Genetic Diversity Patterns in the SR-BI/II Locus Can Be Explained by a Recent Selective Sweep
Bibliographic record
Abstract
The human scavenger receptor class B type I (SR-BI and splice variant SR-BII) plays a central role in HDL cholesterol metabolism and represents a candidate gene for a number of related diseases. We examined the genetic diversity of its coding and flanking regions in a sample of 178 chromosomes from individuals of European, African, East Asian (including Southeast Asian), Middle-Eastern as well as Amerindian descent. Nine of the 14 polymorphisms observed are new. Four of the five variants causing amino acid replacements, G2S, S229G, R484W, and G499R, are likely to affect protein structure and function. SR-BI/BII diversity is partitioned among 19 haplotypes; all but one interconnected by single mutation or a recombination event. Such tight haplotype network and the unusual geographic partitioning of this diversity, high not only in Africa but in East Asia as well, suggests its recent origin and possible effect of selection. Coalescent analysis infers a relatively short time to the most recent common ancestor and points to population expansion in Africa and East Asia. These two continents differ significantly in pairwise F(ST) values, differing as well from a single cluster formed by Europe, Middle East and America. In the context of findings for similarly analyzed other loci, we propose that a selective sweep at the origin of modern human populations could explain the low level of ancestral SR-BI/II diversity. The unusually deep split between Africa and Asia, well beyond the Upper Paleolithic when inferred under neutrality, is consistent with subsequent geographical and demographic expansion favoring the accumulation of new variants, especially in groups characterized by large effective population sizes, such as Asians and Africans. The relevance of such partitioning of SR-BI/II diversity remains to be investigated in genetic epidemiological studies which can be guided by the present findings.
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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 | 0.000 | 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) | 0.001 | 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".