Mendelian randomization analysis of 34,497 German Holstein cows to infer causal associations between milk production and health traits.

BACKGROUND: Claw diseases and mastitis represent the most important health issues in dairy cattle with a frequently mentioned connection to milk production. Although many studies have aimed at investigating this connection in more detail by estimating genetic correlations, they do not provide information about causality. An alternative is to carry out Mendelian randomization (MR) studies using genetic variants to investigate the effect of an exposure on an outcome trait mediated by genetic variants. No study has yet investigated the causal association of milk yield (MY) with health traits in dairy cattle. Hence, we performed a MR analysis of MY and seven health traits using imputed whole-genome sequence data from 34,497 German Holstein cows. We applied a method that uses summary statistics and removes horizontal pleiotropic variants (having an effect on both traits), which improves the power and unbiasedness of MR studies. In addition, genetic correlations between MY and each health trait were estimated to compare them with the estimates of causal effects that we expected. RESULTS: All genetic correlations between MY and each health trait were negative, ranging from - 0.303 (mastitis) to - 0.019 (digital dermatitis), which indicates a reduced health status as MY increases. The only non-significant correlation was between MY and digital dermatitis. In addition, each causal association was negative, ranging from - 0.131 (mastitis) to - 0.034 (laminitis), but the number of significant associations was reduced to five nominal and two experiment-wide significant results. The latter were between MY and mastitis and between MY and digital phlegmon. Horizontal pleiotropic variants were identified for mastitis, digital dermatitis and digital phlegmon. They were located within or nearby variants that were previously reported to have a horizontal pleiotropic effect, e.g., on milk production and somatic cell count. CONCLUSIONS: Our results confirm the known negative genetic connection between health traits and MY in dairy cattle. In addition, they provide new information about causality, which for example points to the negative energy balance mediating the connection between these traits. This knowledge helps to better understand whether the negative genetic correlation is based on pleiotropy, linkage between causal variants for both trait complexes, or indeed on a causal association.

Genetic investigations on backfat thickness and body condition score in German Holstein cattle.

Up to now, little has been known about backfat thickness (BFT) in dairy cattle. The objective of this study was to investigate the lactation curve and genetic parameters for BFT as well as its relationship with body condition score (BCS) and milk yield (MKG). For this purpose, a dataset was analysed including phenotypic observations of 1929 German Holstein cows for BFT, BCS and MKG recorded on a single research dairy farm between September 2005 and December 2022. Additionally, pedigree and genomic information was available. Lactation curves were predicted and genetic parameters were estimated for all traits in first to third lactation using univariate random regression models. For BCS, lactation curves had nadirs at 94 DIM, 101 DIM and 107 DIM in first, second and third lactation. By contrast, trajectories of BFT showed lowest values later in lactation at 129 DIM, 117 DIM and 120 DIM in lactation numbers 1 to 3, respectively. Although lactation curves of BCS and BFT had similar shapes, the traits showed distinct sequence of curves for lactation number 2 and 3. Cows in third lactation had highest BCS, whereas highest BFT values were found for second parity animals. Average heritabilities were 0.315 ± 0.052, 0.297 ± 0.048 and 0.332 ± 0.061 for BCS in lactation number 1 to 3, respectively. Compared to that, BFT had considerably higher heritability in all lactation numbers with estimates ranging between 0.357 ± 0.028 and 0.424 ± 0.034. Pearson correlation coefficients between estimated breeding values for the 3 traits were negative between MKG with both BCS (r = -0.245 to -0.322) and BFT (r = -0.163 to -0.301). Correlation between traits BCS and BFT was positive and consistently high (r = 0.719 to 0.738). Overall, the results of this study suggest that BFT and BCS show genetic differences in dairy cattle, which might be due to differences in depletion and accumulation of body reserves measured by BFT and BCS. Therefore, routine recording of BFT on practical dairy farms could provide valuable information beyond BCS measurements and might be useful, for example, to better assess the nutritional status of cows.

Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows.

BACKGROUND: Over the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecular mechanisms shaping complex traits and the accuracies of genomic prediction, especially in small populations and across-breed settings. Still, little is known about the contribution of different functional and evolutionary genome partitioning subsets to milk production and dairy health. Thus, we performed a uni- and a bivariate analysis of milk yield (MY) and eight health traits using a set of ~34,497 German Holstein cows with 50K chip genotypes and ~17 million imputed sequence variants divided into 27 subsets depending on their functional and evolutionary annotation. In the bivariate analysis, eight trait-combinations were observed that contrasted MY with each health trait. Two genomic relationship matrices (GRM) were included, one consisting of the 50K chip variants and one consisting of each set of subset variants, to obtain subset heritabilities and genetic correlations. In addition, 50K chip heritabilities and genetic correlations were estimated applying merely the 50K GRM. RESULTS: In general, 50K chip heritabilities were larger than the subset heritabilities. The largest heritabilities were found for MY, which was 0.4358 for the 50K and 0.2757 for the subset heritabilities. Whereas all 50K genetic correlations were negative, subset genetic correlations were both, positive and negative (ranging from -0.9324 between MY and mastitis to 0.6662 between MY and digital dermatitis). The subsets containing variants which were annotated as noncoding related, splice sites, untranslated regions, metabolic quantitative trait loci, and young variants ranked highest in terms of their contribution to the traits` genetic variance. We were able to show that linkage disequilibrium between subset variants and adjacent variants did not cause these subsets` high effect. CONCLUSION: Our results confirm the connection of milk production and health traits in dairy cattle via the animals` metabolic state. In addition, they highlight the potential of including functional information in genomic analyses, which helps to dissect the extent and direction of the observed traits` connection in more detail.

Impact of inbreeding on production, fertility, and health traits in German Holstein dairy cattle utilizing various inbreeding estimators.

In dairy cattle production, it is important to understand how inbreeding affects production, fertility, and health traits. However, there is still limited use of genomic information to estimate inbreeding, despite advancements in genotyping technologies. To address this gap, we investigated the impact of inbreeding on German Holstein dairy cattle using both pedigree-based and genomic-based inbreeding estimators. We employed one method based on pedigree information (Fped) together with 6 genomic-based methods, including 3 GCTA estimators (Fhat1, Fhat2, Fhat3), VanRaden's first method (FVR1, with observed allele frequencies and FVR0.5 when allele frequencies are set to 0.5), and one based on runs of homozygosity (Froh). Data from 24,489 cows with both phenotypes and genotypes were used, with a pedigree including 232,780 animals born between 1970 and 2018. We analyzed the effects of inbreeding depression on production, fertility, and health traits separately, using single-trait linear animal models as well as threshold models to account for the binary nature of the health traits. For the health traits, we transformed solutions from the liability scale to a probability scale for easier interpretation. Our results showed that the mean inbreeding coefficients from all estimators ranged from -0.003 to 0.243, with negative values observed for most genomic-based methods. We found out that a 1% increase in inbreeding caused a depression ranging from 25.94 kg (Fhat1) to 40.62 kg (Fhat3), 1.18 kg (Fhat2) to 1.70 kg (Fhat3), 0.90 kg (Fhat2) to 1.45 kg (Froh and Fhat3), 0.19 (Fped) to 0.34 d (Fhat3) for 305 d milk yield, fat, protein, and calving interval respectively. The health traits showed slight changes when inbreeding was gradually increased by 5% with digital dermatitis showing rather a contrasting trend to that of mastitis which reduced the more an animal was inbred. Overall, our study highlights the importance of considering both pedigree-based and genomic-based inbreeding estimators when assessing the impact on inbreeding, emphasizing that not all inbreeding is harmful.

The Resilient Dairy Genome Project-A general overview of methods and objectives related to feed efficiency and methane emissions.

The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries (i.e., Australia, Canada, Denmark, Germany, Spain, Switzerland, and United States) contribute with genotypes and phenotypes including DMI and CH4. However, combining data are challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.

Effects of the Breeding Strategy Beef-on-Dairy at Animal, Farm and Sector Levels.

The decline in farm revenue due to volatile milk prices has led to an increase in the use of beef semen in dairy herds. While this strategy ("Beef-on-dairy" (BoD)) can have economic benefits, it can also lead to unintended consequences affecting animal welfare. Semen sale trends from breeding organizations depict increasing sales of beef semen across the globe. Calves born from such breeding strategies can perform better when compared to purebred dairy calves, especially in terms of meat quality and growth traits. The Beef-on-dairy strategy can lead to unintentional negative impacts including an increase in gestation length, and increased dystocia and stillbirth rates. Studies in this regard have found the highest gestation length for Limousin crossbred calves followed by calves from the Angus breed. This increase in gestation length can lead to economic losses ranging from 3 to 5 US$ per animal for each additional day. In terms of the growth performance of crossbred animals, literature studies are inconclusive due to the vast differences in farming structure across the regions. But almost all the studies agree regarding improvement in the meat quality in terms of color, fiber type, and intra-muscular fat content for crossbred animals. Utilization of genomic selection, and development of specialized Beef-on-dairy indexes for the sires, can be a viable strategy to make selection easier for the farmers.

Molecular Structural Analysis of Porcine CMAH-Native Ligand Complex and High Throughput Virtual Screening to Identify Novel Inhibitors.

Porcine meat is the most consumed red meat worldwide. Pigs are also vital tools in biological and medical research. However, xenoreactivity between porcine's N-glycolylneuraminic acid (Neu5Gc) and human anti-Neu5Gc antibodies poses a significant challenge. On the one hand, dietary Neu5Gc intake has been connected to particular human disorders. On the other hand, some pathogens connected to pig diseases have a preference for Neu5Gc. The Cytidine monophospho-N-acetylneuraminic acid hydroxylase (CMAH) catalyses the conversion of N-acetylneuraminic acid (Neu5Ac) to Neu5Gc. In this study, we predicted the tertiary structure of CMAH, performed molecular docking, and analysed the protein-native ligand complex. We performed a virtual screening from a drug library of 5M compounds and selected the two top inhibitors with Vina scores of -9.9 kcal/mol for inhibitor 1 and -9.4 kcal/mol for inhibitor 2. We further analysed their pharmacokinetic and pharmacophoric properties. We conducted stability analyses of the complexes with molecular dynamic simulations of 200 ns and binding free energy calculations. The overall analyses revealed the inhibitors' stable binding, which was further validated by the MMGBSA studies. In conclusion, this result may pave the way for future studies to determine how to inhibit CMAH activities. Further in vitro studies can provide in-depth insight into these compounds' therapeutic potential.

An In Silico Functional Analysis of Non-Synonymous Single-Nucleotide Polymorphisms of Bovine CMAH Gene and Potential Implication in Pathogenesis.

The sugar molecule N-glycolylneuraminic acid (Neu5Gc) is one of the most common sialic acids discovered in mammals. Cytidine monophospho-N-acetylneuraminic acid hydroxylase (CMAH) catalyses the conversion of N-acetylneuraminic acid (Neu5Ac) to Neu5Gc, and it is encoded by the CMAH gene. On the one hand, food metabolic incorporation of Neu5Gc has been linked to specific human diseases. On the other hand, Neu5Gc has been shown to be highly preferred by some pathogens linked to certain bovine diseases. We used various computational techniques to perform an in silico functional analysis of five non-synonymous single-nucleotide polymorphisms (nsSNPs) of the bovine CMAH (bCMAH) gene identified from the 1000 Bull Genomes sequence data. The c.1271C>T (P424L) nsSNP was predicted to be pathogenic based on the consensus result from different computational tools. The nsSNP was also predicted to be critical based on sequence conservation, stability, and post-translational modification site analysis. According to the molecular dynamic simulation and stability analysis, all variations promoted stability of the bCMAH protein, but mutation A210S significantly promoted CMAH stability. In conclusion, c.1271C>T (P424L) is expected to be the most harmful nsSNP among the five detected nsSNPs based on the overall studies. This research could pave the way for more research associating pathogenic nsSNPs in the bCMAH gene with diseases.

Genomic dominance variance analysis of health and milk production traits in German Holstein cattle.

Genomic analyses commonly explore the additive genetic variance of traits. The non-additive variance, however, is usually small but often significant in dairy cattle. This study aimed at dissecting the genetic variance of eight health traits that recently entered the total merit index in Germany and the somatic cell score (SCS), as well as four milk production traits by analysing additive and dominance variance components. The heritabilities were low for all health traits (between 0.033 for mastitis and 0.099 for SCS), and moderate for the milk production traits (between 0.261 for milk energy yield and 0.351 for milk yield). For all traits, the contribution of dominance variance to the phenotypic variance was low, varying between 0.018 for ovarian cysts and 0.078 for milk yield. Inbreeding depression, inferred from the SNP-based observed homozygosity, was significant only for the milk production traits. The contribution of dominance variance to the genetic variance was larger for the health traits, ranging from 0.233 for ovarian cysts to 0.551 for mastitis, encouraging further studies that aim at discovering QTLs based on their additive and dominance effects.

Quantitative trait locus for calving traits on Bos taurus autosome 18 in Holstein cattle is embedded in a complex genomic region.

Although the quantitative trait locus (QTL) on chromosome 18 (BTA18) associated with paternal calving ease and stillbirth in Holstein Friesian cattle and its cross has been known for over 20 years, to our knowledge, the exact causal genetic sequence has yet escaped identification. The aim of this study was to re-examine the region of the published QTL on BTA18 and to investigate the possible reasons behind this elusiveness. For this purpose, we carried out a combined linkage disequilibrium and linkage analysis using genotyping data of 2,697 German Holstein Friesian (HF) animals and subsequent whole-genome sequencing (WGS) data analyses and genome assembly of HF samples. We confirmed the known QTL in the 95% confidence interval of 1.089 Mbp between 58.34 and 59.43 Mbp on BTA18. Additionally, these 4 SNPs in the near-perfect linkage disequilibrium with the QTL haplotype were identified: rs381577268 (on 57,816,137 bp, C/T), rs381878735 (on 59,574,329 bp, A/T), rs464221818 (on 59,329,176 bp, C/T), and rs472502785 (on 59,345,689 bp, T/C). Search for the causal mutation using short and long-read sequences, and methylation data of the BTA18 QTL region did not reveal any candidates though. The assembly showed problems in the region, as well as an abundance of segmental duplications within and around the region. Taking the QTL of BTA18 in Holstein cattle as an example, the data presented in this study comprehensively characterize the genomic features that could also be relevant for other such elusive QTL in various other cattle breeds and livestock species as well.

A genomic assessment of the correlation between milk production traits and claw and udder health traits in Holstein dairy cattle.

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.

Genetic analysis of production traits and body size measurements and their relationships with metabolic diseases in German Holstein cattle.

This study sheds light on the genetic complexity and interplay of production, body size, and metabolic health in dairy cattle. Phenotypes for body size-related traits from conformation classification (130,166 animals) and production (101,562 animals) of primiparous German Holstein cows were available. Additionally, 21,992, 16,641, and 7,096 animals were from herds with recordings of the metabolic diseases ketosis, displaced abomasum, and milk fever in first, second, and third lactation. Moreover, all animals were genotyped. Heritabilities of traits and genetic correlations between all traits were estimated and GWAS were performed. Heritability was between 0.240 and 0.333 for production and between 0.149 and 0.368 for body size traits. Metabolic diseases were lowly heritable, with estimates ranging from 0.011 to 0.029 in primiparous cows, from 0.008 to 0.031 in second lactation, and from 0.037 to 0.052 in third lactation. Production was found to have negative genetic correlations with body condition score (BCS; -0.279 to -0.343) and udder depth (-0.348 to -0.419). Positive correlations were observed for production and body depth (0.138-0.228), dairy character (DCH) (0.334-0.422), and stature (STAT) (0.084-0.158). In first parity cows, metabolic disease traits were unfavorably correlated with production, with genetic correlations varying from 0.111 to 0.224, implying that higher yielding cows have more metabolic problems. Genetic correlations of disease traits in second and third lactation with production in primiparous cows were low to moderate and in most cases unfavorable. While BCS was negatively correlated with metabolic diseases (-0.255 to -0.470), positive correlations were found between disease traits and DCH (0.269-0.469) as well as STAT (0.172-0.242). Thus, the results indicate that larger and sharper animals with low BCS are more susceptible to metabolic disorders. Genome-wide association studies revealed several significantly associated SNPs for production and conformation traits, confirming previous findings from literature. Moreover, for production and conformation traits, shared significant signals on Bos taurus autosome (BTA) 5 (88.36 Mb) and BTA 6 (86.40 to 87.27 Mb) were found, implying pleiotropy. Additionally, significant SNPs were observed for metabolic diseases on BTA 3, 10, 14, 17, and 26 in first lactation and on BTA 2, 6, 8, 17, and 23 in third lactation. Overall, this study provides important insights into the genetic basis and interrelations of relevant traits in today's Holstein cattle breeding programs, and findings may help to improve selection decisions.

Structural variants and tandem repeats in the founder individuals of four F2 pig crosses and implications to F2 GWAS results.

BACKGROUND: Structural variants and tandem repeats are relevant sources of genomic variation that are not routinely analyzed in genome wide association studies mainly due to challenging identification and genotyping. Here, we profiled these variants via state-of-the-art strategies in the founder animals of four F2 pig crosses using whole-genome sequence data (20x coverage). The variants were compared at a founder level with the commonly screened SNPs and small indels. At the F2 level, we carried out an association study using imputed structural variants and tandem repeats with four growth and carcass traits followed by a comparison with a previously conducted SNPs and small indels based association study. RESULTS: A total of 13,201 high confidence structural variants and 103,730 polymorphic tandem repeats (with a repeat length of 2-20 bp) were profiled in the founders. We observed a moderate to high (r from 0.48 to 0.57) level of co-localization between SNPs or small indels and structural variants or tandem repeats. In the association step 56.56% of the significant variants were not in high LD with significantly associated SNPs and small indels identified for the same traits in the earlier study and thus presumably not tagged in case of a standard association study. For the four growth and carcass traits investigated, many of the already proposed candidate genes in our previous studies were confirmed and additional ones were identified. Interestingly, a common pattern on how structural variants or tandem repeats regulate the phenotypic traits emerged. Many of the significant variants were embedded or nearby long non-coding RNAs drawing attention to their functional importance. Through which specific mechanisms the identified long non-coding RNAs and their associated structural variants or tandem repeats contribute to quantitative trait variation will need further investigation. CONCLUSIONS: The current study provides insights into the characteristics of structural variants and tandem repeats and their role in association studies. A systematic incorporation of these variants into genome wide association studies is advised. While not of immediate interest for genomic prediction purposes, this will be particularly beneficial for elucidating biological mechanisms driving the complex trait variation.

Replacement of microsatellite markers by imputed medium-density SNP arrays for parentage control in German warmblood horses.

In horses, parentage control is currently performed based on an internationally standardized panel of 17 microsatellite (MS) markers comprising 12 mandatory and five optional markers. Unlike MS, single nucleotide polymorphism (SNP) profiles support a wider portfolio of genomic applications, including parentage control. A transition to SNP-based parentage control is favorable, but requires additional efforts for ensuring generation-overlapping availability of marker genotypes of the same type. To avoid double genotyping of either parents or offspring for changing to SNP technology and enable efficient transition, we tested whether MS genotypes used for parentage control could be reliably imputed from a medium-density SNP panel in German warmblood horses. Imputation accuracy was tested in a tenfold cross-validation with two approaches: within breed (option A) and across breeds (option B). Average imputation accuracies of 97.98% (A) and 96.17% (B) were achieved, respectively. Due to interbreed differences in genotyping rates, five MS markers of low genotyping rate (GTR; < 90%) could be imputed with higher accuracy within breed (98.18%) than across breeds (90.73%). MS markers with high GTR performed homogeneously well in option B (98.44%) and showed slightly lower accuracy in option A (97.90%). Among these markers, AHT5 proved to be problematic for imputation regardless of the approach, revealing accuracies of 86.40% (A) and 88.70% (B). Better results for MS markers with high GTR and savings in computational processing justified the choice of option B for routine implementation. To date, more than 9500 horses have undergone the new parentage control based on imputed MS genotypes.

Roan coat color in livestock.

Since domestication, a wide variety of phenotypes including coat color variation has developed in livestock. This variation is mostly based on selective breeding. During the beginning of selective breeding, potential negative consequences did not become immediately evident due to low frequencies of homozygous animals and have been occasionally neglected. However, numerous studies of coat color genetics have been carried out over more than a century and, meanwhile, pleiotropic effects for several coat color genes, including disorders of even lethal impact, were described. Similar coat color phenotypes can often be found across species, caused either by conserved genes or by different genes. Even in the same species, more than one gene could cause the same or similar coat color phenotype. The roan coat color in livestock species is characterized by a mixture of white and colored hair in cattle, pig, sheep, goat, alpaca, and horse. So far, the genetic background of this phenotype is not fully understood, but KIT and its ligand KITLG (MGF) are major candidate genes in livestock species. For some of these species, pleiotropic effects such as subfertility in homozygous roan cattle or homozygous embryonic lethality in certain horse breeds have been described. This review aims to point out the similarities and differences of the roan phenotype across the following livestock species: cattle, pig, sheep, goat, alpaca, and horse; and provides the current state of knowledge on genetic background and pleiotropic effects.

An Overview of the Importance and Value of Porcine Species in Sialic Acid Research.

Humans frequently interact with pigs, whose meat is also one of the primary sources of animal protein. They are one of the main species at the center of sialic acid (Sia) research. Sias are sugars at terminals of glycoconjugates, are expressed at the cell surfaces of mammals, and are important in cellular interactions. N-glycolylneuraminic acid (Neu5Gc) and N-acetylneuraminic acid (Neu5Ac) are notable Sias in mammals. Cytidine monophospho-N-acetylneuraminic acid hydroxylase (CMAH) encodes the CMAH enzyme that biosynthesizes Neu5Gc. Although humans cannot endogenously synthesize Neu5Gc due to the inactivation of this gene by a mutation, Neu5Gc can be metabolically incorporated into human tissues from red meat consumption. Interactions between Neu5Gc and human anti-Neu5Gc antibodies have been associated with certain diseases and disorders. In this review, we summarized the sialic acid metabolic pathway, its regulation and link to viral infections, as well as the importance of the pig as a model organism in Sia research, making it a possible source of Neu5Gc antigens affecting human health. Future research in solving the structures of crucial enzymes involved in Sia metabolism, as well as their regulation and interactions with other enzymes, especially CMAH, could help to understand their function and reduce the amount of Neu5Gc.

Mitochondrial DNA Variation Contributes to the Aptitude for Dressage and Show Jumping Ability in the Holstein Horse Breed.

Maternal lineages are considered an important factor in breeding. Mitochondrial DNA (mtDNA) is maternally inherited and plays an important role in energy metabolism. It has already been associated with energy consumption and performances, e.g., stamina in humans and racehorses. For now, corresponding studies are lacking for sport performance of warmblood breeds. MtDNA sequences were available for 271 Holstein mares from 75 maternal lineages. As all mares within a lineage showed identical haplotypes regarding the non-synonymous variants, we expanded our data set by also including non-sequenced mares and assigning them to the lineage-specific haplotype. This sample consisting of 6334 to 16,447 mares was used to perform mitochondrial association analyses using breeding values (EBVs) estimated on behalf of the Fédération Équestre Nationale (FN) and on behalf of the Holstein Breeding Association (HOL). The association analyses revealed 20 mitochondrial SNPs (mtSNPs) significantly associated with FN-EBVs and partly overlapping 20 mtSNPs associated with HOL-EBVs. The results indicated that mtDNA contributes to performance differences between maternal lineages. Certain mitochondrial haplogroups were associated with special talents for dressage or show jumping. The findings encourage to set up innovative genetic evaluation models that also consider information on maternal lineages.

Short- and long-term consequences of collaboration between Northern European Red dairy and dual-purpose cattle.

In Northern European countries, a great variety of Red cattle populations exists which can be broadly categorized in two groups: specialized dairy and dual-purpose breeds. Collaboration between these breeds (i.e. the exchange of sires across breeds) can be beneficial but is limited so far. The aim of this study was to demonstrate and evaluate consequences of collaboration between Red breeds using stochastic simulations. Two breeding lines (dairy type and dual purpose) were simulated. As a special aspect of this study, differences in genetic levels of breeding traits (milk production, beef production, mastitis resistance, fertility, feed efficiency) have been taken into account. Various scenarios were investigated where across-breed selection was either restricted or allowed and with different correlations between breeding goals in the two lines. The results of this study were influenced by the different genetic levels in breeding traits only in the first years of simulation. In the long run, the breed differences did not affect the degree of collaboration between lines. When the correlation between breeding goals was close to unity, the selection of external bulls was highly beneficial in terms of genetic gain and total monetary gain. Additionally, the lowest rate of inbreeding was found in that case. With decreasing correlations between environments, degree of cooperation between lines rapidly terminated and lines operated individually. In last years of simulation, cooperation was only found when the correlation between breeding goals was close to unity. From a long-term perspective, the exchange of breeding sires across lines also caused negative effects. In the dual-purpose line, deterioration of genetic gain in mastitis resistance and fertility was observed. Additionally, breeding lines genetically converged, which decreased genetic diversity. Collectively, short-term benefits and long-term negative effects have to be reconciled if collaboration between Red breeds in Northern Europe is to be pursued.

Genetic and genomic characterization followed by single-step genomic evaluation of withers height in German Warmblood horses.

Reliability of genomic predictions is influenced by the size and genetic composition of the reference population. For German Warmblood horses, compilation of a reference population has been enabled through the cooperation of five German breeding associations. In this study, preliminary data from this joint reference population were used to genetically and genomically characterize withers height and to apply single-step methodology for estimating genomic breeding values for withers height. Using data on 2113 mares and their genomic information considering about 62,000 single nucleotide polymorphisms (SNPs), analysis of the genomic relationship revealed substructures reflecting breed origin and different breeding goals of the contributing breeding associations. A genome-wide association study confirmed a known quantitative trait locus (QTL) for withers height on equine chromosome (ECA) 3 close to LCORL and identified a further significant peak on ECA 1. Using a single-step approach with a combined relationship matrix, the estimated heritability for withers height was 0.31 (SE = 0.08) and the corresponding genomic breeding values ranged from - 2.94 to 2.96 cm. A mean reliability of 0.38 was realized for these breeding values. The analyses of withers height showed that compiling a reference population across breeds is a suitable strategy for German Warmblood horses. The single-step method is an appealing approach for practical genomic prediction in horses, because not many genotypes are available yet and animals without genotypes can by this way directly contribute to the estimation system.

Exploring the Origin and Relatedness of Maternal Lineages Through Analysis of Mitochondrial DNA in the Holstein Horse.

Maternal lineages are important for the breeding decision in the Holstein horse breed. To investigate the genetic diversity of the maternal lineages and the relationships between founder mares, the maternal inherited mitochondrial genome (except the repetitive part of the non-coding region) of 271 mares representing 75 lineages was sequenced. The sequencing predominantly revealed complete homology in the nucleotide sequences between mares from one lineage with exceptions in 13 lineages, where differences in one to three positions are probably caused by de novo mutations or alternate fixation of heteroplasmy. We found 78 distinct haplotypes that have not yet been described in other breeds. Six of these occurred in two or three different lineages indicating a common ancestry. Haplotypes can be divided into eight clusters with all mares from one lineage belonging to the same cluster. Within a cluster, the average number of pairwise differences ranged from zero to 16.49 suggesting close maternal relationships between these mares. The results showed that the current breeding population originated from at least eight ancestral founder mares.