Resolving sampling and population-size biases in domestication genomics supports a South Asian origin of walnuts

Abstract

Background The inference of population structure in domestication studies is prone to biases whenever sampling is unbalanced and effective population sizes (Ne) differ across populations. Such biases can lead to the misclassification of large ancestral populations as admixed, particularly under single-origin domestication scenarios. Results We propose a novel parameterization strategy for the STRUCTURE software, combining the F model and alternative ancestry prior (along with a smaller initial ALPHA value), and simulations demonstrate that the strategy mitigates unbalanced sampling and unequal population size biases. We apply our strategy to the domestication history of the common walnut (Juglans regia), using whole-genome resequencing data from 298 individuals from across its range. The results support an origin of J. regia in South Asia, where walnut populations are characterized by high genetic diversity, extensive private allele content, low mutation load, and demographic stability. Building on this demographic framework, we further identify genomic regions under recent positive selection and candidate domestication genes involved in shell structure, pollen development, and lipid transport. Conclusions Our results clarify the long-standing debate on the geographic origin of walnut domestication and demonstrate that an optimized, model-aware use of STRUCTURE can substantially improve population-genetic inference in domestication studies and other systems characterized by complex demography. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-026-03959-6. Keywords: Crop domestication, Effective population size, Parameter optimization, Population clustering, Sampling bias, STRUCTURE software