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直接测量与傅里叶变换中红外预测的牛乳脂肪酸和蛋白质的遗传特征比较

Comparison of the genetic characteristics of directly measured and Fourier-transform mid-infrared-predicted bovine milk fatty acids and proteins.

作者信息

Tiplady Kathryn M, Lopdell Thomas J, Sherlock Richard G, Johnson Thomas J J, Spelman Richard J, Harris Bevin L, Davis Stephen R, Littlejohn Mathew D, Garrick Dorian J

机构信息

Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand; School of Agriculture and Environment, Massey University, Ruakura, Hamilton 3240, New Zealand.

Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand.

出版信息

J Dairy Sci. 2022 Nov;105(12):9763-9791. doi: 10.3168/jds.2022-22089. Epub 2022 Oct 26.

DOI:10.3168/jds.2022-22089
PMID:36307235
Abstract

Fourier-transform mid-infrared (FT-MIR) spectroscopy is a high-throughput and inexpensive methodology used to evaluate concentrations of fat and protein in dairy cattle milk samples. The objective of this study was to compare the genetic characteristics of FT-MIR predicted fatty acids and individual milk proteins with those that had been measured directly using gas and liquid chromatography methods. The data used in this study was based on 2,005 milk samples collected from 706 Holstein-Friesian × Jersey animals that were managed in a seasonal, pasture-based dairy system, with milk samples collected across 2 consecutive seasons. Concentrations of fatty acids and protein fractions in milk samples were directly determined by gas chromatography and high-performance liquid chromatography, respectively. Models to predict each directly measured trait based on FT-MIR spectra were developed using partial least squares regression, with spectra from a random selection of half the cows used to train the models, and predictions for the remaining cows used as validation. Variance parameters for each trait and genetic correlations for each pair of measured/predicted traits were estimated from pedigree-based bivariate models using REML procedures. A genome-wide association study was undertaken using imputed whole-genome sequence, and quantitative trait loci (QTL) from directly measured traits were compared with QTL from the corresponding FT-MIR predicted traits. Cross-validation prediction accuracies based on partial least squares for individual and grouped fatty acids ranged from 0.18 to 0.65. Trait prediction accuracies in cross-validation for protein fractions were 0.53, 0.19, and 0.48 for α-casein, β-casein, and κ-casein, 0.31 for α-lactalbumin, 0.68 for β-lactoglobulin, and 0.36 for lactoferrin. Heritability estimates for directly measured traits ranged from 0.07 to 0.55 for fatty acids; and from 0.14 to 0.63 for individual milk proteins. For FT-MIR predicted traits, heritability estimates were mostly higher than for the corresponding measured traits, ranging from 0.14 to 0.46 for fatty acids, and from 0.30 to 0.70 for individual proteins. Genetic correlations between directly measured and FT-MIR predicted protein fractions were consistently above 0.75, with the exceptions of C18:0 and C18:3 cis-3, which had genetic correlations of 0.72 and 0.74, respectively. The GWAS identified trait QTL for fatty acids with likely candidates in the DGAT1, CCDC57, SCD, and GPAT4 genes. Notably, QTL for SCD were largely absent in the FT-MIR predicted traits, and QTL for GPAT4 were absent in directly measured traits. Similarly, for directly measured individual proteins, we identified QTL with likely candidates in the CSN1S1, CSN3, PAEP, and LTF genes, but the QTL for CSN3 and LTF were absent in the FT-MIR predicted traits. Our study indicates that genetic correlations between directly measured and FT-MIR predicted fatty acid and protein fractions are typically high, but that phenotypic variation in these traits may be underpinned by differing genetic architecture.

摘要

傅里叶变换中红外(FT-MIR)光谱法是一种高通量且成本低廉的方法,用于评估奶牛牛奶样本中的脂肪和蛋白质浓度。本研究的目的是比较FT-MIR预测的脂肪酸和个体乳蛋白的遗传特征与那些通过气相色谱和液相色谱法直接测量的遗传特征。本研究中使用的数据基于从706头荷斯坦-弗里生×泽西奶牛采集的2005份牛奶样本,这些奶牛饲养在一个季节性的、以牧场为基础的奶牛养殖系统中,牛奶样本在连续两个季节采集。牛奶样本中的脂肪酸和蛋白质组分浓度分别通过气相色谱法和高效液相色谱法直接测定。使用偏最小二乘回归建立基于FT-MIR光谱预测每个直接测量性状的模型,随机选择一半奶牛的光谱用于训练模型,其余奶牛的预测值用作验证。使用REML程序从基于系谱的双变量模型中估计每个性状的方差参数以及每对测量/预测性状的遗传相关性。使用推算的全基因组序列进行全基因组关联研究,并将直接测量性状的数量性状位点(QTL)与相应FT-MIR预测性状的QTL进行比较。基于偏最小二乘的个体和分组脂肪酸交叉验证预测准确率在0.18至0.65之间。蛋白质组分交叉验证中的性状预测准确率,α-酪蛋白为0.53,β-酪蛋白为0.19,κ-酪蛋白为0.48,α-乳白蛋白为0.31,β-乳球蛋白为0.68,乳铁蛋白为0.36。直接测量性状的遗传力估计值,脂肪酸为0.07至0.55;个体乳蛋白为0.14至0.63。对于FT-MIR预测性状,遗传力估计值大多高于相应的测量性状,脂肪酸为0.14至0.46,个体蛋白质为0.30至0.70。直接测量和FT-MIR预测的蛋白质组分之间的遗传相关性始终高于0.75,但C18:0和顺式-3 C18:3除外,它们的遗传相关性分别为0.72和0.74。全基因组关联研究确定了脂肪酸的性状QTL,可能的候选基因有DGAT1、CCDC57、SCD和GPAT4。值得注意的是,FT-MIR预测性状中基本不存在SCD的QTL,直接测量性状中不存在GPAT4的QTL。同样,对于直接测量的个体蛋白质,我们确定了可能的候选基因在CSN1S1、CSN3、PAEP和LTF基因中的QTL,但FT-MIR预测性状中不存在CSN3和LTF的QTL。我们的研究表明,直接测量和FT-MIR预测的脂肪酸和蛋白质组分之间的遗传相关性通常较高,但这些性状的表型变异可能由不同的遗传结构支撑。

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