Dataset Information

Influence of the Casein Composite Genotype on Milk Quality and Coagulation Properties in the Endangered Agerolese Cattle Breed.

ABSTRACT: The aim of this study was the characterization of CSN1S1, CSN2 and CSN3 genetic variability in Agerolese cattle, and the investigation of the effect of casein composite genotypes (CSN1S1, CSN2 and CSN3) on quality and coagulation traits of the corresponding milk. To these purposes, blood and milk from 84 cows were sampled and analysed. Allele frequencies at CSN2 and CSN3 revealed no Hardy-Weinberg equilibrium in the population with a prevalence of allele A2 for CSN2 and allele B for CSN3. BBA1A2AB and BBA2A2AB composite genotypes were the most common in the population. BBA1A2AB showed a higher total solids and fat content (12.70 ± 0.16 and 3.93 ± 0.10, respectively), while BBA2A2BB showed the best coagulation properties (RCT 12.62 ± 0.81; k20 5.84 ± 0.37; a30 23.72 ± 1.10). Interestingly, the A2 allele of CSN2 was very widespread in the population; thus, it will be intriguing to verify if A2A2 Agerolese cattle milk and the derived cheese may have better nutraceutical characteristics.

SUBMITTER: Albarella S

PROVIDER: S-EPMC7278449 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Influence of the Casein Composite Genotype on Milk Quality and Coagulation Properties in the Endangered Agerolese Cattle Breed.

Albarella Sara S Selvaggi Maria M D'Anza Emanuele E Cosenza Gianfranco G Caira Simonetta S Scaloni Andrea A Fontana Annunziata A Peretti Vincenzo V Ciotola Francesca F

Animals : an open access journal from MDPI 20200520 5

The aim of this study was the characterization of CSN1S1, CSN2 and CSN3 genetic variability in Agerolese cattle, and the investigation of the effect of casein composite genotypes (CSN1S1, CSN2 and CSN3) on quality and coagulation traits of the corresponding milk. To these purposes, blood and milk from 84 cows were sampled and analysed. Allele frequencies at CSN2 and CSN3 revealed no Hardy-Weinberg equilibrium in the population with a prevalence of allele A2 for CSN2</ ...[more]

PMID: 32443876

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Project description:BackgroundGenome-wide association studies (GWAS) were performed at the sequence level to identify candidate mutations that affect the expression of six major milk proteins in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) dairy cattle. Whey protein (α-lactalbumin and β-lactoglobulin) and casein (αs1, αs2, β, and κ) contents were estimated by mid-infrared (MIR) spectrometry, with medium to high accuracy (0.59 ≤ R2 ≤ 0.92), for 848,068 test-day milk samples from 156,660 cows in the first three lactations. Milk composition was evaluated as average test-day measurements adjusted for environmental effects. Next, we genotyped a subset of 8080 cows (2967 MON, 2737 NOR, and 2306 HOL) with the BovineSNP50 Beadchip. For each breed, genotypes were first imputed to high-density (HD) using HD single nucleotide polymorphisms (SNPs) genotypes of 522 MON, 546 NOR, and 776 HOL bulls. The resulting HD SNP genotypes were subsequently imputed to the sequence level using 27 million high-quality sequence variants selected from Run4 of the 1000 Bull Genomes consortium (1147 bulls). Within-breed, multi-breed, and conditional GWAS were performed.ResultsThirty-four distinct genomic regions were identified. Three regions on chromosomes 6, 11, and 20 had very significant effects on milk composition and were shared across the three breeds. Other significant effects, which partially overlapped across breeds, were found on almost all the autosomes. Multi-breed analyses provided a larger number of significant genomic regions with smaller confidence intervals than within-breed analyses. Combinations of within-breed, multi-breed, and conditional analyses led to the identification of putative causative variants in several candidate genes that presented significant protein-protein interactions enrichment, including those with previously described effects on milk composition (SLC37A1, MGST1, ABCG2, CSN1S1, CSN2, CSN1S2, CSN3, PAEP, DGAT1, AGPAT6) and those with effects reported for the first time here (ALPL, ANKH, PICALM).ConclusionsGWAS applied to fine-scale phenotypes, multiple breeds, and whole-genome sequences seems to be effective to identify candidate gene variants. However, although we identified functional links between some candidate genes and milk phenotypes, the causality between candidate variants and milk protein composition remains to be demonstrated. Nevertheless, the identification of potential causative mutations that underlie milk protein composition may have immediate applications for improvements in cheese-making.

Project description:The accuracy of breeding values strongly depends on the population and herd structure, i.e., the number of animals considered in genetic evaluations and the size of contemporary groups (CGs). Local breeds are usually kept in small-sized family farms under alternative husbandry conditions. For such herd structure, consideration of classical herd or herd-test-day effects in CG modeling approaches implies only a few records per effect level. In consequence, the present study aimed on methodological evaluations of different herd clustering strategies, considering social-ecological and herd characteristics. In this regard, we considered 19 herds keeping cows from the small local population of German Black Pied cattle (Deutsches Schwarzbuntes Niederungsrind; DSN), 10 herds keeping Holstein Friesian (HF) cows and one mixed herd with HF and DSN cows. Herds were characterized for 106 variables, reflecting farm conditions, husbandry practices, feeding regime, herd management, herd fertility status, herd health status and breeding strategies as well as social-ecological descriptors. The variables were input data for different clustering approaches including agglomerative hierarchical clustering (AHC), partition around medoids (PAM), fuzzy clustering (FZC) and a clustering of variables combined with agglomerative hierarchical clustering (CoVAHC). The evaluation criterion was the average silhouette width (ASW), suggesting a CoVAHC application and consideration of four herd clusters (HCs) for herd allocation (ASW of 0.510). HC1 comprised the larger, half organic and half conventional DSN family farms, which generate their main income from milk production. HC2 consisted of small organic DSN family farms where cows are kept in tie stables. HC3 included the DSN sub-population from former East Germany, reflecting the large-scale farm types. The specialized HF herds were well separated and allocated to HC4. Generalized linear mixed models with appropriate link functions were applied to compare test-day and female fertility traits of 5538 cows (2341 DSN and 3197 HF) from the first three lactations among the four HCs. Least squares means for milk, fat and protein yield (Mkg, Fkg and Pkg) significantly differed between HC. The significant differences among the four HCs clearly indicate the influence of varying herd conditions on cow traits. The similarities of herds within HC suggested the application of HCs in statistical models for genetic evaluations for DSN. In this regard, we found an increase of accuracies of estimated breeding values of cows and sires and of heritabilities for milk yield when applying models with herd-cluster-test-day or herd-cluster-test-month effects compared to classical herd-test-day models. The identified increase for the number of cows and cow records in CG due to HC effects may be the major explanation for the identified superiority.

Dataset Information

Influence of the Casein Composite Genotype on Milk Quality and Coagulation Properties in the Endangered Agerolese Cattle Breed.

Publications

Influence of the Casein Composite Genotype on Milk Quality and Coagulation Properties in the Endangered Agerolese Cattle Breed.

Similar Datasets

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