Unravelling genetic variation underlying de novo-synthesis of bovine milk fatty acids

The Genetic Characteristics of FT-MIRS-Predicted Milk Fatty Acids in Chinese Holstein Cows

Fourier Transform Mid-Infrared Spectroscopy (FT-MIRS) can be used for quantitative detection of milk components. Here, milk samples of 458 Chinese Holstein cows from 11 provinces in China were collected and we established a total of 22 quantitative prediction models in milk fatty acids by FT-MIRS. The coefficient of determination of the validation set ranged from 0.59 (C18:0) to 0.76 (C4:0). The models were adopted to predict the milk fatty acids from 2138 cows and a new high-throughput computing software HiBLUP was employed to construct a multi-trait model to estimate and analyze genetic parameters in dairy cows. Finally, genome-wide association analysis was performed and seven novel SNPs significantly associated with fatty acid content were selected, investigated, and verified with the FarmCPU method, which stands for "Fixed and random model Circulating Probability Unification". The findings of this study lay a foundation and offer technical support for the study of fatty acid trait breeding and the screening and grouping of characteristic dairy cows in China with rich, high-quality fatty acids. It is hoped that in the future, the method established in this study will be able to screen milk sources rich in high-quality fatty acids.

Review: genetic background of milk fatty acid synthesis in bovines

Milk fat composition is an important trait for the dairy industry as it directly influences the nutritional and technological properties of milk and other dairy products. The synthesis of milk fat is a complex process regulated by a network of genes. Thus, understanding the genetic variation and molecular mechanisms regulating milk fat synthesis will help to improve the nutritional quality of dairy products. In this review, we provide an overview of milk fat synthesis in bovines along with the candidate genes involved in the pathway. We also discuss de novo synthesis of fatty acids (ACSS, ACACA, FASN), uptake of FAs (FATP, FAT, LPL), intracellular activation and channelling of FAs (ACSL, FABP), elongation (EVOLV6), desaturation (SCD, FADS), formation of triglycerides (GPAM, AGPAT, LIPIN, DGAT), and milk lipid secretion (BTN1A1, XDH, PLIN2). The genetic variability of individual fatty acids will help to develop selection strategies for obtaining a healthier milk fat profile in bovines. Thus, this review will offer a potential understanding of the molecular mechanisms that regulate milk fat synthesis in bovines.

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.

Association of Single Nucleotide Polymorphism in the DGAT1 Gene with the Fatty Acid Composition of Cows Milked Once and Twice a Day

A single nucleotide polymorphism (SNP) rs109421300 of the diacylglycerol acyltransferase 1 (DGAT1) on bovine chromosome 14 is associated with fat yield, fat percentage, and protein percentage. This study aimed to investigate the effect of SNP rs109421300 on production traits and the fatty acid composition of milk from cows milked once a day (OAD) and twice a day (TAD) under New Zealand grazing conditions. Between September 2020 and March 2021, 232 cows from a OAD herd and 182 cows from a TAD herd were genotyped. The CC genotype of SNP rs109421300 was associated with significantly (p < 0.05) higher fat yield, fat percentage, and protein percentage, and lower milk and protein yields in both milking frequencies. The CC genotype was also associated with significantly (p < 0.05) higher proportions of C16:0 and C18:0, higher predicted solid fat content at 10 °C (SFC₁₀), and lower proportions of C4:0 and C18:1 cis-9 in both milking frequencies. The association of SNP with fatty acids was similar in both milking frequencies, with differences in magnitudes. The SFC₁₀ of cows milked OAD was lower than cows milked TAD for all three SNP genotypes suggesting the suitability of OAD milk for producing easily spreadable butter. These results demonstrate that selecting cows with the CC genotype is beneficial for New Zealand dairy farmers with the current payment system, however, this would likely result in less spreadable butter.

Heat stress on breeding value prediction for milk yield and composition of a Brazilian Holstein cattle population

Due to the high milk production of Holstein cows, many countries have chosen to import semen to improve local dairy herds. This strategy would be more effective if this semen was used in the same environment conditions in which the bulls were selected. If the effect of genotype by environment (G × E) interaction is not considered, the estimated breeding values (EBVs) may vary, potentially reducing the selection response. We evaluate the impact of heat stress on selection for milk yield and composition of Holstein cows using random regression models. To verify the interference of heat stress in milk yield (MY) and composition traits (fat, protein, total saturated, and total unsaturated fatty acids content in milk), temperature-humidity index (THI) on test-day milk records was used. The threshold value to divide the environments using test-day information from Brazilian Holstein cows was 72 units of THI, i.e., < 72 represented no heat stress and > 72 represented heat stress. Legendre polynomials of second-order (Leg 2) model and two lactation points (33 and 122 DIM) were used to estimate heritabilities and EBVs for five important dairy traits. The heritabilities of milk components and fatty acids were low (0.09-0.29), regardless of lactation period and degree of heat stress, with the exception of protein content (0.30-0.35). Fat content was the only milk component that was reduced according to the degree of heat stress and lactation period. The EBVs tended to decrease in heat stress conditions, thus animals with high genetic potential demonstrated evidence of G × E interaction. However, acclimatization of dairy cows to heat stress in the farm production systems may have been responsible for the low differences among genetic parameters and EBVs with and without heat stress found in this study.

Genetic variants associated with two major bovine milk fatty acids offer opportunities to breed for altered milk fat composition

Background

Although bovine milk is regarded as healthy and nutritious, its high content of saturated fatty acids (FA) may be harmful to cardiovascular health. Palmitic acid (C16:0) is the predominant saturated FA in milk with adverse health effects that could be countered by substituting it with higher levels of unsaturated FA, such as oleic acid (C18:1cis-9). In this work, we performed genome-wide association analyses for milk fatty acids predicted from FTIR spectroscopy data using 1811 Norwegian Red cattle genotyped and imputed to a high-density 777k single nucleotide polymorphism (SNP)-array. In a follow-up analysis, we used imputed whole-genome sequence data to detect genetic variants that are involved in FTIR-predicted levels of C16:0 and C18:1cis-9 and explore the transcript profile and protein level of candidate genes.

Results

Genome-wise significant associations were detected for C16:0 on Bos taurus (BTA) autosomes 11, 16 and 27, and for C18:1cis-9 on BTA5, 13 and 19. Closer examination of a significant locus on BTA11 identified the PAEP gene, which encodes the milk protein β-lactoglobulin, as a particularly attractive positional candidate gene. At this locus, we discovered a tightly linked cluster of genetic variants in coding and regulatory sequences that have opposing effects on the levels of C16:0 and C18:1cis-9. The favourable haplotype, linked to reduced levels of C16:0 and increased levels of C18:1cis-9 was also associated with a marked reduction in PAEP expression and β-lactoglobulin protein levels. β-lactoglobulin is the most abundant whey protein in milk and lower levels are associated with important dairy production parameters such as improved cheese yield.

Conclusions

The genetic variants detected in this study may be used in breeding to produce milk with an improved FA health-profile and enhanced cheese-making properties.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-022-00731-9.

Genome-wide associations for heat stress response suggest potential candidate genes underlying milk fatty acid composition in dairy cattle

Contents of milk fatty acids (FA) display remarkable alterations along climatic gradients. Detecting candidate genes underlying such alterations might be beneficial for the exploration of climate sensitivity in dairy cattle. Consequently, we aimed on the definition of FA heat stress indicators, considering FA breeding values in response to temperature-humidity index (THI) alterations. Indicators were used in GWAS, in ongoing gene annotations and for the estimation of chromosome-wide variance components. The phenotypic data set consisted of 39,600 test-day milk FA records from 5,757 first-lactation Holstein dairy cows kept in 16 large-scale German cooperator herds. The FA traits were C18:0, polyunsaturated fatty acids (PUFA), saturated fatty acids (SFA), and unsaturated fatty acids (UFA). After genotype quality control, 40,523 SNP markers from 3,266 cows and 930 sires were considered. Meteorological data from the weather station in closest herd distance were used for the calculation of maximum hourly daily THI, which were allocated to 10 different THI classes. The same FA from 3 stages of lactation were considered as different, but genetically correlated traits. Consequently, a 3-trait reaction norm model was used to estimate genetic parameters and breeding values for FA along THI classes, considering either pedigree (A) or genomic (G) relationship matrices. De-regressed proofs and genomic estimated breeding values at the intermediate THI class 5 and at the extreme THI class 10 were used as pseudophenotypes in ongoing genomic analyses for thermoneutral (TNC) and heat stress conditions (HSC), respectively. The differences in de-regressed proofs and in genomic estimated breeding values from both THI classes were pseudophenotypes for heat stress response (HSR). Genetic correlations between the same FA under TNC and HSC were smallest in the first lactation stage and ranged from 0.20 for PUFA to 0.87 for SFA when modeling with the A matrix, and from 0.35 for UFA to 0.86 for SFA when modeling with the G matrix. In the first lactation stage, larger additive genetic variances under HSC compared with TNC indicate climate sensitivity for C18:0, PUFA, and UFA. Climate sensitivity was also reflected by pronounced chromosome-wide genetic variances for HSR of PUFA and UFA in the first stage of lactation. For all FA under TNC, HSC, and HSR, quite large genetic variance proportions were explained by BTA14. In GWAS, 30 SNP (within or close to 38 potential candidate genes) overlapped for HSR of the different FA. One unique potential candidate gene (AMFR) was detected for HSR of PUFA, 15 for HSR of SFA (ADGRB1, DENND3, DUSP16, EFR3A, EMP1, ENSBTAG00000003838, EPS8, MGP, PIK3C2G, STYK1, TMEM71, GSG1, SMARCE1, CCDC57, and FASN) and 3 for HSR of UFA (ENSBTAG00000048091, PAEP, and EPPK1). The identified unique genes play key roles in milk FA synthesis and are associated with disease resistance in dairy cattle. The results suggest consideration of FA in combination with climatic responses when inferring genetic mechanisms of heat stress in dairy cows.

FASN, SCD1 and ANXA9 gene polymorphism as genetic predictors of the fatty acid profile of sheep milk

In this study, single nucleotide polymorphisms (SNPs) in the ANXA9 (annexin 9), FASN (fatty acid synthase) and SCD1 (stearoyl-CoA desaturase 1) genes were analyzed as factors influencing fatty acid profiles in milk from Zošľachtená valaška sheep. SNP in selected genes was identified using polymerase chain reaction (PCR) and restriction fragment length polymorphism (PCR–RFLP). The long-chain fatty acids profile in sheep milk was identified by gas chromatography. Statistical analysis of the SCD1/Cfr13I polymorphism showed that the milk of the homozygous AA animals was characterized by a lower (P < 0.05) share of C4:0, C6:0, C8:0, C10:0, C12:0, C14:0 in comparison to the homozygous CC sheep. The milk of heterozygous sheep was characterized by a higher (P < 0.05) proportion of C13:0 acid compared to the milk of sheep with the homozygous AA type. A higher (P < 0.05) level of saturated fatty acids (SFA) was found in the milk of CC genotype sheep compared to the AA genotype. Our results lead to the conclusion that the greatest changes were observed for the SCD1/Cfr13I polymorphism and the least significant ones for FASN/AciI. Moreover, it is the first evidence that milk from sheep with SCD1/Cfr13I polymorphism and the homozygous AA genotype showed the most desirable fatty acids profile.

Comparative Structural and Compositional Analyses of Cow, Buffalo, Goat and Sheep Cream

Factors affecting milk and milk fraction composition, such as cream, are poorly understood, with most research and human health application associated with cow cream. In this study, proteomic and lipidomic analyses were performed on cow, goat, sheep and Bubalus bubalis (from now on referred to as buffalo), bulk milk cream samples. Confocal laser scanning microscopy was used to determine the composition, including protein, lipid and their glycoconjugates, and the structure of the milk fat globules. BLAST2GO was used to annotate functional indicators of cream protein. Functional annotation of protein highlighted a broad level of similarity between species. However, investigation of specific biological process terms revealed distinct differences in antigen processing and presentation, activation, and production of molecular mediators of the immune response. Lipid analyses revealed that saturated fatty acids were lowest in sheep cream and similar in the cream of the other species. Palmitic acid was highest in cow and lowest in sheep cream. Cow and sheep milk fat globules were associated with thick patches of protein on the surface, while buffalo and goat milk fat globules were associated with larger areas of aggregated protein and significant surface adsorbed protein, respectively. This study highlights the differences between cow, goat, sheep, and buffalo milk cream, which can be used to support their potential application in functional foods such as infant milk formula.

Identification of genes affecting milk fat and fatty acid composition in Vrindavani crossbred cattle using 50 K SNP-Chip

The aim of this study was to identify candidate genes associated with milk fat per cent and fatty acid (FA) composition in Vrindavani cattle using the Illumina 50 K single-nucleotide polymorphism (SNP) array. After quality control, a total of 41,427 informative and high-quality SNPs were used for a genome-wide association study (GWAS) for milk fat percentage and 16 different types of fatty acids. Lactation stage, parity, test day milk yield, and proportion of exotic inheritance were included as fixed effects in the GWAS model. A total of 67 genome-wide significant (P < 1.20 × 10^-06) SNPs and 176 suggestive significant (P < 2.41 × 10^-05) SNPs were identified. Out of these, 15 SNPs were associated with more than one trait. The strongest associations were found on BTA14 for milk fat percentage and on BTA2 and BTA16 for polyunsaturated fatty acids. Several significant SNPs were identified close to or within the genes ELOVL6, FABP4, PMP2, PLIN1, MFGE8, GHRL2, and LDLRAD3 which are known to be associated with fat percentage and FA composition in dairy cattle breeds. This study is a step forward to better characterize the molecular mechanisms of phenotypic variation in milk fatty acids in a taurine-indicine composite cattle breed reared in tropical environments.

Compositional and functional properties of milk and dairy products derived from cows fed pasture or concentrate-based diets

Worldwide milk production is predominantly founded on indoor, high-concentrate feeding systems, whereas pasture-based feeding systems are most common in New Zealand and Ireland but have received greater attention recently in countries utilizing conventional systems. Consumer interest in 'pasture-fed' dairy products has also increased, arising from environmental, ethical, and nutritional concerns. A substantial body of research exists describing the effect of different feeding strategies on the composition of milk, with several recent studies focusing on the comparison of pasture- and concentrate-based feeding regimes. Significant variation is typically observed in the gross composition of milk produced from different supplemental feeds, but various changes in the discrete composition of macromolecular components in milk have also been associated with dietary influence, particularly in relation to the fatty acid profile. Changes in milk composition have also been shown to have implications for milk and dairy product processability, functionality and sensory properties. Methods to determine the traceability of dairy products or verify marketing claims such as 'pasture-fed' have also been established, based on compositional variation due to diet. This review explores the effects of feed types on milk composition and quality, along with the ultimate effect of diet-induced changes on milk and dairy product functionality, with particular emphasis placed on pasture- and concentrate-based feeding systems.

Chemical and fatty acid composition of Manchego type and Panela cheeses manufactured from either hair sheep milk or cow milk

This study compared the chemical composition and fatty acid (FA) profile of Manchego type cheese and Panela cheese made from hair sheep milk and compared these with both types of cheese manufactured with cow milk as a reference. In addition, this study aimed to determine differences in sensory characteristics between Manchego type cheeses manufactured with either hair sheep milk or cow milk. A total of 25 and 14 Manchego type cheeses from hair sheep milk and cow milk were manufactured, respectively. In addition, 30 and 15 Panela cheeses from hair sheep milk and cow milk were manufactured, respectively. The chemical composition and FA profile were determined in all cheeses. In addition, a sensory analysis was performed in Manchego type cheeses manufactured from either hair sheep milk or cow milk. Moisture content was lower in Manchego type cheeses (37.5 ± 1.26 and 37.5 ± 1.26 g/100 g in cheeses manufactured from hair sheep milk and cow milk, respectively) than in Panela cheeses (54.0 ± 1.26 and 56.1 ± 1.26 g/100 g in cheeses manufactured from hair sheep milk and cow milk, respectively). Ash, protein, and sodium contents were higher in Manchego type cheeses than in Panela cheeses. Manchego type cheese manufactured from hair sheep milk contained more C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C18:2 cis-9,cis-12, total saturated FA, total short-chain FA, total medium-chain FA, total polyunsaturated FA, and de novo FA than Manchego type cheeses from cow milk. Total content of short-chain FA was higher in hair sheep cheeses (24.4 ± 1.30 and 19.6 ± 1.30 g/100 g in Manchego type and Panela cheeses, respectively) than in cow cheeses (8.89 ± 1.30 and 8.26 ± 1.30 g/100 g in Manchego type and Panela cheeses, respectively). Manchego type cheeses from hair sheep milk obtained higher scores for odor (7.05), texture (6.82), flavor (7.16), and overall acceptance (7.16) compared with those made from cow milk (6.37, 6.12, 6.17, and 6.83, respectively). In conclusion, both Manchego type cheese and Panela cheese manufactured with hair sheep milk had a similar chemical composition and contained higher levels of short-chain FA, total polyunsaturated FA, and de novo FA than those manufactured with cow milk.

Sequence-based GWAS and post-GWAS analyses reveal a key role of SLC37A1, ANKH, and regulatory regions on bovine milk mineral content

The mineral composition of bovine milk plays an important role in determining its nutritional and cheese-making value. Concentrations of the main minerals predicted from mid-infrared spectra produced during milk recording, combined with cow genotypes, provide a unique opportunity to decipher the genetic determinism of these traits. The present study included 1 million test-day predictions of Ca, Mg, P, K, Na, and citrate content from 126,876 Montbéliarde cows, of which 19,586 had genotype data available. All investigated traits were highly heritable (0.50-0.58), with the exception of Na (0.32). A sequence-based genome-wide association study (GWAS) detected 50 QTL (18 affecting two to five traits) and positional candidate genes and variants, mostly located in non-coding sequences. In silico post-GWAS analyses highlighted 877 variants that could be regulatory SNPs altering transcription factor (TF) binding sites or located in non-coding RNA (mainly lncRNA). Furthermore, we found 47 positional candidate genes and 45 TFs highly expressed in mammary gland compared to 90 other bovine tissues. Among the mammary-specific genes, SLC37A1 and ANKH, encoding proteins involved in ion transport were located in the most significant QTL. This study therefore highlights a comprehensive set of functional candidate genes and variants that affect milk mineral content.

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.

MicroRNA-193a-5p Regulates the Synthesis of Polyunsaturated Fatty Acids by Targeting Fatty Acid Desaturase 1 (FADS1) in Bovine Mammary Epithelial Cells

Cardiovascular diseases (CVDs) are seriously threatening to human life and health. Polyunsaturated fatty acids (PUFAs) are known for their role in preventing CVDs. It is beneficial to population health to promote the content of PUFAs in bovine milk. In recent years, limited research based on molecular mechanisms has focused on this field. The biological roles of numerous microRNAs (miRNAs) remain unknown. In this study, a promising and negatively correlated pair of the miRNA (miRNA-193a-5p) and a fatty acid desaturase 1 (FADS1) gene are identified and screened to explore whether they are potential factors of PUFAs’ synthesis in bovine milk. The targeted relationship between miRNA-193a-5p and FADS1 in bovine mammary epithelial cells (BMECs) is demonstrated by dual luciferase reporter assays. qRT-PCR and western blot assays indicate that both the expression of mRNA and the protein FADS1 show a negative correlation with miRNA-193a-5p expression in BMECs. Also, miR-193a-5p expression is positively correlated with the expression of genes associated with milk fatty acid metabolism, including ELOVL fatty acid elongase 6 (ELOVL6) and diacylglycerol O-acyltransferase 2 (DGAT2). The expression of fatty acid desaturase 2 (FADS2) is negatively correlated with miR-193a-5p expression in BMECs. The contents of triglycerides (TAG), eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA) have a significant positive correlation with the expression of FADS1 and a significant negative correlation with the expression of miR-193a-5p in BMECs. For the first time, this study confirms that miRNA-193a-5p regulates PUFAs metabolism in BMECs by targeting FADS1, indicating that miRNA-193a-5p and FADS1 are underlying factors that improve PUFAs content in bovine milk.

Confirmed effects of candidate variants for milk production, udder health, and udder morphology in dairy cattle

Background

Over the last years, genome-wide association studies (GWAS) based on imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci (QTL) and highlight candidate genes for important traits. However, in general this approach does not allow to validate the effects of candidate mutations or determine if they are truly causative for the trait(s) in question. To address these questions, we applied a two-step, within-breed GWAS approach on 15 traits (5 linked with milk production, 2 with udder health, and 8 with udder morphology) in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) cattle. We detected the most-promising candidate variants (CV) using imputed WGS of 2515 MON, 2203 NOR, and 6321 HOL bulls, and validated their effects in three younger populations of 23,926 MON, 9400 NOR, and 51,977 HOL cows.

Results

Bull sequence-based GWAS detected 84 QTL: 13, 10, and 30 for milk production traits; 3, 0, and 2 for somatic cell score (SCS); and 8, 2 and 16 for udder morphology traits, in MON, NOR, and HOL respectively. Five genomic regions with effects on milk production traits were shared among the three breeds whereas six (2 for production and 4 for udder morphology and health traits) had effects in two breeds. In 80 of these QTL, 855 CV were highlighted based on the significance of their effects and functional annotation. The subsequent GWAS on MON, NOR, and HOL cows validated 8, 9, and 23 QTL for production traits; 0, 0, and 1 for SCS; and 4, 1, and 8 for udder morphology traits, respectively. In 47 of the 54 confirmed QTL, the CV identified in bulls had more significant effects than single nucleotide polymorphisms (SNPs) from the standard 50K chip. The best CV for each validated QTL was located in a gene that was functionally related to production (36 QTL) or udder (9 QTL) traits.

Conclusions

Using this two-step GWAS approach, we identified and validated 54 QTL that included CV mostly located within functional candidate genes and explained up to 6.3% (udder traits) and 37% (production traits) of the genetic variance of economically important dairy traits. These CV are now included in the chip used to evaluate French dairy cattle and can be integrated into routine genomic evaluation.

Gene Networks Driving Genetic Variation in Milk and Cheese-Making Traits of Spanish Assaf Sheep

Most of the milk produced by sheep is used for the production of high-quality cheese. Consequently, traits related to milk coagulation properties and cheese yield are economically important to the Spanish dairy industry. The present study aims to identify candidate genes and their regulators related to 14 milk and cheese-making traits and to develop a low-density panel of markers that could be used to predict an individual's genetic potential for cheese-making efficiency. In this study, we performed a combination of the classical genome-wide association study (GWAS) with a stepwise regression method and a pleiotropy analysis to determine the best combination of the variants located within the confidence intervals of the potential candidate genes that may explain the greatest genetic variance for milk and cheese-making traits. Two gene networks related to milk and cheese-making traits were created using the genomic relationship matrices built through a stepwise multiple regression approach. Several co-associated genes in these networks are involved in biological processes previously found to be associated with milk synthesis and cheese-making efficiency. The methodology applied in this study enabled the selection of a co-association network comprised of 374 variants located in the surrounding of genes showing a potential influence on milk synthesis and cheese-making efficiency.

Rumen Fermentation and Fatty Acid Composition of Milk of Mid Lactating Dairy Cows Grazing Chicory and Ryegrass

The goals of the current study were to investigate the effects of including chicory (Cichorium intybus L.) into the traditional feeding regime of ryegrass/white clover (Lolium perenne L./Trifolium repens L.), and time of its allocation on milk production, rumen fermentation, and FA composition of milk and rumen digesta of dairy cows. Nine groups of four cows were allocated one of three replicated feeding regimes: (1) ryegrass/white clover only (RGWC), (2) ryegrass/white clover + morning allocation of chicory (CHAM), and (3) ryegrass/white clover + afternoon allocation of chicory (CHPM). One cow per group had a rumen cannulae fitted. Treatment did not affect total grazing time or estimated dry matter intake, but cows ruminated more when fed RGWC than chicory. Allocating chicory in the afternoon elevated milk production compared with RGWC and CHAM. Milk from cows grazing chicory contained greater concentrations of polyunsaturated FA (PUFA) such as C18:3 c9, 12, 15 and C18:2 c9, 12 than those on RGWC. As with milk, rumen digesta concentration of PUFA increased when cows grazed on chicory rather than RGWC, which corresponded with lower concentrations of intermediate vaccenic and biohydrogenation end-product stearic acid for cows grazing on chicory. Mean ruminal pH was lower for cows offered chicory than those on RGWC, reflecting greater rumen concentrations of volatile fatty acids (VFA) for cows fed chicory. Allocating chicory during the afternoon is a useful strategy that can translate to improved milk production. The lower rumen pH, lower concentration of vaccenic and stearic acids, and elevated concentration of PUFA in the rumen of cows fed chicory suggest reduced biohydrogenation and may explain the elevated concentration of PUFA in the milk of cows fed chicory compared with those fed RGWC.

Putative biomarkers for early detection of mastitis in cattle

Context Mastitis is an inflammation of mammary gland parenchyma, and is an unending cause of economic loss to the dairy industry. The interest in research on biomarker discovery for the diagnosis of bovine mastitis stems largely from the need to identify reliable biomarkers. Aim To determine the putative biomarkers of mastitis by using bioinformatics analysis, and experimental validation of pro-inflammatory cytokines and oxidative stress biomarkers of the mammary gland in healthy and diseased animals. Methods Various in silico analysis tools were applied to screen for gene expression in mastitis. Milk, as well as blood samples, was collected aseptically from the animals, which were then classified into three groups; namely, clinical, subclinical and control. Samples were subjected to assay of pro-inflammatory cytokines and oxidative biomarkers using enzyme-linked immunosorbent assay kits and the prescribed methodology respectively. Key results In silico analysis revealed that mastitis reduces the expression of fat metabolism and immune system-related genes, whereas it increased the expression of inflammatory genes. On laboratory analysis of cytokines and acute phase protein, it was revealed that interleukin-1∝, interleukin-8 and haptoglobin were significantly (P &lt; 0.01) increased in both blood serum and milk whey in subclinical and clinical mastitis cows. On analysis of oxidative biomarkers, our results showed that oxidative stress was significantly (P &lt; 0.05) increased with progression of mastitis in dairy cows. There was a significant (P &lt; 0.05) increase in the blood serum level of malondialdehyde and nitric oxide, and a decrease in the level of anti-oxidant enzymes – glutathione peroxidase, superoxide dismutase and catalase – compared with healthy animals. Conclusion In conclusion, bioinformatics analysis of high-throughput gene expression revealed the involvement of multiple pathways, including the inflammatory pathway, fatty acid pathway and triglyceride synthesis pathway, in mastitis. Experimental validation confirmed that interleukin-8 and haptoglobin are putative early diagnostic markers for mastitis in dairy cattle. This study also concluded that milk can be used for the detection of cytokines as a non-invasive technique.

Predicting milk fatty acids and energy balance of dairy cows in Australia using milk mid-infrared spectroscopy

Mid-infrared spectroscopy (MIRS) is traditionally used for analysing milk fat, protein and lactose concentrations in dairy production, but there is growing interest in using it to predict difficult, or expensive-to-measure, phenotypes on a large scale. The resulting prediction equations can be applied to MIRS data from commercial herd-testing, to facilitate management and feeding decisions, or for genomic selection purposes. We investigated the ability of MIRS of milk samples to predict milk fatty acids (FAs) and energy balance (EB) of dairy cows in Australia. Data from 240 Holstein lactating cows that were part of two 32-day experiments, were used. Milk FAs were measured twice during the experimental period. Prediction models were developed using partial least-square regression with a 10-fold cross-validation. Measures of prediction accuracy included the coefficient of determination (R2cv) and root mean-square error. Milk FAs with a chain length of ≤16 were accurately predicted (0.89 ≤ R2cv ≤ 0.95), while prediction accuracy for FAs with a chain length of ≥17 was slightly lower (0.72 ≤ R2cv ≤ 0.82). The accuracy of the model prediction was moderate for EB, with the value of R2cv of 0.48. In conclusion, the ability of MIRS to predict milk FAs was high, while EB was moderately predicted. A larger dataset is needed to improve the accuracy and the robustness of the prediction models.

The "Grass-Fed" Milk Story: Understanding the Impact of Pasture Feeding on the Composition and Quality of Bovine Milk

Milk is a highly nutritious food that contains an array of macro and micro components, scientifically proven to be beneficial to human health. While the composition of milk is influenced by a variety of factors, such as genetics, health, lactation stage etc., the animal's diet remains a key mechanism by which its nutrition and processing characteristics can be altered. Pasture feeding has been demonstrated to have a positive impact on the nutrient profile of milk, increasing the content of some beneficial nutrients such as Omega-3 polyunsaturated fatty acids, vaccenic acid, and conjugated linoleic acid (CLA), while reducing the levels of Omega-6 fatty acids and palmitic acid. These resultant alterations to the nutritional profile of "Grass-Fed" milk resonate with consumers that desire healthy, "natural", and sustainable dairy products. This review provides a comprehensive comparison of the impact that pasture and non-pasture feeding systems have on bovine milk composition from a nutritional and functional (processability) perspective, highlighting factors that will be of interest to dairy farmers, processors, and consumers.

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.

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.

Sequence-based GWAS, network and pathway analyses reveal genes co-associated with milk cheese-making properties and milk composition in Montbéliarde cows

BACKGROUND

Milk quality in dairy cattle is routinely assessed via analysis of mid-infrared (MIR) spectra; this approach can also be used to predict the milk's cheese-making properties (CMP) and composition. When this method of high-throughput phenotyping is combined with efficient imputations of whole-genome sequence data from cows' genotyping data, it provides a unique and powerful framework with which to carry out genomic analyses. The goal of this study was to use this approach to identify genes and gene networks associated with milk CMP and composition in the Montbéliarde breed.

RESULTS

Milk cheese yields, coagulation traits, milk pH and contents of proteins, fatty acids, minerals, citrate, and lactose were predicted from MIR spectra. Thirty-six phenotypes from primiparous Montbéliarde cows (1,442,371 test-day records from 189,817 cows) were adjusted for non-genetic effects and averaged per cow. 50 K genotypes, which were available for a subset of 19,586 cows, were imputed at the sequence level using Run6 of the 1000 Bull Genomes Project (comprising 2333 animals). The individual effects of 8.5 million variants were evaluated in a genome-wide association study (GWAS) which led to the detection of 59 QTL regions, most of which had highly significant effects on CMP and milk composition. The results of the GWAS were further subjected to an association weight matrix and the partial correlation and information theory approach and we identified a set of 736 co-associated genes. Among these, the well-known caseins, PAEP and DGAT1, together with dozens of other genes such as SLC37A1, ALPL, MGST1, SEL1L3, GPT, BRI3BP, SCD, GPAT4, FASN, and ANKH, explained from 12 to 30% of the phenotypic variance of CMP traits. We were further able to identify metabolic pathways (e.g., phosphate and phospholipid metabolism and inorganic anion transport) and key regulator genes, such as PPARA, ASXL3, and bta-mir-200c that are functionally linked to milk composition.

CONCLUSIONS

By using an approach that integrated GWAS with network and pathway analyses at the whole-genome sequence level, we propose candidate variants that explain a substantial proportion of the phenotypic variance of CMP traits and could thus be included in genomic evaluation models to improve milk CMP in Montbéliarde cows.

The use of mid-infrared spectra to map genes affecting milk composition

The aim of this study was to investigate the feasibility of using mid-infrared (MIR) spectroscopy analysis of milk samples to increase the power and precision of genome-wide association studies (GWAS) for milk composition and to better distinguish linked quantitative trait loci (QTL). To achieve this goal, we analyzed phenotypic data of milk composition traits, related MIR spectra, and genotypic data comprising 626,777 SNP on 5,202 Holstein, Jersey, and crossbred cows. We performed a conventional GWAS on protein, lactose, fat, and fatty acid concentrations in milk, a GWAS on individual MIR wavenumbers, and a partial least squares regression (PLS), which is equivalent to a multi-trait GWAS, exploiting MIR data simultaneously to predict SNP genotypes. The PLS detected most of the QTL identified using single-trait GWAS, usually with a higher significance value, as well as previously undetected QTL for milk composition. Each QTL tends to have a different pattern of effects across the MIR spectrum and this explains the increased power. Because SNP tracking different QTL tend to have different patterns of effect, it was possible to distinguish closely linked QTL. Overall, the results of this study suggest that using MIR data through either GWAS or PLS analysis applied to genomic data can provide a powerful tool to distinguish milk composition QTL.

Proteomic analysis of goat milk kefir: Profiling the fermentation-time dependent protein digestion and identification of potential peptides with biological activity

Kefir is a fermented dairy product, associated to health benefits because of being a probiotic and due to the presence of molecules with biological activity. In this work, we have profiled the peptide composition of goat milk kefir at three different fermentation times using a peptidomics approach, in order to study changes in peptide concentrations and patterns of protein digestion throughout the fermentation time. We identified 2328 unique peptides corresponding to 22 protein annotations, with a maximum of peptides found after 24 h fermentation. We established different digestion patterns according to the nature of the proteins, and quantified the changes in the peptides appearing in all the fermentation times. We also identified 11 peptides that matched exactly to sequences with biological activity in databases, almost all of them belonging to caseins. This is the most comprehensive proteomic analysis of goat milk kefir to date.

Genome-wide association study for milk production traits in a Brazilian Holstein population

Advances in the molecular area of selection have expanded knowledge of the genetic architecture of complex traits through genome-wide association studies (GWAS). Several GWAS have been performed so far, but confirming these results is not always possible due to several factors, including environmental conditions. Thus, our objective was to identify genomic regions associated with traditional milk production traits, including milk yield, somatic cell score, fat, protein and lactose percentages, and fatty acid composition in a Holstein cattle population producing under tropical conditions. For this, 75,228 phenotypic records from 5,981 cows and genotypic data of 56,256 SNP from 1,067 cows were used in a weighted single-step GWAS. A total of 46 windows of 10 SNP explaining more than 1% of the genetic variance across 10 Bos taurus autosomes (BTA) harbored well-known and novel genes. The MGST1 (BTA5), ABCG2 (BTA6), DGAT1 (BTA14), and PAEP (BTA11) genes were confirmed within some of the regions identified in our study. Potential novel genes involved in tissue damage and repair of the mammary gland (COL18A1), immune response (LTTC19), glucose homeostasis (SLC37A1), synthesis of unsaturated fatty acids (LTBP1), and sugar transport (SLC37A1 and MFSD4A) were found for milk yield, somatic cell score, fat percentage, and fatty acid composition. Our findings may assist genomic selection by using these regions to design a customized SNP array to improve milk production traits on farms with similar environmental conditions.

Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition

Background

The power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis. Milk fatty acid (FA) traits are scarcely recorded due to expensive and time-consuming analytical techniques. Combining multi-population datasets can enhance the power of GWAS enabling detection of genomic region explaining medium to low proportions of the genetic variation. GWAS often detect broader genomic regions containing several positional candidate genes making it difficult to untangle the causative candidates. Post-GWAS analyses with data on pathways, ontology and tissue-specific gene expression status might allow prioritization among positional candidate genes.

Results

Multi-population GWAS for 16 FA traits quantified using gas chromatography (GC) in sample populations of the Chinese, Danish and Dutch Holstein with high-density (HD) genotypes detects 56 genomic regions significantly associated to at least one of the studied FAs; some of which have not been previously reported. Pathways and gene ontology (GO) analyses suggest promising candidate genes on the novel regions including OSBPL6 and AGPS on Bos taurus autosome (BTA) 2, PRLH on BTA 3, SLC51B on BTA 10, ABCG5/8 on BTA 11 and ALG5 on BTA 12. Novel genes in previously known regions, such as FABP4 on BTA 14, APOA1/5/7 on BTA 15 and MGST2 on BTA 17, are also linked to important FA metabolic processes.

Conclusion

Integration of multi-population GWAS and enrichment analyses enabled detection of several novel genomic regions, explaining relatively smaller fractions of the genetic variation, and revealed highly likely candidate genes underlying the effects. Detection of such regions and candidate genes will be crucial in understanding the complex genetic control of FA metabolism. The findings can also be used to augment genomic prediction models with regions collectively capturing most of the genetic variation in the milk FA traits.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5573-9) contains supplementary material, which is available to authorized users.

Effect of different exogenous fatty acids on the cytosolic triacylglycerol content in bovine mammary cells

The objective of this study was to determine how cytosolic triacylglycerols (TAG) are stored in mammary cells and whether this depends on the individual chemical configuration of fatty acids (FA). This objective was accomplished by addition of different FA to a FA-free medium used to culture mammary alveolar cells-large T antigen cells (MAC-T). Treatments consisted of adding FA (palmitate, stearate, oleate, linoleate, rumenic acid [CLA], elaidate and vaccinate) solutions to the medium at 100, 200, 300 and 400 mmol/L concentrations for a 24-h incubation period. At the end of each incubation period, cytosolic TAG, DNA and protein contents were measured. Palmitate, vaccenate, linoleate and CLA increased (P < 0.05) cytosolic TAG (μg/mg protein). Palmitate and CLA increased (P < 0.05) cytosolic TAG adjusted for DNA content. Overall, effects on cytosolic TAG accumulation depended on individual FA structure (chain length, degree of saturation, and number and orientation of FA double bonds). In addition, the long-chain FA used in this study did not have a detrimental effect on MAC-T cells as indicated by cytosolic protein and DNA contents reflecting their biological role in lipid accumulation.