Locally epistatic genomic relationship matrices for genomic association and prediction.
Locally epistatic genomic relationship matrices for genomic association and prediction.
复制标题
用于基因组关联和预测的局部表观基因组关系矩阵。
DOI：
10.1534/genetics.114.173658
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发表时间：
2015-03
期刊：
影响因子：
3.3
通讯作者：
Jannink JL
中科院分区：
文献类型：
--
作者：
Akdemir D;Jannink JL
在植物和动物育种研究中，对个体的遗传价值（加性上位遗传效应）和育种价值（加性遗传效应）进行了区分，因为预计某些上位遗传效应将因重组而丧失。在本文中，我们认为育种者可以利用低重组区域的上位标记效应。该模型旨在利用遗传图谱信息，结合局部加性和上位性效应来估计局部上位系遗传力。为此，我们使用了具有多个局部基因组关系矩阵和分层设计的半参数混合模型。采用弹性网络后处理引入稀疏性。我们的模型产生了良好的预测性能以及有用的解释信息。
In plant and animal breeding studies a distinction is made between the genetic value (additive plus epistatic genetic effects) and the breeding value (additive genetic effects) of an individual since it is expected that some of the epistatic genetic effects will be lost due to recombination. In this article, we argue that the breeder can take advantage of the epistatic marker effects in regions of low recombination. The models introduced here aim to estimate local epistatic line heritability by using genetic map information and combining local additive and epistatic effects. To this end, we have used semiparametric mixed models with multiple local genomic relationship matrices with hierarchical designs. Elastic-net postprocessing was used to introduce sparsity. Our models produce good predictive performance along with useful explanatory information.