorders. Several lines of evidence indicate that HLA-G polymorphisms at the 5'-upstream regulatory region (5' URR) and 3'-untranslated region (3' UTR) may influence the HLA-G expression levels. Because Brazilians represent one of the most heterogeneous populations in the world with the widest HLA-G coding region variability already detected among the studied populations, a high level of variability and haplotype diversity would be expected in Brazilians. On this basis, the 5' URR, coding, and 3' UTR variability were evaluated in a Brazilian series consisting of 100 healthy bone marrow donors, as well as the linkage disequilibrium pattern along the gene and the extended haplotypes encompassing several gene segment variations. The HLA-G locus seems to present six different HLA-G lineages showing functional variations mainly in nucleotides of the regulatory regions. Differences were observed at the 5' URR in positions that either coincide with or are close to transcription factor-binding sites and at the 3' UTR mainly in positions that have already been reported to influence HLA-G mRNA availability. We report several lines of evidence for balancing selection acting on the regulatory regions, which may indicate that these HLA-G lineages may be related to the differential HLA-G expression profiles.
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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 | 0.002 |
| 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".