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A Quantitative Model for RhD-Negative Allele Frequency Peaks in Ibero Berber Populations via Synergistic Selection

Ubau, J. C.; Gomez, R.

2026-01-02 genetics
10.64898/2026.01.01.697308 bioRxiv
Show abstract

The RhD-negative blood type reaches its global frequency peak in the Basque population ([~]30-35%), with a secondary peak in isolated Berber groups ([~]15-20%). This discontinuous distribution challenges models based solely on demography or drift. We propose a quantitative model in which allele frequency dynamics are shaped by conditional synergistic selection operating within a unique eco-evolutionary niche. Our framework synthesizes archaeogenomic data to show that admixture between indigenous Western Hunter-Gatherers (carrying a high-frequency RHD deletion) and incoming Neolithic farmers (carrying the SLC24A5 allele) in Iberia generated statistical associations between these unlinked loci. Population-genetic modeling indicates that selection acting on this multi-locus genotype combination can drive co-amplification of both alleles. We argue that this process was maximized in the proto-Basque region--a biocultural refuge characterized by geographic isolation, resource stability, and reduced effective cost of Hemolytic Disease of the Newborn. Subsequent Neolithic gene flow across the Strait of Gibraltar provides a parsimonious mechanism for the shared European RHD deletion observed in Berber populations. Forward-time Wright-Fisher simulations in a structured three-deme framework demonstrate that models incorporating synergistic selection robustly reproduce the observed Ibero-Berber discontinuity across a broad region of parameter space, whereas drift-only models achieve similar outcomes only under comparatively restricted parameter configurations. Parsimony volume comparisons quantify this difference in robustness. Additional deterministic and finite-population simulations confirm that the inferred parameter regime permits directional amplification under both mean-field and stochastic reproduction. Together, these results provide a testable evolutionary framework integrating genetics, environmental history, and epidemiology to explain one of the most striking allele-frequency outliers in human populations.

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