Genetic gain & Inbreeding

Evaluating the Influence of Sample Size and SNP Density on Genomic Estimates of Effective Population Size in Livestock

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Abstract

The effective population size (Ne) is a fundamental parameter in conservation genetics and livestock breeding, as it reflects the level of genetic diversity and the long-term evolutionary potential of a population. An accurate estimate of Ne is therefore essential for understanding the level of genetic diversity in a population, establishing conservation strategies, and managing breeding programs with the aim of preserving genetic variability. Among the main factors influencing the accuracy of Ne estimates derived from genomic data are (i) the number of single nucleotide polymorphisms (SNPs) used in the analysis and (ii) the number of individuals sampled. The present study evaluated the sensitivity of Ne estimates to variation in both parameters by systematically testing different combinations of sample size and marker density. Estimates of Ne were obtained from gametic/linkage disequilibrium information implemented in the GONE software, which allows for estimation current and historical effective population size from genomic data. The analysis was performed using publicly available, high-density SNP datasets from several domestic species, including two breeds each of cattle, horses, sheep, and dogs. To assess the effect of sample size, different subsets of individuals were randomly selected, beginning with a minimum of 10 individuals, increasing by increments of 10 up to 100, and subsequently by 50 until the full dataset was reached. A similar strategy was applied to evaluate the impact of SNP density, starting with 5,000 randomly chosen SNPs and progressively increasing by 5,000 up to 100,000, and then by 50,000 up to the full density of the available data. Each scenario was replicated ten times to assess variability and reproducibility of the results. A threshold for Ne stability was determined using piecewise linear regression, which identified the point at which additional data yielded negligible improvements in estimate precision. Based on this analysis, the minimum sample size required for accurate Ne estimation was determined to be approximately 24 individuals, while the optimal size, providing consistent and stable estimates, was around 45 individuals or more. Below these thresholds, particularly below the minimum sample size of 24 individuals, Ne value were under- or overestimated in most cases. For marker density, reliable estimates were obtained using a minimum of 25,000 SNPs. This methodological framework offers a systematic and data-driven approach to identifying resource-efficient thresholds for accurate Ne estimation. The results confirm the robustness of Ne estimates derived from genomic data and provide practical guidance for optimizing study design. Future work will extend this analysis to additional livestock populations and species, further refining recommendations for cost-effective genomic applications in conservation and breeding management. This research was supported by the GACR 24-14325L, QL25020022, VEGA 1/0316/25 and APVV-20-016.

Keywords: 2026

How to Cite:

Vostrý, L., Vostra-Vydrova, H., Moravcikova, N., Kasarda, R., Halvonik, A., Shihabi, M., Cubric-Curik, V. & Curik, I., (2026) “Evaluating the Influence of Sample Size and SNP Density on Genomic Estimates of Effective Population Size in Livestock”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2286333. doi: https://doi.org/10.31274/wcgalp.23934

Rights: 1