Christine Große-Brinkhaus

Peripheral blood mononuclear cells (PBMCs) are the most immunologically active and readily accessible fraction of whole blood, and they initiate host immune responses following infection and vaccination. Since PBMC transcriptomes capture diverse host–pathogen interactions, they offer a promising tool to uncover the genetic drivers of viral resistance and tolerance. As a detailed case study of this principle, we examine porcine reproductive and respiratory syndrome (PRRS), which remains one of the most economically important viral diseases of swine worldwide. Following PRRS virus (PRRSV) exposure, pigs rely on two complementary defense strategies: resistance, the capacity to limit viral replication, and tolerance, the capacity to sustain performance despite infection. Since resistance and tolerance phenotypes are difficult to measure directly through experimental challenge, indirect immune-trait measurements collected after vaccination offer a practical alternative. Most transcriptomic studies of the host response to PRRSV have focused on respiratory tissues, reflecting the virus’s tropism for pulmonary macrophages. However, intramuscularly delivered modified-live PRRSV vaccine reaches the bloodstream, bypassing the lung, so PBMCs, as the frontline defense system, mount the earliest measurable innate response. This review synthesizes the current literature on PBMC transcriptome models for deciphering innate resistance and tolerance to viral disease, using PRRS as our principal worked example; presents our own approach to profiling PBMCs after PRRSV vaccination; and outlines how the field has advanced since the original candidate-gene and QTL studies of the 2010s, including the recent FDA approval of the first CD163 gene-edited PRRSV-resistant pig line, and the emergence of single-cell and multi-tissue PBMC atlases, before considering how the same PBMC-based approach could extend to other host–virus interactions.

Using genetic selection for raising intact boars, which improves growth and feed efficiency, is a promising alternative to castration for mitigating boar taint. Selective breeding has the potential to help to identify and select genetic lines with a reduced risk of boar taint. Common phenotypes are laboratory measurements of skatole (SKA) and androstenone (ANON) i.e., the major compounds responsible for boar taint, in backfat. However, an alternative exists: sensory evaluation by human assessors. The objectives of this study were (1) to estimate the genetic relationships among sensory scores (SENS) obtained by different assessors, (2) to correlate these scores with SKA and ANON, (3) to establish the independence of SENS from the causal traits, here SKA and ANON, by recursive modeling, holding those constant, and (4) to combine different assessors to allow an efficient selection against boar taint. Data included up to 1,016 records of SKA, ANON, and SENS (0–5) from 10 trained assessors on the backfat of intact males reared at least until puberty at three performance testing stations testing the products of Pietrain × commercial crossbred sows. Genetic parameters were estimated using restricted estimate maximum likelihood. Traits SKA and ANON were log10 transformed (SKAt and ANONt) and SENS traits were Snell transformed SENS (SENSt). Heritability estimates were 0.52 for SKAt and 0.53 for ANONt, those for SENSt ranged from 0.07 to 0.30. Moderate to high genetic correlations between some SENSt and SKAt (up to 0.87) and ANONt (up to 0.61) were found. Heritabilities and correlations indicated that some SENSt could be used to select against boar taint. Studying the independence of SENSt from SKAt and ANONt based on a posteriori recursive model revealed a large range of reductions of genetic variance: up to 71.08%. However, some SENSt remained moderately heritable (0.04–0.19) indicating independent genetic variance from SKAt and ANONt. This reflects that some heritable compounds potentially not related to SKA or ANON are perceived. Finally, the combination of assessors allowed, here shown with three assessors, to obtain a high heritability of 0.40, associated to high genetic and phenotypic correlations. Moreover, these results demonstrate the potential of using the sensory scores of several trained assessors for selection against boar taint.

Background: Immune traits are considered to serve as potential biomarkers for pig’s health. Medium to high heritabilities have been observed for some of the immune traits suggesting genetic variability of these phenotypes. Consideration of previously established genetic correlations between immune traits can be used to identify pleiotropic genetic markers. Therefore, genome-wide association study (GWAS) approaches are required to explore the joint genetic foundation for health biomarkers. Usually, GWAS explores phenotypes in a univariate (uv), trait-by-trait manner. Besides two uv GWAS methods, four multivariate (mv) GWAS approaches were applied on combinations out of 22 immune traits for Landrace (LR) and Large White (LW) pig lines. Results: In total 433 (LR: 351, LW: 82) associations were identified with the uv approach implemented in PLINK and a Bayesian linear regression uv approach (BIMBAM) software. Single Nucleotide Polymorphisms (SNPs) that were identified with both uv approaches (n = 32) were mostly associated with immune traits such as haptoglobin, red blood cell characteristics and cytokines, and were located in protein-coding genes. Mv GWAS approaches detected 647 associations for different mv immune trait combinations which were summarized to 133 Quantitative Trait Loci (QTL). SNPs for different trait combinations (n = 66) were detected with more than one mv method. Most of these SNPs are associated with red blood cell related immune trait combinations. Functional annotation of these QTL revealed 453 immune-relevant protein-coding genes. With uv methods shared markers were not observed between the breeds, whereas mv approaches were able to detect two conjoint SNPs for LR and LW. Due to unmapped positions for these markers, their functional annotation was not clarified. Conclusions: This study evaluated the joint genetic background of immune traits in LR and LW piglets through the application of various uv and mv GWAS approaches. In comparison to uv methods, mv methodologies identified more significant associations, which might reflect the pleiotropic background of the immune system more accurately. In genetic research of complex traits, the SNP effects are generally small. Furthermore, one genetic variant can affect several correlated immune traits at the same time, termed pleiotropy. As mv GWAS methods consider strong dependencies among traits, the power to detect SNPs can be boosted. Both methods revealed immune-relevant potential candidate genes. Our results indicate that one single test is not able to detect all the different types of genetic effects in the most powerful manner and therefore, the methods should be applied complementary.

The proceedings of the 12th World Congress on Genetics Applied to Livestock Production provide you with 816 papers representing the leading research in livestock genetics around the globe. This boo...

Improving the immunocompetence towards pathogens represents a desirable objective of breeding strategies to increase resilience. However, the immune system is complex and the genetic foundation of the underlying components is not yet clarified. In the present study, we focused on 22 blood parameters of 1,144 Landrace (LR) and Large White (LW) piglets at the age of 6–7 weeks. The immune profiles covered immune cells, red blood cell characteristics and cytokines. Genetic parameters based on pedigree information along with possible environmental effects were estimated. Litter effects play an important role in the expression of immune parameters of their young progenies. Hence, litter impacts on the piglet's immune profile including the immune parameters of the dam itself were investigated by different models. To incorporate the complexity of the immune network, the data were further investigated with a principal component analysis. Immune traits showed low to high breed‐specific heritabilities (h²). Strong positive r_g were estimated among red blood cell characteristics (0.77–0.99) and among cytokines (0.48–0.99). Neutrophils and lymphocytes illustrated a high negative r_g (−0.96 to −0.98). The litter impact on piglet's immunity was examined and strengthened already observed breed differences. In LR, h² (0.22–0.15) and litter effect (c²) (0.52–0.44) for IFN‐γ decreased after statistical consideration of maternal impact. In LW, a decrease in h² (0.32–0.18) for IFN‐γ and an increase in c² (0.54–0.56) were observed. Here, sufficient correlations were detected within various immune traits and functional biological networks of principal components. Most immune traits are heritable and are promising to cover global breed‐specific immunocompetence in pigs. The analysis of immune traits has to be extended in order to find an optimal range and to characterize relationships between immunity and performance to gain an improved immune system without accidental losses in productivity.

Next-generation sequencing is a promising approach for the detection of causal variants within previously identified quantitative trait loci. Because of the costs of re-sequencing experiments, this application is currently mainly restricted to subsets of animals from already genotyped populations. Imputation from a lower to a higher marker density could represent a useful complementary approach. An analysis of the literature shows that several strategies are available to select animals for re-sequencing. This study demonstrates an animal selection workflow under practical conditions. Our approach considers different data sources and limited resources such as budget and availability of sampling material. The workflow combines previously described approaches and makes use of genotype and pedigree information from a Landrace and Large White population. Genotypes were phased and haplotypes were accurately estimated with AlphaPhase. Then, AlphaSeqOpt was used to optimize selection of animals for re-sequencing, reflecting the existing diversity of haplotypes. AlphaSeqOpt and ENDOG were used to select individuals based on pedigree information and by taking into account key animals that represent the genetic diversity of the populations. After the best selection criteria were determined, a subset of 57 animals was selected for subsequent re-sequencing. In order to evaluate and assess the advantage of this procedure, imputation accuracy was assessed by setting a set of single nucleotide polymorphism (SNP) chip genotypes to missing. Accuracy values were compared to those of alternative selection scenarios and the results showed the clear benefits of a targeted selection within this practical-driven approach. Especially imputation of low-frequency markers benefits from the combined approach described here. Accuracy was increased by up to 12% compared to a randomized or exclusively haplotype-based selection of sequencing candidates.

Background: In recent years, animal welfare and health has become more and more important in pig breeding. So far, numerous parameters have been considered as important biomarkers, especially in the immune reaction and inflammation. Previous studies have shown moderate to high heritabilities in most of these traits. However, the genetic background of health and robustness of pigs needs to be extensively clarified. The objective of this study was to identify genomic regions with a biological relevance for the immunocompetence of piglets. Genome-wide Association Studies (GWAS) in 535 Landrace (LR) and 461 Large White (LW) piglets were performed, investigating 20 immune relevant traits. Besides the health indicators of the complete and differential blood count, eight different cytokines and haptoglobin were recorded in all piglets and their biological dams to capture mediating processes and acute phase reactions. Additionally, all animals were genotyped using the Illumina PorcineSNP60v2 BeadChip.Results: In summary, GWAS detected 25 genome-wide and 452 chromosome-wide significant SNPs associated with 17 immune relevant traits in the two maternal pig lines LR and LW. Only small differences were observed considering the maternal immune records as covariate within the statistical model. Furthermore, the study identified across- and within-breed differences as well as relevant candidate genes. In LR more significant associations and related candidate genes were detected, compared with LW. The results detected in LR and LW are partly in accordance with previously identified quantitative trait loci (QTL) regions. In addition, promising novel genomic regions were identified which might be of interest for further detailed analysis. Especially putative pleiotropic regions on SSC5, SSC12, SSC15, SSC16 and SSC17 are of major interest with regard to the interacting structure of the immune system. The comparison with already identified QTL gives indications on interactions with traits affecting piglet survival and also production traits.Conclusion: In conclusion, results suggest a polygenic and breed-specific background of immune relevant traits. The current study provides knowledge about regions with biological relevance for health and immune traits. Identified markers and putative pleiotropic regions provide first indications in the context of balancing a breeding-based modification of the porcine immune system.

The surgical castration of young male piglets without anesthesia is no longer allowed in Germany from 2021. One alternative is breeding against boar taint, but shared synthesis pathways of androstenone (AND) and several endocrine fertility parameters (EFP) indicate a risk of decreasing fertility. The objective of this study was to investigate the genetic background between AND, skatole (SKA), and six EFP in purebred Landrace (LR) and Large White (LW) populations. The animals were clustered according to their genetic relatedness because of their different origins. Estimated heritabilities (h²) of AND and SKA ranged between 0.52 and 0.34 in LR and LW. For EFP, h² differed between the breeds except for follicle-stimulating hormone (FSH) (h²: 0.28–0.37). Both of the breeds showed unfavorable relationships between AND and testosterone, 17-β estradiol, and FSH. The genetic relationships (r_g) between SKA and EFP differed between the breeds. A genome-wide association analysis revealed 48 significant associations and confirmed a region for SKA on Sus Scrofa chromosome (SSC) 14. For EFP, the results differed between the clusters. In conclusion, r_g partly confirmed physiologically expected antagonisms between AND and EFP. Particular attention should be spent on fertility traits that are based on EFP when breeding against boar taint to balance the genetic progress in both of the trait complexes.