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

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

Affiliations

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

Chunfang Li et al. Animals (Basel). .

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.

Keywords: Fourier Transform Mid-Infrared Spectroscopy (FT-MIRS); fatty acid content; genetic characteristics; genome-wide association study; milk.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
The spectra of cow’s milk(lines of different colors represent different samples). (a) The original spectra of all reference samples. (b) The average spectra of all reference samples. (c) The D1 preprocessing spectra of all reference samples. (d) The D2 preprocessing pretreated spectra of all reference samples.
Figure 2
Figure 2
Multraits-QQplot and Circular Manhattan for C6:0. (a) The quantile–quantile plot based on the GLM, MLM, and FarmCPU methods. The red line represents x = y. The grey shaded place represents the 0.95 confidence interval (b) The cyclic Manhattan plot based on the GLM, MLM and FarmCPU methods combined with chip density.
Figure 3
Figure 3
Seven validated SNPs significantly related to fatty acid content.‘*’ means p-Value Bonferroni < 0.05, and ‘**’ means p-Value Bonferroni < 0.01. (a) Difference and significance of C6:0 among three genotypes of ARS-BFGL-NGS-22276 gene; (b) Difference and significance of C8:0 among three genotypes of ARS-BFGL-NGS-33001 gene; (c) Difference and significance of C10:0 among three genotypes of Bovine HD 0100019865 gene; (d) Difference and significance of C14:0 among three genotypes of Bovine HD 3000029498 gene; (e) Difference and significance of C14:1,cis-9 among three genotypes of Bovine HD 1600000152 gene; (f) Difference and significance of C18:3,n3 cis-9/12/15 among three genotypes of ARS-BFGL-NGS-15402 gene; (g) Difference and significance of LCFA among three genotypes of ARS-BFGL-NGS-15402 gene.

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