Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction
Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction
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DOI：
10.3168/jds.2014-9005
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发表时间：
2015-06-01
影响因子：
3.5
通讯作者：
Lund, M. S.
中科院分区：
文献类型：
--
作者：
Brondum, R. F.;Su, G.;Lund, M. S.
本研究探讨了当基于全基因组序列数据的单标记分析的少量显著变异被添加到常规的54k单核苷酸多态性（SNP）阵列数据时对基因组预测可靠性的影响。选择额外的标记物，目的是增强北欧国家使用的定制低密度Illumina BovineLD SNP芯片（San Diego，CA）。对北欧荷斯坦牛、丹麦泽西牛和北欧红牛的育种目标中包括的所有16个指标性状加上总价值指数本身进行品种方面的单标记分析。根据性状的经济重量，每个品种每个性状选择15、10或5个数量性状基因座（QTL），并选择3至5个标记来标记每个QTL。在去除重复标记（选择用于多于一个性状或品种的相同标记）并过滤高成对连锁不平衡和测定阵列上的性能之后，选择总共1，623个QTL标记用于包含在定制芯片上。使用基因组BLUP或贝叶斯变量选择模型对北欧和法国荷斯坦和北欧红动物进行基因组预测分析。当在分析中使用包括QTL标记的基因组BLUP模型时，北欧荷斯坦牛动物的生产性状的可靠性增加了4个百分点，北欧红牛增加了3个百分点，法国荷斯坦牛增加了5个百分点。乳腺炎的增幅较小，最多为1个百分点，但生育率仅增加了0.5个百分点。与基因组BLUP方法相比，当使用贝叶斯模型时，只有54k数据的准确性通常较高，但当包括QTL标记时，可靠性的增加相对较小。这项研究的结果表明，基因组预测的可靠性可以通过包括在全基因组序列数据的全基因组关联研究中显着的标记以及54k SNP集来增加。
This study investigated the effect on the reliability of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k single nucleotide polymorphism (SNP) array data. The extra markers were selected with the aim of augmenting the custom low-density Illumina BovineLD SNP chip (San Diego, CA) used in the Nordic countries. The single-marker analysis was done breed-wise on all 16 index traits included in the breeding goals for Nordic Holstein, Danish Jersey, and Nordic Red cattle plus the total merit index itself. Depending on the trait's economic weight, 15, 10, or 5 quantitative trait loci (QTL) were selected per trait per breed and 3 to 5 markers were selected to tag each QTL. After removing duplicate markers (same marker selected for more than one trait or breed) and filtering for high pairwise linkage disequilibrium and assaying performance on the array, a total of 1,623 QTL markers were selected for inclusion on the custom chip. Genomic prediction analyses were performed for Nordic and French Holstein and Nordic Red animals using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model including the QTL markers in the analysis, reliability was increased by up to 4 percentage points for production traits in Nordic Holstein animals, up to 3 percentage points for Nordic Reds, and up to 5 percentage points for French Holstein. Smaller gains of up to 1 percentage point was observed for mastitis, but only a 0.5 percentage point increase was seen for fertility. When using a Bayesian model accuracies were generally higher with only 54k data compared with the genomic BLUP approach, but increases in reliability were relatively smaller when QTL markers were included. Results from this study indicate that the reliability of genomic prediction can be increased by including markers significant in genome-wide association studies on whole genome sequence data alongside the 54k SNP set.