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基于高密度 SNP 标记的基因组途径信息整合的中国黄羽肉鸡基因组预测的单体型分析。

Haplotype analysis of genomic prediction by incorporating genomic pathway information based on high-density SNP marker in Chinese yellow-feathered chicken.

机构信息

Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, 510642 China; Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, 510642 China.

Wen's Nanfang Poultry Breeding Co. Ltd, Guangdong Province, Yunfu 527400, China.

出版信息

Poult Sci. 2023 May;102(5):102549. doi: 10.1016/j.psj.2023.102549. Epub 2023 Feb 7.

Abstract

Genomic selection using single nucleotide polymorphism (SNP) markers is now intensively investigated in breeding and has been widely utilized for genetic improvement. Currently, several studies have used haplotype (consisting of multiallelic SNPs) for genomic prediction and revealed its performance advantage. In this study, we comprehensively evaluated the performance of haplotype models for genomic prediction in 15 traits, including 6 growth, 5 carcass, and 4 feeding traits in a Chinese yellow-feathered chicken population. We adopted 3 methods to define haplotypes from high-density SNP panels, and our strategy included combining Kyoto Encyclopedia of Genes and Genomes pathway information and considering linkage disequilibrium (LD) information. Our results showed an increase in prediction accuracy due to haplotypes ranging from -0.04∼27.16% in all traits, where the significant improvements were found in 12 traits. The estimates of haplotype epistasis heritability were strongly correlated with the accuracy increase by haplotype models. In addition, incorporating genomic annotation information could further increase the accuracy of the haplotype model, where the further increase in accuracy is significantly relative to the increase of relative haplotype epistasis heritability. The genomic prediction using LD information for constructing haplotypes has the best prediction performance among the 4 traits. These results uncovered that haplotype methods were beneficial for genomic prediction, and the accuracy could be further increased by incorporating genomic annotation information. Moreover, using LD information would potentially improve the performance of genomic prediction.

摘要

利用单核苷酸多态性 (SNP) 标记进行基因组选择现在在育种中得到了深入研究,并已广泛用于遗传改良。目前,已有几项研究使用单倍型(由多等位基因 SNP 组成)进行基因组预测,并揭示了其性能优势。在这项研究中,我们综合评估了单倍型模型在 15 个性状中的基因组预测性能,包括中国黄羽肉鸡群体中的 6 个生长性状、5 个胴体性状和 4 个饲养性状。我们采用了 3 种方法从高密度 SNP 面板中定义单倍型,我们的策略包括结合京都基因与基因组百科全书(KEGG)通路信息和考虑连锁不平衡(LD)信息。我们的结果表明,由于单倍型的存在,预测准确性有所提高,所有性状的预测准确性提高幅度在-0.04∼27.16%之间,其中 12 个性状的预测准确性有显著提高。单倍型上位性遗传力的估计值与单倍型模型提高的准确性密切相关。此外,结合基因组注释信息可以进一步提高单倍型模型的准确性,其中准确性的进一步提高与相对单倍型上位性遗传力的增加显著相关。利用 LD 信息构建单倍型的基因组预测在 4 个性状中具有最佳的预测性能。这些结果表明,单倍型方法有利于基因组预测,并且通过结合基因组注释信息可以进一步提高准确性。此外,利用 LD 信息可能会提高基因组预测的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/075c/10024239/ad7879c6b128/gr1.jpg

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