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Simple Summary: Fourier Transform Infrared Spectroscopy (FT-MIRS) is widely used in milk quality detection, dairy herd improvement (DHI), and other fields. It is an economical, fast, accurate, and nondestructive batch tool for determining production performance phenotypes of dairy cows. Milk is one of the most important ways to provide the human body with the fatty acids it needs. There are a huge number of dairy cows in China. Therefore, it is possible to control fatty acid production in the milk source through targeted husbandry and breeding on large pastures to improve the quality of milk production. However, this work has not yet officially begun in China. In summary, our work uses FT-MIRS for the first time to study the phenotypic properties of milk fatty acid content and the genetic mechanism of its formation and to estimate genetic parameters. At the same time, SNPs significantly related to fatty acid content were discovered and the genes or adjacent genes had critical regulatory effects on milk fat synthesis, milk protein synthesis, adipocyte differentiation, mammary gland development, milk synthesis, and growth and development in dairy cows, thus providing a new perspective for cow genetic selection in China. 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. [ABSTRACT FROM AUTHOR]

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.