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Background <p>The inference of population structure in domestication studies is prone to biases whenever sampling is unbalanced and effective population sizes (<i>N</i><sub>e</sub>) differ across populations. Such biases can lead to the misclassification of large ancestral populations as admixed, particularly under single-origin domestication scenarios.</p> Results <p>We propose a novel parameterization strategy for the STRUCTURE software, combining the <i>F</i> 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 (<i>Juglans regia</i>), using whole-genome resequencing data from 298 individuals from across its range. The results support an origin of <i>J. regia</i> 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.</p> Conclusions <p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月30日

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  • Cai-Jin Chen,
  • Xiao-Xu Pang,
  • Ya-Mei Ding,
  • Wei-Ping Zhang,
  • Yang Yang,
  • Jie Liu,
  • Anush Nersesyan,
  • Bo-Wen Zhang,
  • Susanne S. Renner,
  • Da-Yong Zhang,
  • Wei-Ning Bai

摘要

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.