仔猪初生窝重性状的遗传评估
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广东省自然科学基金(2018B030313011);广东省现代农业产业技术体系生猪创新团队项目(2019KJ126)


Genetic assessment of the trait of litter birth weight
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    摘要:

    本文旨在计算温氏某育种场大白猪初生窝重性状的遗传参数,并评估基因组选择不同计算方法对初生窝重性状的选择准确性。利用DMU软件和动物模型估计初生窝重的方差组分,包括加性方差组分和永久环境效应方差组分,并计算性状的遗传力。通过简化基因组测序分型方法,构建大白猪基因组选择参考群体,并利用GVCBLUP和BLUPF90软件,验证群体分别使用BLUP、GBLUP和ssGBLUP方法计算估计育种值的准确性。结果显示:初生窝重的遗传力为0.08,为低遗传力性状。初生窝重与总产仔数、产活仔数、健仔数和弱差猪仔数遗传相关系数分别为0.59,0.68,0.88和-0.17。基因组选择结果显示,验证群体ssGBLUP育种值估计的准确性最高,达到0.38,比常规BLUP方法提高了15.79%,与BLUP估计育种值秩相关达到0.63。对初生窝重的选择,可有效提高产仔数;且结合ssGBLUP方法的基因组选择,能够有效提高估计育种值的准确性。

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    This study was aimed to estimate breed-specific genetic parameters of Large White pigs in Wen's Group and evaluate the accuracy of different methods of genomic selection of the trait of litter birth weight (LBW). Animal model and DMU software were used to estimate variances for the trait of LBW, including additive variance components and permanent environmental effect variance components, as well as heritabilities of the trait. The reproductive reference population for Large White pig genomic selection were built based on genotype-by-sequence (GBS) technology. The accuracy of genomic estimated breeding values (GEBV) were compared using different methods of BLUP, GBLUP and ssGBLUP in the validation group. Estimation of heritability was 0.08 for LBW, which was a trait with low heritability. The genetic correlation coefficients between LBW and some quantitative traits, such as total number born, number born alive, number born robust, number of weak, deformed, stillborn and mummified pigs, were 0.59 0.68, 0.88 and -0.17, respectively. According to the results of the genomic selection, the ssGBLUP had a higher accuracy of 0.38, increased 15.79% compared to the traditional BLUP method. The spearman rank correlation coefficient of GEBV between ssGBLUP and BLUP was 0.63. Selection of LBW has a positive effect on the improvement of litter size. The accuracy of genomic selection can be improved effectively combined with ssGBLUP method.

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叶健,谈成,蔡更元,吴珍芳.仔猪初生窝重性状的遗传评估[J].华南农业大学学报,2019,40(S1):72-75

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  • 收稿日期:2019-03-02
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  • 在线发布日期: 2020-04-11