Although bovine milk is regarded as healthy and nutritious, its high content of saturated fatty acids (FA) may be harmful to cardiovascular health. Palmitic acid (C16:0) is the predominant saturated FA in milk with adverse health effects that could be countered by substituting it with higher levels of unsaturated FA, such as oleic acid (C18:1cis-9). In this work, we performed genome-wide association analyses for milk fatty acids predicted from FTIR spectroscopy data using 1811 Norwegian Red cattle genotyped and imputed to a high-density 777k single nucleotide polymorphism (SNP)-array. In a follow-up analysis, we used imputed whole-genome sequence data to detect genetic variants that are involved in FTIR-predicted levels of C16:0 and C18:1cis-9 and explore the transcript profile and protein level of candidate genes. Genome-wise significant associations were detected for C16:0 on Bos taurus (BTA) autosomes 11, 16 and 27, and for C18:1cis-9 on BTA5, 13 and 19. Closer examination of a significant locus on BTA11 identified the PAEP gene, which encodes the milk protein β-lactoglobulin, as a particularly attractive positional candidate gene. At this locus, we discovered a tightly linked cluster of genetic variants in coding and regulatory sequences that have opposing effects on the levels of C16:0 and C18:1cis-9. The favourable haplotype, linked to reduced levels of C16:0 and increased levels of C18:1cis-9 was also associated with a marked reduction in PAEP expression and β-lactoglobulin protein levels. β-lactoglobulin is the most abundant whey protein in milk and lower levels are associated with important dairy production parameters such as improved cheese yield. The genetic variants detected in this study may be used in breeding to produce milk with an improved FA health-profile and enhanced cheese-making properties.

The relative abundance of specific fatty acids in milk can be important for consumer health and manufacturing properties of dairy products. Understanding of genes controlling milk fat synthesis may contribute to the development of dairy products with high quality and nutritional value. This study aims to identify key genes and genetic variants affecting de novo synthesis of the short- and medium-chained fatty acids C4:0 to C14:0. A genome-wide association study using 609,361 SNP markers and 1,811 animals was performed to detect genomic regions affecting fatty acid levels. These regions were further refined using sequencing data to impute millions of additional genetic variants. Results suggest associations of PAEP with the content of C4:0, AACS with the content of fatty acids C4:0-C6:0, NCOA6 or ACSS2 with the longer chain fatty acids C6:0-C14:0, and FASN mainly associated with content of C14:0. None of the top-ranking markers caused amino acid shifts but were mostly situated in putatively regulating regions and suggested a regulatory role of the QTLs. Sequencing mRNA from bovine milk confirmed the expression of all candidate genes which, combined with knowledge of their roles in fat biosynthesis, supports their potential role in de novo synthesis of bovine milk fatty acids.

BACKGROUND:Bovine milk is widely regarded as a nutritious food source for humans, although the effects of individual fatty acids on human health is a subject of debate. Based on the assumption that genomic selection offers potential to improve milk fat composition, there is strong interest to understand more about the genetic factors that influence the biosynthesis of bovine milk and the molecular mechanisms that regulate milk fat synthesis and secretion. For this reason, the work reported here aimed at identifying genetic variants that affect milk fatty acid composition in Norwegian Red cattle. Milk fatty acid composition was predicted from the nation-wide recording scheme using Fourier transform infrared spectroscopy data and applied to estimate heritabilities for 36 individual and combined fatty acid traits. The recordings were used to generate daughter yield deviations that were first applied in a genome-wide association (GWAS) study with 17,343 markers to identify quantitative trait loci (QTL) affecting fatty acid composition, and next on high-density and sequence-level datasets to fine-map the most significant QTL on BTA13 (BTA for Bos taurus chromosome).RESULTS:The initial GWAS revealed 200 significant associations, with the strongest signals on BTA1, 13 and 15. The BTA13 QTL highlighted a strong functional candidate gene for de novo synthesis of short- and medium-chained saturated fatty acids; acyl-CoA synthetase short-chain family member 2. However, subsequent fine-mapping using single nucleotide polymorphisms (SNPs) from a high-density chip and variants detected by resequencing showed that the effect was more likely caused by a second nearby gene; nuclear receptor coactivator 6 (NCOA6). These findings were confirmed with results from haplotype studies. NCOA6 is a nuclear receptor that interacts with transcription factors such as PPARγ, which is a major regulator of bovine milk fat synthesis.CONCLUSIONS:An initial GWAS revealed a highly significant QTL for de novo-synthesized fatty acids on BTA13 and was followed by fine-mapping of the QTL within NCOA6. The most significant SNPs were either synonymous or situated in introns; more research is needed to uncover the underlying causal DNA variation(s).

Background: Clinical mastitis is an inflammation of the mammary gland and causes significant costs to dairy production. It is unfavourably genetically correlated to milk production, and, thus, knowledge of the mechanisms that underlie these traits would be valuable to improve both of them simultaneously through breeding. A quantitative trait locus (QTL) that affects both clinical mastitis and milk production has recently been fine-mapped to around 89 Mb on bovine chromosome 6 (BTA6), but identification of the gene that underlies this QTL was not possible due to the strong linkage disequilibrium between single nucleotide polymorphisms (SNPs) within this region. Our aim was to identify the gene and, if possible, the causal polymorphism(s) responsible for this QTL through association analysis of high-density SNPs and imputed full sequence data in combination with analyses of transcript and protein levels of the identified candidate gene.Results: Associations between SNPs and the studied traits were strongest for SNPs that were located within and immediately upstream of the group-specific component (GC) gene. This gene encodes the vitamin D-binding protein (DBP) and has multiple roles in immune defense and milk production. A 12-kb duplication that was identified downstream of this gene covered its last exon and segregated with the QTL allele that is associated with increased mastitis susceptibility and milk production. However, analyses of GC mRNA levels on the available samples revealed no differences in expression between animals having or lacking this duplication. Moreover, we detected no differences in the concentrations of DBP and its ligand vitamin D between the animals with different GC genotypes that were available for this study.Conclusions: Our results suggest GC as the gene that underlies the QTL for clinical mastitis and milk production. However, since only healthy animals were sampled for transcription and expression analyses, we could not draw any final conclusion on the absence of quantitative differences between animals with different genotypes. Future studies should investigate GC RNA expression and protein levels in cows with different genotypes during an infection.

A high resolution SNP map was constructed for the bovine casein region to identify haplotype structures and study associations with milk traits in Norwegian Red cattle. Our analyses suggest separation of the casein cluster into two haplotype blocks, one consisting of the CSN1S1 , CSN2 and CSN1S2 genes and another one consisting of the CSN3 gene. Highly significant associations with both protein and milk yield were found for both single SNPs and haplotypes within the CSN1S1-CSN2-CSN1S2 haplotype block. In contrast, no significant association was found for single SNPs or haplotypes within the CSN3 block. Our results point towards CSN2 and CSN1S2 as the most likely loci harbouring the underlying causative DNA variation. In our study, the most significant results were found for the SNP CSN2_67 with the C allele consistently associated with both higher protein and milk yields. CSN2_67 calls a C to an A substitution at codon 67 in β-casein gene resulting in histidine replacing proline in the amino acid sequence. This polymorphism determines the protein variants A1/B ( CSN2_67 A allele) versus A2/A3 ( CSN2_67 C allele). Other studies have suggested that a high consumption of A1/B milk may affect human health by increasing the risk of diabetes and heart diseases. Altogether these results argue for an increase in the frequency of the CSN2_67 C allele or haplotypes containing this allele in the Norwegian Red cattle population by selective breeding.

Genotype-by-environment interactions for production traits in dairy cattle have often been observed, while QTL analyses have focused on detecting genes with general effects on production traits. In this study, a QTL search for genes with environmental interaction for the traits milk yield, protein yield, and fat yield were performed on Bos taurus autosome 6 (BTA6), also including information about the previously investigated candidate genes ABCG2 and OPN. The animals in the study were Norwegian Red. Eighteen grandsires and 716 sires were genotyped for 362 markers on BTA6. Every marker bracket was regarded as a putative QTL position. The effects of the candidate genes and the putative QTL were modeled as a regression on an environmental parameter (herd year), which is based on the predicted herd-year effect for the trait. Two QTL were found to have environmentally dependent effects on milk yield. These QTL were located 3.6 cM upstream and 9.1 cM downstream from ABCG2. No environmentally dependent QTL was found to significantly affect protein or fat yield.

BACKGROUND:Our group has previously identified a quantitative trait locus (QTL) affecting fat and protein percentages on bovine chromosome 6, and refined the QTL position to a 420-kb interval containing six genes. Studies performed in other cattle populations have proposed polymorphisms in two different genes (ABCG2 and OPN) as the underlying functional QTL nucleotide. Due to these conflicting results, we have included these QTNs, together with a large collection of new SNPs produced from PCR sequencing, in a dense marker map spanning the QTL region, and reanalyzed the data using a combined linkage and linkage disequilibrium approach.RESULTS:Our results clearly exclude the OPN SNP (OPN_3907) as causal site for the QTL. Among 91 SNPs included in the study, the ABCG2 SNP (ABCG2_49) is clearly the best QTN candidate. The analyses revealed the presence of only one QTL for the percentage traits in the tested region. This QTL was completely removed by correcting the analysis for ABCG2_49. Concordance between the sires' marker genotypes and segregation status for the QTL was found for ABCG2_49 only. The C allele of ABCG2_49 is found in a marker haplotype that has an extremely negative effect on fat and protein percentages and positive effect on milk yield. Of the 91 SNPs, ABCG2_49 was the only marker in perfect linkage disequilibrium with the QTL.CONCLUSION:Based on our results, OPN_3907 can be excluded as the polymorphism underlying the QTL. The results of this and other papers strongly suggest the [A/C] mutation in ABCG2_49 as the causal mutation, although the possibility that ABCG2_49 is only a marker in perfect LD with the true mutation can not be completely ruled out.

Norway has a field recording system for dairy cattle that includes recording of all veterinary treatments on an individual animal basis from 1978 onwards. Application of these data in a genome search for quantitative trait loci (QTL) verified genome-wise significant QTL affecting clinical mastitis on Chromosome (Chr) 6. Additional putative QTL for clinical mastitis were localized to Chrs. 3, 4, 14, and 27. The comprehensive field recording system includes information on somatic cell count as well. This trait is often used in selection against mastitis when direct information on clinical mastitis is not available. The absence of common QTL positions for the two traits in our study indicates that the use of somatic cell count data in QTL studies aimed for reducing the incidence of mastitis should be carefully evaluated.