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中国荷斯坦奶牛中FT-MIRS预测的乳脂肪酸的遗传特征

The Genetic Characteristics of FT-MIRS-Predicted Milk Fatty Acids in Chinese Holstein Cows.

作者信息

Li Chunfang, Fan Yikai, Wang Dongwei, Chu Chu, Shen Xiong, Wang Haitong, Luo Xuelu, Nan Liangkang, Ren Xiaoli, Chen Shaohu, Yan Qingxia, Ni Junqing, Li Jianming, Ma Yabin, Zhang Shujun

机构信息

Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China.

Frontiers Science Center for Animal Breeding and Sustainable Production, Huazhong Agricultural University, Wuhan 430070, China.

出版信息

Animals (Basel). 2024 Oct 8;14(19):2901. doi: 10.3390/ani14192901.

Abstract

Fourier Transform Mid-Infrared Spectroscopy (FT-MIRS) can be used for quantitative detection of milk components. Here, milk samples of 458 Chinese Holstein cows from 11 provinces in China were collected and we established a total of 22 quantitative prediction models in milk fatty acids by FT-MIRS. The coefficient of determination of the validation set ranged from 0.59 (C18:0) to 0.76 (C4:0). The models were adopted to predict the milk fatty acids from 2138 cows and a new high-throughput computing software HiBLUP was employed to construct a multi-trait model to estimate and analyze genetic parameters in dairy cows. Finally, genome-wide association analysis was performed and seven novel SNPs significantly associated with fatty acid content were selected, investigated, and verified with the FarmCPU method, which stands for "Fixed and random model Circulating Probability Unification". The findings of this study lay a foundation and offer technical support for the study of fatty acid trait breeding and the screening and grouping of characteristic dairy cows in China with rich, high-quality fatty acids. It is hoped that in the future, the method established in this study will be able to screen milk sources rich in high-quality fatty acids.

摘要

傅里叶变换中红外光谱法(FT-MIRS)可用于牛奶成分的定量检测。在此,收集了来自中国11个省份的458头中国荷斯坦奶牛的牛奶样本,并通过FT-MIRS建立了总共22个牛奶脂肪酸定量预测模型。验证集的决定系数范围为0.59(C18:0)至0.76(C4:0)。采用这些模型预测了2138头奶牛的牛奶脂肪酸,并使用一种新的高通量计算软件HiBLUP构建了一个多性状模型,以估计和分析奶牛的遗传参数。最后,进行了全基因组关联分析,选择了7个与脂肪酸含量显著相关的新单核苷酸多态性(SNP),并使用“固定和随机模型循环概率统一”(FarmCPU)方法进行了研究和验证。本研究结果为中国富含优质脂肪酸的特色奶牛脂肪酸性状育种研究以及筛选和分组奠定了基础并提供了技术支持。希望未来本研究建立的方法能够筛选出富含优质脂肪酸的奶源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f893/11476120/a01cf8c22e93/animals-14-02901-g001.jpg

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