Dataset Information

Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle.

ABSTRACT: The milk fat profile of the Danish Holstein (DH) and Danish Jersey (DJ) show clear differences. Identification of the genomic regions, genes and biological pathways underlying the milk fat biosynthesis will improve the understanding of the biology underlying bovine milk fat production and may provide new possibilities to change the milk fat composition by selective breeding. In this study a genome wide association scan (GWAS) in the DH and DJ was performed for a detailed milk fatty acid (FA) profile using the HD bovine SNP array and subsequently a biological pathway analysis based on the SNP data was performed.The GWAS identified in total 1,233 SNPs (FDR < 0.10) spread over 18 chromosomes for nine different FA traits for the DH breed and 1,122 SNPs (FDR < 0.10) spread over 26 chromosomes for 13 different FA traits were detected for the DJ breed. Of these significant SNPs, 108 SNP markers were significant in both DH and DJ (C14-index, BTA26; C16, BTA14; fat percentage (FP), BTA14). This was supported by an enrichment test. The QTL on BTA14 and BTA26 represented the known candidate genes DGAT and SCD. In addition we suggest ACSS3 to be a good candidate gene for the QTL on BTA5 for C10:0 and C15:0. In addition, genetic correlations between the FA traits within breed showed large similarity across breeds. Furthermore, the biological pathway analysis revealed that fat digestion and absorption (KEGG04975) plays a role for the traits FP, C14:1, C16 index and C16:1.There was a clear similarity between the underlying genetics of FA in the milk between DH and DJ. This was supported by the fact that there was substantial overlap between SNPs for FP, C14 index, C14:1, C16 index and C16:1. In addition genetic correlations between FA showed a similar pattern across DH and DJ. Furthermore the biological pathway analysis suggested that fat digestion and absorption KEGG04975 is important for the traits FP, C14:1, C16 index and C16:1.

SUBMITTER: Buitenhuis B

PROVIDER: S-EPMC4377848 | biostudies-other | 2014

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle.

Buitenhuis Bart B Janss Luc L G LL Poulsen Nina A NA Larsen Lotte B LB Larsen Mette K MK Sørensen Peter P

BMC genomics 20141215

<h4>Background</h4>The milk fat profile of the Danish Holstein (DH) and Danish Jersey (DJ) show clear differences. Identification of the genomic regions, genes and biological pathways underlying the milk fat biosynthesis will improve the understanding of the biology underlying bovine milk fat production and may provide new possibilities to change the milk fat composition by selective breeding. In this study a genome wide association scan (GWAS) in the DH and DJ was performed for a detailed milk ...[more]

PMID: 25511820

Similar Datasets

Project description:BACKGROUND: Contemporary dairy breeding goals have broadened to include, along with milk production traits, a number of non-production-related traits in an effort to improve the overall functionality of the dairy cow. Increased indirect selection for resistance to mastitis, one of the most important production-related diseases in the dairy sector, via selection for reduced somatic cell count has been part of these broadened goals. A number of genome-wide association studies have identified genetic variants associated with milk production traits and mastitis resistance, however the majority of these studies have been based on animals which were predominantly kept in confinement and fed a concentrate-based diet (i.e. high-input production systems). This genome-wide association study aims to detect associations using genotypic and phenotypic data from Irish Holstein-Friesian cattle fed predominantly grazed grass in a pasture-based production system (low-input). RESULTS: Significant associations were detected for milk yield, fat yield, protein yield, fat percentage, protein percentage and somatic cell score using separate single-locus, frequentist and multi-locus, Bayesian approaches. These associations were detected using two separate populations of Holstein-Friesian sires and cows. In total, 1,529 and 37 associations were detected in the sires using a single SNP regression and a Bayesian method, respectively. There were 103 associations in common between the sires and cows across all the traits. As well as detecting associations within known QTL regions, a number of novel associations were detected; the most notable of these was a region of chromosome 13 associated with milk yield in the population of Holstein-Friesian sires. CONCLUSIONS: A total of 276 of novel SNPs were detected in the sires using a single SNP regression approach. Although obvious candidate genes may not be initially forthcoming, this study provides a preliminary framework upon which to identify the causal mechanisms underlying the various milk production traits and somatic cell score. Consequently this will deepen our understanding of how these traits are expressed.

Project description:BackgroundKetosis in dairy cattle has been shown to cause a high morbidity in the farm and substantial financial losses to dairy farmers. Ketosis symptoms, however, are difficult to identify, therefore, the amount of ketone bodies (mainly β-hydroxybutyric acid, BHB) is used as an indicator of subclinical ketosis in cows. It has also been shown that milk BHB concentrations have a strong correlation with ketosis in dairy cattle. Mid-infrared spectroscopy (MIR) has recently became a fast, cheap and high-throughput method for analyzing milk components. The aim of this study was to perform a genome-wide association study (GWAS) on the MIR-predicted milk BHB to identify genomic regions, genes and pathways potentially affecting subclinical ketosis in North American Holstein dairy cattle.ResultsSeveral significant regions were identified associated with MIR-predicted milk BHB concentrations (indicator of subclinical ketosis) in the first lactation (SCK1) and second and later lactations (SCK2) in Holstein dairy cows. The strongest association was located on BTA6 for SCK1 and BTA14 on SCK2. Several SNPs on BTA6 were identified in regions and variants reported previously to be associated with susceptibility to ketosis and clinical mastitis in Jersey and Holstein dairy cattle, respectively. One highly significant SNP on BTA14 was found within the DGAT1 gene with known functions on fat metabolism and inflammatory response in dairy cattle. A region on BTA6 and three SNPs on BTA20 were found to overlap between SCK1 and SCK2. However, a novel region on BTA20 (55-63 Mb) for SCK2 was also identified, which was not reported in previous association studies. Enrichment analysis of the list of candidate genes within the identified regions for MIR-predicted milk BHB concentrations yielded molecular functions and biological processes that may be involved in the inflammatory response and lipid metabolism in dairy cattle.ConclusionsThe results of this study confirmed several SNPs and genes identified in previous studies as associated with ketosis susceptibility and immune response, and also found a novel region that can be used for further analysis to identify causal variations and key regulatory genes that affect clinical/ subclinical ketosis.

Project description:Recently, Jersey cattle was introduced and produced by embryo transfer to Korea. This study was conducted to investigate the differences of milk compositions between Jersey and Holstein cows and the relationship between days in milk (DIM) and milk compositions during early lactation. Data were collected from twelve lactating cows from Department of Animal Resources Development at National Institute of Animal Science. Cows in parity 1 were used, and calved at spring from April to March of 2017. All cows were housed in two sections within a free-stall barn, which divided into six from each breed, and received a basal total mixed ration. Milk samples of each cow were collected at 3 DIM and 30 DIM for analyzing the milk compositions, including fatty acids (FA), amino acids and minerals. Total solids, citrate, and milk urea nitrogen level were differed between the breeds (p < 0.05). As DIM went from 3 to 30, milk protein, total solids, and somatic cell count decreased (p < 0.05), but lactose increased in all breed milk (p < 0.05). Citrate and free fatty acid (FFA) elevated in Jersey milk (p < 0.05), whereas reduced in Holstein milk (p < 0.05). Proportions of some individual FA varied from the breeds. Myristic (C14:0), palmitic (C16:0), and arachidonic acid (C20:4) in milk from all cows were higher at 3 DIM than at 30 DIM (p < 0.05). Also, stearic (C18:0) and oleic acid (C18:1) were lower at 3 DIM than at 30 DIM (p < 0.05), and the C18:1 to C18:0 ratio was significantly differed in DIM × breed interactions (p < 0.05). The contents of the individual amino acids did not differ from the breeds. Calcium, phosphorous, magnesium, and zinc (Zn) contents was significantly increased in Holstein milk than Jersey milk at 3 DIM. Also, K and Zn concentrations were higher in Holstein milk than in Jersey milk at 30 DIM (p < 0.05). It was concluded that Jersey cows would produce more effective milk in processing dairy products and more proper energy status compared with Holstein cows in early lactation under the same environmental and nutritional conditions.

Dataset Information

Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle.

Publications

Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets