Abstract Large-scale genomic resources enable systematic investigation of genetic variation and tissue-specific expression of immune-related pathways in livestock species. Here, we integrated population-level whole-genome sequence data with tissue-specific transcriptional profiling to characterize genomic differentiation and expression patterns of NF-κB pathway-related genes in cattle. Using whole-genome sequence data from the 1000 Bull Genomes Project, we identified prioritized differentiated variants within several NF-κB pathway–related genes, including CD14 , NF-κB1 , IL-1β , and BAFFR . The mRNA expression levels of selected NF-κB signaling-related genes were quantified across four tissues with relevance to host defense and metabolism in bulls and cows of both breeds. Expression analyses revealed pronounced tissue-dependent regulation, with distinct organ-specific transcriptional patterns across the investigated genes. Intestinal tissues showed lower expression of several innate immune genes, whereas CD14 expression was more prominent in liver-associated comparisons, highlighting functional tissue specialization within the NF-κB signaling network. Breed- and sex-associated effects were gene-dependent rather than uniform across the pathway. Histological assessment of the spleen was performed to provide an anatomical context for observed transcriptional variations. A population-prioritized CD14 missense variant (Asn177Asp), identified from the 1000 Bull Genomes dataset, was contextualized using in silico structural annotation to provide structural context for coding variation. These findings provide descriptive evidence that population-level genomic differentiation in selected NF-κB pathway genes is accompanied by tissue-specific transcriptional differences in cattle.

Genomic inbreeding coefficients, when calculated in a way to reflect the true level of homozygosity of an individual at genomic markers, result in considerably higher inbreeding trends per year at a population level when compared with pedigree-based estimates. Using data from dual-purpose Fleckvieh cattle, we compare inbreeding trends and estimates of inbreeding-effective population sizes calculated from genomic data against those using a conventional pedigree-based approach. By repeating the calculation of genomic inbreeding trends using different subsets of SNPs, we illustrate how genomic inbreeding coefficients are shaped by the effects of trends in allele frequencies over time. Three SNP subsets were defined according to specific patterns of allele frequency changes over time: SNPs whose allele frequencies move toward intermediate frequencies, SNPs whose allele frequencies move away from intermediate frequencies, and SNPs that show no directional allele frequency trends at all (“neutral”). As expected, genomic inbreeding trends based on subsets of “neutral” SNPs only show the closest agreement with the pedigree-based estimates, which highlights the fundamental theoretical difference between both approaches. This demonstrates that the validity of the overall estimate using all SNPs depends on their distribution across the genome. It therefore represents some kind of “average” of effects caused by the balance of SNPs with differential allele frequency changes. Genomic estimates therefore can provide the basis to monitor the distribution, amount, and progress of neutral sites in the genome as well as the changes caused by drift and strong artificial selection at other sites. As a conclusion, we argue against the use of traditional probabilistic measures of inbreeding and in favor of the development and use of approaches capable of reflecting the complexity of various processes at the genome level, given that a sufficient and representative part of the breeding-population is genotyped for at least a decade.

Sperm mitochondria are crucial for sperm quality and functional competence before and after ejaculation. However, the link between mitochondrial genome features and mitochondrial functional resilience in post-ejaculated mature sperm remains unclear. Seasonal variation offers a useful framework to investigate whether mitochondrial performance in ejaculated sperm reflects stable regulatory features established before ejaculation rather than de novo post-ejaculatory activity. Using a repeated-measures approach within bulls (n = 6), semen collected during spring (late March-early April) and summer (late July-early August) was cryopreserved and later incubated in vitro for 12 h at 37 °C or 41 °C. We evaluated sperm-borne mitochondrial DNA copy number and mitochondria-encoded transcript abundance, mitochondrial bioenergetic functions (membrane potential-dependent activity and ATP content), and sperm chromatin and acrosome integrity. Chromatin damage and mitochondrial membrane potential-dependent activity showed a significant overall effect of season, with condition-dependent differences. While ATP content and acrosome integrity showed significant overall effects of season and/or incubation condition, no consistent seasonal differences were detected within individual incubation conditions. Relative mtDNA copy number showed a significant overall effect of season, with differences only under 41 °C incubation. In contrast, mitochondrial transcript abundance showed gene-specific changes with incubation. No consistent increase in transcript abundance was observed at 41 °C compared with 37 °C. Taken together, these findings suggest that mitochondrial bioenergetic competence in mature sperm primarily reflects regulatory features established before ejaculation. In contrast, transcript abundance patterns did not uniformly parallel the functional readouts under the incubation conditions tested.

The Angler Saddleback pig is an endangered local breed from northern Germany, characterized by high genetic diversity and exceptional meat quality, but with reduced growth performance compared to commercial pigs. As intestinal microbiota is known to influence health, metabolism, and fat deposition, this study aimed to provide the first characterization of the gut microbial community of this breed. Fecal samples from 37 Angler Saddleback pigs, raised under semi-controlled conditions and fed a restricted diet supplemented with grass-clover silage, were collected at slaughter. Bacterial community composition was analyzed by 16S rRNA gene amplicon sequencing and evaluated using QIIME2, followed by statistical analyses of alpha and beta diversity. The intestinal microbiota was highly diverse, with Bacteroidota (49.5%) and Firmicutes (34.3%) as the dominant phyla, complemented by Spirochaetota and Proteobacteria. Core taxa included Lactobacillus amylovorus, Prevotella, and Streptococcus, while strong inter-individual variability was observed. Beta diversity analysis revealed significant effects of breeder and fattening period on microbial composition, whereas sex, age, and maternal lineage showed no significant influence. These findings suggest that both diet and early-life environment shape the intestinal microbiota of Angler Saddleback pigs. The study provides a foundation for exploring microbiota-associated traits that may contribute to conservation and breeding strategies for this endangered pig breed.

The Angler Saddleback (AS) pig is an endangered breed that originates from Germany. To date there is a lack of scientific research into the meat quality of this local breed, particularly with regard to fatty acid composition. Due to the limited availability of AS piglets, a fattening experiment was conducted with 58 individuals as a pilot study. To meet this slower-growing breed's lower nutritional demands, the pigs were fed a diet rich in silage and low in concentrate feed. In connection with the high backfat (BF) thickness (M=37.8mm), increased levels of monounsaturated fatty acids were observed in both the intramuscular fat (IMF; M=46.6%) and the subcutaneous fat (M=48.6%) as compared to other pig breeds. The saturated fatty acids amounts were rather low in intramuscular fat (M=33.6%) and in BF (M=38.7%), as was to be expected for a fatty pig breed. Furthermore, the proportion of polyunsaturated fatty acids in the BF was very low (M=12.7%), despite the high proportion of grass-clover silage in the diet. These results, along with some unexpected correlations among the target variables, might be due to a genetic effect of the AS pig. Therefore, genome-wide association studies (GWASs) were performed using SNP-array data from the 58 pigs. Based on this, 38 significant variants related to pork quality traits were identified. The significant loci were distributed over 10 chromosomes and further underlined the influence of genetics. Given the limited sample size for genomic analysis, these findings can only provide an initial insight. However, the results clearly indicate that examining the fatty acid composition of local pig breeds in more detail could provide valuable information to enhance selection for pork quality.

The Angler Saddleback (AS) pig is a local breed in Northern Germany which is considered endangered. Today, the conservation of traditional pig breeds gets relevant in terms of ensuring genetic diversity and thus coping with future challenges in animal husbandry. A representative dataset with SNP array data of 244 AS pigs was analyzed to assess the conservation value of the breed. Genetic diversity of the AS population was high with an observed heterozygosity of 0.35 and the level of genomic inbreeding was low (FROH = 13.6%). The mainly short ROHs found in the AS population, with an average number of 54 per pig and an average length of 308 Mb, primarily indicate the influence of genetic drift. Further, the identification of only six short ROH islands indicates less strong and directed selection pressure. Reflecting the documented history of the breed, effective population size declined during the recent fourteen generations with a bottleneck likely occurring four generations ago. The admixture analysis of different European and Chinese pig breeds identified the AS pig as being extensive genetically unique, which further underlines the conservation value of the breed. However, a previous study revealed that economically relevant phenotypic traits vary greatly among AS pigs, a possible downside of the high genetic diversity. This might be the result of conservation breeding based solely on visual appraisal of traits. As profitability is a key driver of conservation, future breeding management decisions may be constrained by considerations for production traits, without losing sight of genetic diversity.

BACKGROUND:Milk production traits are complex and influenced by many genetic and environmental factors. Although extensive research has been performed for these traits, with many associations unveiled thus far, due to their crucial economic importance, complex genetic architecture, and the fact that causal variants in cattle are still scarce, there is a need for a better understanding of their genetic background. In this study, we aimed to identify new candidate loci associated with milk production traits in German Holstein cattle, the most important dairy breed in Germany and worldwide. For that purpose, 180,217 cattle were imputed to the sequence level and large-scale genome-wide association study (GWAS) followed by fine-mapping and evolutionary and functional annotation were carried out to identify and prioritize new association signals. RESULTS:Using the imputed sequence data of a large cattle dataset, we identified 50,876 significant variants, confirming many known and identifying previously unreported candidate variants for milk (MY), fat (FY), and protein yield (PY). Genome-wide significant signals were fine-mapped with the Bayesian approach that determines the credible variant sets and generates the probability of causality for each signal. The variants with the highest probabilities of being causal were further classified using external information about the function and evolution, making the prioritization for subsequent validation experiments easier. The top potential causal variants determined with fine-mapping explained a large percentage of genetic variance compared to random ones; 178 variants explained 11.5%, 104 explained 7.7%, and 68 variants explained 3.9% of the variance for MY, FY, and PY, respectively, demonstrating the potential for causality. CONCLUSIONS:Our findings proved the power of large samples and sequence-based GWAS in detecting new association signals. In order to fully exploit the power of GWAS, one should aim at very large samples combined with whole-genome sequence data. These can also come with both computational and time burdens, as presented in our study. Although milk production traits in cattle are comprehensively investigated, the genetic background of these traits is still not fully understood, with the potential for many new associations to be revealed, as shown. With constantly growing sample sizes, we expect more insights into the genetic architecture of milk production traits in the future.

In recent years, Beef-on-Dairy (BoD) crossbreeding programs have gained momentum to enhance dairy cattle's economic and genetic merits while meeting the demand for high-quality beef. However, bulls with superior growth potential can lead to calving problems; thus, Holstein dairy farmers must decide which semen to use to avoid calving problems while producing heavier BoD calves. In this study, our objective was to genetically evaluate beef sires using a BoD crossbred reference population for three major economic traits, i.e., gestation length (GL), birth weight (BW), and calving ease (CE). A population comprising 4420 BoD calves sired by bulls from Angus (ANG), Limousin (LIM), Wagyu (WAG), and White-Belgian Blue (WBB) was used to perform a joint genetic evaluation of the sire for traits. Univariate and bivariate (linear-linear or threshold-linear) models were applied to estimate variance components and genomic breeding values using single-step methods. Estimates from CE models were transformed from the liability to the observable scale for more straightforward interpretation. Direct heritabilities for GL, BW, and CE (after transformations) ranged from 0.33 to 0.35, 0.33 to 0.37, and 0.02 to 0.14, respectively, while maternal heritabilities ranged from 0.11 to 0.17 for all traits. Generally, male BoD calves had higher probabilities for calving difficulty, with calvings being more difficult if sired by LIM (13%) as compared to ANG (7%) and WBB (9%) when considering male calves. The bivariate models outperformed the univariate models. For CE, the accuracy of predictions was up by 95% with a reduction in bias and dispersion. WBB sires were preferred when crossing with higher parity cows compared to ANG sires. These findings demonstrate that a well-structured BoD reference population enables accurate genomic evaluation of beef sires, facilitating the selection of sires that produce economically viable calves with reduced calving difficulties.

The typical objective of genomic analyses is to assess additive genetic variance in traits. However, the nonadditive component of genetic variation is often disregarded. Consequently, genomic analyses may not directly elucidate the complex genomic structures or other potential underlying mechanisms, such as pleiotropy, dominance, or epistatic effects. Furthermore, polygenic traits are likely to be subject to nonadditive interactions. Specifically regarding traits pertaining to fitness, including fertility, genomic regions exhibiting nonadditive genetic effects, potentially resulting from directional dominance or epistatic effects, have been identified and require further investigation. In this study, data from more than 7,400 German Holsteins dairy cows with continuous observations of their reproduction performance across the first 3 lactations were analyzed. In the first instance, variance component estimations for 12 observations, distributed across 4 different traits across the 3 lactations, were conducted. The results obtained confirmed low h2 for all traits, with the lowest value, h2 = 0.016, observed for stillbirth maternal in the third lactation and the highest being h2 = 0.128 for metritis in the first lactation. Hereafter, GWAS were employed as an initial step to identify chromosomes of interest for each trait and lactation combination. Hereby, a total of 23 genomic regions were identified as significantly associated and subsequently investigated using a machine learning random forest (RF) approach to screen for putative further nonadditive regions of interest. The correlation (r) between repeated RF models exhibited a mean value of r = 0.854 to r = 0.973, while the average proportion of incorrectly predicted animals remained between 0.102 and 0.244. A direct comparison with the 35 significantly associated markers identified by GWAS revealed common markers, as well as the chromosome- and trait-specific architecture, which displayed different patterns of association signals across the complex of reproduction traits. Screening database records confirmed the identified markers in proximity to previously described genes in the context of reproduction as well as dairy cattle genomics. The findings of our study represent a contribution to a better understanding of the complexity of further nonadditive genetics underlying functional traits using GWAS results, with particular attention to regional clustering. Furthermore, they may serve as a foundation for regional in-depth analysis using a broader cohort of animals.

Background Single-step Single Nucleotide Polymorphism best linear unbiased prediction (ssSNPBLUP) is a comprehensive method for obtaining genomically enhanced breeding values for animals and SNP effects in a single evaluation. The ssSNPBLUP model integrates phenotypic, pedigree, and genomic data for genomic evaluations. However, there has been no framework for estimating the reliability and p-values of the SNP effects obtained from a ssSNPBLUP genomic model. This study investigates the reliability and significance of the SNP effects estimated using a ssSNPBLUP framework in German Limousin (LIM) and Holstein (HOL) cattle populations. Methods This study introduces a novel approach for calculating p-values within the ssSNPBLUP framework and compares it to a conventional single-marker regression GWAS approach. SNP reliabilities were computed using prediction error variances of SNP effect estimates, enabling the identification of statistically significant SNP markers. LIM data included weaning weight (200-DW) evaluated with a maternal effect BLUP model, while HOL data comprised production traits (milk yield, protein yield, fat yield, and somatic cell score) analysed via a random regression test-day model. Results The results reveal significant SNP effects in both LIM and HOL evaluations, with notable differences attributed to the size of the reference populations. Average SNP reliabilities were higher in HOL (Mean SNP reliability: 0.42) compared to LIM (Mean SNP reliability: 0.02), underscoring the critical role of the size of the reference population in determining the accuracy and reliability of SNP effects obtained from genomic evaluations. Conclusions The calculation of p-values from the ssSNPBLUP framework offers an efficient approach to identify quantitative trait loci (QTL) that significantly influences traits in populations. Our approach provides a framework that could be implemented in large and complex datasets such as those used in many national routine evaluations, where only a proportion of the animals are genotyped. ### Competing Interest Statement The authors have declared no competing interest.

Twin births in dairy cattle are rare but present significant challenges for animal welfare, as both the health of the cow and the calves are affected. This causes economic losses, which prompts breeders to select against twin births and identify associated risk factors. This study examines the phenotypic relationship between milk yield, fertility traits and twin births in German Holstein cattle using a large, population-wide dataset. GEBV correlations for twin births, milk production and fertility traits were estimated. Genome-wide association studies (GWAS) were conducted for calving numbers 1-3 in order to explore the genetic background in more detail. The twin birth rate showed a strong phenotypic association with milk production and a moderate phenotypic association with the timing of successful insemination. However, GEBV correlations were low: 0.04 with milk yield and -0.10 to 0.01 with fertility traits. GWAS revealed two potential candidate genes on BTA11: LHCGR and FSHR, which encode receptors for LH and FSH, two hormones crucial to estrus. In contrast to the first calving, significantly associated regions on BTA5 and BTA25 were found in calving numbers 2 and 3. This study demonstrates the interaction between genotype and environment, concluding that a genetic predisposition for twin births, in combination with a favourable endocrine state (environment), increases the likelihood of twin births.

This study offers insight into the genetic complexity of the interaction between production and reproduction in German dairy cows. The phenotypes and genotypes of 32,352 primiparous German Holstein cows were available for investigation, and datasets (DS) of similar size were generated according to their milk yield. Five distinct DS, each including more than 6,400 animals, from lowest to highest milk yield (DSLowest, DSLow, DSMean, DSHigh, DSHighest) were included for subsequent analysis. Heritabilities and genetic correlations (rG) between traits were estimated, followed by GWAS. The overall heritability estimates were relatively low, with a maximum of h2 = 0.127 for ovary cycle disturbances in DSHighest and a minimum of h2 = 0.026 for retained placenta (NGV) in the complete DS. The rG between milk yield and reproduction traits exhibited a range from rG = -0.436 between milk yield and metritis (MET) in DSHigh to rG = 0.435 between milk yield and NGV in DSHigh. Genetic correlations between the various reproduction traits were moderate, as evidenced by the correlation between calving ease maternal (CEm) and MET in DSHigh (rG = 0.329). In contrast, a striking divergence within the specific traits was evident contingent on the performance subset. The range of rG between CEm and NGV was covered from rG = -0.146 in DSLowest up to rG = 0.318 in DSHighest. The heritabilities and rG estimates did not demonstrate a straightforward linear relationship between milk yield and the analyzed reproduction parameters. Moreover, GWAS identified several significant SNPs across the various DS, with a total of 86 genome-wide and chromosome-wide signals. These findings led to the identification of previously described genes in the context of reproduction, as well as the postulation of additional potential candidate genes, including a high number of zinc finger proteins. Overall, this study provides important insights into the genetic background and interrelations of reproduction traits with special regards to the nonlinear relationship between milk yield and reproduction, and the findings may help to further improve selection decisions.

BackgroundReproduction is vital to welfare, health, and economics in animal husbandry and breeding. Health and reproduction are increasingly being considered because of the observed genetic correlations between reproduction, health, conformation, and performance traits in dairy cattle. Understanding the detailed genetic architecture underlying these traits would represent a major step in comprehending their interplay. Identifying known, putative or novel associations in genomics could improve animal health, welfare, and performance while allowing further adjustments in animal breeding.ResultsWe conducted genome-wide association studies for 25 different traits belonging to four different complexes, namely reproduction (n = 13), conformation (n = 6), production (n = 3), and metabolism (n = 3), using a cohort of over 235,000 dairy cows. As a result, we identified genome-wide significant signals for all the studied traits. The obtained summary statistics collected served as the input for a Mendelian randomisation approach (GSMR) to infer causal associations between putative exposure and reproduction traits. The study considered conformation, production, and metabolism as exposure and reproduction as outcome. A range of 139 to 252 genome-wide significant SNPs per combination were identified as instrumental variables (IVs). Out of 156 trait combinations, 135 demonstrated statistically significant effects, thereby enabling the identification of the responsible IVs. Combinations of traits related to metabolism (38 out of 39), conformation (68 out of 78), or production (29 out of 39) were found to have significant effects on reproduction. These relationships were partially non-linear. Moreover, a separate variance component estimation supported these findings, strongly correlating with the GSMR results and offering suggestions for improvement. Downstream analyses of selected representative traits per complex resulted in identifying and investigating potential physiological mechanisms. Notably, we identified both trait-specific SNPs and genes that appeared to influence specific traits per complex, as well as more general SNPs that were common between exposure and outcome traits.ConclusionsOur study confirms the known genetic associations between reproduction traits and the three complexes tested. It provides new insights into causality, indicating a non-linear relationship between conformation and reproduction. In addition, the downstream analyses have identified several clustered genes that may mediate this association.

Twinning in dairy cattle poses substantial risks for both cows and calves, including increased rates of calving difficulties, stillbirths, postpartum complications, and negative effects on calf viability and growth. These challenges lead to substantial economic losses and raise serious concerns for animal health and welfare. Consequently, selecting against twin births in German Holstein cattle could be beneficial. In this study, we analyzed the trait twin birth by estimating variance components and genetic correlations with other traits using population-wide data from German Holstein cattle. Breeding values were calculated using a single-step SNP BLUP model, treating twin births as 2 genetically correlated traits: (1) in first parity, and (2) in second and later parities. Heritability was estimated at 0.008 (± 0.0004) for the first parity and 0.026 (± 0.0008) for later parities. Genetic correlations with milk traits were close to zero, slightly positive with fertility, and slightly negative with longevity. The highest genetic correlation of 0.326 (± 0.0229) was observed for stillbirth rate. Comparison of breeding values with daughter phenotypes revealed substantial variability among bulls, whose genetic potential was expressed in varying twin birth rates among their daughters. It is therefore possible to lower twin birth rate through breeding. The estimation of the phenotypic impact of twin births on milk, longevity, calving ease, stillbirth, and health traits highlights the potential to breed against twin births to improve economics, herd performance and animal welfare.

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.

BACKGROUND:Reproductive performance plays an important role in animal welfare, health and profitability in animal husbandry and breeding. It is well established that there is a negative correlation between performance and reproduction in dairy cattle. This relationship is being increasingly considered in breeding programs. By elucidating the genetic architecture of underlying reproduction traits, it will be possible to make a more detailed contribution to this. Our study followed two approaches to elucidate this area; in a first part, variance components were estimated for 14 different calving and fertility traits, and then genome-wide association studies were performed for 13 reproduction traits on imputed sequence-level genotypes with subsequent enrichment analyses. RESULTS:Variance components analyses showed a low to moderate heritability (h2) for the traits analysed, ranging from 0.014 for endometritis up to 0.271 for stillbirth, indicating variable degrees of variation within the reproduction traits. For genome-wide association studies, we were able to detect genome-wide significant association signals for nine out of 13 analysed traits after Bonferroni correction on chromosome 6, 18 and the X chromosome. In total, we detected over 2700 associated SNPs encircling more than 90 different genes using the imputed whole-genome sequence data. Functional associations were reviewed so far known and potential candidate regions in the proximity of reproduction events were hypothesised. CONCLUSION:Our results confirm previous findings of other authors in a comprehensive cohort including 13 different traits at the same time. Additionally, we identified new candidate genes involved in dairy cattle reproduction and made initial suggestions regarding their potential impact, with special regard to the X chromosome as a putative information source for further research. This work can make a contribution to reveal the genetic architecture of reproduction traits in context of trait specific interactions.

Abstract 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.

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.