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Estimating Heritabilities and Genetic Correlations: Comparing the ‘Animal Model’ with Parent-Offspring Regression Using Data from a Natural Population

机译:估计遗传力和遗传相关性:使用自然种群的数据将动物模型与父子后代进行比较

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摘要

Quantitative genetic parameters are nowadays more frequently estimated with restricted maximum likelihood using the ‘animal model’ than with traditional methods such as parent-offspring regressions. These methods have however rarely been evaluated using equivalent data sets. We compare heritabilities and genetic correlations from animal model and parent-offspring analyses, respectively, using data on eight morphological traits in the great reed warbler (Acrocephalus arundinaceus). Animal models were run using either mean trait values or individual repeated measurements to be able to separate between effects of including more extended pedigree information and effects of replicated sampling from the same individuals. We show that the inclusion of more pedigree information by the use of mean traits animal models had limited effect on the standard error and magnitude of heritabilities. In contrast, the use of repeated measures animal model generally had a positive effect on the sampling accuracy and resulted in lower heritabilities; the latter due to lower additive variance and higher phenotypic variance. For most trait combinations, both animal model methods gave genetic correlations that were lower than the parent-offspring estimates, whereas the standard errors were lower only for the mean traits animal model. We conclude that differences in heritabilities between the animal model and parent-offspring regressions were mostly due to the inclusion of individual replicates to the animal model rather than the inclusion of more extended pedigree information. Genetic correlations were, on the other hand, primarily affected by the inclusion of more pedigree information. This study is to our knowledge the most comprehensive empirical evaluation of the performance of the animal model in relation to parent-offspring regressions in a wild population. Our conclusions should be valuable for reconciliation of data obtained in earlier studies as well as for future meta-analyses utilizing estimates from both traditional methods and the animal model.
机译:如今,与传统方法(如父子后代回归法)相比,使用“动物模型”以更大的可能性限制了遗传基因参数的估计。但是,这些方法很少使用等效数据集进行评估。我们使用大苇莺(Acrocephalus arundinaceus)中八个形态性状的数据,分别比较了动物模型和父母-后代分析的遗传力和遗传相关性。使用平均特征值或个体重复测量来运行动物模型,以便能够在包括更多扩展谱系信息的作用与来自同一个体的重复采样的作用之间进行区分。我们表明,通过使用平均性状动物模型纳入更多的谱系信息对标准误差和遗传力的大小影响有限。相反,使用重复测量的动物模型通常对采样准确性有积极影响,并导致较低的遗传力。后者是由于较低的加性方差和较高的表型方差。对于大多数性状组合,两种动物模型方法的遗传相关性均低于亲代后代的估计值,而标准误仅对于平均性状动物模型而言较低。我们得出的结论是,动物模型与亲子后代回归之间的遗传力差异主要是由于在动物模型中包含了单个重复,而不是包含了更多的谱系信息。另一方面,遗传相关性主要受到包含更多谱系信息的影响。就我们所知,这项研究是对野生种群中动物模型与父母-子女回归相关的性能的最全面的经验评估。我们的结论对于整合早期研究中获得的数据以及利用传统方法和动物模型的估计进行的将来的荟萃分析都将是有价值的。

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