Dataset Information

Genetic effects of FASN, PPARGC1A, ABCG2 and IGF1 revealing the association with milk fatty acids in a Chinese Holstein cattle population based on a post genome-wide association study.

ABSTRACT: A previous genome-wide association study deduced that one (ARS-BFGL-NGS-39328), two (Hapmap26001-BTC-038813 and Hapmap31284-BTC-039204), two (Hapmap26001-BTC-038813 and BTB-00246150), and one (Hapmap50366-BTA-46960) genome-wide significant single nucleotide polymorphisms (SNPs) associated with milk fatty acids were close to or within the fatty acid synthase (FASN), peroxisome proliferator-activated receptor gamma, coactivator 1 alpha (PPARGC1A), ATP-binding cassette, sub-family G, member 2 (ABCG2) and insulin-like growth factor 1 (IGF1) genes. To further confirm the linkage and reveal the genetic effects of these four candidate genes on milk fatty acid composition, genetic polymorphisms were identified and genotype-phenotype associations were performed in a Chinese Holstein cattle population.Nine SNPs were identified in FASN, among which SNP rs41919985 was predicted to result in an amino acid substitution from threonine (ACC) to alanine (GCC), five SNPs (rs136947640, rs134340637, rs41919992, rs41919984 and rs41919986) were synonymous mutations, and the remaining three (rs41919999, rs132865003 and rs133498277) were found in FASN introns. Only one SNP each was identified for PPARGC1A, ABCG2 and IGF1. Association studies revealed that FASN, PPARGC1A, ABCG2 and IGF1 were mainly associated with medium-chain saturated fatty acids and long-chain unsaturated fatty acids, especially FASN for C10:0, C12:0 and C14:0. Strong linkage disequilibrium was observed among ARS-BFGL-NGS-39328 and rs132865003 and rs134340637 in FASN (D´?>?0.9), and among Hapmap26001-BTC-038813 and Hapmap31284-BTC-039204 and rs109579682 in PPARGC1A (D´?>?0.9). Subsequently, haplotype-based analysis revealed significant associations of the haplotypes encompassing eight FASN SNPs (rs41919999, rs132865003, rs134340637, rs41919992, rs133498277, rs41919984, rs41919985 and rs41919986) with C10:0, C12:0, C14:0, C18:1n9c, saturated fatty acids (SFA) and unsaturated fatty acids (UFA) (P?=?0.0204 to P?

SUBMITTER: Li C

PROVIDER: S-EPMC4963957 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genetic effects of FASN, PPARGC1A, ABCG2 and IGF1 revealing the association with milk fatty acids in a Chinese Holstein cattle population based on a post genome-wide association study.

Li Cong C Sun Dongxiao D Zhang Shengli S Yang Shaohua S Alim M A MA Zhang Qin Q Li Yanhua Y Liu Lin L

BMC genetics 20160728

<h4>Background</h4>A previous genome-wide association study deduced that one (ARS-BFGL-NGS-39328), two (Hapmap26001-BTC-038813 and Hapmap31284-BTC-039204), two (Hapmap26001-BTC-038813 and BTB-00246150), and one (Hapmap50366-BTA-46960) genome-wide significant single nucleotide polymorphisms (SNPs) associated with milk fatty acids were close to or within the fatty acid synthase (FASN), peroxisome proliferator-activated receptor gamma, coactivator 1 alpha (PPARGC1A), ATP-binding cassette, sub-famil ...[more]

PMID: 27468856

Similar Datasets

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:Holstein cattle are well known for their high average milk yield but are more susceptible to disease and have lower fecundity than other breeds of cattle. The purpose of this study was to explore the relationship between ruminal metabolites and both milk performance and ruminal microbiota composition as a means of assessing the benefits of crossbreeding Montbéliarde and Holstein cattle. This experiment crossbred Holstein with Montbéliarde cattle, aimed to act as a reference for producing high-quality dairy products and improving the overall efficiency of dairy cattle breeding. Based on similar age, parity and lactation time, 46 cows were selected and divided into two groups (n = 23 per group) for comparison experiment and fed the same formula: Montbéliarde×Holstein (MH, DIM = 33.23 ± 5.61 d), Holstein (H, DIM = 29.27 ± 4.23 d). Dairy herd improvement (DHI) data is an important basis for evaluating the genetic quality of bulls, understanding the quality level of milk, and improving feeding management. We collected the DHI data of these cows in the early lactation, middle lactation and late lactation period of 10 months. The results showed that the average milk production and protein content in Montbéliarde×Holstein were 1.76 kg (34.41 kg to 32.65 kg, p > 0.05) and 0.1% (3.54 to 3.44%, p < 0.05) higher than in Holstein cattle. Moreover, milk from Montbéliarde×Holstein cattle had lesser somatic cell score (1.66 to 2.02) than Holstein cattle (p < 0.01). A total of 10 experimental cattle in early lactation were randomly selected in the two groups (Lactation time = 92.70 ± 6.81), and ruminal fluid were collected by oral gastric tube. Using 16S rRNA microbial sequencing, we compared the ruminal microbiota composition and found that Montbéliarde×Holstein cattle had a lower abundance of Alphaproteobacteria (p < 0.05) and higher abundance of Selenomonas than Holstein cattle (p < 0.05). These bacteria play roles in protein degradation, nitrogen fixation and lactic acid degradation. The abundance of Succiniclasticum was also greater in Montbéliarde×Holstein cattle (p = 0.053). Through ruminal metabolome analysis, we found that the levels of trans-ferulic acid, pyrrole-2-carboxylic acid, and quinaldic acid were significantly increased in Montbéliarde×Holstein cattle, while that of lathosterol was significantly decreased. The changes in the levels of these metabolites could confer improved antioxidant, anti-inflammatory, and antibacterial activities.

Project description:Milk oligosaccharides (MOs) can be prebiotic and antiadhesive, while fatty acids (MFAs) can be antimicrobial. Both have been associated with milk microbes or mammary gland inflammation in humans. Relationships between these milk components and milk microbes or inflammation have not been determined for cows and could help elucidate a novel approach for the dairy industry to promote desired milk microbial composition for improvement of milk quality and reduction of milk waste. We aimed to determine relationships among milk microbiota, MFAs, MOs, lactose, and somatic cell counts (SCC) from Holstein cows, using our previously published data. Raw milk samples were collected at three time points, ranging from early to late lactation. Data were analyzed using linear mixed-effects modeling and repeated-measures correlation. Unsaturated MFA and short-chain MFA had mostly negative relationships with potentially pathogenic genera, including Corynebacterium, Pseudomonas, and an unknown Enterobacteriaceae genus but numerous positive relationships with symbionts Bifidobacterium and Bacteroides. Conversely, many MOs were positively correlated with potentially pathogenic genera (e.g., Corynebacterium, Enterococcus, and Pseudomonas), and numerous MOs were negatively correlated with the symbiont Bifidobacterium. The neutral, nonfucosylated MO composed of eight hexoses had a positive relationship with SCC, while lactose had a negative relationship with SCC. One interpretation of these trends might be that in milk, MFAs disrupt primarily pathogenic bacterial cells, causing a relative increase in abundance of beneficial microbial taxa, while MOs respond to and act on pathogenic taxa primarily through antiadhesive methods. Further research is needed to confirm the potential mechanisms driving these correlations. IMPORTANCE Bovine milk can harbor microbes that cause mastitis, milk spoilage, and foodborne illness. Fatty acids found in milk can be antimicrobial and milk oligosaccharides can have antiadhesive, prebiotic, and immune-modulatory effects. Relationships among milk microbes, fatty acids, oligosaccharides, and inflammation have been reported for humans. To our knowledge, associations among the milk microbial composition, fatty acids, oligosaccharides, and lactose have not been reported for healthy lactating cows. Identifying these potential relationships in bovine milk will inform future efforts to characterize direct and indirect interactions of the milk components with the milk microbiota. Since many milk components are associated with herd management practices, determining if these milk components impact milk microbes may provide valuable information for dairy cow management and breeding practices aimed at minimizing harmful and spoilage-causing microbes in raw milk.

Project description:BackgroundMethane emission by ruminants has contributed considerably to the global warming and understanding the genomic architecture of methane production may help livestock producers to reduce the methane emission from the livestock production system. The goal of our study was to identify genomic regions affecting the predicted methane emission (PME) from volatile fatty acids (VFAs) indicators and VFA traits using imputed whole-genome sequence data in Iranian Holstein cattle.ResultsBased on the significant-association threshold (p < 5 × 10- 8), 33 single nucleotide polymorphisms (SNPs) were detected for PME per kg milk (n = 2), PME per kg fat (n = 14), and valeric acid (n = 17). Besides, 69 genes were identified for valeric acid (n = 18), PME per kg milk (n = 4) and PME per kg fat (n = 47) that were located within 1 Mb of significant SNPs. Based on the gene ontology (GO) term analysis, six promising candidate genes were significantly clustered in organelle organization (GO:0004984, p = 3.9 × 10- 2) for valeric acid, and 17 candidate genes significantly clustered in olfactory receptors activity (GO:0004984, p = 4 × 10- 10) for PME traits. Annotation results revealed 31 quantitative trait loci (QTLs) for milk yield and its components, body weight, and residual feed intake within 1 Mb of significant SNPs.ConclusionsOur results identified 33 SNPs associated with PME and valeric acid traits, as well as 17 olfactory receptors activity genes for PME traits related to feed intake and preference. Identified SNPs were close to 31 QTLs for milk yield and its components, body weight, and residual feed intake traits. In addition, these traits had high correlations with PME trait. Overall, our findings suggest that marker-assisted and genomic selection could be used to improve the difficult and expensive-to-measure phenotypes such as PME. Moreover, prediction of methane emission by VFA indicators could be useful for increasing the size of reference population required in genome-wide association studies and genomic selection.

Dataset Information

Genetic effects of FASN, PPARGC1A, ABCG2 and IGF1 revealing the association with milk fatty acids in a Chinese Holstein cattle population based on a post genome-wide association study.

Publications

Genetic effects of FASN, PPARGC1A, ABCG2 and IGF1 revealing the association with milk fatty acids in a Chinese Holstein cattle population based on a post genome-wide association study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets