Genomic selection: prediction of accuracy and maximisation of long term response
Genomic selection: prediction of accuracy and maximisation of long term response
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DOI：
10.1007/s10709-008-9308-0
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发表时间：
2009-06-01
期刊：
影响因子：
1.5
通讯作者：
Goddard, Mike
中科院分区：
文献类型：
--
作者：
Goddard, Mike
基因组选择是指利用覆盖整个基因组的密集标记来估计选择候选性状的育种价值。本文认为预测育种值的基础上的线性组合的标记。在这种情况下，每个标记效应的最佳估计是基于数据的条件效应的期望。要计算这一点，需要标记效应的先验分布。如果标记效应是正态分布且方差恒定，则BLUP可用于计算标记的估计效应，从而计算估计育种值（EBV）。在这种情况下，该模型相当于传统的动物模型，其中动物之间的关系矩阵是从标记而不是谱系估计的。EBV的精度可以接近1.0，但需要非常大量的数据。研究了一种替代模型，其中只有一些标记物具有非零效应，并且这些效应遵循反射指数分布。在这种情况下，标记物的预期效应是数据的非线性函数，使得明显小的效应回归到几乎为零，因此这些标记物可以从模型中删除。在这种情况下的准确性是相当高的比当标记效应正态分布。如果基因组选择进行了几代，响应下降的方式，可以从标记等位基因频率预测。基因组选择可能导致比表型选择更快的选择反应下降，除非新的标记不断加入育种值的预测。一种方法来找到最佳的指数，以最大限度地提高长期选择响应。该指数根据其频率改变给予标记物的权重，使得有利等位基因具有低频率的标记物在指数中获得更多权重。
Genomic selection refers to the use of dense markers covering the whole genome to estimate the breeding value of selection candidates for a quantitative trait. This paper considers prediction of breeding value based on a linear combination of the markers. In this case the best estimate of each marker's effect is the expectation of the effect conditional on the data. To calculate this requires a prior distribution of marker effects. If the marker effects are normally distributed with constant variance, BLUP can be used to calculate the estimated effects of the markers and hence the estimated breeding value (EBV). In this case the model is equivalent to a conventional animal model in which the relationship matrix among the animals is estimated from the markers instead of the pedigree. The accuracy of the EBV can approach 1.0 but a very large amount of data is required. An alternative model was investigated in which only some markers have non-zero effects and these effects follow a reflected exponential distribution. In this case the expected effect of a marker is a non-linear function of the data such that apparently small effects are regressed back almost to zero and consequently these markers can be deleted from the model. The accuracy in this case is considerably higher than when marker effects are normally distributed. If genomic selection is practiced for several generations the response declines in a manner that can be predicted from the marker allele frequencies. Genomic selection is likely to lead to a more rapid decline in the selection response than phenotypic selection unless new markers are continually added to the prediction of breeding value. A method to find the optimum index to maximise long term selection response is derived. This index varies the weight given to a marker according to its frequency such that markers where the favourable allele has low frequency receive more weight in the index.