The inbreeding coefficient (F) of individuals can be estimated from molecular marker data, such as SNPs, using measures of homozygosity of individual markers or runs of homozygosity (ROH) across the genome. These different measures of F can then be used to estimate the rate of inbreeding depression (ID) for quantitative traits. Some recent simulation studies have investigated the accuracy of this estimation with contradictory results. Whereas some studies suggest that estimates of inbreeding from ROH account more accurately for ID, others suggest that inbreeding measures from SNP‐by‐SNP homozygosity giving a large weight to rare alleles are more accurate. Here, we try to give more light on this issue by carrying out a set of computer simulations considering a range of population genetic parameters and population sizes. Our results show that the previous studies are indeed not contradictory. In populations with low effective size, where relationships are more tight and selection is relatively less intense, F measures based on ROH provide very accurate estimates of ID whereas SNP‐by‐SNP‐based F measures with high weight to rare alleles can show substantial upwardly biased estimates of ID. However, in populations of large effective size, with more intense selection and trait allele frequencies expected to be low if they are deleterious for fitness because of purifying selection, average estimates of ID from SNP‐by‐SNP‐based F values become unbiased or slightly downwardly biased and those from ROH‐based F values become slightly downwardly biased. The noise attached to all these estimates, nevertheless, can be very high in large‐sized populations. We also investigate the relationship between the different F measures and the homozygous mutation load, which has been suggested as a proxy of inbreeding depression.

中文翻译：

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利用分子标记的不同近交测量方法估计近交抑郁

可以使用单个标记的纯合度或整个基因组中纯合度（ROH）的序列，根据分子标记数据（例如SNP）估算个体的近交系数（F）。F的这些不同度量然后可以用来估计数量性状的近交抑制率（ID）。最近的一些模拟研究已经调查了这种估计的准确性，并得出了相互矛盾的结果。尽管有些研究表明ROH的近交估计更准确地说明了ID，但其他研究表明SNP-by-SNP纯合性的近交测量对稀有等位基因的权重较大。在这里，我们尝试通过考虑一组种群遗传参数和种群大小的一组计算机模拟，为这个问题提供更多的启示。我们的结果表明，以前的研究确实并不矛盾。在有效人数较少的人群中，人际关系更加紧密，选择相对较少，F基于ROH的测量可提供非常准确的ID估计值，而对稀有等位基因具有高权重的基于SNP的SNP F测量可显示ID的估计值明显偏向。但是，在有效大小较大的人群中，如果由于纯化选择而对适应性有害，那么选择和性状等位基因的频率会更高，选择和性状等位基因频率会降低，基于SNP的SNP F值对ID的平均估计会变得无偏或略有偏见向下偏斜，基于ROH的F值的偏斜略微向下偏斜。但是，所有这些估计值附带的噪声在大型人群中可能会非常高。我们还研究了不同F之间的关系 措施和纯合突变负荷，这被认为是近交性抑郁症的代表。