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QTLMAS XIII通用数据集分析的比较。I:基因组选择。

Comparison of analyses of the QTLMAS XIII common dataset. I: genomic selection.

作者信息

Bastiaansen John W M, Bink Marco C A M, Coster Albart, Maliepaard Chris, Calus Mario P L

机构信息

Animal Breeding and Genomics Centre, Wageningen University, Wageningen, The Netherlands .

出版信息

BMC Proc. 2010 Mar 31;4 Suppl 1(Suppl 1):S1. doi: 10.1186/1753-6561-4-s1-s1.

Abstract

BACKGROUND

Genomic selection, the use of markers across the whole genome, receives increasing amounts of attention and is having more and more impact on breeding programs. Development of statistical and computational methods to estimate breeding values based on markers is a very active area of research. A simulated dataset was analyzed by participants of the QTLMAS XIII workshop, allowing a comparison of the ability of different methods to estimate genomic breeding values.

METHODS

A best case scenario was analyzed by the organizers where QTL genotypes were known. Participants submitted estimated breeding values for 1000 unphenotyped individuals together with a description of the applied method(s). The submitted breeding values were evaluated for correlation with the simulated values (accuracy), rank correlation of the best 10% of individuals and error in predictions. Bias was tested by regression of simulated on estimated breeding values.

RESULTS

The accuracy obtained from the best case scenario was 0.94. Six research groups submitted 19 sets of estimated breeding values. Methods that assumed the same variance for markers showed accuracies, measured as correlations between estimated and simulated values, ranging from 0.75 to 0.89 and rank correlations between 0.58 and 0.70. Methods that allowed different marker variances showed accuracies ranging from 0.86 to 0.94 and rank correlations between 0.69 and 0.82. Methods assuming equal marker variances were generally more biased and showed larger prediction errors.

CONCLUSIONS

The best performing methods achieved very high accuracies, close to accuracies achieved in a best case scenario where QTL genotypes were known without error. Methods that allowed different marker variances generally outperformed methods that assumed equal marker variances. Genomic selection methods performed well compared to traditional, pedigree only, methods; all methods showed higher accuracies than those obtained for breeding values estimated solely on pedigree relationships.

摘要

背景

基因组选择,即利用全基因组范围内的标记,正受到越来越多的关注,并对育种计划产生着越来越大的影响。开发基于标记估计育种值的统计和计算方法是一个非常活跃的研究领域。QTLMAS XIII研讨会的参与者分析了一个模拟数据集,从而能够比较不同方法估计基因组育种值的能力。

方法

组织者分析了一个最佳情况,即已知QTL基因型。参与者提交了1000个未表型个体的估计育种值以及所应用方法的描述。对提交的育种值进行评估,以确定其与模拟值的相关性(准确性)、最佳10%个体的秩相关性以及预测误差。通过将模拟育种值对估计育种值进行回归来检验偏差。

结果

最佳情况下获得的准确性为0.94。六个研究小组提交了19组估计育种值。假设标记具有相同方差的方法,以估计值与模拟值之间的相关性衡量,准确性范围为0.75至0.89,秩相关性在0.58至0.70之间。允许标记具有不同方差的方法,准确性范围为0.86至0.94,秩相关性在0.69至0.82之间。假设标记方差相等的方法通常偏差更大,预测误差也更大。

结论

表现最佳的方法获得了非常高的准确性,接近在已知QTL基因型无误差的最佳情况下所达到的准确性。允许标记具有不同方差的方法通常优于假设标记方差相等的方法。与仅基于系谱的传统方法相比,基因组选择方法表现良好;所有方法的准确性均高于仅根据系谱关系估计育种值所获得的准确性。

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