Genetic parameters for beef and milk production in Dutch Red and White dual-purpose cattle and their implications for a breeding program

Claw diseases and mastitis represent the most important disease traits in dairy cattle with increasing incidences and a frequently mentioned connection to milk yield. Yet, many studies aimed to detect the genetic background of both trait complexes via fine-mapping of quantitative trait loci. However, little is known about genomic regions that simultaneously affect milk production and disease traits. For this purpose, several tools to detect local genetic correlations have been developed. In this study, we attempted a detailed analysis of milk production and disease traits as well as their interrelationship using a sample of 34,497 50K genotyped German Holstein cows with milk production and claw and udder disease traits records. We performed a pedigree-based quantitative genetic analysis to estimate heritabilities and genetic correlations. Additionally, we generated GWAS summary statistics, paying special attention to genomic inflation, and used these data to identify shared genomic regions, which affect various trait combinations. The heritability on the liability scale of the disease traits was low, between 0.02 for laminitis and 0.19 for interdigital hyperplasia. The heritabilities for milk production traits were higher (between 0.27 for milk energy yield and 0.48 for fat-protein ratio). Global genetic correlations indicate the shared genetic effect between milk production and disease traits on a whole genome level. Most of these estimates were not significantly different from zero, only mastitis showed a positive one to milk (0.18) and milk energy yield (0.13), as well as a negative one to fat-protein ratio (-0.07). The genomic analysis revealed significant SNPs for milk production traits that were enriched on Bos taurus autosome 5, 6, and 14. For digital dermatitis, we found significant hits, predominantly on Bos taurus autosome 5, 10, 22, and 23, whereas we did not find significantly trait-associated SNPs for the other disease traits. Our results confirm the known genetic background of disease and milk production traits. We further detected 13 regions that harbor strong concordant effects on a trait combination of milk production and disease traits. This detailed investigation of genetic correlations reveals additional knowledge about the localization of regions with shared genetic effects on these trait complexes, which in turn enables a better understanding of the underlying biological pathways and putatively the utilization for a more precise design of breeding schemes.

The aims of this study were to: (1) estimate genetic correlation for milk production traits (milk, fat and protein yields and fat and protein contents) and fatty acids (FA: C16:0, C18:1 cis-9, LCFA, SFA, and UFA) over days in milk, (2) investigate the performance of genomic predictions using single-step GBLUP (ssGBLUP) based on random regression models (RRM), and (3) identify the optimal scaling and weighting factors to be used in the construction of the H matrix. A total of 302 684 test-day records of 63.875 first lactation Walloon Holstein cows were used. Positive genetic correlations were found between milk yield and fat and protein yield (rg from 0.46 to 0.85) and between fat yield and milk FA (rg from 0.17 to 0.47). On the other hand, negative correlations were estimated between fat and protein contents (rg from -0.22 to -0.59), between milk yield and milk FA (rg from -0.22 to -0.62), and between protein yield and milk FA (rg from -0.11 to -0.19). The selection for high fat content increases milk FA throughout lactation (rg from 0.61 to 0.98). The test-day ssGBLUP approach showed considerably higher prediction reliability than the parent average for all milk production and FA traits, even when no scaling and weighting factors were used in the H matrix. The highest validation reliabilities (r2 from 0.09 to 0.38) and less biased predictions (b1 from 0.76 to 0.92) were obtained using the optimal parameters (i.e., ω = 0.7 and α = 0.6) for the genomic evaluation of milk production traits. For milk FA, the optimal parameters were ω = 0.6 and α = 0.6. However, biased predictions were still observed (b1 from 0.32 to 0.81). The findings suggest that using ssGBLUP based on RRM is feasible for the genomic prediction of daily milk production and FA traits in Walloon Holstein dairy cattle.

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

Breeding for veal and beef production in Dutch Red and White cattle

ObjectiveThe purpose of this study was to compare intended and actual yearly genetic gains for milk production and conformation traits and to investigate the simple selection criterion practiced among milk production and conformation traits during the last two decades in Japan. Learning how to utilize the information on intended and actual genetic gains during the last two decades into the genomic era is vital.MethodsGenetic superiority for each trait for four paths of selection (sires to breed bulls [SB], sires to breed cows [SC], dams to breed bulls [DB], and dams to breed cows [DC]) was estimated. Actual practiced simple selection criteria were investigated among milk production and conformation traits and relative emphasis on milk production and conformation traits was compared.ResultsSelection differentials in milk production traits were greater than those of conformation traits in all four paths of selection. Realized yearly genetic gain was less than that intended for milk production traits. Actual annual genetic gain for conformation traits was equivalent to or greater than intended. Retrospective selection weights of milk production and conformation traits were 0.73:0.27 and 0.56:0.44 for intended and realized genetic gains, respectively.ConclusionSelection was aimed more toward increasing genetic gain in milk production than toward conformation traits over the past two decades in Japan. In contrast, actual annual genetic gain for conformation traits was equivalent to or greater than intended. Balanced selection between milk production and conformation traits tended to be favored during actual selection. Each of four paths of selection (SB, SC, DB, and DC) has played an individual and important role. With shortening generation interval in the genomic era, a young sire arises before the completion of sire’s daughters’ milk production records. How to integrate these four paths of selection in the genomic era is vital.

Data comprising 7211 lactation records of 2894 cows were used to estimate genetic and phenotypic parameters for milk production (lactation milk yield, LMY and lactation length, LL) and fertility (calving interval, CI; number of services per conception, NSC and age at first calving, AFC) traits. Genetic, environmental and phenotypic trends were also estimated. Variance components were estimated using univariate, bivariate and trivariate animal models on based restricted maximum likelihood procedures. Univariate models were used for each trait, while bivariate models were used to estimate genetic and phenotypic correlations between milk production and fertility traits and between LMY, LL, CI and NSC within each lactation. Trivariate models were used in the analysis of LMY, LL, CI and NSC in the first three lactations. Heritability estimates from the univariate model were 0.16, 0.07, 0.03, 0.04 and 0.01 for LMY, LL, CI, AFC and NSC, respectively. The heritability estimates from trivariate analysis were higher for milk production traits than those from univariate analyses. Genetic correlations were high and undesirable between milk production and fertility traits, while phenotypic correlations were correspondingly low. Genetic trends were close to zero for all traits, while environmental and phenotypic trends fluctuated over the study period.

Major quantitative trait loci influencing milk production and conformation traits in Guernsey dairy cattle detected on Bos taurus autosome 19

Derivation of economic values for veal, beef and milk production traits using profit equations

Genetic relationship between heifers and cows fertility and milk yield traits in first-parity Iranian Holstein dairy cows

This study was carried out to investigate genetic, non-genetic affecting factors and estimate genetic parameters for milk production and reproductive traits of Holstein cows via animal model. The data was obtained from a commercial farm (Safi Masr for Developing the Animal Resources), located in the Nile Delta, Dakahlia, Egypt. Data included 4791 records of 1797 cows, 794 dams and 67 sires that represented the period from 2002 to 2012. The means and coefficient of variability (CV%) of milk traits as total milk yield (TMY), 305 day milk yield (305-dMY), lactation period (LP) and dry period (DP) were 5787.8 kg (31.1%), 4695 kg (22.1%), 332 day (14.9%) and 72.3 day (27.7%), respectively. Also, the means (CV%) of reproductive traits as days open (DO) and age at first calving (AFC) were 157.9 day (22.6%) and 30.5 month (16.8%), respectively. Sire, dam, parity of cow, year and season of calving had significant effects on traits studied. Heritability estimated were 0.223, 0.184, 0.112, 0.118, 0.105 and 0.285 for TMY, 305-dMY, LP, DP, DO and AFC, respectively. Estimated rG and rP among milk production traits were positive but it takes negative trend with DP and DO. Moderate heritability estimates and positive genetic correlation for most of traits studied suggested that genetic improvement of these traits would be achieved via multi-trait selection.

The aim of this study was to evaluate milk production and reproductive performance of Sahiwal cattle in semi‐arid Kenya. Milk production traits considered were lactation milk yield, lactation length and test‐day milk yield, while reproductive traits included age at first calving, calving interval and number of services per conception. Various fixed effects affected performance of milk production and reproductive traits to varying significance levels. The mean estimates for milk production traits were 1368 kg, 282 days and 4.9 kg for lactation milk yield, lactation length and test‐day milk yield, respectively. For reproductive traits, mean estimates were 468 days, 2.2 and 1345 days for calving interval, number of services per conception and age at first calving, respectively. There was a decline in lactation milk yield and lactation length, and an increase in calving interval and age at first calving over the years. Satisfactory management and appropriate genetic improvement strategies would result in improved performance. Implications of the results for genetic improvement of the breed in Kenya are discussed. Copyright © 2007 John Wiley & Sons, Ltd

Simple SummaryThe two non-synonymous g.11685G>A and g.11773T>C SNPs of PRLR(L2) were significantly associated with milk yield, fat%, and protein%, and mRNA and protein levels of PRL and PRLR in milk somatic cells. GT-animals had the best milk performance; however, AC-animals had inferior milk production. Thus, the selection of buffaloes with GT haplotypes may enhance milk performance in Egyptian buffaloes.Prolactin (PRL) and its receptor (PRLR) were considered as potential genetic markers for milk production and quality traits in cattle. However, little information is available regarding PRLR genetic diversity and association studies with milk traits in Egyptian water buffaloes. Therefore, the present study was conducted to search for mutations in PRLR and determine their associations with milk performance in these animals. Exon3 (E3) and E10 of PRLR were screened for polymorphisms using single strand conformation polymorphism (SSCP) and sequencing in 400 buffaloes. The associations between haplotypes and milk production (fat%, protein%, lactose%, and solid%) traits as well as mRNA and protein levels of PRL and PRLR were studied. Two single nucleotide polymorphisms (SNPs) in E10 were detected: g.11685G>A (p.Ala494Thr) and g.11773T>C (p.Val523Aal). The G and T alleles were wild (ancestral) alleles, while the A and C alleles were mutant alleles. These SNPs resulted in four haplotypes; AC, AT, GC, and GT. Buffaloes with wild GT haplotypes showed significantly higher milk yield, fat% and protein%, mRNA and protein levels of PRL and PRLR in milk somatic cells than other animals. Animals carrying mutant AC haplotype had inferior milk traits and lowest levels of associated mRNAs and proteins. With these results, we could conclude that the selection of buffaloes with wild GT haplotypes for g.11685G>A and g.11773T>C SNPs of the PRLR gene might improve the milk production traits of Egyptian water buffaloes.

The objective of the present study was to investigate single nucleotide polymorphisms (SNPs) located in three candidate genes previously reported to have effects on fertility and milk production traits in a population of 123 Holstein cows. The milk production traits evaluated included lifetime averages of milk yield, protein concentration, and fat concentration. Fertility traits evaluated included lifetime averages of services per conception and days-open. Candidate genes included those encoding diacylglycerol acyltransferase (DGAT1), leptin receptor (LEPR), and calpastatin (CAST). A total of 60 SNPs were selected (20 per gene) at equidistant locations on each candidate gene to identify potential linkage with causative mutations. Four SNPs were identified as being significantly associated with the evaluated fertility traits. Specifically, SNPs rs109663724 and rs137673193 were significantly associated with lifetime average days-open, while rs109663724 and rs135560721 were significantly associated with lifetime average number of services per conception. Five SNP (rs109663724, rs132699547, rs135423283, rs135576599, and rs13675432) were significantly associated with lifetime averages of milk protein concentration and milk fat concentration, with only one SNP (rs109663724) being significantly associated with the average lifetime milk yield. Although multiple SNPs were identified in the current study as being significantly associated with milk production and fertility traits, it is essential that these SNPs are validated in larger populations, under more diverse environments, and that additional SNPs and candidate genes are evaluated prior to their implementation into selection strategies.

<p><strong>Objective: </strong>The objective of this study was to analyze <em>CSN2</em> variants in Indonesian Friesian Holstein (FH) cow and their association with milk protein allergy and production traits.</p><p><strong>Methods: </strong>Genomic DNA was extracted from bloods of twelve Indonesian FH cow. Exon 7 of the <em>CSN2</em> was amplified using novel primer pair to produce 683 bp amplicon. The primers were 5’-ACCCCAATTTCTTAACCAAACCA-3’ as a forward primer and 5’-CATCAGAAGTTAAACAGCACAGT-3’ as a reverse primer. The PCR products were analyzed to determine the nucleotide sequence of <em>CSN2</em> using Bioedit version 7.2.5. Moreover, Hardy-Weinberg equilibrium (HWE) was calculated and one-way analysis of variance (ANOVA) was conducted to associate between <em>CSN2</em> variants and milk production traits.</p><p><strong>Results: </strong>Two polymorphisms, c.350A>C and c.516G>C, were identified in the <em>CSN2 </em>exon 7. Base substitution from adenine (A) to cytosine (C) of c.350A>C changed amino acid codon from histidine (CAU) to proline (CCU), and base substitution guanine (G) to cytosine (C) of c.516G>C changed amino acid codon from arginine (AGG) to serine (AGC). The CC genotype frequency for c.350A>C SNP was 33% and they were able to produce A2 <em>CSN2</em> variant which is favorable for preventing lactose intolerance. In addition, there were no association between c.350 A>C and c.516 G>C SNP of the <em>CSN2</em> with milk production traits.</p><p><strong>Conclusions: </strong>In conclusion, A1 and A2 variants of <em>CSN2</em> were identified in Indonesian FH population and they did not associate with milk production in Indonesian FH.</p><p> </p>

Simple SummaryBeta-lactoglobulin (β-LG), prolactin (PRL), and Kappa casein (CSN3) all contribute to the determination of milk production and composition, but have not been assessed in local Awassi sheep. Therefore, our aim was to analyze the contribution of these genes in milk production and composition traits in commercial Awassi ewe population by genotyping and sequencing these genes. Our results showed the prevalence of the different variations (alleles) of the tested genes in the Awassi population, and no association among β-LG and CSN3 polymorphic genotypes and milk production, or PRL and fat%. Also, all 3 genes help determine the milk production potential of Awassi ewes and help assess milk components, and thus can be used in breeding programs to select for milk potential.A participatory animal-breeding program was applied to 9 commercial Awassi sheep flocks in Jordan. This study aimed to assess the influence of Beta-lactoglobulin (β-LG), Prolactin (PRL), and Kappa casein (CSN3) genes, genotypes and their interaction on milk production and composition traits of 167 genotyped Awassi ewes via Polymerase Chain Reaction (PCR) followed by sequencing. Allele frequencies for the two variants were 0.42 and 0.58 for β-LG, 0.82 and 0.18 for PRL, and 0.92 and 0.08 for CSN3. No association was found among β-LG and CSN3 polymorphic genotypes with milk production traits. However, ewes with PRL AA genotype showed higher milk production, β-LG AB was associated with lowest fat%, high solid not fat (SNF)%, protein%, and lactose%. β-LG BB was associated with highest milk density. PRL, β-LG, and CSN3 polymorphic genotypes were differentially associated with milk production and component traits. Furthermore, β-LG × PRL interaction showed the highest milk production and fat%; β-LG × PRL recorded the highest SNF%, protein%, lactose%, and milk density, while the PRL × CSN3 had the highest fat% and SNF%. The enhancing effects of these gene interactions can be incorporated in Awassi breeding programs to improve milk production and composition.