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Assessment of milk quality based on bovine BAF60c gene mutation

Published online by Cambridge University Press:  15 August 2018

J. Liao Open the ORCID record for J. Liao [Opens in a new window] ,
T. Ku ,
Y. F. Liu  and
J. Zhao
J. Liao
Affiliation:
College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, Shaanxi 710119, China
T. Ku
Affiliation:
College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, Shaanxi 710119, China
Y. F. Liu*
Affiliation:
College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, Shaanxi 710119, China
J. Zhao
Affiliation:
College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, Shaanxi 710119, China
*
Author for correspondence: Y. F. Liu, E-mail: Yongfeng200@126.com
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Abstract

Monitoring milk quality traits and the classification of raw milk are important steps for generating high-quality dairy products. Given the important roles of the BRG1/BRM-associated factor 60c (BAF60c) gene in the regulation of physiological growth and production, the objective of the current study was to analyse the association between the BAF60c gene and milk quality and establish a gene-based method for pre-evaluating raw milk quality. For this purpose, DNA was isolated from 507 milk samples and genotyped using the polymerase chain reaction-restricted fragment length polymorphism method. Milk quality traits including milk protein percentage (MPP), milk fat percentage (MFP), lactose percentage (LP) and total solids content (TSC) were also evaluated from the same 507 milk samples. The newly found 6060 T > C mutation of the BAF60c gene was associated significantly with MPP and LP, but not with MFP and TSC. The results demonstrated that this mutation could be used for the pre-evaluation of MPP and LP; therefore, raw milk could be graded according to different genotypes.

Keywords

BAF60cbovine genomic DNAmilk qualitymutation
Type
Animal Research Paper
Information
The Journal of Agricultural Science , Volume 156 , Issue 4 , May 2018 , pp. 570 - 574
Copyright
Copyright © Cambridge University Press 2018 

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