A better understanding of the role of the major genes coding for milk protein fractions should be pursued for improving dairy cattle breeding programs. The aim of the present work was to study the effect of the CSN2, CSN3 and BLG genes on the major protein fractions (αs1-CN, αs2-CN, β-CN, κ-CN, β-LG, α-LA), expressed qualitatively as percentage of total nitrogen content (%N) and quantitatively as content in milk (g/l). A total of 1,264 Brown Swiss cows were sampled individually in 85 commercial herds in North-East Italy, and 989 cows were genotyped using the Illumina Bovine SNP50 v.2 BeadChip, from which 37,519 SNP markers were used. The Reversed-Phase High Performance Liquid Chromatography was used for quantifying the content of the six major milk protein fractions, with β-CN, κ-CN and β-LG genetic variants being quantified separately. The protein fractions were analysed using a Bayesian animal model implemented via Gibbs sampling. Effects of days in milk, parity order and the CSN2, CSN3 and BLG genotypes were assigned flat priors; herd and animal additive effects were assigned Gaussian prior distributions. Marginal posterior distributions of parameters of interest were compared between the standard animal model and the mixed inheritance model (i.e. the one with the protein loci included in the model). Results indicated that a considerable portion of the genetic variance was explained by the effect of the three major genes for most of the protein fractions. In particular, the CSN2, CSN3 and BLG genotypes affected not only the proteins they codify for, but also the synthesis of the other protein fractions. For the CSN genes, the B allele was associated with an overexpression of the protein synthesis compared to the κ-CN A and β-CN A2. Conversely, the β-LG B was associated with a lower concentration of this protein compared with the β-LG A. Overall, the results could be useful for establishing more efficient selection programs aimed to improve the value of milk for dairy industry and also for consumer health.
On the role of CSN2, CSN3 and BLG genes on the milk protein profile of Brown Swiss cows
N. Amalfitano;Lucio Mota;A. Cecchinato;G. Bittante
2020
Abstract
A better understanding of the role of the major genes coding for milk protein fractions should be pursued for improving dairy cattle breeding programs. The aim of the present work was to study the effect of the CSN2, CSN3 and BLG genes on the major protein fractions (αs1-CN, αs2-CN, β-CN, κ-CN, β-LG, α-LA), expressed qualitatively as percentage of total nitrogen content (%N) and quantitatively as content in milk (g/l). A total of 1,264 Brown Swiss cows were sampled individually in 85 commercial herds in North-East Italy, and 989 cows were genotyped using the Illumina Bovine SNP50 v.2 BeadChip, from which 37,519 SNP markers were used. The Reversed-Phase High Performance Liquid Chromatography was used for quantifying the content of the six major milk protein fractions, with β-CN, κ-CN and β-LG genetic variants being quantified separately. The protein fractions were analysed using a Bayesian animal model implemented via Gibbs sampling. Effects of days in milk, parity order and the CSN2, CSN3 and BLG genotypes were assigned flat priors; herd and animal additive effects were assigned Gaussian prior distributions. Marginal posterior distributions of parameters of interest were compared between the standard animal model and the mixed inheritance model (i.e. the one with the protein loci included in the model). Results indicated that a considerable portion of the genetic variance was explained by the effect of the three major genes for most of the protein fractions. In particular, the CSN2, CSN3 and BLG genotypes affected not only the proteins they codify for, but also the synthesis of the other protein fractions. For the CSN genes, the B allele was associated with an overexpression of the protein synthesis compared to the κ-CN A and β-CN A2. Conversely, the β-LG B was associated with a lower concentration of this protein compared with the β-LG A. Overall, the results could be useful for establishing more efficient selection programs aimed to improve the value of milk for dairy industry and also for consumer health.
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