H. Bovenhuis

Milk Fatty Acid Unsaturation : Genetic Parameters and Effects of Stearoyl-CoA Desaturase (SCD1) and Acyl CoA: Diacylglycerol Acyltransferase 1 (DGAT1)

With regard to human health aspects of milk fat, increasing the amount of unsaturated fatty acids in milk is an important selection objective. The cows diet has an influence on the degree of unsaturation, but literature suggests that genetics also plays a role. To estimate genetic variation in milk fatty acid unsaturation indices, milk fatty acid composition of 1,933 Dutch Holstein Friesian heifers was measured and unsaturation indices were calculated. An unsaturation index represents the concentration of the unsaturated product proportional to the sum of the unsaturated product and the saturated substrate. Intraherd heritabilities were moderate, ranging from 0.23 +/- 0.07 for conjugated linoleic acid (CLA) index to 0.46 +/- 0.09 for C16 index. We genotyped the cows for the SCD1 A293V and DGAT1 K232A polymorphisms, which are known to alter milk fatty acid composition. Both genes explain part of the genetic variation in unsaturation indices. The SCD1 V allele is associated with lower C10, C12, and C14 indices, and with higher C16, C18, and CLA indices in comparison to the SCD1 A allele, with no differences in total unsaturation index. In comparison to the DGAT1 K allele, the DGAT1 A allele is associated with lower C10, C12, C14, and C16 indices and with higher C18, CLA, and total indices. We conclude that selective breeding can contribute to higher unsaturation indices, and that selective breeding can capitalize on genotypic information of both the SCD1 A293V and the DGAT1 K232A polymorphism.

Effects of milk protein variants on the protein composition of bovine milk.

The effects of beta-lactoglobulin (beta-LG), beta-casein (beta-CN), and kappa-CN variants and beta-kappa-CN haplotypes on the relative concentrations of the major milk proteins alpha-lactalbumin (alpha-LA), beta-LG, alpha(S1)-CN, alpha(S2)-CN, beta-CN, and kappa-CN and milk production traits were estimated in the milk of 1,912 Dutch Holstein-Friesian cows. We show that in the Dutch Holstein-Friesian population, the allele frequencies have changed in the past 16 years. In addition, genetic variants and casein haplotypes have a major impact on the protein composition of milk and explain a considerable part of the genetic variation in milk protein composition. The beta-LG genotype was associated with the relative concentrations of beta-LG (A >> B) and of alpha-LA, alpha(S1)-CN, alpha(S2)-CN, beta-CN, and kappa-CN (B > A) but not with any milk production trait. The beta-CN genotype was associated with the relative concentrations of beta-CN and alpha(S2)-CN (A(2) > A(1)) and of alpha(S1)-CN and kappa-CN (A(1) > A(2)) and with protein yield (A(2) > A(1)). The kappa-CN genotype was associated with the relative concentrations of kappa-CN (B > E > A), alpha(S2)-CN (B > A), alpha-LA, and alpha(S1)-CN (A > B) and with protein percentage (B > A). Comparing the effects of casein haplotypes with the effects of single casein variants can provide better insight into what really underlies the effect of a variant on protein composition. We conclude that selection for both the beta-LG genotype B and the beta-kappa-CN haplotype A(2)B will result in cows that produce milk that is more suitable for cheese production.

Effect of lactation stage and energy status on milk fat composition of Holstein-Friesian cows

The effects of lactation stage, negative energy balance (NEB), and milk fat depression (MFD) were estimated on detailed milk fat composition in primiparous Holstein-Friesian cows. One morning milk sample was collected from each of 1,933 cows from 398 commercial Dutch herds in winter 2005. Milk fat composition was measured using gas chromatography, and fat and protein percentage were measured using infrared spectrometry. Each fatty acid changed 0.5 to 1 phenotypic standard deviation over lactation, except odd-chain C5:0 to C15:0, branched-chain fatty acids, and trans-10, cis-12 conjugated linoleic acid (CLA). The greatest change was an increase from 31.2 to 33.3% (wt/wt) for C16:0 from d 80 to 150 of lactation. Energy status was estimated for each cow as the deviation from each average lactation fat-to-protein ratio (FPdev). A high FPdev (>0.12) indicated NEB. Negative energy balance was associated with an increase in C16:0 (0.696 +/- 0.178) and C18:0 (0.467 +/- 0.093), which suggested mobilization of body fat reserves. Furthermore, NEB was associated with a decrease in odd-chain C5:0 to C15:0 (-0.084 +/- 0.020), which might reflect a reduced allocation of C3 components to milk fat synthesis. A low FPdev indicated MFD (<-0.12) and was associated with a decrease in C16:0 (-0.681 +/- 0.255) and C18:0 (-0.128 +/- 0.135) and an increase in total unsaturated fatty acids (0.523 +/- 0.227). The study showed that both lactation stage and energy balance significantly contribute to variation in milk fat composition and alter the activity of different fatty acid pathways.

Effect of polymorphisms in the FASN, OLR1, PPARGC1A, PRL and STAT5A genes on bovine milk-fat composition

The aim of our study was to estimate effects of polymorphisms in the ATP-binding cassette G2 (ABCG2), fatty acid synthase (FASN), oxidized low-density lipoprotein receptor 1 (OLR1), peroxysome proliferator-activated receptor-gamma coactivator-1alpha (PPARGC1A), prolactin (PRL) and signal transducer and activator of transcription 5A (STAT5A) genes on milk production traits and detailed milk-fat composition. Milk-fat composition phenotypes were available for 1905 Dutch Holstein-Friesian cows. First, the presence of each SNP in the Dutch Holstein-Friesian population was evaluated by direct sequencing of the PCR product surrounding the SNP in 22 proven Dutch Holstein-Friesian bulls. The ABCG2 SNP did not segregate in the bull population. Second, we genotyped the cows for the FASN(g.16024G>A), FASN(g.17924A>G), OLR1(g.8232C>A), PPARGC1A(c.1790+514G>A), PPARGC1A(c.1892+19G>A), PRL(g.8398G>A) and STAT5A(g.9501G>A) polymorphisms, and estimated genotype effects on milk production traits and milk-fat composition. FASN(g.17924A>G) and OLR(g.8232C>A) had a significant effect (P < 0.05) on milk-fat percentage. However, we were not able to confirm results reported in the literature that showed effects of all evaluated polymorphisms on milk-fat percentage or milk-fat yield. All polymorphisms showed significant effects (P < 0.05) on milk-fat composition. The polymorphisms in FASN and STAT5A, which had an effect on C14:0 and were located on chromosome 19, could not fully explain the quantitative trait locus for C14:0 that was previously detected on chromosome 19 in a genome-wide scan using linkage analysis.

Predicting bovine milk fat composition using infrared spectroscopy based on milk samples collected in winter and summer

It has recently been shown that Fourier transform infrared spectroscopy has potential for the prediction of detailed milk fat composition, even based on a limited number of observations. Therefore, there seems to be an opportunity for improvement by means of using more observations. The objective of this study was to verify whether the use of more data would add to the accuracy of predicting milk fat composition. In addition, the effect of season on modeling was quantified because large differences in milk fat composition between winter and summer samples exist. We concluded that the use of 3,622 observations does increase predictability of milk fat composition based on infrared spectroscopy. However, for fatty acids with low concentrations, the use of many observations does not increase predictability to a level at which application of the model becomes obvious. Furthermore, the effect of season on validation r-square was limited but was occasionally large on prediction bias. For fatty acids that show large differences in level and standard deviation between winter and summer, a representative sample that includes observations collected in various seasons is critical for unbiased prediction. This research shows that all major fatty acids, combined groups of fatty acids, and the ratio of saturated to unsaturated fatty acids can be predicted accurately.

Whole genome scan for quantitative trait loci affecting body weight in chickens using a three generation design

Abstract An experimental population containing 10 full sib families of a cross between two broiler lines was created. In this population blood samples from 20 full sib animals in generation 1 and 451 full sib animals in generation 2 were used for marker genotyping. Data on body weight at slaughter age (48 days) collected in a feed conversion experiment with 2049 individually housed grandoffspring was analysed. Large differences in mean and variance between male and female body weight were found. To account for these differences, a bivariate analysis treating body weight of males and females as separate traits was used to estimate (co)variance components and breeding values. The model accounted for systematic environmental effects and maternal effects. The estimated heritability of body weight was 0.28 in the males and 0.33 in the females and the genetic correlation between male and female body weight did not significantly deviate from unity. Estimated breeding values, fixed and maternal genetic effects were used to calculate average adjusted progeny trait values for all generation 2 animals adjusted for fixed and maternal genetic effects and for the additive genetic contribution of the other parent. Male and female progeny trait values were combined in one trait value adjusting for sex differences by standardisation for mean and variance. This average adjusted progeny trait value was used for QTL detection. To study presence of QTLs, an across family weighted regression interval mapping approach was used both in half sib as well as a full sib QTL analysis. Genotypes from 368 markers mapped on 24 autosomal linkage groups were available. The most likely position for a QTL affecting body weight was found on chromosome 1 at 240 cM with a test statistic of 2.32. Significance levels were obtained using the permutation test. The chromosomewise significance level of this QTL was 10%, whereas the genomewise significance level was 41%. New aspects of this study are: Genomewide QTL analysis in poultry, full sib analysis in an outbred population structure and correction for heterogeneous variances between sexes.

A genome-wide association study on androstenone levels in pigs reveals a cluster of candidate genes on chromosome 6

BackgroundIn many countries, male piglets are castrated shortly after birth because a proportion of un-castrated male pigs produce meat with an unpleasant flavour and odour. Main compounds of boar taint are androstenone and skatole. The aim of this high-density genome-wide association study was to identify single nucleotide polymorphisms (SNPs) associated with androstenone levels in a commercial sire line of pigs. The identification of major genetic effects causing boar taint would accelerate the reduction of boar taint through breeding to finally eliminate the need for castration.ResultsThe Illumina Porcine 60K+SNP Beadchip was genotyped on 987 pigs divergent for androstenone concentration from a commercial Duroc-based sire line. The association analysis with 47,897 SNPs revealed that androstenone levels in fat tissue were significantly affected by 37 SNPs on pig chromosomes SSC1 and SSC6. Among them, the 5 most significant SNPs explained together 13.7% of the genetic variance in androstenone. On SSC6, a larger region of 10 Mb was shown to be associated with androstenone covering several candidate genes potentially involved in the synthesis and metabolism of androgens. Besides known candidate genes, such as cytochrome P450 A19 (CYP2A19), sulfotransferases SULT2A1, and SULT2B1, also new members of the cytochrome P450 CYP2 gene subfamilies and of the hydroxysteroid-dehydrogenases (HSD17B14) were found. In addition, the gene encoding the ß-chain of the luteinizing hormone (LHB) which induces steroid synthesis in the Leydig cells of the testis at onset of puberty maps to this area on SSC6. Interestingly, the gene encoding the α-chain of LH is also located in one of the highly significant areas on SSC1.ConclusionsThis study reveals several areas of the genome at high resolution responsible for variation of androstenone levels in intact boars. Major genetic factors on SSC1 and SSC6 showing moderate to large effects on androstenone concentration were identified in this commercial breeding line of pigs. Known and new candidate genes cluster especially on SSC6. For one of the most significant SNP variants, the difference in the proportion of animals surpassing the threshold of consumer acceptance between the two homozygous genotypes was as much as 15.6%.

Genome-wide association of milk fatty acids in Dutch dairy cattle

BackgroundIdentifying genomic regions, and preferably individual genes, responsible for genetic variation in milk fat composition of bovine milk will enhance the understanding of biological pathways involved in fatty acid synthesis and may point to opportunities for changing milk fat composition via selective breeding. An association study of 50,000 single nucleotide polymorphisms (SNPs) was performed for even-chain saturated fatty acids (C4:0-C18:0), even-chain monounsaturated fatty acids (C10:1-C18:1), and the polyunsaturated C18:2cis9,trans11 (CLA) to identify genomic regions associated with individual fatty acids in bovine milk.ResultsThe two-step single SNP association analysis found a total of 54 regions on 29 chromosomes that were significantly associated with one or more fatty acids. Bos taurus autosomes (BTA) 14, 19, and 26 showed highly significant associations with seven to ten traits, explaining a relatively large percentage of the total additive genetic variation. Many additional regions were significantly associated with the fatty acids. Some of the regions harbor genes that are known to be involved in fat synthesis or were previously identified as underlying quantitative trait loci for fat yield or content, such as ABCG2 and PPARGC1A on BTA 6; ACSS2 on BTA 13; DGAT1 on BTA 14; ACLY, SREBF1, STAT5A, GH, and FASN on BTA 19; SCD1 on BTA26; and AGPAT6 on BTA 27.ConclusionsMedium chain and unsaturated fatty acids are strongly influenced by polymorphisms in DGAT1 and SCD1. Other regions also showed significant associations with the fatty acids studied. These additional regions explain a relatively small percentage of the total additive genetic variance, but they are relevant to the total genetic merit of an individual and in unraveling the genetic background of milk fat composition. Regions identified in this study can be fine mapped to find causal mutations. The results also create opportunities for changing milk fat composition through breeding by selecting individuals based on their genetic merit for milk fat composition.

Genetic parameters for major milk proteins in Dutch Holstein-Friesians

The objective of this study was to estimate genetic parameters for major milk proteins. One morning milk sample was collected from 1,940 first-parity Holstein-Friesian cows in February or March 2005. Each sample was analyzed with capillary zone electrophoresis to determine the relative concentrations of the 6 major milk proteins. The results show that there is considerable genetic variation in milk protein composition. The intraherd heritabilities for the relative protein concentrations were high and ranged from 0.25 for beta-casein to 0.80 for beta-lactoglobulin. The intraherd heritability for the summed whey fractions (0.71) was higher than that for the summed casein fractions (0.41). Further, there was relatively more variation in the summed whey fraction (coefficient of variation was 11% and standard deviation was 1.23) compared with the summed casein fraction (coefficient of variation was 2% and standard deviation was 1.72). For the caseins and alpha-lactalbumin, the proportion of phenotypic variation explained by herd was approximately 14%. For beta-lactoglobulin, the proportion of phenotypic variation explained by herd was considerably lower (5%). Eighty percent of the genetic correlations among the relative contributions of the major milk proteins were between -0.38 and +0.45. The genetic correlations suggest that it is possible to change the relative proportion of caseins in milk. Strong negative genetic correlations were found for beta-lactoglobulin with the summed casein fractions (-0.76), and for beta-lactoglobulin with casein index (-0.98). This study suggests that there are opportunities to change the milk protein composition in the cows milk using selective breeding.

QTL for body weight, morphometric traits and stress response in European sea bass Dicentrarchus labrax

Natural mating and mass spawning in the European sea bass (Dicentrarchus labrax L., Moronidae, Teleostei) complicate genetic studies and the implementation of selective breeding schemes. We utilized a two-step experimental design for detecting QTL in mass-spawning species: 2122 offspring from natural mating between 57 parents (22 males, 34 females and one missing) phenotyped for body weight, eight morphometric traits and cortisol levels, had been previously assigned to parents based on genotypes of 31 DNA microsatellite markers. Five large full-sib families (five sires and two dams) were selected from the offspring (570 animals), which were genotyped with 67 additional markers. A new genetic map was compiled, specific to our population, but based on the previously published map. QTL mapping was performed with two methods: half-sib regression analysis (paternal and maternal) and variance component analysis accounting for all family relationships. Two significant QTL were found for body weight on linkage group 4 and 6, six significant QTL for morphometric traits on linkage groups 1B, 4, 6, 7, 15 and 23 and three suggestive QTL for stress response on linkage groups 3, 14 and 23. The QTL explained between 8% and 38% of phenotypic variance. The results are the first step towards identifying genes involved in economically important traits like body weight and stress response in European sea bass.