1. Genotyping, physicochemical characterization, and protein isoform quantification of β-casein A2 milk in chinese simmental and Angus cattle.
- Author
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Prabakusuma, Adhita Sri, Aleryani, Hamzah, Xiaoyan Kong, Xianwei Shi, and Aixiang Huang
- Subjects
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ABERDEEN-Angus cattle , *SIMMENTAL cattle , *CASEINS , *MILK proteins , *ENZYME-linked immunosorbent assay , *MILK , *ISOELECTRIC point - Abstract
The recent findings on β-casein (β-CN) A2 cattle’s milk variant have triggered global research interest, as it is claimed to be a safer choice for human health. Only a few studies have been performed to investigate the presence of β-CN A1 and A2 alleles of the CSN2 gene in dual-purpose Simmental and Angus cattle in Yunnan province, China. This present study aimed to genotype cattle producing A2 milk, predict the physicochemical properties, and quantify the isoform concentration of β-CN A2 protein. Blood samples were collected from 286 cattle (201 Simmental and 85 Angus breeds). Genotyping was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) coupled with the sequencing method. Physicochemical properties were predicted using several web-based bioinformatics tools. A sandwich enzyme-linked immunosorbent assay (ELISA) was used to measure β-CN A2 protein isoform concentration in fresh A2 milk. Allele frequencies of β-CN A2 were more dominant in Simmental (0.642) and Angus (0.835) than A1. The β-CN A1A2 genotype was most frequent in Simmental (44.8%), while A2A2 genotype was primarily found in Angus (70.6%). The predicted monoisotopic mass, molecular weight, isoelectric point (pI), net charge at pH 7, total number of atoms, instability index, and grand average of hydropathicity (GRAVY) of β-CN A2 were 23,567.23 Da, 23,582.30 Da, 5.24, –6.5, 3,357, 96.53, and –0.355, respectively. The β-CN A2 protein isoform concentration in Angus (17.8 ng/ml) was higher than in Simmental (16.7 ng/ml). Identifying β-CN A2 milk provides new insights for screening favorable alleles and establishing breeding programs based on marker-assisted selection. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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