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.

Epilepsy is a complex genetic disorder that affects about 2% of the global population. Although the frequency and severity of epileptic seizures can be reduced by a range of pharmacological interventions, there are no disease-modifying treatments for epilepsy. The development of new and more effective drugs is hindered by a lack of suitable animal models. Available rodent models may not recapitulate all key aspects of the disease. Spontaneous epileptic convulsions were observed in few Göttingen Minipigs (GMPs), which may provide a valuable alternative animal model for the characterisation of epilepsy-type diseases and for testing new treatments. We have characterised affected GMPs at the genome level and have taken advantage of primary fibroblast cultures to validate the functional impact of fixed genetic variants on the transcriptome level. We found numerous genes connected to calcium metabolism that have not been associated with epilepsy before, such as ADORA2B , CAMK1D , ITPKB , MCOLN2 , MYLK , NFATC3 , PDGFD , and PHKB . Our results have identified two transcription factor genes, EGR3 and HOXB6 , as potential key regulators of CACNA1H , which was previously linked to epilepsy-type disorders in humans. Our findings provide the first set of conclusive results to support the use of affected subsets of GMPs as an alternative and more reliable model system to study human epilepsy. Further neurological and pharmacological validation of the suitability of GMPs as an epilepsy model is therefore warranted.

Background The use of genome-wide association studies (GWAS) has led to the identification of numerous quantitative trait loci and candidate genes in dairy cattle. To obtain sufficient power of GWAS and to identify quantitative trait nucleotides, whole-genome sequence data is required. Sequence data facilitates the identification of potential causal variants; however, sequencing of whole genomes is still expensive for a large number of animals. Imputation is a quick and efficient way of obtaining sequence data from large datasets. 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 causative 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, 252,285 cattle were imputed to the sequence level and large-scale GWAS was carried out to identify new association signals. Results We confirmed many known and identified 30 previously unreported candidate genes for milk, fat, and protein yield. While all of the genes were functionally associated with the traits, some showed pleiotropic effects as well. Specifically, association with mammary gland development, fatty acid synthesis, metabolism of lipids, or milk production QTLs in other farm animals has been reported. Variants associated with these genes explained a large percentage of genetic variance, compared to random ones. 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. Although milk production traits in cattle are comprehensively researched, the genetic background of these traits is still not fully understood, with the potential for many new associations to be revealed, as shown in our study. With constantly growing sample sizes, we expect more insights into the genetic architecture of production traits in the future.

Background This paper highlights the relationships between economic weights, genetic progress, and phenotypic progress in genomic breeding programs that aim at generating genetic progress in complex, i.e., multi-trait, breeding objectives via a combination of estimated breeding values for different trait complexes. Results Based on classical selection index theory in combination with quantitative genetic models, we provide a methodological framework for calculating expected genetic and phenotypic progress for all components of a complex breeding objective. We further provide an approach to study the sensitivity of the system to modifications, e.g. to changes in the economic weights. We propose a novel approach to derive the covariance structure of the stochastic errors of estimated breeding values from the observed correlations of estimated breeding values. We define ‘realized economic weights’ as those weights that would coincide with the observed composition of the genetic trend and show, how they can be calculated. The suggested methodology is illustrated with an index that aims at achieving a breeding goal composed of six trait complexes, that was applied in German Holstein cattle breeding until 2021. Conclusions Based on the presented results, the main conclusions are (i) the composition of the observed genetic progress matches the expectations well, with predictions being slightly better when the covariance of estimation errors is taken into account; (ii) the composition of the expected phenotypic trend deviates significantly from the expected genetic trend due to the differences in trait heritabilities; and (iii) the realized economic weights derived from the observed genetic trend deviate substantially from the predefined ones, in one case even with a reversed sign. Further results highlight the implications of the change to a modified breeding goal based on the example of a new index comprising eight, partly new, trait complexes, which is used since 2021 in the German Holstein breeding program. The proposed framework and the analytical tools and software provided will be useful to define more rational and generally accepted breeding objectives in the future.

Background Porcine endogenous retroviruses (PERVs) can infect human cells and pose a risk for xenotransplantation when pig cells, tissues or organs are transplanted to human recipients. Xenotransplantation holds great promise to overcome the shortage of human donor organs after solving the problems of rejection, functionality and virus safety. We recently described the transmission of a human-tropic recombinant PERV-A/C, designated PERV-F, from peripheral blood mononuclear cells (PBMCs) of a Göttingen Minipig (GöMP) to human 293 cells (Krüger et al., in Viruses 12(1):38, 2019). The goal of this study was to characterize PERV-F in more detail and to analyze the probability of virus isolation from other animals. Methods The recombination site in the envelope ( env ) gene, the long terminal repeats (LTR), the proteins and the morphology of the recombinant PERV-F were characterized by polymerase chain reaction (PCR), sequencing, Western blot analysis, immunofluorescence, and transmissible electron microscopy. Mitogen-stimulated PBMCs from 47 additional pigs, including 17 new GöMP, were co-cultured with highly susceptible human 293 T cells, and the PERV-A/C prevalence and PERV transmission was analyzed by PCR. Results PERV-F, isolated from a GöMP, is an infectious human-tropic PERV-A/C virus with a novel type of recombination in the env gene. The length of the LTR of PERV-F increased after passaging on human cells. In a few minipigs, but not in German landrace pigs, PERV-A/C were found. There was no transmission of human-tropic PERV-A/C from additional 47 pigs, including 17 GöMP, to human cells. Conclusion These data show that human-tropic recombinant PERV-A/C proviruses can only be found in a very small number of minipigs, but not in other pigs, and that their isolation as infectious virus able to replicate on human cells is an extremely rare event, even when using highly susceptible 293 cells.

Background Structural variants (SV) are causative for some prominent phenotypic traits of livestock as different comb types in chickens or color patterns in pigs. Their effects on production traits are also increasingly studied. Nevertheless, accurately calling SV remains challenging. It is therefore of interest, whether close-by single nucleotide polymorphisms (SNPs) are in strong linkage disequilibrium (LD) with SVs and can serve as markers. Literature comes to different conclusions on whether SVs are in LD to SNPs on the same level as SNPs to other SNPs. The present study aimed to generate a precise SV callset from whole-genome short-read sequencing (WGS) data for three commercial chicken populations and to evaluate LD patterns between the called SVs and surrounding SNPs. It is thereby the first study that assessed LD between SVs and SNPs in chickens. Results The final callset consisted of 12,294,329 bivariate SNPs, 4,301 deletions (DEL), 224 duplications (DUP), 218 inversions (INV) and 117 translocation breakpoints (BND). While average LD between DELs and SNPs was at the same level as between SNPs and SNPs, LD between other SVs and SNPs was strongly reduced (DUP: 40%, INV: 27%, BND: 19% of between-SNP LD). A main factor for the reduced LD was the presence of local minor allele frequency differences, which accounted for 50% of the difference between SNP - SNP and DUP - SNP LD. This was potentially accompanied by lower genotyping accuracies for DUP, INV and BND compared with SNPs and DELs. An evaluation of the presence of tag SNPs (SNP in highest LD to the variant of interest) further revealed DELs to be slightly less tagged by WGS SNPs than WGS SNPs by other SNPs. This difference, however, was no longer present when reducing the pool of potential tag SNPs to SNPs located on four different chicken genotyping arrays. Conclusions The results implied that genomic variance due to DELs in the chicken populations studied can be captured by different SNP marker sets as good as variance from WGS SNPs, whereas separate SV calling might be advisable for DUP, INV, and BND effects.

Structural variants (SV) have gained increasing interest within the last years. However, calling SVs from array genotypes or short-read data is known to suffer from high false-positive rates and low specificity at the same time. In contrast, long-read technologies promise to derive accurate and sensitive SV callsets. We hereby present the first study that uses PacBio and Nanopore long-reads to derive quantitative estimates of the amount of SVs in chicken, based on four trios. We estimated the mean size of the reference genome affected by at least heterozygous SV calls to range from 0.2% for insertions to 0.7% for deletions. We further compared the results to a short-read based calling approach. This revealed more than 2/3 of short-read based initial SV calls not being backed by long-read based calls, while more than 50% of the long-read based calls would have been missed by the short-read approach.

Spirulina is an interesting candidate for fish nutrition. This study aims to investigate the effect of the complete replacement of fishmeal with spirulina (Arthrospira platensis) in the diets of brook trout (Salvelinus fontinalis), rainbow trout (Oncorhynchus mykiss) and brown trout (Salmo trutta fario), in relation to growth and product quality. Two isoenergetic and isonitrogenous experimental diets containing either fishmeal or spirulina as a main source of protein were used for a 10-week feeding trial. Differences in the spirulina acceptance and conversion between species were observed. The experimental diets were well accepted except for brown trout. A species-diet interaction was observed, which led to a reduction in final body weight due to the spirulina supplementation for brook and rainbow trout (p$$ p $$ < 0.05). Parallel, the feed conversion ratio increased to the same extent in the spirulina-fed fish (p$$ p $$ < 0.05), fostering the assumption, that both species did not differ in converting the spirulina diet. Spirulina led to a significant increase (p$$ p $$ < 0.05) in yellow and red coloration in both raw and cooked fillets. The diet had a significant effect on the fatty acid profile, resulting in an increase in SFA and MUFA, while PUFA levels decreased significantly in spirulina-fed fish (p$$ p $$ < 0.05). Overall, total replacement of fishmeal with Spirulina goes along with a reduced production performance and effects on major product quality traits such as fillet colour and fatty acid pattern. In particular, consumer acceptance of the yellow fillet colour should be further investigated.

Genetic rescue using external breeders or cryo-preserved semen is a reasonable strategy to restore diversity in small breeds. It is also known from natural populations that animals from large populations can convey substantial genetic load when they migrate into small, highly inbred populations, which may compromise the recipient population. We used stochastic simulation to evaluate different scenarios of genetic rescue of two conservation stocks of different sizes and found that introgression of males from larger stocks had a more detrimental effect on the viability of offspring than from smaller stocks, even though both strategies partially restored diversity. Using samples from gene-banks had a comparably negative effect on offspring viability, if the population was substantially larger at the time of cryo-conservation. Our results suggest that careful assessment of genetic load and its consequences is required whenever external animals should be transferred into endangered stocks. As larger breeds have higher genetic load due to less efficient purging, animals from small breeds seem beneficial for genetic rescue.

BACKGROUND:Migration of a population from its founder population is expected to cause a reduction of its genetic diversity and facilitates differentiation between the population and its founder population, as predicted by the theory of genetic isolation by distance. Consistent with that theory, a model of expansion from a single founder predicts that patterns of genetic diversity in populations can be explained well by their geographic expansion from their founders, which is correlated with genetic differentiation.METHODS:To investigate this in chicken, we estimated the relationship between the genetic diversity of 160 domesticated chicken populations and their genetic distances to wild chicken populations.RESULTS:Our results show a strong inverse relationship, i.e. 88.6% of the variation in the overall genetic diversity of domesticated chicken populations was explained by their genetic distance to the wild populations. We also investigated whether the patterns of genetic diversity of different types of single nucleotide polymorphisms (SNPs) and genes are similar to that of the overall genome. Among the SNP classes, the non-synonymous SNPs deviated most from the overall genome. However, genetic distance to the wild chicken still explained more variation in domesticated chicken diversity across all SNP classes, which ranged from 83.0 to 89.3%.CONCLUSIONS:Genetic distance between domesticated chicken populations and their wild relatives can predict the genetic diversity of the domesticated populations. On the one hand, genes with little genetic variation across populations, regardless of the genetic distance to the wild population, are associated with major functions such as brain development. Changes in such genes may be detrimental to the species. On the other hand, genetic diversity seems to change at a faster rate within genes that are associated with e.g. protein transport and protein and lipid metabolic processes. In general, such genes may be flexible to changes according to the populations' needs. These results contribute to the knowledge of the evolutionary patterns of different functional genomic regions in the chicken.

Single nucleotide polymorphisms (SNPs), genotyped with arrays, have become a widely used marker type in population genetic analyses over the last 10 years. However, compared to whole genome re-sequencing data, arrays are known to lack a substantial proportion of globally rare variants and tend to be biased towards variants present in populations involved in the development process of the respective array. This affects population genetic estimators and is known as SNP ascertainment bias. We investigated factors contributing to ascertainment bias in array development by redesigning the Axiom™ Genome-Wide Chicken Array in silico and evaluating changes in allele frequency spectra and heterozygosity estimates in a stepwise manner. A sequential reduction of rare alleles during the development process was shown. This was mainly caused by the identification of SNPs in a limited set of populations and a within-population selection of common SNPs when aiming for equidistant spacing. These effects were shown to be less severe with a larger discovery panel. Additionally, a generally massive overestimation of expected heterozygosity for the ascertained SNP sets was shown. This overestimation was 24% higher for populations involved in the discovery process than not involved populations in case of the original array. The same was observed after the SNP discovery step in the redesign. However, an unequal contribution of populations during the SNP selection can mask this effect but also adds uncertainty. Finally, we make suggestions for the design of specialized arrays for large scale projects where whole genome re-sequencing techniques are still too expensive.

Context Breeding programs aim at improving the genetic characteristics of livestock populations with respect to productivity, fitness and adaptation, while controlling negative effects such as inbreeding or health and welfare issues. As breeding is affected by a variety of interdependent factors, the analysis of the effect of certain breeding actions and the optimisation of a breeding program are highly complex tasks. Aims This study was conducted to display the potential of using stochastic simulation to analyse, evaluate and compare breeding programs and to show how the Modular Breeding Program Simulator (MoBPS) simulation framework can further enhance this. Methods In this study, a simplified version of the breeding program of Göttingen Minipigs was simulated to analyse the impact of genotyping and optimum contribution selection in regard to both genetic gain and diversity. The software MoBPS was used as the backend simulation software and was extended to allow for a more realistic modelling of pig breeding programs. Among others, extensions include the simulation of phenotypes with discrete observations (e.g. teat count), variable litter sizes, and a breeding value estimation in the associated R-package miraculix that utilises a graphics processing unit. Key results Genotyping with the subsequent use of genomic best linear unbiased prediction (GBLUP) led to substantial increases in genetic gain (15.3%) compared with a pedigree-based BLUP, while reducing the increase of inbreeding by 24.8%. The additional use of optimum genetic selection was shown to be favourable compared with the plain selection of top boars. The use of graphics processing unit-based breeding value estimation with known heritability was ~100 times faster than the state-of-the-art R-package rrBLUP. Conclusions The results regarding the effect of both genotyping and optimal contribution selection are in line with well established results. Paired with additional new features such as the modelling of discrete phenotypes and adaptable litter sizes, this confirms MoBPS to be a unique tool for the realistic modelling of modern breeding programs. Implications The MoBPS framework provides a powerful tool for scientists and breeders to perform stochastic simulations to optimise the practical design of modern breeding programs to secure standardised breeding of high-quality animals and answer associated research questions.

Abstract Background Population genetic studies based on genotyped single nucleotide polymorphisms (SNPs) are influenced by a non-random selection of the SNPs included in the used genotyping arrays. The resulting bias in the estimation of allele frequency spectra and population genetics parameters like heterozygosity and genetic distances relative to whole genome sequencing (WGS) data is known as SNP ascertainment bias. Full correction for this bias requires detailed knowledge of the array design process, which is often not available in practice. This study suggests an alternative approach to mitigate ascertainment bias of a large set of genotyped individuals by using information of a small set of sequenced individuals via imputation without the need for prior knowledge on the array design. Results The strategy was first tested by simulating additional ascertainment bias with a set of 1566 chickens from 74 populations that were genotyped for the positions of the Affymetrix Axiom™ 580 k Genome-Wide Chicken Array. Imputation accuracy was shown to be consistently higher for populations used for SNP discovery during the simulated array design process. Reference sets of at least one individual per population in the study set led to a strong correction of ascertainment bias for estimates of expected and observed heterozygosity, Wright’s Fixation Index and Nei’s Standard Genetic Distance. In contrast, unbalanced reference sets (overrepresentation of populations compared to the study set) introduced a new bias towards the reference populations. Finally, the array genotypes were imputed to WGS by utilization of reference sets of 74 individuals (one per population) to 98 individuals (additional commercial chickens) and compared with a mixture of individually and pooled sequenced populations. The imputation reduced the slope between heterozygosity estimates of array data and WGS data from 1.94 to 1.26 when using the smaller balanced reference panel and to 1.44 when using the larger but unbalanced reference panel. This generally supported the results from simulation but was less favorable, advocating for a larger reference panel when imputing to WGS. Conclusions The results highlight the potential of using imputation for mitigation of SNP ascertainment bias but also underline the need for unbiased reference sets.

Additional file 4 Supplementary Table 4. Functional annotation of SNPs dependent on the FST value between two colonies.

Background Göttingen Minipigs (GMP) is the smallest commercially available minipig breed under a controlled breeding scheme and is globally bred in five isolated colonies. The genetic isolation harbors the risk of stratification which might compromise the identity of the breed and its usability as an animal model for biomedical and human disease. We conducted whole genome re-sequencing of two DNA-pools per colony to assess genomic differentiation within and between colonies. We added publicly available samples from 13 various pig breeds and discovered overall about 32 M loci, ~ 16 M. thereof variable in GMPs. Individual samples were virtually pooled breed-wise. F ST between virtual and DNA pools, a phylogenetic tree, principal component analysis (PCA) and evaluation of functional SNP classes were conducted. An F-test was performed to reveal significantly differentiated allele frequencies between colonies. Variation within a colony was quantified as expected heterozygosity. Results Phylogeny and PCA showed that the GMP is easily discriminable from all other breads, but that there is also differentiation between the GMP colonies. Dependent on the contrast between GMP colonies, 4 to 8% of all loci had significantly different allele frequencies. Functional annotation revealed that functionally non-neutral loci are less prone to differentiation. Annotation of highly differentiated loci revealed a couple of deleterious mutations in genes with putative effects in the GMPs . Conclusion Differentiation and annotation results suggest that the underlying mechanisms are rather drift events than directed selection and limited to neutral genome regions. Animal exchange seems not yet necessary. The Relliehausen colony appears to be the genetically most unique GMP sub-population and could be a valuable resource if animal exchange is required to maintain uniformity of the GMP.

The size and shape of organs is tightly controlled to achieve optimal function. Natural morphological variations often represent functional adaptations to an ever-changing environment. For instance, variation in head morphology is pervasive in insects and the underlying molecular basis is starting to be revealed in the Drosophila genus for species of the melanogaster group. However, it remains unclear whether similar diversifications are governed by similar or different molecular mechanisms over longer timescales. To address this issue, we used species of the virilis phylad because they have been diverging from D. melanogaster for at least 40 million years. Our comprehensive morphological survey revealed remarkable differences in eye size and head shape among these species with D. novamexicana having the smallest eyes and southern D. americana populations having the largest eyes. We show that the genetic architecture underlying eye size variation is complex with multiple associated genetic variants located on most chromosomes. Our genome wide association study (GWAS) strongly suggests that some of the putative causative variants are associated with the presence of inversions. Indeed, northern populations of D. americana share derived inversions with D. novamexicana and they show smaller eyes compared to southern ones . Intriguingly, we observed a significant enrichment of genes involved in eye development on the 4th chromosome after intersecting chromosomal regions associated with phenotypic differences with those showing high differentiation among D. americana populations. We propose that variants associated with chromosomal inversions contribute to both intra- and interspecific variation in eye size among species of the virilis phylad.

Xenotransplantation using pig tissues and organs is under development in order to alleviate the increasing shortage of human transplants. Since xenotransplantation may be associated with the transmission of porcine microorganisms to the human recipient, the donor pigs should be carefully analyzed, especially for the presence of potentially zoonotic viruses. Göttingen Minipigs (GöMP) are potential donors of islet cells for the treatment of diabetes. Despite the fact that all animals produced at Ellegaard Göttingen Minipigs A/S carry porcine endogenous retroviruses (PERVs) in their genome and that very few animals were infected with porcine cytomegalovirus (PCMV), hepatitis E virus (HEV) and porcine lymphotropic herpesvirus (PLHV), no transmission of these viruses was observed in a preclinical trial transplanting GöMP islet cells into cynomolgus monkeys. Using a new comprehensive strategy, we then analyzed an isolated subpopulation of Göttingen Minipigs which remained at the University of Göttingen. We concentrated on 11 xenotransplantation-relevant viruses and combined co-incubation assays with susceptible human target cells and molecular biological methods to evaluate the risk posed by PERV. All animals in Göttingen carry PERV-A, PERV-B, and PERV-C in their genome but they are not infected with PCMV, PLHV and HEV. The difference may be explained by selection of negative animals and/or de novo infection. The PERV copy number was established using ddPCR (93 copies) and a human-tropic PERV-A/C was found released from PBMCs of one animal with a high expression of PERV-C.