Extent of linkage disequilibrium, consistency of gametic phase, and imputation accuracy within and across Canadian dairy breeds
Extent of linkage disequilibrium, consistency of gametic phase, and imputation accuracy within and across Canadian dairy breeds
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DOI：
10.3168/jds.2013-6826
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发表时间：
2014-05-01
影响因子：
3.5
通讯作者：
Schenkel, F. S.
中科院分区：
文献类型：
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作者：
Larmer, S. G.;Sargolzaei, M.;Schenkel, F. S.
基因组选择需要大量的参考群体来准确估计单核苷酸多态性（SNP）效应。在一些加拿大奶牛品种，可用的参考群体是不够大，准确估计SNP的影响性状的利益。如果多个品种的标记物相位高度一致，理论上可以通过将多个品种汇集到一个共同的参考群体中来提高一个或所有品种的基因组预测的准确性。本研究使用50，000（50 K）SNP面板和使用777，000（777 K）SNP面板的3个相同品种调查了5个主要奶牛品种的连锁不平衡（LD）程度。还在两个图上研究了成对SNP相位的相关性。LD的水平用2个基因座的等位基因的平方相关性（r（2））来测量，SNP配子阶段的一致性用这些值的有符号平方根来关联。由于777 K样本组的成本较高，因此在品种内以及使用荷斯坦、艾尔郡和根西岛的多品种参考群体检查了较低密度标记样本组[6，000（6 K）或50 K]的插补准确性。使用Functionpute V2.2和Beagle 3.3.2软件进行插补。然后将插补准确度计算为正确SNP填充的比例（一致率）和等位基因R-2。还探讨了计算时间，以确定不同插补算法的效率。分析表明，LD值>0.2发现在所有品种中的距离等于或小于50 K面板上SNP之间的平均相邻成对距离。然而，当使用777 K SNP面板检查平均成对距离时，r值的相关性没有达到高水平（0.94）。在50 ~ 777 K温度范围内进行FImpute插补时，所有品种的一致率（0.968-0.995）和等位基因R-2（0.946-0.991）均较高。在比格犬中使用插补方法时，根西岛和艾尔郡的插补准确度略低。当使用Beagle软件时，计算时间显著更长，与FImpute相比，所有可比程序在时间方面的效率低9至13倍。这些研究结果表明，使用多品种参考人群可能会增加使用777 K SNP面板的预测准确性，777 K基因型可以有效地和有效地插补使用较低密度的50 K SNP面板。
Genomic selection requires a large reference population to accurately estimate single nucleotide polymorphism (SNP) effects. In some Canadian dairy breeds, the available reference populations are not large enough for accurate estimation of SNP effects for traits of interest. If marker phase is highly consistent across multiple breeds, it is theoretically possible to increase the accuracy of genomic prediction for one or all breeds by pooling several breeds into a common reference population. This study investigated the extent of linkage disequilibrium (LD) in 5 major dairy breeds using a 50,000 (50K) SNP panel and 3 of the same breeds using the 777,000 (777K) SNP panel. Correlation of pair-wise SNP phase was also investigated on both panels. The level of LD was measured using the squared correlation of alleles at 2 loci (r(2)), and the consistency of SNP gametic phases was correlated using the signed square root of these values. Because of the high cost of the 777K panel, the accuracy of imputation from lower density marker panels [6,000 (6K) or 50K] was examined both within breed and using a multi-breed reference population in Holstein, Ayrshire, and Guernsey. Imputation was carried out using FInipute V2.2 and Beagle 3.3.2 software. Imputation accuracies were then calculated as both the proportion of correct SNP filled in (concordance rate) and allelic R-2. Computation time was also explored to determine the efficiency of the different algorithms for imputation. Analysis showed that LD values >0.2 were found in all breeds at distances at or shorter than the average adjacent pair-wise distance between SNP on the 50K panel. Correlations of r-values, however, did not reach high levels (0.94) when the average pair-wise distances using the 777K SNP panel were examined. High concordance rate (0.968-0.995) and allelic R-2 (0.946-0.991) were found for all breeds when imputation was carried out with FImpute from 50K to 777K. Imputation accuracy for Guernsey and Ayrshire was slightly lower when using the imputation method in Beagle. Computing time was significantly greater when using Beagle software, with all comparable procedures being 9 to 13 times less efficient, in terms of time, compared with FImpute. These findings suggest that use of a multibreed reference population might increase prediction accuracy using the 777K SNP panel and that 777K genotypes can be efficiently and effectively imputed using the lower density 50K SNP panel.