Genetic parameters for noncoagulating milk, milk coagulation properties, and detailed milk composition in Swedish Red Dairy Cattle.

The rennet-induced coagulation ability of milk is important in cheese production. For Swedish Red Dairy Cattle (RDC), this ability is reduced because of a high prevalence of noncoagulating (NC) milk. In this study, we simultaneously combined genetic parameters for NC milk, milk coagulation properties, milk composition, physical traits, and milk protein composition. Our aim was to estimate heritability and genetic and phenotypic correlations for NC milk and 24 traits (milk coagulation properties, milk composition, physical traits, and milk protein composition). Phenotypes and ∼7,000 SNP genotypes were available for all 600 Swedish RDC. The genotypes were imputed from ∼7,000 SNP to 50,000 SNP. Variance components and genetic parameters were estimated with an animal model. In Swedish RDC, a moderate heritability estimate of 0.28 was found for NC milk. For the other 24 traits, heritability estimates ranged from 0.12 to 0.77 (standard errors from 0.08 to 0.18). A total of 300 phenotypic and genetic correlations were estimated. For phenotypic and genetic correlations, 172 and 95 were significant, respectively. In general, most traits showing significant genetic correlations also showed significant phenotypic correlations. In this study, phenotypic and genetic correlations with NC milk suggest that many correlations between traits exist, making it difficult to predict the real consequences on the composition of milk, if selective breeding is applied on NC milk. We speculate that some of these consequences may lead to changes in the composition of milk, most likely affecting its physical and organoleptic properties. However, our results suggest that κ-casein could be used as an indicator trait to predict the occurrence of NC milk at the herd level.

Effects of milk proteins and posttranslational modifications on noncoagulating milk from Swedish Red dairy cattle.

Milk that does not coagulate after rennet addition, also called noncoagulating (NC) milk, is unwanted in cheese production due to prolonged processing time. Amounts of whey and casein proteins, genetic variants, as well as posttranslational modifications (PTM) of proteins are all contributing factors in rennet-induced coagulation of milk. In this study, we conducted a wide-ranging investigation of milk proteins in milk samples from 616 Swedish Red dairy cattle using liquid chromatography-high resolution mass spectrometry. Relative concentration of proteins, genetic variants, and PTM were compared between NC milk and coagulating milk. The PTM investigated were phosphorylation of caseins and glycosylation of κ-casein. Several genetic variants and PTM were found, including rare phosphorylation variants of the αS-caseins. Genetic variants were found to effect the expressed amount of different proteins. Further, the effect of protein amounts and PTM on a binary NC milk trait was modeled using a generalized linear model. The model showed that NC milk significantly correlated with higher relative concentrations of α-lactalbumin and ß-casein and lower relative concentrations of ß-lactoglobulin and κ-casein. Regarding PTM of caseins, an effect on NC milk from a lower relative concentration of αS1-casein with 8 phosphate groups were found, even though an effect from total relative concentration of αS1-casein was not found. This study has provided insights into protein variants and PTM important for NC milk to improve this undesirable property.

Genome-wide association study of normal and atypical progesterone profiles in Holstein-Friesian dairy cows.

Female fertility has a major role in dairy production and affects the profitability of dairy cattle. The genetic progress obtained by traditional selection can be slow because of the low heritability of classical fertility traits. Endocrine fertility traits based on progesterone concentration in milk have higher heritability and more directly reflect the cow's own reproductive physiology. The aim of our study was to identify genomic regions for 7 endocrine fertility traits in dairy cows by performing a genome-wide association study with 54,000 SNP. The next step was to fine-map targeted genomic regions with significant SNP using imputed sequences to identify potential candidate genes associated with the normal and atypical progesterone profiles. The association between a SNP and a phenotype was assessed by a single SNP analysis, using a linear mixed model that included a random polygenic effect. Phenotypes and genotypes were available for 1,126 primiparous and multiparous Holstein-Friesian cows from research herds in Ireland, the Netherlands, Sweden, and the United Kingdom. In total, 44 significant SNP associated with 7 endocrine fertility traits were identified on Bos taurus autosome (BTA) 1-4, 6, 8-9, 11-12, 14-17, 19, 21-24, and 29. Three chromosomes, BTA8, BTA17, and BTA23, were imputed from 54,000 SNP genotypes to the whole-genome sequence level with Beagle version 4.1. The fine-mapping identified several significant associations with delayed cyclicity, cessation of cyclicity, commencement of luteal activity, and inter-ovulatory interval. These associations may contribute to an index of markers for genetic improvement of fertility. Several potential candidate genes reported to affect reproduction were also identified in the targeted genomic regions. However, due to high linkage disequilibrium, it was not possible to identify putative causal genes or polymorphisms for any of the regions.

Genome-wide association study for αS1- and αS2-casein phosphorylation in Dutch Holstein Friesian.

Phosphorylation of caseins (CN) is a crucial post-translational modification that allows caseins to form colloid particles known as casein micelles. Both αS1- and αS2-CN show varying degrees of phosphorylation (isoforms) in cow milk and were suggested to be more relevant for stabilizing internal micellar structure than ß- and κ-CN. However, little is known about the genetic background of individual αS2-CN phosphorylation isoforms and the phosphorylation degrees of αS1- and αS2-CN (αS1-CN PD and αS2-CN PD), defined as the proportion of isoforms with higher degrees of phosphorylation in total αS1- and αS2-CN, respectively. We aimed to identify genomic regions associated with these traits using 50K single nucleotide polymorphisms for 1,857 Dutch Holstein Friesian cows. A total of 10 quantitative trait loci (QTL) regions were identified for all studied traits on 10 Bos taurus autosomes (BTA1, 2, 6, 9, 11, 14, 15, 18, 24, and 28). Regions associated with multiple traits were found on BTA1, 6, 11, and 14. We showed 2 QTL regions on BTA1, one affecting αS2-CN production and the other harboring the SLC37A1 gene, which encodes a phosphorus antiporter and affects αS1- and αS2-CN PD. The QTL on BTA6 harbors the casein gene cluster and affects individual αS2-CN phosphorylation isoforms. The QTL on BTA11 harbors the PAEP gene that encodes for ß-lactoglobulin and affects relative concentrations of αS2-CN-10P and αS2-CN-11P as well as αS1-CN PD and αS2-CN PD. The QTL on BTA14 harbors the DGAT1 gene and affects relative concentrations of αS2-CN-10P and αS2-CN-11P as well as αS1-CN PD and αS2-CN PD. Our results suggest that effects of identified genomic regions on phosphorylation of αS1- and αS2-CN are related to changes in milk synthesis and phosphorus secretion in milk. The actual roles of SLC37A1, PAEP, and DGAT1 in αS1- and αS2-CN phosphorylation in Dutch Holstein Friesian require further investigation.

Fine-mapping of BTA17 using imputed sequences for associations with de novo synthesized fatty acids in bovine milk.

The aim of this study was to fine-map a genomic region associated with milk fatty acids (FA) on Bos taurus autosome (BTA) 17. This genomic region has been discovered with 50,000 (50k) single nucleotide polymorphisms (SNP) imputed to 777,000 (777k) SNP. In this study, high-density genotypes were imputed to whole-genome sequences level to identify candidate gene(s) associated with milk FA composition on BTA17. Phenotypes and genotypes were available for 1,640 cows sampled in winter, and for 1,581 cows sampled in summer. Phenotypes consisted of gas chromatography measurements in winter and in summer milk samples of 6 individual FA and the indicator of de novo synthesis, C6:0-C14:0. Genotypes consisted of imputed 777k SNP, and 89 sequenced ancestors of the population of genotyped cows. In addition, 450 whole-genome sequences from the 1,000 Bull Genome Consortium were available. Using 495 Holstein-Friesian sequences as a reference population, the 777k SNP genotypes of the cows were imputed to sequence level. We then applied single-variant analyses with an animal model, and identified thousands of significant associations with C6:0, C8:0, C10:0, C12:0, C14:0, and C6:0-C14:0. For C8:0 in summer milk samples, the genomic region located between 29 and 34 Mbp on BTA17 revealed a total of 646 significant associations. The most significant associations [-log10(P-value) = 7.82] were 8 SNP in perfect linkage disequilibrium. After fitting one of these 8 SNP as a fixed effect in the model, and re-running the single-variant analyses, no further significant associations were found for any of the 6 FA or C6:0-C14:0. These findings suggest that one polymorphism underlying this QTL on BTA17 influences multiple de novo synthesized milk FA. Thirteen genes in the QTL region were identified and analyzed carefully. Six out of the 8 SNP that showed the strongest associations were located in the La ribonucleoprotein domain family, member 1B (LARP1B) gene, and we suggest LARP1B as a primary candidate gene. Another gene of interest for this QTL region might be PKL4. None of these suggested candidate genes have previously been associated with milk fat synthesis or milk FA composition.

A quantitative trait locus on Bos taurus autosome 17 explains a large proportion of the genetic variation in de novo synthesized milk fatty acids.

A genomic region associated with milk fatty acid (FA) composition has been detected on Bos taurus autosome (BTA)17 based on 50,000 (50K) single nucleotide polymorphism (SNP) genotypes. The aim of our study was to fine-map BTA17 with imputed 777,000 (777 K) SNP genotypes to identify candidate genes associated with milk FA composition. Phenotypes consisted of gas chromatography measurements of 14 FA based on winter and summer milk samples. Phenotypes and genotypes were available on 1,640 animals in winter milk, and on 1,581 animals in summer milk samples. Single-SNP analyses showed that several SNP in a region located between 29.0 and 34.0 Mbp were in strong association with C6:0, C8:0, and C10:0. This region was further characterized based on haplotypes. In summer milk samples, for example, these haplotypes explained almost 10% of the genetic variance in C6:0, 9% in C8:0, 3.5% in C10:0, 1.8% in C12:0, and 0.9% in C14:0. Two groups of haplotypes with distinct predicted effects could be defined, suggesting the presence of one causal variant. Predicted haplotype effects tended to increase from C6:0 to C14:0; however, the proportion of genetic variance explained by the haplotypes tended to decrease from C6:0 to C14:0. This is an indication that the quantitative trait locus (QTL) region is involved either in the elongation process or in early termination of de novo synthesized FA. Although many genes are present in this QTL region, most of these genes on BTA17 have not been characterized yet. The strongest association was found close to the progesterone receptor membrane component 2 (PGRMC2) gene, which has not yet been associated with milk FA composition. Therefore, no clear candidate gene associated with milk FA composition could be identified for this QTL.

Genomic selection in the French Lacaune dairy sheep breed.

Genomic selection aims to increase accuracy and to decrease generation intervals, thus increasing genetic gains in animal breeding. Using real data of the French Lacaune dairy sheep breed, the purpose of this study was to compare the observed accuracies of genomic estimated breeding values using different models (infinitesimal only, markers only, and joint estimation of infinitesimal and marker effects) and methods [BLUP, Bayes Cπ, partial least squares (PLS), and sparse PLS]. The training data set included results of progeny tests of 1,886 rams born from 1998 to 2006, whereas the validation set had results of 681 rams born in 2007 and 2008. The 3 lactation traits studied (milk yield, fat content, and somatic cell scores) had heritabilities varying from 0.14 to 0.41. The inclusion of molecular information, as compared with traditional schemes, increased accuracies of estimated breeding values of young males at birth from 18 up to 25%, according to the trait. Accuracies of genomic methods varied from 0.4 to 0.6, according to the traits, with minor differences among genomic approaches. In Bayes Cπ, the joint estimation of marker and infinitesimal effects had a slightly favorable effect on the accuracies of genomic estimated breeding values, and were especially beneficial for somatic cell counts, the less heritable trait. Inclusion of infinitesimal effects also improved slopes of predictive regression equations. Methods that select markers implicitly (Bayes Cπ and sparse PLS) were advantageous for some models and traits, and are of interest for further quantitative trait loci studies.