Genetic analysis of groups of mid-infrared predicted fatty acids in milk

Association of new SNPs at DGAT1 gene with milk quality in Egyptian Zaraibi goat breed

This study aimed to detect putative genomic loci in candidate genes associated with milk composition in Egyptian Zaraibi goats. A total number of 50 samples were tested to detect polymorphism in exons 15 and 16 of the diacylglycerol acyltransferase 1 (DGAT1) gene. The PCR products were sequenced and aligned. Sequence analysis showed three new genotypes in the studied samples: T1C1 (T12C SNP), T2C2 (T84C), and AG (G219A), then three groups were created: the first group was BB with C1T1 and AG genotypes, the second was DD which contains C2T2 and AG genotypes, and the third was AG with only AG genotype. GLM showed that the DD group with C84T and G219A SNPs had significantly the highest fat percent. Meanwhile, the BB group with C84T and G219A SNPs recorded significantly the highest total solids levels. On the other hand, the AG group which has G219A SNP showed a non-significant effect on milk components. Those new SNPs were submitted to GenBank and approved to be published. Moreover, translation of those sequences showed that the G219A SNP causes a substitution of Glycine to Serine in exon 16 at position 106. This SNP (G106S) was predicted to be tolerated by SIFT with a score of 0.48.

Single-step genome-wide association for selected milk fatty acids in Dual-Purpose Belgian Blue cows

The aim of this study was to estimate genetic parameters and identify genomic regions associated with selected individual and groups of milk fatty acids (FA) predicted by milk mid-infrared spectrometry in Dual-Purpose Belgian Blue cows. The used data were 69,349 test-day records of milk yield, fat percentage, and protein percentage along with selected individual and groups FA of milk (g/dL milk) collected from 2007 to 2020 on 7,392 first-parity (40,903 test-day records), and 5,185 second-parity (28,446 test-day records) cows distributed in 104 herds in the Walloon Region of Belgium. Data of 28,466 SNPs, located on 29 Bos taurus autosomes (BTA), of 1,699 animals (639 males and 1,060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by each 25-SNP sliding window (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Average daily heritability estimated for the included milk FA traits ranged from 0.01 (C4:0) to 0.48 (C12:0) and 0.01 (C4:0) to 0.42 (C12:0) in the first and second parities, respectively. Genetic correlations found between milk yield and the studied individual milk FA, except for C18:0, C18:1 trans, C18:1 cis-9, were positive. The results showed that fat percentage and protein percentage were positively genetically correlated with all studied individual milk FA. Genome-wide association analyses identified 11 genomic regions distributed over 8 chromosomes [BTA1, BTA4, BTA10, BTA14 (4 regions), BTA19, BTA22, BTA24, and BTA26] associated with the studied FA traits, though those found on BTA14 partly overlapped. The genomic regions identified differed between parities and lactation stages. Although these differences in genomic regions detected may be due to the power of quantitative trait locus detection, it also suggests that candidate genes underlie the phenotypic expression of the studied traits may vary between parities and lactation stages. These findings increase our understanding about the genetic background of milk FA and can be used for the future implementation of genomic evaluation to improve milk FA profile in Dual-Purpose Belgian Blue cows.

Random regression test-day models to describe milk production and fatty acid traits in first lactation Walloon Holstein cows

We investigated the use of different Legendre polynomial orders to estimate genetic parameters for milk production and fatty acid (FA) traits in the first lactation Walloon Holstein cows. The data set comprised 302,684 test-day records of milk yield, fat and protein contents, and FAs generated by mid-infrared (MIR) spectroscopy, C16:0 (palmitic acid), C18:1 cis-9 (oleic acid), LCFAs (long-chain FAs), SFAs (saturated FAs) and UFAs (unsaturated FAs) were studied. The models included random regression coefficients for herd-year of calving (h), additive genetic (a) and permanent environment (p) effects. The selection of the best random regression model (RRM) was based on the deviance information criterion (DIC), and genetic parameters were estimated via a Bayesian approach. For all analysed random effects, DIC values decreased as the order of the Legendre polynomials increased. Best-fit models had fifth-order (degree 4) for the p effect and ranged from second- to fifth-order (degree 1-4) for the a and h effects (LEGhap: LEG555 for milk yield and protein content; LEG335 for fat content and SFA; LEG545 for C16:0 and UFA; and LEG535 for C18:1 cis-9 and LCFA). Based on the best-fit models, an effect of overcorrection was observed in early lactation (5-35 days in milk [DIM]). On the contrary, third-order (LEG333; degree 2) models showed flat residual trajectories throughout lactation. In general, the estimates of genetic variance tended to increase over DIM, for all traits. Heritabilities for milk production traits ranged from 0.11 to 0.58. Milk FA heritabilities ranged from low-to-high magnitude (0.03-0.56). High Spearman correlations (>0.90 for all bulls and >0.97 for top 100) were found among breeding values for 155 and 305 DIM between the best RRM and LEG333 model. Therefore, third-order Legendre polynomials seem to be most parsimonious and sufficient to describe milk production and FA traits in Walloon Holstein cows.

Association of DGAT1 With Cattle, Buffalo, Goat, and Sheep Milk and Meat Production Traits

Milk fatty acids are essential for many dairy product productions, while intramuscular fat (IMF) is associated with the quality of meat. The triacylglycerols (TAGs) are the major components of IMF and milk fat. Therefore, understanding the polymorphisms and genes linked to fat synthesis is important for animal production. Identifying quantitative trait loci (QTLs) and genes associated with milk and meat production traits has been the objective of various mapping studies in the last decade. Consistently, the QTLs on chromosomes 14, 15, and 9 have been found to be associated with milk and meat production traits in cattle, goat, and buffalo and sheep, respectively. Diacylglycerol O-acyltransferase 1 (DGAT1) gene has been reported on chromosomes 14, 15, and 9 in cattle, goat, and buffalo and sheep, respectively. Being a key role in fat metabolism and TAG synthesis, the DGAT1 has obtained considerable attention especially in animal milk production. In addition to milk production, DGAT1 has also been a subject of interest in animal meat production. Several polymorphisms have been documented in DGAT1 in various animal species including cattle, buffalo, goat, and sheep for their association with milk production traits. In addition, the DGAT1 has also been studied for their role in meat production traits in cattle, sheep, and goat. However, very limited studies have been conducted in cattle for association of DGAT1 with meat production traits in cattle. Moreover, not a single study reported the association of DGAT1 with meat production traits in buffalo; thus, further studies are warranted to fulfill this huge gap. Keeping in view the important role of DGAT1 in animal production, the current review article was designed to highlight the major development and new insights on DGAT1 effect on milk and meat production traits in cattle, buffalo, sheep, and goat. Moreover, we have also highlighted the possible future contributions of DGAT1 for the studied species.

Single-step genomic best linear unbiased predictor genetic parameter estimations and genome-wide associations for milk fatty acid profiles, interval from calving to first insemination, and ketosis in Holstein cattle

Milk fatty acids (FA) have been suggested as biomarkers for early-lactation metabolic diseases and for female fertility status. The aim of the present study was to infer associations between FA, the metabolic disorder ketosis (KET), and the interval from calving to first insemination (ICF) genetically and genomically. In this regard, we focused on a single-step genomic BLUP approach, allowing consideration of genotyped and ungenotyped cows simultaneously. The phenotypic data set considered 38,375 first-lactation Holstein cows, kept in 45 large-scale co-operator herds from 2 federal states in Germany. The calving years for these cows were from 2014 to 2017. Concentrations in milk from the first official milk recording test-day for saturated, unsaturated (UFA), monounsaturated (MUFA), polyunsaturated, palmitic, and stearic (C18:0) FA were determined via Fourier-transform infrared spectroscopy. Ketosis was defined as a binary trait according to a veterinarian diagnosis key, considering diagnoses within a 6-wk interval after calving. A subset of 9,786 cows was genotyped for 40,989 SNP markers. Variance components and heritabilities for all Gaussian distributed FA and for ICF, and for binary KET were estimated by applying single-step genomic BLUP single-trait linear and threshold models, respectively. Genetic correlations were estimated in series of bivariate runs. Genomic breeding values for the single-step genomic BLUP estimations were dependent traits in single-step GWAS. Heritabilities for FA were moderate in the range from 0.09 to 0.20 (standard error = 0.02-0.03), but quite small for ICF (0.08, standard error = 0.01) and for KET (0.05 on the underlying liability scale, posterior standard deviation = 0.02). Genetic correlations between KET and UFA, MUFA, and C18:0 were large (0.74 to 0.85, posterior standard deviation = 0.14-0.19), and low positive between KET and ICF (0.17, posterior standard deviation = 0.22). Genetic correlations between UFA, MUFA, and C18:0 with ICF ranged from 0.34 to 0.46 (standard error = 0.12). In single-step GWAS, we identified a large proportion of overlapping genomic regions for the different FA, especially for UFA and MUFA, and for saturated and palmitic FA. One identical significantly associated SNP was identified for C18:0 and KET on BTA 15. However, there was no genomic segment simultaneously significantly affecting all trait categories ICF, FA, and KET. Nevertheless, some of the annotated potential candidate genes DGKA, IGFBP4, and CXCL8 play a role in lipid metabolism and fertility mechanisms, and influence production diseases in early lactation. Genetic and genomic associations indicate that Fourier-transform infrared spectroscopy FA concentrations in milk from the first official test-day are valuable predictors for KET and for ICF.

Determination of genetic effects and functional SNPs of bovine HTR1B gene on milk fatty acid traits

BACKGROUND

Our previous genome-wide association study (GWAS) on milk fatty acid traits in Chinese Holstein cows revealed, the SNP, BTB-01556197, was significantly associated with C10:0 at genome-wide level (P = 0.0239). It was located in the down-stream of 5-hydroxytryptamine receptor 1B (HTR1B) gene that has been shown to play an important role in the regulation of fatty acid oxidation. Hence, we considered it as a promising candidate gene for milk fatty acids in dairy cattle. In this study, we aimed to investigate whether the HTR1B gene had significant genetic effects on milk fatty acid traits.

RESULTS

We re-sequenced the entire coding region and 3000 bp of 5' and 3' flanking regions of HTR1B gene. A total of 13 SNPs was identified, containing one in 5' flanking region, two in 5' untranslated region (UTR), two in exon 1, five in 3' UTR, and three in 3' flanking region. By performing genotype-phenotype association analysis with SAS9.2 software, we observed that 13 SNPs were significantly associated with medium-chain saturated fatty acids such as C6:0, C8:0 and C10:0 (P < 0.0001 ~ 0.042). With Haploview 4.1 software, linkage disequilibrium (LD) analysis was performed. Two haplotype blocks formed by two and ten SNPs were observed. Haplotype-based association analysis indicated that both haplotype blocks were strongly associated with C6:0, C8:0 and C10:0 as well (P < 0.0001 ~ 0.0071). With regards to the missense mutation in exon 1 (g.17303383G > T) that reduced amino acid change from alanine to serine, we predicted that it altered the secondary structure of HTR1B protein with SOPMA. In addition, we predicted that three SNPs in promoter region, g.17307103A > T, g.17305206 T > G and g.17303761C > T, altered the binding sites of transcription factors (TFs) HMX2, PAX2, FOXP1ES, MIZ1, CUX2, DREAM, and PPAR-RXR by Genomatix. Of them, luciferase assay experiment further confirmed that the allele T of g.17307103A > T significantly increased the transcriptional activity of HTR1B gene than allele A (P = 0.0007).

CONCLUSIONS

In conclusion, our findings provided first evidence that the HTR1B gene had significant genetic effects on milk fatty acids in dairy cattle.

A post-GWAS confirming the genetic effects and functional polymorphisms of AGPAT3 gene on milk fatty acids in dairy cattle

BACKGROUND

People are paying more attention to the healthy and balanced diet with the improvement of their living standards. Milk fatty acids (FAs) have been reported that they were related to some atherosclerosis and coronary heart diseases in human. In our previous genome-wide association study (GWAS) on milk FAs in dairy cattle, 83 genome-wide significant single nucleotide polymorphisms (SNPs) were detected. Among them, two SNPs, ARS-BFGL-NGS-109493 and BTA-56389-no-rs associated with C18index (P = 0.0459), were located in the upstream of 1-acylglycerol-3-phosphate O-acyltransferase 3 (AGPAT3) gene. AGPAT3 is involved in glycerol-lipid, glycerol-phospholipid metabolism and phospholipase D signaling pathways. Hence, it was inferred as a candidate gene for milk FAs. The aim of this study was to further confirm the genetic effects of the AGPAT3 gene on milk FA traits in dairy cattle.

RESULTS

Through re-sequencing the complete coding region, and 3000 bp of 5' and 3' regulatory regions of the AGPAT3 gene, a total of 17 SNPs were identified, including four in 5' regulatory region, one in 5' untranslated region (UTR), three in introns, one in 3' UTR, and eight in 3' regulatory region. By the linkage disequilibrium (LD) analysis with Haploview4.1 software, two haplotype blocks were observed that were formed by four and 12 identified SNPs, respectively. Using SAS9.2, we performed single locus-based and haplotype-based association analysis on 24 milk FAs in 1065 Chinese Holstein cows, and discovered that all the SNPs and the haplotype blocks were significantly associated with C6:0, C8:0 and C10:0 (P < 0.0001-0.0384). Further, with Genomatix, we predicted that four SNPs in 5' regulatory region (g.146702957G > A, g.146704373A > G, g.146704618A > G and g.146704699G > A) changed the transcription factor binding sites (TFBSs) for transcription factors SMARCA3, REX1, VMYB, BRACH, NKX26, ZBED4, SP1, USF1, ARNT and FOXA1. Out of them, two SNPs were validated to impact transcriptional activity by performing luciferase assay that the alleles A of both SNPs, g.146704373A > G and g.146704618A > G, increased the transcriptional activities of AGPAT3 promoter compared with alleles G (P = 0.0004).

CONCLUSIONS

In conclusion, our findings first demonstrated the significant genetic associations of the AGPAT3 gene with milk FAs in dairy cattle, and two potential causal mutations were detected.

Genetic Parameters of Bovine Milk Fatty Acid Profile, Yield, Composition, Total and Differential Somatic Cell Count

The growing interest of consumers for milk and dairy products of high nutritional value has pushed researchers to evaluate the feasibility of including fatty acids (FA) in selection programs to modify milk fat profile and improve its nutritional quality. Therefore, the aim of this study was to estimate genetic parameters of FA profile predicted by mid-infrared spectroscopy, milk yield, composition, and total and differential somatic cell count. Edited data included 35,331 test-day records of 25,407 Italian Holstein cows from 652 herds. Variance components and heritability were estimated using single-trait repeatability animal models, whereas bivariate repeatability animal models were used to estimate genetic and phenotypic correlations between traits, including the fixed effects of stage of lactation, parity, and herd-test-date, and the random effects of additive genetic animal, cow permanent environment and the residual. Heritabilities and genetic correlations obtained in the present study reflected both the origins of FA (extracted from the blood or synthesized de novo by the mammary gland) and their grouping according to saturation or chain length. In addition, correlations among FA groups were in line with correlation among individual FA. Moderate negative genetic correlations between FA and milk yield and moderate to strong positive correlations with fat, protein, and casein percentages suggest that actual selection programs are currently affecting all FA groups, not only the desired ones (e.g., polyunsaturated FA). The absence of association with differential somatic cell count and the weak association with somatic cell score indicate that selection on FA profile would not affect selection on resistance to mastitis and vice versa. In conclusion, our findings suggest that genetic selection on FA content is feasible, as FA are variable and moderately heritable. Nevertheless, in the light of correlations with other milk traits estimated in this study, a clear breeding goal should first be established.

Genetic correlations of milk fatty acid contents predicted from milk mid-infrared spectra in New Zealand dairy cattle

The objective of this study was to estimate genetic correlations among milk fatty acid (FA) concentrations in New Zealand dairy cattle. Concentrations of each of the most common FA, expressed as a percentage of the total FA, were determined by gas chromatography on a specific cohort of animals. Using this data set, prediction equations were derived using mid-infrared (MIR) spectroscopy data collected from the same samples. These prediction equations were applied to a large data set of MIR measurements in 34,141 milk samples from 3,445 Holstein-Friesian, 2,935 Jersey, and 3,609 crossbred Holstein-Friesian × Jersey cows, sampled an average of 3.42 times during the 2007-2008 season. Data were analyzed using univariate and bivariate repeatability animal models. Heritability of predicted FA concentration in milk fat ranged from 0.21 to 0.42, indicating that genetic selection could be used to change the FA composition of milk. The de novo synthesized FA (C6:0, C8:0, C10:0, C12:0, and C14:0) showed strong positive genetic correlations with each other, ranging from 0.24 to 0.99. Saturated FA were negatively correlated with unsaturated (-0.93) and polyunsaturated (-0.84) FA. The saturated FA were positively correlated with milk fat yield and fat percentage, whereas the unsaturated FA were negatively associated with fat yield and fat percentage. Our results indicate that bovine milk FA composition can be changed through genetic selection using MIR as a phenotypic proxy.

Identification of genetic effects and potential causal polymorphisms of CPM gene impacting milk fatty acid traits in Chinese Holstein

Our previous GWAS revealed 83 significant SNPs and 20 promising candidate genes associated with milk fatty acid traits in dairy cattle. Out of them, the carboxypeptidase M (CPM) gene contains a genome-wide significant SNP, Hapmap49848-BTA-106779, which is strongly associated with myristic acid (C14:0; P = 0.0064). Herein, we aimed to confirm the genetic effects of CPM on milk fatty acids in Chinese Holstein. Seven SNPs were detected by re-sequencing the sequences of entire exons and 3000 bp of up-/downstream flanking regions of the CPM gene, of which three were in 5' flanking region, one in the 3' UTR and three were in the 3' flanking region. Using the Haploview 4.1, we estimated the LD among the identified SNPs and found two haplotype blocks. With the animal model, we performed the SNP- and haplotype-based association analyses, and observed that these SNPs and haplotype blocks mainly had strong genetic associations with medium-chain saturated fatty acids (caproic acid, C6:0; caprylic acid, C8:0; capric acid, C10:0; and lauric acid, C12:0) (P < 0.0001-0.0257). In addition, using the Genomatix software, we predicted that three SNPs in the 5' flanking region of CPM (g.45079507A>G, g.45080228C>A and g.45080335C>G) changed the transcription factor binding sites for PREF (progesterone receptor biding site), ZBRK1 (transcription factor with eight central zinc fingers and an N-terminal KRAB domain), SOX9 (sex-determining region Y-box 9, dimeric binding sites), SOX6 (sex-determining region Y-box 6) and FOXP1-ES (alternative splicing variant of FOXP1, activated in ESCs). Further, the dual-luciferase reporter assay showed these three SNPs altered the transcriptional activity of CPM gene (P ≤ 0.0006). In summary, using the post-GWAS strategy, we first confirmed the significant genetic effects of CPM with milk fatty acids in dairy cattle, and identified three potential causal mutations.

The evolving role of Fourier-transform mid-infrared spectroscopy in genetic improvement of dairy cattle

Over the last 100 years, significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs. Technological progress has enabled a shift from labour intensive, on-farm collection and processing of samples that assess yield and fat levels in milk, to large-scale processing of samples through centralised laboratories, with the scope extended to include quantification of other traits. Fourier-transform mid-infrared (FT-MIR) spectroscopy has had a significant role in the transformation of milk composition phenotyping, with spectral-based predictions of major milk components already being widely used in milk payment and animal evaluation systems globally. Increasingly, there is interest in analysing the individual FT-MIR wavenumbers, and in utilising the FT-MIR data to predict other novel traits of importance to breeding programs. This includes traits related to the nutritional value of milk, the processability of milk into products such as cheese, and traits relevant to animal health and the environment. The ability to successfully incorporate these traits into breeding programs is dependent on the heritability of the FT-MIR predicted traits, and the genetic correlations between the FT-MIR predicted and actual trait values. Linking FT-MIR predicted traits to the underlying mutations responsible for their variation can be difficult because the phenotypic expression of these traits are a function of a diverse range of molecular and biological mechanisms that can obscure their genetic basis. The individual FT-MIR wavenumbers give insights into the chemical composition of milk and provide an additional layer of granularity that may assist with establishing causal links between the genome and observed phenotypes. Additionally, there are other molecular phenotypes such as those related to the metabolome, chromatin accessibility, and RNA editing that could improve our understanding of the underlying biological systems controlling traits of interest. Here we review topics of importance to phenotyping and genetic applications of FT-MIR spectra datasets, and discuss opportunities for consolidating FT-MIR datasets with other genomic and molecular data sources to improve future dairy cattle breeding programs.

Estimation of genetic parameters for mid-infrared-predicted lactoferrin and milk fat globule size in Holstein cattle

Lactoferrin (LF) and milk fat globule (MFG) are 2 biologically active components of milk with great economical and nutritional value in the dairy industry. The objectives of this study were to estimate (1) the heritability of mid-infrared (MIR)-predicted LF and MFG size (MFGS) and (2) the genetic correlations between predicted LF and MFGS with milk, fat, and protein yields, fat and protein percentages, and somatic cell score in first-parity Canadian Holstein cattle. A total of 109,029 test-day records from 22,432 cows and 1,572 farms for MIR-predicted LF and 109,212 test-day records from 22,424 cows and 1,559 farms for MIR-predicted MFGS were used in the analyses. Four separate 5-trait random regression test-day models were used. The models included days in milk, herd test date, and a polynomial regression on DIM nested in age-season of calving classes as fixed effects, random polynomial regressions on DIM nested in herd-year of calving, animal additive genetic and permanent environment classes, and a residual effect. Regression curves were modeled using orthogonal Legendre polynomials of order 4 for the fixed age-season of calving effect and of order 5 for the random effects. Moderate overall heritability estimates of 0.34 and 0.46 were estimated for the MIR-predicted LF and MIR-predicted MFGS, respectively. These heritability estimates were similar to the ones estimated for the direct measure of MFGS in a previous study. The genetic correlations between predicted MFGS and fat percentage (0.53) and between predicted LF and protein percentage (0.41) were both moderate and positive. Predicted LF and somatic cell score showed a weaker correlation (0.06) compared with other studies. The moderate genetic correlation between MIR-predicted MFGS and fat percentage and between MIR-predicted LF and protein percentage suggests that MIR predictions of MFGS and LF are not simply a function of the amount of fat and protein percentage, respectively, in the milk (i.e., the prediction equations are not simply predicting fat or protein percentages). Thus, these MIR-predicted values may provide additional information for selecting for fine milk components in Holstein cattle.

Genome-Wide Association Study for Milk Fatty Acids in Holstein Cattle Accounting for the DGAT1 Gene Effect

The identification of genomic regions and candidate genes associated with milk fatty acids contributes to better understand the underlying biology of these traits and enables breeders to modify milk fat composition through genetic selection. The main objectives of this study were: (1) to perform genome-wide association analyses for five groups of milk fatty acids in Holstein cattle using a high-density (777K) SNP panel; and (2) to compare the results of GWAS accounting (or not) for the DGAT1 gene effect as a covariate in the statistical model. The five groups of milk fatty acids analyzed were: (1) saturated (SFA); (2) unsaturated (UFA); (3) short-chain (SCFA); (4) medium-chain (MCFA); and (5) long-chain (LCFA) fatty acids. When DGAT1 was not fitted as a covariate in the model, significant SNPs and candidate genes were identified on BTA5, BTA6, BTA14, BTA16, and BTA19. When fitting the DGAT1 gene in the model, only the MGST1 and PLBD1 genes were identified. Thus, this study suggests that the DGAT1 gene accounts for most of the variability in milk fatty acid composition and the PLBD1 and MGST1 genes are important additional candidate genes in Holstein cattle.

Polymorphisms and genetic effects of PRLR, MOGAT1, MINPP1 and CHUK genes on milk fatty acid traits in Chinese Holstein

BACKGROUND

Our initial genome-wide association study (GWAS) identified 20 promising candidate genes for milk fatty acid (FA) traits in a Chinese Holstein population, including PRLR, MOGAT1, MINPP1 and CHUK genes. In this study, we performed whether they had significant genetic effects on milk FA traits in Chinese Holstein.

RESULTS

We re-sequenced the entire exons and 3000 bp of the 5' and 3' flanking regions, and identified 11 single nucleotide polymorphisms (SNPs), containing four in PRLR, two in MOGAT1, two in MINPP1, and three in CHUK. The SNP-based association analyses showed that all the 11 SNPs were significantly associated with at least one milk FA trait (P = 0.0456 ~ < 0.0001), and none of them had association with C11:0, C13:0, C15:0 and C16:0 (P > 0.05). By the linkage disequilibrium (LD) analyses, we found two, one, one, and one haplotype blocks in PRLR, MOGAT1, MINPP1, and CHUK, respectively, and each haplotype block was significantly associated with at least one milk FA trait (P = 0.0456 ~ < 0.0001). Further, g.38949011G > A in PRLR, and g.111599360A > G and g.111601747 T > A in MOGAT1 were predicted to alter the transcription factor binding sites (TFBSs). A missense mutation, g.39115344G > A, could change the PRLR protein structure. The g.20966385C > G of CHUK varied the binding sequences for microRNAs. Therefore, we deduced the five SNPs as the potential functional mutations.

CONCLUSION

In summary, we first detected the genetic effects of PRLR, MOGAT1, MINPP1 and CHUK genes on milk FA traits, and researched the potential functional mutations. These data provided the basis for further investigation on function validation of the four genes in Chinese Holstein.

Identification of genetic associations of ECHS1 gene with milk fatty acid traits in dairy cattle

Our previous genome-wide association study identified 83 genome-wide significant SNPs and 20 novel promising candidate genes for milk fatty acids in Chinese Holstein. Among them, the enoyl-CoA hydratase, short chain 1 (ECHS1) and enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase (EHHADH) genes were located near two SNPs and one SNP respectively, and they play important roles in fatty acid metabolism pathways. We herein validated whether the two genes have genetic effects on milk fatty acid traits in dairy cattle. By re-sequencing the full-length coding region, partially adjacent introns and 3000 bp up/downstream flanking sequences, we identified 12 SNPs in ECHS1: two in exons, four in the 3' flanking region and six in introns. The g.25858322C>T SNP results in an amino acid replacement from leucine to phenylalanine and changes the secondary structure of the ECHS1 protein, and single-locus association analysis showed that it was significantly associated with three milk fatty acids (P = 0.0002-0.0013). The remaining 11 SNPs were found to be significantly associated with at least one milk fatty acid (P = <0.0001-0.0040). Also, we found that two haplotype blocks, consisting of nine and two SNPs respectively, were significantly associated with eight milk fatty acids (P = <0.0001-0.0125). However, none of polymorphisms was observed in the EHHADH gene. In conclusion, our findings are the first to indicate that the ECHS1 gene has a significant genetic impact on long-chain unsaturated and medium-chain saturated fatty acid traits in dairy cattle, although the biological mechanism is still undetermined and requires further in-depth validation.

A post-GWAS confirming effects of PRKG1 gene on milk fatty acids in a Chinese Holstein dairy population

BACKGROUND

We previously conducted a genome-wide association study (GWAS) strategy for milk fatty acids in Chinese Holstein, and identified 83 genome-wide significant single nucleotide polymorphisms (SNPs) and 314 suggestive significant SNPs. Among them, two SNPs, BTB-01077939 and BTA-11275-no-rs associated with C10:0, C12:0, and C14 index (P = 0.000014 ~ 0.000024), were within and close to (0.85 Mb) protein kinase, cGMP-dependent, type І (PRKG1) gene on BTA26, respectively. PRKG1 gene plays a key role in lipolysis to release fatty acids and glycerol through the hydrolysis of triacyglycerol in adipocytes. We herein considered it as a promising candidate for milk fatty acids. The purpose of this study was to investigate whether PRKG1 had effects on milk fatty acids.

RESULTS

By direct sequencing the PCR products of pooled DNA, we identified a total of six SNPs, including one in 5' flanking region, four in 3' untranslated region (UTR), and one in 3' flanking region. The single-locus association analysis was carried out, and showed that the six SNPs mainly had significant associations with C6:0, C8:0 and C17:1 (P < 0.0001 ~ 0.0035). In addition, we observed a haplotype block formed by g.6903810G > A and g.6904047G > T with Haploview 4.1, and it was strongly associated with C8:0, C10:0, C16:1, C17:1, C20:0 and C16 index (P = < 0.0001 ~ 0.0123). The SNP, g.8344262A > T, was predicted to alter the binding site (BS) of transcription factor (TF) GAGA box with Genomatix software, and the subsequent luciferase assay verified that it really changed the transcriptional activity of PRKG1 gene (P = 0.0009).

CONCLUSION

In conclusion, to our best of knowledge, we are the first who identified the significant effects of PRKG1 on milk fatty acids in dairy cattle.

Determination of Genetic Effects of LIPK and LIPJ Genes on Milk Fatty Acids in Dairy Cattle

In our previous genome-wide association study (GWAS) on milk fatty acids (FAs) in Chinese Holstein, we discovered 83 genome-wide significant single nucleotide polymorphisms (SNPs) associated with milk FAs. Two of them were close to lipase family member K (LIPK) and lipase family member J (LIPJ), respectively. Hence, this study is a follow-up to verify whether the LIPK and LIPJ have significant genetic effects on milk FAs in dairy cattle. By re-sequencing the entire exons, and 3 kb of 5′ and 3′ flanking regions, two and seven SNPs were identified in LIPK and LIPJ, respectively, including a novel SNP, ss158213049726. With the Haploview 4.1 software, we found that five of the SNPs in LIPJ formed a haplotype block (D′ = 0.96 ~ 1.00). Single-locus association analyses revealed that each SNP in LIPK and LIPJ was significantly associated with at least one milk FA (p = < 1.00 × 10⁻⁴ ~ 4.88 × 10⁻²), and the haplotype-based association analyses showed significant genetic effects on nine milk FAs (p = < 1.00 × 10⁻⁴ ~ 3.98 × 10⁻²). Out of these SNPs, the missense mutation in LIPK gene, rs42774527, could change the protein secondary structure and function predicted by SOPMA, SIFT, and PROVEAN softwares. With the Genomatix software, we predicted that two SNPs, rs110322221 in LIPK and rs211373799 in LIPJ, altered the transcription factors binding sites (TFBSs), indicating their potential regulation on promoter activity of the genes. Furthermore, we found that both LIPK and LIPJ had relatively high expressions in the mammary gland. In conclusion, our research is the first to demonstrate that LIPK and LIPJ genes have significant associations with milk FAs, and the identified SNPs might be served as genetic markers to optimize breeding programs for milk FAs in dairy cattle. This research deserves in-depth verification.

Role of Fatty Acids in Milk Fat and the Influence of Selected Factors on Their Variability-A Review

Fatty acids (FAs) of milk fat are considered to be important nutritional components of the diets of a significant portion of the human population and substantially affect human health. With regard to dairy farming, the FA profile is also seen as an important factor in the technological quality of raw milk. In this sense, making targeted modifications to the FA profile has the potential to significantly contribute to the production of dairy products with higher added value. Thus, FAs also have economic importance. Current developments in analytical methods and their increasing efficiency enable the study of FA profiles not only for scientific purposes but also in terms of practical technological applications. It is important to study the sources of variability of FAs in milk, which include population genetics, type of farming, and targeted animal nutrition. It is equally important to study the health and technological impacts of FAs. This review summarizes current knowledge in the field regarding sources of FA variability, including the impact of factors such as: animal nutrition, seasonal feed changes, type of animal farming (conventional and organic), genetic parameters (influence of breed), animal individuality, lactation, and milk yield. Potential practical applications (to improve food technology and consumer health) of FA profile information are also reviewed.