Effects of the diacylglycerol o-acyltransferase 1 (DGAT1) K232A polymorphism on fatty acid, protein, and mineral composition of dairy cattle milk

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Phosphorylation of caseins (CN) is a crucial posttranslational modification that allows caseins to form colloid particles known as casein micelles. Both α S1and α S2 -CN show varying degrees of phosphorylation (isoforms) in cow milk and were suggested to be more relevant for stabilizing internal micellar structure than β-and κ-CN. However, little is known about the genetic background of individual α S2 -CN phosphorylation isoforms and the phosphorylation degrees of α S1 -and α S2 -CN (α S1 -CN PD and α S2 -CN PD), defined as the proportion of isoforms with higher degrees of phosphorylation in total α S1 -and α S2 -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 α S2 -CN production and the other harboring the SLC37A1 gene, which encodes a phosphorus antiporter and affects α S1 -and α S2 -CN PD. The QTL on BTA6 harbors the casein gene cluster and affects individual α S2 -CN phosphorylation isoforms. The QTL on BTA11 harbors the PAEP gene that encodes for β-lactoglobulin and affects relative concentrations of α S2 -CN-10P and α S2 -CN-11P as well as α S1 -CN PD and α S2 -CN PD. The QTL on BTA14 harbors the DGAT1 gene and affects relative concentrations of α S2 -CN-10P and α S2 -CN-11P as well as α S1 -CN PD and α S2 -CN PD. Our results suggest that effects of identified genomic regions on phosphorylation of α S1 -and α S2 -CN are related to changes in milk synthesis and phosphorus secretion in milk. The actual roles of SLC37A1, PAEP, and DGAT1 in α S1 -and α S2 -CN phosphorylation in Dutch Holstein Friesian require further investigation.

Section: Bta14supporting

confidence: 91%

Section: Bta14mentioning

confidence: 99%

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

Fang

Bovenhuis

Valenberg

et al. 2019

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“…These results are largely in agreement with data in the literature. According to Schennink et al (2007), Van Arendonk et al (2009, Duchemin et al (2013), and Bovenhuis et al (2016), the DGAT1 K allele is associated with a larger fraction of C16:0, and smaller fractions of C14:0 (also reported by Lu et al, 2015), and C18 UFA in milk. In addition, Duchemin et al (2013) reported an increase in milk C14:1 cis-9, C16:1 cis-9, and total SFA, and a decrease in total milk UFA for the DGAT1 K allele.…”

Section: Lactation Performance and Milk Fatty Acid Profilementioning

confidence: 92%

“…In addition, Duchemin et al (2013) reported an increase in milk C14:1 cis-9, C16:1 cis-9, and total SFA, and a decrease in total milk UFA for the DGAT1 K allele. Furthermore, according to Van Arendonk et al 2009, Lu et al (2015), and Bovenhuis et al (2016), the DGAT1 K allele is associated with increased contents of C15:0 and C17:0 in milk.…”

Section: Lactation Performance and Milk Fatty Acid Profilementioning

confidence: 95%

Linseed oil and DGAT1 K232A polymorphism: Effects on methane emission, energy and nitrogen metabolism, lactation performance, ruminal fermentation, and rumen microbial composition of Holstein-Friesian cows

Gastelen

Visker

Edwards

et al. 2017

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Complex interactions between rumen microbiota, cow genetics, and diet composition may exist. Therefore, the effect of linseed oil, DGAT1 K232A polymorphism (DGAT1), and the interaction between linseed oil and DGAT1 on CH and H emission, energy and N metabolism, lactation performance, ruminal fermentation, and rumen bacterial and archaeal composition was investigated. Twenty-four lactating Holstein-Friesian cows (i.e., 12 with DGAT1 KK genotype and 12 with DGAT1 AA genotype) were fed 2 diets in a crossover design: a control diet and a linseed oil diet (LSO) with a difference of 22 g/kg of dry matter (DM) in fat content between the 2 diets. Both diets consisted of 40% corn silage, 30% grass silage, and 30% concentrates (DM basis). Apparent digestibility, lactation performance, N and energy balance, and CH emission were measured in climate respiration chambers, and rumen fluid samples were collected using the oral stomach tube technique. No linseed oil by DGAT1 interactions were observed for digestibility, milk production and composition, energy and N balance, CH and H emissions, and rumen volatile fatty acid concentrations. The DGAT1 KK genotype was associated with a lower proportion of polyunsaturated fatty acids in milk fat, and with a higher milk fat and protein content, and proportion of saturated fatty acids in milk fat compared with the DGAT1 AA genotype, whereas the fat- and protein-corrected milk yield was unaffected by DGAT1. Also, DGAT1 did not affect nutrient digestibility, CH or H emission, ruminal fermentation or ruminal archaeal and bacterial concentrations. Rumen bacterial and archaeal composition was also unaffected in terms of the whole community, whereas at the genus level the relative abundances of some bacterial genera were found to be affected by DGAT1. The DGAT1 KK genotype was associated with a lower metabolizability (i.e., ratio of metabolizable to gross energy intake), and with a tendency for a lower milk N efficiency compared with the DGAT1 AA genotype. The LSO diet tended to decrease CH production (g/d) by 8%, and significantly decreased CH yield (g/kg of DM intake) by 6% and CH intensity (g/kg of fat- and protein-corrected milk) by 11%, but did not affect H emission. The LSO diet also decreased ruminal acetate molar proportion, the acetate to propionate ratio, and the archaea to bacteria ratio, whereas ruminal propionate molar proportion and milk N efficiency increased. Ruminal bacterial and archaeal composition tended to be affected by diet in terms of the whole community, with several bacterial genera found to be significantly affected by diet. These results indicate that DGAT1 does not affect enteric CH emission and production pathways, but that it does affect traits other than lactation characteristics, including metabolizability, N efficiency, and the relative abundance of Bifidobacterium. Additionally, linseed oil reduces CH emission independent of DGAT1 and affects the rumen microbiota and its fermentative activity.

“…In the separate analysis with the Dutch samples, significant associations were also detected with these traits, except C14:1. Previous studies have shown that the K allele of DGAT1 polymorphisms has a reducing effect in C14:0 (Schennink et al, 2008;Bovenhuis et al, 2016). Through reduction of C14:0, DGAT1 is also expected to affect the concentrations (%wt/wt) of C14:1.…”

Section: Detection Of Genomic Regions Under the Different Scenariosmentioning

confidence: 98%

Combining multi-population datasets for joint genome-wide association and meta-analyses: The case of bovine milk fat composition traits

Gebreyesus

Buitenhuis

Poulsen

et al. 2019

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In genome-wide association studies (GWAS), sample size is the most important factor affecting statistical power that is under control of the investigator, posing a major challenge in understanding the genetics underlying difficult-to-measure traits. Combining data sets available from different populations for joint or meta-analysis is a promising alternative to increasing sample sizes available for GWAS. Simulation studies indicate statistical advantages from combining raw data or GWAS summaries in enhancing quantitative trait loci (QTL) detection power. However, the complexity of genetics underlying most quantitative traits, which itself is not fully understood, is difficult to fully capture in simulated data sets. In this study, population-specific and combined-population GWAS as well as a meta-analysis of the population-specific GWAS summaries were carried out with the objective of assessing the advantages and challenges of different data-combining strategies in enhancing detection power of GWAS using milk fatty acid (FA) traits as examples. Gas chromatography (GC) quantified milk FA samples and high-density (HD) genotypes were available from 1,566 Dutch, 614 Danish, and 700 Chinese Holstein Friesian cows. Using the joint GWAS, 28 additional genomic regions were detected, with significant associations to at least 1 FA, compared with the populationspecific analyses. Some of these additional regions were also detected using the implemented meta-analysis. Furthermore, using the frequently reported variants of the diacylglycerol acyltransferase 1 (DGAT1) and stearoyl-CoA desaturase (SCD1) genes, we show that significant associations were established with more FA traits in the joint GWAS than the remaining scenarios. However, there were few regions detected in the population-specific analyses that were not detected using the joint GWAS or the meta-analyses. Our results show that combining multi-population data set can be a powerful tool to enhance detection power in GWAS for seldom-recorded traits. Detection of a higher number of regions using the meta-analysis, compared with any of the population-specific analyses also emphasizes the utility of these methods in the absence of raw multipopulation data sets to undertake joint GWAS.