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Reference Population Design and the Illusion of Genetic Intermediacy in Mediterranean Population Models

Submitted:

05 February 2026

Posted:

06 February 2026

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Abstract
Genome-wide ancestry inference depends critically on reference population design, yet the sensitivity of inferred population relationships to reference choice is often underexamined. Here, I evaluate how asymmetric reference population construction can generate the appearance of genetic intermediacy in Mediterranean population models, using Ashkenazi Jewish populations as a focused test case. I analyze multiple independent frameworks, including qpAdm admixture modeling, pairwise autosomal FST distances, principal component analysis, identity-by-descent sharing, Global25-based affinity modeling, and reassessment of published uniparental marker studies. Across methods, I vary European and eastern Mediterranean reference sets to test the stability of inferred ancestry patterns under alternative, historically grounded configurations. When Southern European populations, particularly Southern Italian, Sicilian, Maltese, and Aegean groups, are included explicitly, Ashkenazi Jews consistently resolve within a Southern European and central Mediterranean genetic continuum rather than as an intermediate population between Europe and the Levant. In contrast, models that represent Europe using Northern Italian, Tuscan, or genetically drifted Sardinian proxies reproducibly shift Ashkenazi Jews toward an apparent Europe–Levant midpoint. Autosomal FST distances identify the closest affinities with Southern Italians, Cretans, Sicilians, and mainland Greeks, with substantially greater divergence from Levantine populations. qpAdm and identity-by-descent analyses likewise support predominant Southern European ancestry. These results demonstrate that apparent genetic intermediacy is largely a methodological artifact arising from reference population exclusion and underscore the need for explicit sensitivity testing in ancestry inference.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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