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Comparison of conventional BLUP and single-step genomic BLUP evaluations for yearling weight and carcass traits in Hanwoo beef cattle using single trait and multi-trait models

机译:使用单性状和多性状模型比较常规BLUP和单步基因组BLUP对Hanwoo肉牛一岁体重和car体性状的评估

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摘要

Hanwoo, an important indigenous and popular breed of beef cattle in Korea, shows rapid growth and has high meat quality. Its yearling weight (YW) and carcass traits (backfat thickness, carcass weight- CW, eye muscle area, and marbling score) are economically important for selection of young and proven bulls. However, measuring carcass traits is difficult and expensive, and can only be performed postmortem. Genomic selection has become an appealing procedure for genetic evaluation of these traits (by inclusion of the genomic data) along with the possibility of multi-trait analysis. The aim of this study was to compare conventional best linear unbiased prediction (BLUP) and single-step genomic BLUP (ssGBLUP) methods, using both single-trait (ST-BLUP, ST-ssGBLUP) and multi-trait (MT-BLUP, MT-ssGBLUP) models to investigate the improvement of breeding-value accuracy for carcass traits and YW. The data comprised of 15,279 phenotypic records for YW and 5,824 records for carcass traits, and 1,541 genotyped animals for 34,479 single-nucleotide polymorphisms. Accuracy for each trait and model was estimated only for genotyped animals by five-fold cross-validation. ssGBLUP models (ST-ssGBLUP and MT-ssGBLUP) showed ~19% and ~36% greater accuracy than conventional BLUP models (ST-BLUP and MT-BLUP) for YW and carcass traits, respectively. Within ssGBLUP models, the accuracy of the genomically estimated breeding value for CW increased (19%) when ST-ssGBLUP was replaced with the MT-ssGBLUP model, as the inclusion of YW in the analysis led to a strong genetic correlation with CW (0.76). For backfat thickness, eye muscle area, and marbling score, ST- and MT-ssGBLUP models yielded similar accuracy. Thus, combining pedigree and genomic data via the ssGBLUP model may be a promising way to ensure acceptable accuracy of predictions, especially among young animals, for ongoing Hanwoo cattle breeding programs. MT-ssGBLUP is highly recommended when phenotypic records are limited for one of the two highly correlated genetic traits.
机译:Hanwoo是韩国重要的本地和流行的肉牛品种,生长迅速且肉质高。它的一岁体重(YW)和体特征(后脂肪厚度,weight体重量-CW,眼肌面积和大理石花纹得分)对于选择年轻和成熟的公牛在经济上很重要。但是,测量car体性状既困难又昂贵,并且只能在事后进行。基因组选择已成为对这些性状进行遗传评估(通过包含基因组数据)以及进行多性状分析的一种有吸引力的程序。这项研究的目的是比较传统最佳线性无偏预测(BLUP)和单步基因组BLUP(ssGBLUP)方法,同时使用单特征(ST-BLUP,ST-ssGBLUP)和多特征(MT-BLUP, MT-ssGBLUP)模型,以研究car体性状和YW育种值准确性的提高。该数据包括YW的15,279个表型记录和car体性状的5,824个记录,以及34,479个单核苷酸多态性的1,541个基因型动物。通过五倍交叉验证,仅对基因型动物评估每种性状和模型的准确性。 ssGBLUP模型(ST-ssGBLUP和MT-ssGBLUP)显示出的YW和car体特征的准确性分别比传统BLUP模型(ST-BLUP和MT-BLUP)高出约19%和〜36%。在ssGBLUP模型中,用MT-ssGBLUP模型替换ST-ssGBLUP模型后,通过基因组估计的CW育种值的准确性提高了(19%),因为分析中包含YW导致与CW的遗传相关性很强(0.76 )。对于后脂肪厚度,眼肌面积和大理石花纹得分,ST-和MT-ssGBLUP模型产生了相似的准确性。因此,通过正在进行的Hanwoo牛育种计划,通过ssGBLUP模型将谱系和基因组数据结合起来可能是一种确保有希望的预测准确性的有前途的方法,尤其是在幼小的动物中。当表型记录仅限于两个高度相关的遗传性状之一时,强烈建议使用MT-ssGBLUP。

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