For numerically small breeds, obtaining a sufficiently large breed-specific reference population for genomic prediction is challenging or simply not possible, but may be overcome by adding individuals from another breed. To prioritize among available breeds, the effective number of chromosome segments (Me ) can be used as an indicator of relatedness between individuals from different breeds. The Me is also an important parameter in determining the accuracy of genomic prediction. The Me can be estimated both within a population and between two populations or breeds, as the reciprocal of the variance of genomic relationships. However, the threshold for number of individuals needed to accurately estimate within or between populations Me is currently unknown. It is also unknown if a discrepancy in number of genotyped individuals in two breeds affects the estimates of Me between populations. In this study, we conducted a simulation that mimics current domestic cattle populations in order to investigate how estimated Me is affected by number of genotyped individuals, single-nucleotide polymorphism (SNP) density and pedigree availability. Our results show that a small sample of 10 genotyped individuals may result in substantial over or underestimation of Me . While estimates of within population Me were hardly affected by SNP density, between population Me values were highly dependent on the number of available SNPs, with higher SNP densities being able to detect more independent chromosome segments. When subtracting pedigree from genomic relationships before computing Me , estimates of within population Me were three to four times higher than estimates with genotypes only; however, between Me estimates remained the same. For accurate estimation of within and between population Me , at least 50 individuals should be genotyped per population. Estimates of within Me were highly affected by whether pedigree was used or not. For within Me , even the smallest SNP density (~11k) resulted in accurate representation of family relationships in the population; however, for between Me , many more markers are needed to capture all independent segments.

中文翻译：

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影响小品种染色体片段有效估计数准确性的因素


对于数量较少的品种，获得足够大的品种特定参考群体用于基因组预测是具有挑战性的或根本不可能，但可以通过添加来自另一个品种的个体来克服。为了对可用品种进行优先排序，染色体片段的有效数量 (Me ) 可以用作不同品种个体之间相关性的指标。 Me也是确定基因组预测准确性的重要参数。 Me 可以在一个群体内以及两个群体或品种之间进行估计，作为基因组关系方差的倒数。然而，准确估计群体 Me 内部或群体之间所需的个体数量阈值目前未知。尚不清楚两个品种中基因分型个体数量的差异是否会影响种群间 Me 的估计。在这项研究中，我们进行了模拟当前家养牛种群的模拟，以研究估计的 Me 是如何受到基因分型个体数量、单核苷酸多态性 (SNP) 密度和谱系可用性的影响的。我们的结果表明，10 个基因分型个体的小样本可能会导致 Me 的大幅高估或低估。虽然群体内 Me 的估计值几乎不受 SNP 密度的影响，但群体间 Me 值高度依赖于可用 SNP 的数量，较高的 SNP 密度能够检测更多独立的染色体片段。当在计算 Me 之前从基因组关系中减去谱系时，群体内 Me 的估计值比仅使用基因型的估计值高出三到四倍；然而，我之间的估计保持不变。 为了准确估计群体内部和群体之间的 Me ，每个群体至少应对 50 个个体进行基因分型。我内部的估计很大程度上受到是否使用谱系的影响。对于 Me 而言，即使是最小的 SNP 密度 (~11k) 也能准确表示人群中的家庭关系；然而，对于 Between Me ，需要更多的标记来捕获所有独立的片段。