Genetic analysis of orotic acid predicted with Fourier transform infrared milk spectra

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Abstract

Fourier transform infrared spectral analysis is a cheap and fast method to predict milk composition. A not very well studied milk component is orotic acid. Orotic acid is an intermediate in the biosynthesis pathway of pyrimidine nucleotides and is an indicator for the metabolic cattle disorder deficiency of uridine monophosphate synthase. The function of orotic acid in milk and its effect on calf health, health of humans consuming milk or milk products, manufacturing properties of milk, and its potential as an indicator trait are largely unknown. The aims of this study were to determine if milk orotic acid can be predicted from infrared milk spectra and to perform a large-scale phenotypic and genetic analysis of infrared-predicted milk orotic acid. An infrared prediction model for orotic acid was built using a training population of 292 Danish Holstein and 299 Danish Jersey cows, and a validation population of 381 Danish Holstein cows. Milk orotic acid concentration was determined with nuclear magnetic resonance spectroscopy. For genetic analysis of infrared orotic acid, 3 study populations were used: 3,210 Danish Holstein cows, 3,360 Danish Jersey cows, and 1,349 Dutch Holstein Friesian cows. Using partial least square regression, a prediction model for orotic acid was built with 18 latent variables. The error of the prediction for the infrared model varied from 1.0 to 3.2 mg/L, and the accuracy varied from 0.68 to 0.86. Heritability of infrared orotic acid predicted with the standardized prediction model was 0.18 for Danish Holstein, 0.09 for Danish Jersey, and 0.37 for Dutch Holstein Friesian. We conclude that milk orotic acid can be predicted with moderate to good accuracy based on infrared milk spectra and that infrared-predicted orotic acid is heritable. The availability of a cheap and fast method to predict milk orotic acid opens up possibilities to study the largely unknown functions of milk orotic acid.

OriginalsprogEngelsk
TidsskriftJournal of Dairy Science
Vol/bind103
Nummer4
Sider (fra-til)3334-3348
Antal sider15
ISSN0022-0302
DOI
StatusUdgivet - apr. 2020

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