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

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.