Most high-yielding dairy cows enter a state of negative energy balance (NEB) during early lactation. This, in turn, results in changes in the level of various metabolites in the blood and follicular fluid microenvironment which contributes to disturbed fertility. Extracellular vesicles (EVs) are evolutionarily conserved communicasomes that transport cargo of miRNA, proteins and lipids. EV-coupled miRNAs have been reported in follicular fluid. However, the association between postpartum NEB and EV-coupled miRNA signatures in follicular fluid is not yet known. Energy balance analysis in lactating cows shortly after post-calving revealed that the majority of the cows exhibited transiently negative energy balance levels, whereas the remaining cows exhibited either consistently negative or consistently positive energy levels. Metabolic status was associated with EV-coupled miRNA composition in the follicular fluid. Cows experiencing NEB showed reduced expression of a large number of miRNAs while cows with positive energy balances primarily exhibited elevated expression of EV-coupled miRNAs. The miRNAs that were suppressed under NEB were found to be involved in various metabolic pathways. This is the first study to reveal the presence of an association between EV-coupled miRNA in follicular fluid and metabolic stress in dairy cows. The involvement of differentially expressed miRNAs in various pathways associated with follicular growth and oocyte maturation suggest the potential involvement of specific follicular miRNAs in oocyte developmental competence, which may partially explain reduced fertility in cows due to post-calving metabolic stress.
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.
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 rg 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 rg (−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.
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