Association between milk protein gene variants and protein composition traits in dairy cattle

Validation of Bos taurus SNPs for Milk Productivity of Sahiwal Breed (Bos indicus), Pakistan

The aim of the present study was the validation of the already reported Bos taurus SNPs in the Sahiwal breed. A total of nine SNPs of the casein gene were studied. Out of nine, seven Bos taurus SNPs of casein protein genes were found to be significantly associated with milk productivity traits. The genomic DNA was extracted from the mammary alveolar endothelial cells of a flock of 80 purebred Sahiwal lactating dams available at Khizrabad Farm near Sargodha. New allele-specific primers were designed from the NCBI annotated sequence database of Bos taurus to obtain 100 nt-long PCR products. Each dam was tested separately for all the SNPs investigated. Animals with genotype GG for the SNPs rs43703010, rs10500451, and 110323127, respectively, exhibited high milk yield. Similarly, animals with genotype AA for the SNPs rs11079521, rs43703016, and rs43703017 showed high milk yield consistently. For the SNP rs43703015, animals with genotype CC showed high milk productivity. These above-mentioned SNPs have previously been reported to significantly up-regulate casein protein contents in Bos taurus. Our results indicated SNPs that significantly affect the milk protein contents may also significantly increase per capita milk yield. These finding suggest that the above-mentioned reported SNPs can also be used as genetic markers of milk productivity in Sahiwal cattle.

Breeding for improved protein fractions and free amino acids concentration in bovine milk

Considerable resources are required to routinely measure detailed milk compositional traits. Hence, an insufficient volume of phenotypic data can hinder genetic progress in these traits within dairy cow breeding programmes. The objective of the present study was to quantify the opportunities for breeding for improved milk protein and free amino acid (FAA) composition by exploiting mid‐infrared spectroscopy (MIRS) predictions routinely recorded from milk samples. Genetic parameters for protein fractions and FAA composition were estimated using 134,546 test‐day records from 16,166 lactations on 9,572 cows using linear mixed models. Heritability of MIRS‐predicted protein fractions ranged from 0.19 (α‐lactalbumin) to 0.55 (β‐lactoglobulin A), while heritability of MIRS‐predicted FAA ranged from 0.08 for glycine to 0.29 for glutamic acid. Genetic correlations among the MIRS‐predicted FAA were moderate to strong ranging from −0.44 (aspartic acid and lysine) to 0.97 (glutamic acid and total FAA). Adjustment of the genetic correlations for the genetic merit of 24‐h milk yield did not greatly affect the correlations. Results from the current study highlight the presence of exploitable genetic variation for both protein fractions and FAA in dairy cow milk. Besides, the direction of genetic correlations reveals that breeding programmes directly selecting for greater milk protein concentration carry with them favourable improvement in casein and whey fractions.

A hypomorphic mutation in the mouse Csn1s1 gene generated by CRISPR/Cas9 pronuclear microinjection

Caseins are major milk proteins that have an evolutionarily conserved role in nutrition. Sequence variations in the casein genes affect milk composition in livestock species. Regulatory elements of the casein genes could be used to direct the expression of desired transgenes into the milk of transgenic animals. Dozens of casein alleles have been identified for goats, cows, sheep, camels and horses, and these sequence variants are associated with altered gene expression and milk protein content. Most of the known mutations affecting casein genes’ expression are located in the promoter and 3’-untranslated regions. We performed pronuclear microinjections with Cas9 mRNA and sgRNA against the first coding exon of the mouse Csn1s1 gene to introduce random mutations in the α-casein (Csn1s1) signal peptide sequence at the beginning of the mouse gene. Sanger sequencing of the founder mice identified 40 mutations. As expected, mutations clustered around the sgRNA cut site (3 bp from PAM). Most of the mutations represented small deletions (1–10 bp), but we detected several larger deletions as well (100–300 bp). Functionally most mutations led to gene knockout due to a frameshift or a start codon loss. Some of the mutations represented in-frame indels in the first coding exon. Of these, we describe a novel hypomorphic Csn1s1 (Csn1s1c.4-5insTCC) allele. We measured Csn1s1 protein levels and confirmed that the mutation has a negative effect on milk composition, which shows a 50 % reduction in gene expression and a 40–80 % decrease in Csn1s1 protein amount, compared to the wild-type allele. We assumed that mutation affected transcript stability or splicing by an unknown mechanism. This mutation can potentially serve as a genetic marker for low Csn1s1 expression.

Genomewide Association Analyses of Lactation Persistency and Milk Production Traits in Holstein Cattle Based on Imputed Whole-Genome Sequence Data

Lactation persistency and milk production are among the most economically important traits in the dairy industry. In this study, we explored the association of over 6.1 million imputed whole-genome sequence variants with lactation persistency (LP), milk yield (MILK), fat yield (FAT), fat percentage (FAT%), protein yield (PROT), and protein percentage (PROT%) in North American Holstein cattle. We identified 49, 3991, 2607, 4459, 805, and 5519 SNPs significantly associated with LP, MILK, FAT, FAT%, PROT, and PROT%, respectively. Various known associations were confirmed while several novel candidate genes were also revealed, including ARHGAP35, NPAS1, TMEM160, ZC3H4, SAE1, ZMIZ1, PPIF, LDB2, ABI3, SERPINB6, and SERPINB9 for LP; NIM1K, ZNF131, GABRG1, GABRA2, DCHS1, and SPIDR for MILK; NR6A1, OLFML2A, EXT2, POLD1, GOT1, and ETV6 for FAT; DPP6, LRRC26, and the KCN gene family for FAT%; CDC14A, RTCA, HSTN, and ODAM for PROT; and HERC3, HERC5, LALBA, CCL28, and NEURL1 for PROT%. Most of these genes are involved in relevant gene ontology (GO) terms such as fatty acid homeostasis, transporter regulator activity, response to progesterone and estradiol, response to steroid hormones, and lactation. The significant genomic regions found contribute to a better understanding of the molecular mechanisms related to LP and milk production in North American Holstein cattle.

Structural equation modeling for unraveling the multivariate genomic architecture of milk proteins in dairy cattle

The aims of this study were to investigate potential functional relationships among milk protein fractions in dairy cattle and to carry out a structural equation model (SEM) GWAS to provide a decomposition of total SNP effects into direct effects and effects mediated by traits that are upstream in a phenotypic network. To achieve these aims, we first fitted a mixed Bayesian multitrait genomic model to infer the genomic correlations among 6 milk nitrogen fractions [4 caseins (CN), namely κ-, β-, α_S1-, and α_S2-CN, and 2 whey proteins, namely β-lactoglobulin (β-LG) and α-lactalbumin (α-LA)], in a population of 989 Italian Brown Swiss cows. Animals were genotyped with the Illumina BovineSNP50 Bead Chip v.2 (Illumina Inc.). A Bayesian network approach using the max-min hill-climbing (MMHC) algorithm was implemented to model the dependencies or independence among traits. Strong and negative genomic correlations were found between β-CN and α_S1-CN (-0.706) and between β-CN and κ-CN (-0.735). The application of the MMHC algorithm revealed that κ-CN and β-CN seemed to directly or indirectly influence all other milk protein fractions. By integrating multitrait model GWAS and SEM-GWAS, we identified a total of 127 significant SNP for κ-CN, 89 SNP for β-CN, 30 SNP for α_S1-CN, and 14 SNP for α_S2-CN (mostly shared among CN and located on Bos taurus autosome 6) and 15 SNP for β-LG (mostly located on Bos taurus autosome 11), whereas no SNP passed the significance threshold for α-LA. For the significant SNP, we assessed and quantified the contribution of direct and indirect paths to total marker effect. Pathway analyses confirmed that common regulatory mechanisms (e.g., energy metabolism and hormonal and neural signals) are involved in the control of milk protein synthesis and metabolism. The information acquired might be leveraged for setting up optimal management and selection strategies aimed at improving milk quality and technological characteristics in dairy cattle.

Comparative proteomic characterization of bovine milk containing β-casein variants A1A1 and A2A2, and their heterozygote A1A2

BACKGROUND

Genetic variants of β-casein are cosnidered to affect the components of milk. However, limited data are available on the bovine protein components correlated with β-casein variants at the proteome level. In the present study, cows producing milk containing β-casein variants (A1A1 and A2A2) and their heterozygote (A1A2) were identified using a high-resolution melting method, and milk samples were collected and tested. Comparative analyses of casein micelles, whey and milk fat globule membrane fractions in each milk variant were performed using a label-free proteomics approach.

RESULTS

The results obtained showed that ceruloplasmin and cathelicidin-2 were the most abundant proteins in milk containing variant A1A1; lactoferrin and CD5 molecule-like were the most abundant proteins in milk containing variant A2A2; and selenoprotein P and osteopontin were the most abundant proteins in milk containing heterozygote A1A2. Differences in protein components in milk containing the different β-casein variants were visualized using hierarchical clustering, and profiles were separated using principal components analysis. The differentially expressed proteins in milk containing A1A1, A2A2 or A1A2 were predominantly involved in response to stress and defense response according to their Gene Ontology annotations.

CONCLUSION

Our findings provide new insights into differentially expressed milk proteins corresponding to the presence of different β-casein variants. This knowledge will help determine their potential biological functions in dairy products and the effects on human health. © 2020 Society of Chemical Industry.

Association of β-casein gene polymorphism with milk composition traits of Egyptian Maghrebi camels (Camelus dromedarius)

The objectives of this study were to detect the polymorphism of 2126A/G SNP in the β-casein (CSN2) gene among Egyptian Maghrebi camels and to investigate the association of 2126A/G SNP genotypes, parity, lactation stage, and temperature–humidity index (THI) with the milk composition traits of Maghrebi camels. Sixty-eight hair samples were collected from three different populations of Maghrebi camels for DNA extraction. Fat, protein, total solids, solids-not-fat, and lactose percentages were determined in Maghrebi camel milk using an automatic milk analyzer device. Three different genotypes – A/A, A/G, and G/G – were identified in the 5′ flanking region of β-casein gene by using PCR-RFLP method with the A/G genotype showing the highest frequency. Association among these three genotypes with milk composition traits suggests a positive effect of A/A genotype on acidity and protein percentage. Higher protein and acidity values were observed in the milk of individuals carrying the A/A genotype. The protein percentage of this study significantly increased from the first till the fourth parity and then decreased. Fat and total solid percentages were significantly higher in the late stage of lactation, while lactose showed a decreasing trend from the early till the late stages of lactation. Fat and protein percentages were highest in the low THI class. Our results encourage the utilization of Maghrebi camel milk for cheese and butter processing at the late lactation stages of the middle parities of their productive life. Moreover, the A/G SNP of the CSN2 gene may be used as a DNA marker in selection programs for the improvement of camel milk composition. Further studies are needed in order to fully explore the variation in the chemical composition of camel milk due to the effect of CSN2 gene, parity, lactation stage, and THI factors.

Development of TaqMan PCR assay for detection of A and B variants of the bovine β-lactoglobulin

β-Lactoglobulin (BLG) is one of the prevalent whey protein in cattle. To date, several variants of bovine BLG have been found, but the most common are A and B, which differ from each other by SNPs rs109625649 and rs110066229. Numerous studies showed effects of A and B variants of BLG on milk yield, fat and protein content and cheese-making properties. To date, polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), allele-specific polymerase chain reaction (ASPCR), PCR single-strand conformation polymorphism (PCR-SSCP) and high resolution melting (HRM) methods have been proposed for detection of A and B variants of bovine BLG. These methods involve multistep sample processing, which is an essential disadvantage in conducting large-scale cattle genotyping projects. This article describes a development of TaqMan PCR assay for detection of A and B variants (rs109625649) of bovine BLG. In this method a primer pair, initiating amplification of 101-bp fragment of BLG gene, and two allele-specific TaqMan probes are used. Identification of B and A variants of BLG is based on comparison of final fluorescence intensity of FAM and VIC dyes, respectively. The developed one-step method requires less time and is more suitable for large-scale genotyping of cattle compared to the commonly used PCR-RFLP.

Changes in Metabolites from Bovine Milk with β-Casein Variants Revealed by Metabolomics

Simple Summary

Changes in milk protein content have been associated with β-casein variants. However, the specific changes in the metabolites of β-casein variant milk remain unclear. Thus, a metabolomics approach was employed to determine the abundance of different metabolites in milk samples with β-casein variant A1/A1, A2/A2, and their heterozygote. The metabolites with the highest abundance were methionine, proline, and α-lactose in variant A2/A2 milk, choline, glycine, citric acid, and cyclic adenosine monophosphate (cAMP) in variant A1/A1 milk, and uric acid and cytosine in heterozygote milk. These results may facilitate further explorations of the differences in the biosynthesis of milk components in the mammary gland and help to elucidate the potential influence of β-casein variants on the physiological function of milk.

Abstract

β-casein is a primary protein in milk, and its variants have been associated with changes in the protein content of bovine milk. However, there has been little research focused on the effects of β-casein variants on milk metabolites. In the present study, dairy cows producing milk with β-casein variant A1/A1 (A1), A2/A2 (A2), and their heterozygote A1/A2 (A12) were screened by a high-resolution melting method. Individual milk samples were then collected from each of the cows, and the milk metabolites were separated and analyzed using nuclear magnetic resonance spectroscopy- and liquid-chromatography mass spectrometry-based metabolomics techniques. Differences in metabolites among the variant groups were evaluated by multivariate statistical analysis. The relative abundances of methionine, proline, and α-lactose were the highest in β-casein variant A2 milk, whereas choline, glycine, citric acid, and cyclic adenosine monophosphate (cAMP) showed the highest abundances in variant A1 milk. Metabolic pathways analysis indicated that the differential metabolites between variants A1 and A2 were involved in pantothenate and coenzyme A biosynthesis, butanoate metabolism, and valine, leucine, and isoleucine biosynthesis. Our results reveal the differences in milk metabolites among the β-casein variants A1, A2, and the heterozygote. These findings, thus, provide novel insights into the effects of β-casein variants on milk metabolites, facilitating further research into the mechanism of the biosynthesis of milk components in the mammary gland and the potential physiological function of milk associated with β-casein variants.

Genomic Analysis of Milk Protein Fractions in Brown Swiss Cattle

Simple Summary

Milk protein fractions are hugely important in the dairy industry because of the key role they play in milk technological properties. The selection of cows for milk protein fractions may, therefore, improve both the nutritional and technological characteristics of milk, and, consequently, the processing efficiency and value of the dairy product. This study estimated the genetic parameters of the major milk protein fractions (four caseins, and two whey proteins) determined variously as: (i) milk content (g/100g milk), (ii) percentage of milk nitrogen (%N) and (iii) daily yield (g/d) in Brown Swiss dairy cattle. The results showed that the (co)variances and genetic parameter estimates differed according to how the proteins were measured. These results provide useful information for developing selection strategies in dairy cattle breeding programs aimed at improving both the nutritional and technological properties of milk.

Abstract

Depending on whether milk protein fractions are evaluated qualitatively or quantitatively, different genetic outcomes may emerge. In this study, we compared the genetic parameters for the major milk protein fractions—caseins (α_S1-, α_S2-, β-, and к-CN), and whey proteins (β-lactoglobulin, β-LG; α-lactalbumin, α-LA)—estimated using the multi-trait genomic best linear unbiased prediction method and expressed variously as milk content (g/100g milk), percentage of milk nitrogen (%N) and daily yield per cow (g/d). The results showed that the genetic parameter estimates varied according to how the milk protein fractions were expressed. Heritability estimates for the caseins and whey protein fractions expressed as daily yields were lower than when they were expressed as proportions and contents, revealing important differences in genetic outcomes. The proportion and the content of β-CN were negatively correlated with the proportions and contents of α_S1-CN, α_S2-CN, and к-CN, while the daily yield of β–CN was negatively correlated with the daily yields of α_S1-CN and α_S2-CN. The Spearman’s rank correlations and the coincidence rates between the various predicted genomic breeding values (GEBV) for the milk protein fractions expressed in different ways indicated that these differences had a significant effect on the ranking of the animals. The results suggest that the way milk protein fractions are expressed has implications for breeding programs aimed at improving milk nutritional and technological characteristics.

Single-step genome-wide association for longitudinal traits of Canadian Ayrshire, Holstein, and Jersey dairy cattle

Estimating single nucleotide polymorphism (SNP) effects over time is essential to identify and validate candidate genes (or quantitative trait loci) associated with time-dependent variation of economically important traits and to better understand the underlying mechanisms of lactation biology. Therefore, in this study, we aimed to estimate time-dependent effects of SNP and identifying candidate genes associated with milk (MY), fat (FY), and protein (PY) yields, and somatic cell score (SCS) in the first 3 lactations of Canadian Ayrshire, Holstein, and Jersey breeds, as well as suggest their potential pattern of phenotypic effect over time. Random regression coefficients for the additive direct genetic effect were estimated for each animal using single-step genomic BLUP, based on 2 random regression models: one considering MY, FY, and PY in the first 3 lactations and the other considering SCS in the first 3 lactations. Thereafter, SNP solutions were obtained for random regression coefficients, which were used to estimate the SNP effects over time (from 5 to 305 d in lactation). The top 1% of SNP that showed a high magnitude of SNP effect in at least 1 d in lactation were selected as relevant SNP for further analyses of candidate genes, and clustered according to the trajectory of their SNP effects over time. The majority of SNP selected for MY, FY, and PY increased the magnitude of their effects over time, for all breeds. In contrast, for SCS, most selected SNP decreased the magnitude of their effects over time, especially for the Holstein and Jersey breeds. In general, we identified a different set of candidate genes for each breed, and similar genes were found across different lactations for the same trait in the same breed. For some of the candidate genes, the suggested pattern of phenotypic effect changed among lactations. Among the lactations, candidate genes (and their suggested phenotypic effect over time) identified for the second and third lactations were more similar to each other than for the first lactation. Well-known candidate genes with major effects on milk production traits presented different suggested patterns of phenotypic effect across breeds, traits, and lactations in which they were identified. The candidate genes identified in this study can be used as target genes in studies of gene expression.

Genome-Wide Association Study for Milk Protein Composition Traits in a Chinese Holstein Population Using a Single-Step Approach

Genome-wide association studies (GWASs) have been widely used to determine the genetic architecture of quantitative traits in dairy cattle. In this study, with the aim of identifying candidate genes that affect milk protein composition traits, we conducted a GWAS for nine such traits (α_s1-casein, α_s2-casein, β-casein, κ-casein, α-lactalbumin, β-lactoglobulin, casein index, protein percentage, and protein yield) in 614 Chinese Holstein cows using a single-step strategy. We used the Illumina BovineSNP50 Bead chip and imputed genotypes from high-density single-nucleotide polymorphisms (SNPs) ranging from 50 to 777 K, and subsequent to genotype imputation and quality control, we screened a total of 586,304 informative high-quality SNPs. Phenotypic observations for six major milk proteins (α_s1-casein, α_s2-casein, β-casein, κ-casein, α-lactalbumin, and β-lactoglobulin) were evaluated as weight proportions of the total protein fraction (wt/wt%) using a commercial enzyme-linked immunosorbent assay kit. Informative windows comprising five adjacent SNPs explaining no < 0.5% of the genomic variance per window were selected for gene annotation and gene network and pathway analyses. Gene network analysis performed using the STRING Genomics 10.0 database revealed a co-expression network comprising 46 interactions among 62 of the most plausible candidate genes. A total of 178 genomic windows and 194 SNPs on 24 bovine autosomes were significantly associated with milk protein composition or protein percentage. Regions affecting milk protein composition traits were mainly observed on chromosomes BTA 1, 6, 11, 13, 14, and 18. Of these, several windows were close to or within the CSN1S1, CSN1S2, CSN2, CSN3, LAP3, DGAT1, RPL8, and HSF1 genes, which have well-known effects on milk protein composition traits of dairy cattle. Taken together with previously reported quantitative trait loci and the biological functions of the identified genes, we propose 19 novel candidate genes affecting milk protein composition traits: ARL6, SST, EHHADH, PCDHB4, PCDHB6, PCDHB7, PCDHB16, SLC36A2, GALNT14, FPGS, LARP4B, IDI1, COG4, FUK, WDR62, CLIP3, SLC25A21, IL5RA, and ACADSB. Our findings provide important insights into milk protein synthesis and indicate potential targets for improving milk quality.

Genetic Analyses Confirm SNPs in HSPA8 and ERBB2 are Associated with Milk Protein Concentration in Chinese Holstein Cattle

Heat shock 70 kDa protein 8 (HSPA8) and erb-b2 receptor tyrosine kinase 2 (ERBB2) were the promising candidates for milk protein concentration in dairy cattle revealed through previous RNA sequencing (RNA-Seq) study. The objective of this post-RNA-Seq study was to confirm genetic effects of HSPA8 and ERBB2 on milk protein concentration in a large Chinese Holstein population and to evaluate the genetic effects of both genes on other milk production traits. There were 2 single-nucleotide polymorphisms (SNPs) identified for HSPA8 and 11 SNPs for ERBB2 by sequencing 17 unrelated Chinese Holstein sires. The SNP-rs136632043 in HSPA8 had significant associations with all five milk production traits (p = 0.0086 to p < 0.0001), whereas SNP-rs132976221 was remarkably associated with three yield traits (p < 0.0001). Nine (ss1996900615, rs109017161, rs109122971, ss1996900614, rs110133654, rs109941438, rs110552983, rs133031530, and rs109763505) of 11 SNPs in ERBB2 were significantly associated with milk protein percentage (p = 0.0177 to p < 0.0001). A 12 Kb haplotype block was formed in ERBB2 and haplotype associations revealed similar effects on milk protein traits. Our findings confirmed the significant genetic effects of HSPA8 and ERBB2 on milk protein concentration and other milk production traits and SNP phenotypic variances above 1% may serve as genetic markers in dairy cattle breeding programs.

Single nucleotide polymorphisms in candidate genes associated with milk yield in Argentinean Holstein and Holstein x Jersey cows

BACKGROUND

Research on loci influencing milk production traits of dairy cattle is one of the main topics of investigation in livestock. Many genomic regions and polymorphisms associated with dairy production have been reported worldwide. In this context, the purpose of this study was to identify candidate loci associated with milk yield in Argentinean dairy cattle. A database of candidate genes and single nucleotide polymorphisms (SNPs) for milk production and composition was developed. Thirty-nine SNPs belonging to 22 candidate genes were genotyped on 1643 animals (Holstein and Holstein x Jersey). The genotypes obtained were subjected to association studies considering the whole population and discriminating the population by Holstein breed percentage. Phenotypic data consisted of milk production values recorded during the first lactation of 1156 Holstein and 462 Holstein x Jersey cows from 18 dairy farms located in the central dairy area of Argentina. From these records, 305-day cumulative milk production values were predicted.

RESULTS

Eight SNPs (rs43375517, rs29004488, rs132812135, rs137651874, rs109191047, rs135164815, rs43706485, and rs41255693), located on six Bos taurus autosomes (BTA4, BTA6, BTA19, BTA20, BTA22, and BTA26), showed suggestive associations with 305-day cumulative milk production (under Benjamini-Hochberg procedure with a false discovery rate of 0.1). Two of those SNPs (rs43375517 and rs135164815) were significantly associated with milk production (Bonferroni adjusted p-values < 0.05) when considering the Holstein population.

CONCLUSIONS

The results obtained are consistent with previously reported associations in other Holstein populations. Furthermore, the SNPs found to influence bovine milk production in this study may be used as possible candidate SNPs for marker-assisted selection programs in Argentinean dairy cattle.

Recent progress of porcine milk components and mammary gland function

As the only nutritional source for newborn piglets, porcine colostrum and milk contain critical nutritional and immunological components including carbohydrates, lipids, and proteins (immunoglobulins). However, porcine milk composition is more complex than these three components. Recently, scientists identified additional and novel components of sow colostrum and milk, including exosomes, oligosaccharides, and bacteria, which possibly act as biological signals and modulate the intestinal environment and immune status in piglets and later in life. Evaluation of these nutritional and non-nutritional components in porcine milk will help better understand the nutritional and biological function of porcine colostrum and milk. Furthermore, some important functions of the porcine mammary gland have been reported in recent published literature. These preliminary studies hypothesized how glucose, amino acids, and fatty acids are transported from maternal blood to the porcine mammary gland for milk synthesis. Therefore, we summarized recent reports on sow milk composition and porcine mammary gland function in this review, with particular emphasis on macronutrient transfer and synthesis mechanisms, which might offer a possible approach for regulation of milk synthesis in the future.

Integrated analysis of long noncoding RNA and mRNA expression profiles reveals the potential role of long noncoding RNA in different bovine lactation stages

Long noncoding RNA (lncRNA) play a critical role in mammary development and breast cancer biology. Despite their important role in the mammary gland, little is known of the roles of lncRNA in bovine lactation, particularly regarding the molecular processes underlying it. To characterize the role of lncRNA in bovine lactation, 4 samples of Holstein cow mammary gland tissue at peak and late lactation stages were examined after biopsy. We then profiled the transcriptome of the mammary gland using RNA sequencing technology. Further, functional lncRNA-mRNA coexpression pairs were constructed to infer the function of lncRNA using a generalized linear model, followed by gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. More than 1,000 putative lncRNA were identified, 117 of which were differentially expressed between peak and late lactation stages. Bovine lncRNA were shorter, with fewer exon numbers, and expressed at significantly lower levels than protein-coding genes. Seventy-two differentially expressed (DE) lncRNA were coexpressed with 340 different protein-coding genes. The KEGG pathway analysis showed that target mRNA for DE lncRNA were mainly related to lipid and glucose metabolism, including the peroxisome proliferator-activated receptors and 5' adenosine monophosphate-activated protein kinase signaling pathways. Further bioinformatics and integrative analyses revealed that 12 DE lncRNA potentially played important roles in bovine lactation. Our findings provide a valuable resource for future bovine transcriptome studies, facilitate the understanding of bovine lactation biology, and offer functional information for cattle lactation.

Genomewide association study for production and meat quality traits in Canchim beef cattle

The commercial value of the bovine carcass is determined by a set of traits, such as weight, yield, back fat thickness, and marbling; therefore, the genetic improvement of growth, meat, and carcass quality traits is an important tool to add value to the supply chain. Genomewide association studies (GWAS) enable the identification of loci that control phenotypic expression of quantitative traits (QTL). Therefore, the objective of this work was to perform a GWAS to identify genomic regions and genes associated with growth, carcass traits, and meat quality in Canchim beef cattle. These traits were yearling weight (YW), rib eye area (REA), back fat thickness (BFT), and marbling (MARB). To increase sample size and marker density, genotype imputation was performed, and only markers imputed with greater than 95% accuracy were used. Genomewide association study was performed using a Bayesian approach, by the Bayes B statistical method, incorporating genotypes and phenotypes from 614 animals from both the Canchim breed and the MA genetic group (offspring of Charolais bulls and one-half Canchim + one-half Zebu cows). This investigation identified 1 and 4 genomic regions explaining 0.23 and 7.35% of the genetic variance for REA and YW, respectively. These regions harbor a total of 19 genes, 7 of which were classified for biological functions by functional analysis. Significant associations were not observed for BFT and MARB. The identification of QTL that had been previously described in the literature reinforces associations found in this study.

Integration of GWAS, pathway and network analyses reveals novel mechanistic insights into the synthesis of milk proteins in dairy cows

The quantities and proportions of protein fractions have notable effects on the nutritional and technological value of milk. Although much is known about the effects of genetic variants on milk proteins, the complex relationships among the set of genes and pathways regulating the different protein fractions synthesis and secretion into milk in dairy cows are still not completely understood. We conducted genome-wide association studies (GWAS) for milk nitrogen fractions in a cohort of 1,011 Brown Swiss cows, which uncovered 170 significant single nucleotide polymorphism (SNPs), mostly located on BTA6 and BTA11. Gene-set analysis and the network-based Associated Weight Matrix approach revealed that the milk proteins associated genes were involved in several biological functions, particularly ion and cation transmembrane transporter activity and neuronal and hormone signalling, according to the structure and function of casein micelles. Deeper analysis of the transcription factors and their predicted target genes within the network revealed that GFI1B, ZNF407 and NR5A1 might act as master regulators of milk protein synthesis and secretion. The information acquired provides novel insight into the regulatory mechanisms controlling milk protein synthesis and secretion in bovine mammary gland and may be useful in breeding programmes aimed at improving milk nutritional and/or technological properties.

Association of candidate gene polymorphisms with milk technological traits, yield, composition, and somatic cell score in Italian Holstein-Friesian sires

Advances in DNA-based marker technology have enabled the identification of genomic regions underlying complex phenotypic traits in livestock species. The incorporation of detected quantitative trait loci into genetic evaluation provides great potential to enhance selection accuracies, hence expediting the genetic improvement of economically important traits. The objective of the present study was to investigate 96 single nucleotide polymorphisms (SNP) located in 53 candidate genes previously reported to have effects on milk production and quality traits in a population of highly selected Holstein-Friesian bulls. A total of 423 semen samples were used to genotype the bulls through a custom oligo pool assay. Forty-five SNP in 32 genes were found to be associated with at least 1 of the tested traits. Most significant and favorable SNP trait associations were observed for polymorphisms located in CCL3 and AGPAT6 genes for fat yield (0.037 and 0.033 kg/d, respectively), DGKG gene for milk yield (0.698 kg/d), PPARGC1A, CSN1S1, and AGPAT6 genes for fat percentage (0.127, 0.113, and 0.093%, respectively), GHR gene for protein (0.064%) and casein percentage (0.053%), and TLR4 gene for fat (0.090%), protein (0.066%), and casein percentage (0.050%). Somatic cell score was favorably affected by GHR (-0.095) and POU1F1 (-0.137), and interesting SNP-trait associations were observed for polymorphisms located in CSN2, POU1F1, and AGPAT6 genes for rennet coagulation time (-0.592, -0.558, and -0.462 min, respectively), and GHR and CSN2 genes for curd firmness 30 min after rennet addition (1.264 and 1.183 mm, respectively). In addition to the influence of individual SNP, the effects of composite genotypes constructed by grouping SNP according to their individual effects on traits considered in the analysis were also examined. Favorable and significant effects on milk traits were observed for 2 composite genotypes, one including 10 SNP and the other 4 SNP. The former was associated with an increase of milk (0.075 kg/d), fat (0.097 kg/d), protein (0.083 kg/d), and casein yields (0.065 kg/d), and the latter was associated with an increase of fat (0.244%), protein (0.071%), and casein percentage (0.047%). Although further research is required to validate the identified SNP loci in other populations and breeds, our results can be considered as a preliminary foundation for further replication studies on gene-assisted selection programs.

A genome scan for milk production traits in dairy goats reveals two new mutations in Dgat1 reducing milk fat content

The quantity of milk and milk fat and proteins are particularly important traits in dairy livestock. However, little is known about the regions of the genome that influence these traits in goats. We conducted a genome wide association study in French goats and identified 109 regions associated with dairy traits. For a major region on chromosome 14 closely associated with fat content, the Diacylglycerol O-Acyltransferase 1 (DGAT1) gene turned out to be a functional and positional candidate gene. The caprine reference sequence of this gene was completed and 29 polymorphisms were found in the gene sequence, including two novel exonic mutations: R251L and R396W, leading to substitutions in the protein sequence. The R251L mutation was found in the Saanen breed at a frequency of 3.5% and the R396W mutation both in the Saanen and Alpine breeds at a frequencies of 13% and 7% respectively. The R396W mutation explained 46% of the genetic variance of the trait, and the R251L mutation 6%. Both mutations were associated with a notable decrease in milk fat content. Their causality was then demonstrated by a functional test. These results provide new knowledge on the genetic basis of milk synthesis and will help improve the management of the French dairy goat breeding program.

Milk protein polymorphisms and casein haplotypes in Butana cattle

Butana is a Bos indicus dairy cattle breed that is well adapted to the local environment of Sudan. The breed has been gradually declining in number due to breed substitution. Therefore, conservation and improvement strategies are required to maintain this breed. The aim of the present study was to assess genetic variation that is characteristic for Butana cattle in the milk protein genes CSN1S1, CSN2, CSN1S2, CSN3, LALBA, and LGB. In a first step, genomic DNA of five unrelated individuals was comparatively sequenced across all exon and flanking sequences. Ninety-three single nucleotide polymorphisms (SNPs) were identified in Butana cattle compared with the Bos taurus reference sequence at Ensembl. We confirmed the recently identified protein variants CSN2*J, CSN2*L, and LALBA*E. Fifty-two SNPs in non-coding regions are novel. Among the novel SNPs, five are located in promoter regions, three of them are in putative transcription factor binding sites (TFBSs) of the CSN1S2 promoter. Fifteen SNPs potentially affect miRNA target sites. In a second step, 50 unrelated Butana cattle were genotyped. This allowed deriving haplotypes for the casein gene cluster on BTA6. The most frequent haplotype was CSN1S1*C-CSN2*A ² -CSN1S2*A-CSN3*A (C-A ² -A-A, frequency 0.1546). Considering the newly identified CSN1S2 promoter variants, the most frequent haplotype was C-A ² -TTC-A-A (0.1046), with TTC as the promoter variant. The information on protein and promoter variants can be used for the development of conservation and breeding strategies for this local breed.

Biological underpinnings of breastfeeding challenges: the role of genetics, diet, and environment on lactation physiology

Lactation is a dynamic process that has evolved to produce a complex biological fluid that provides nutritive and nonnutritive factors to the nursing offspring. It has long been assumed that once lactation is successfully initiated, the primary factor regulating milk production is infant demand. Thus, most interventions have focused on improving breastfeeding education and early lactation support. However, in addition to infant demand, increasing evidence from studies conducted in experimental animal models, production animals, and breastfeeding women suggests that a diverse array of maternal factors may also affect milk production and composition. In this review, we provide an overview of our current understanding of the role of maternal genetics and modifiable factors, such as diet and environmental exposures, on reproductive endocrinology, lactation physiology, and the ability to successfully produce milk. To identify factors that may affect lactation in women, we highlight some information gleaned from studies in experimental animal models and production animals. Finally, we highlight the gaps in current knowledge and provide commentary on future research opportunities aimed at improving lactation outcomes in breastfeeding women to improve the health of mothers and their infants.

Genome-wide association for milk production and female fertility traits in Canadian dairy Holstein cattle

BACKGROUND

Genome-wide association studies (GWAS) are a powerful tool for detecting genomic regions explaining variation in phenotype. The objectives of the present study were to identify or refine the positions of genomic regions affecting milk production, milk components and fertility traits in Canadian Holstein cattle, and to use these positions to identify genes and pathways that may influence these traits.

RESULT

Several QTL regions were detected for milk production (MILK), fat production (FAT), protein production (PROT) and fat and protein deviation (FATD, PROTD respectively). The identified QTL regions for production traits (including milk production) support previous findings and some overlap with genes with known relevant biological functions identified in earlier studies such as DGAT1 and CPSF1. A significant region on chromosome 21 overlapping with the gene FAM181A and not previous linked to fertility in dairy cattle was identified for the calving to first service interval and days open. A functional enrichment analysis of the GWAS results yielded GO terms consistent with the specific phenotypes tested, for example GO terms GO:0007595 (lactation) and GO:0043627 (response to estrogen) for milk production (MILK), GO:0051057 (positive regulation of small GTPase mediated signal transduction) for fat production (FAT), GO:0040019 (positive regulation of embryonic development) for first service to calving interval (CTFS) and GO:0043268 (positive regulation of potassium ion transport) for days open (DO). In other cases the connection between the enriched GO terms and the traits were less clear, for example GO:0003279 (cardiac septum development) for FAT and GO:0030903 (notochord development) for DO trait.

CONCLUSION

The chromosomal regions and enriched pathways identified in this study confirm several previous findings and highlight new regions and pathways that may contribute to variation in production or fertility traits in dairy cattle.

Bovine chromosomal regions affecting rheological traits in acid-induced skim milk gels

The production of fermented milk products has increased worldwide during the last decade and is expected to continue to increase during the coming decade. The quality of these products may be optimized through breeding practices; however, the relations between cow genetics and technological properties of acid milk gels are not fully known. Therefore, the aim of this study was to identify chromosomal regions affecting acid-induced coagulation properties and possible candidate genes. Skim milk samples from 377 Swedish Red cows were rheologically analyzed for acid-induced coagulation properties using low-amplitude oscillation measurements. The resulting traits, including gel strength, coagulation time, and yield stress, were used to conduct a genome-wide association study. Single nucleotide polymorphisms (SNP) were identified using the BovineHD SNPChip (Illumina Inc., San Diego, CA), resulting in almost 621,000 segregating markers. The genome was scanned for putative quantitative trait loci (QTL) regions, haplotypes based on highly associated SNP were inferred, and the additive genetic effects of haplotypes within each QTL region were analyzed using mixed models. A total of 8 genomic regions were identified, with large effects of the significant haplotype explaining between 4.8 and 9.8% of the phenotypic variance of the studied traits. One major QTL was identified to overlap between gel strength and yield stress, the QTL identified with the most significant SNP closest to the gene coding for κ-casein (CSN3). In addition, a chromosome-wide significant region affecting yield stress on BTA 11 was identified to be colocated with PAEP, coding for β-lactoglobulin. Furthermore, the coagulation properties of the genetic variants within the 2 genes were compared with the coagulation properties identified by the patterns of the haplotypes within the regions, and it was discovered that the haplotypes were more diverse and in one case slightly better at explaining the phenotypic variance. Besides these significant QTL comprising the 2 milk proteins, 3 additional genes are proposed as possible candidates, namely RAB22A, CDH13, and STAT1, and all have previously been found to be expressed in the mammary gland. To our knowledge, this is the first attempt to map QTL regions for acid-induced coagulation properties.

A candidate gene association study for nine economically important traits in Italian Holstein cattle

We genotyped 58 single nucleotide polymorphisms (SNPs) in 25 candidate genes in about 800 Italian Holstein sires. Fifty-six (minor allele frequency >0.02) were used to evaluate their association with single traits: milk yield (MY), milk fat yield (FY), milk protein yield (PY), milk fat percentage (FP), milk protein percentage (PP), milk somatic cell count (MSCC); and complex indexes: longevity, fertility and productivity-functionality type (PFT), using deregressed proofs, after adjustment for familial relatedness. Thirty-two SNPs were significantly associated (proportion of false positives <0.05) with different traits: 16 with MSCC, 15 with PY, 14 with MY, 12 with PFT, eight with longevity, eight with FY, eight with PP, five with FP and two with fertility. In particular, a SNP in the promoter region of the PRLR gene was associated with eight of nine traits. DGAT1 polymorphisms were highly associated with FP and FY. Casein gene markers were associated with several traits, confirming the role of the casein gene cluster in affecting milk yield, milk quality and health traits. Other SNPs in genes located on chromosome 6 were associated with PY, PP, PFT, MY (PPARGC1A) and MSCC (KIT). This latter association may suggest a biological link between the degree of piebaldism in Holstein and immunological functions affecting somatic cell count and mastitis resistance. Other significant SNPs were in the ACACA, CRH, CXCR1, FASN, GH1, LEP, LGB (also known as PAEP), MFGE8, SRC, TG, THRSP and TPH1 genes. These results provide information that can complement QTL mapping and genome-wide association studies in Holstein.

Genomic architecture of bovine κ-casein and β-lactoglobulin

The objective of this study was to characterize the genetic architecture underlying the absolute concentrations of 2 important milk proteins, κ-casein (κ-CN) and β-lactoglobulin (β-LG), in a backcross population of (Holstein × Jersey) × Holstein cattle. A genome-wide association analysis was performed using a selective DNA pooling strategy and the Illumina BovineHD BeadChip assay [777,000 (777K) SNP markers; Illumina Inc., San Diego, CA]. After correction for multiple testing, 25 single nucleotide polymorphisms were found to be associated with κ-CN and 36 single nucleotide polymorphisms were associated with β-LG. A pathway association analysis revealed 15 Gene Ontology (GO) terms associated with the κ-CN trait and 28 GO terms associated with β-LG. In addition, several GO terms were associated with both milk proteins. Further analysis revealed that κ-CN and β-LG production is regulated by both kinase and phosphatase activity, including mechanisms regulating the extracellular matrix. These results are in concordance with the complex multihormonal process controlling the expression of milk proteins and interactions between mammary epithelial cells and extracellular matrix components. Although κ-CN and β-LG milk proteins are expressed by single genes, the results from this study showed that many loci are involved in the regulation of the concentration of these 2 proteins.