Toll-like receptor 3 (TLR3), an endosomal receptor crucial for immune responses upon viral invasion. The TLR3 ectodomain (ECD) is responsible for double-stranded RNA (dsRNA) recognition and mutational analysis suggested that TLR3 ECD C-terminal dimerization is essential for dsRNA binding. Moreover, the L412F polymorphism of TLR3 is associated with human diseases. Although the mouse structure of the TLR3-dsRNA complex provides valuable insights, the structural dynamic behavior of the TLR3-dsRNA complex in humans is not completely understood. Hence, in this study, we performed molecular dynamic simulations of human wild-type and mutant TLR3 complexes. Our results suggested that apoTLR3 ECD dimers are unlikely to be stable due to the distance between the monomers are largely varied during simulations. The observed interaction energies and hydrogen bonds in dsRNA-bound TLR3 wild-type and mutant complexes indicate the presence of a weak dimer interface at the TLR3 ECD C-terminal site, which is required for effective dsRNA binding. The L412F mutant exhibited similar dominant motion compared to wild-type. Additionally, we identified the distribution of crucial residues for signal propagation in TLR3-dsRNA complex through the evaluation of residue betweenness centrality (C_B). The results of this study extend our understanding of TLR3-dsRNA complex, which may assist in TLR3 therapeutics.

Background: In this study, we assessed the accuracy of genomic prediction for carcass weight (CWT), marbling score (MS), eye muscle area (EMA) and back fat thickness (BFT) in Hanwoo cattle when using genomic best linear unbiased prediction (GBLUP), weighted GBLUP (wGBLUP), and a BayesR model. For these models, we investigated the potential gain from using pre-selected single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) on imputed sequence data and from gene expression information. We used data on 13,717 animals with carcass phenotypes and imputed sequence genotypes that were split in an independent GWAS discovery set of varying size and a remaining set for validation of prediction. Expression data were used from a Hanwoo gene expression experiment based on 45 animals. Results: Using a larger number of animals in the reference set increased the accuracy of genomic prediction whereas a larger independent GWAS discovery dataset improved identification of predictive SNPs. Using pre-selected SNPs from GWAS in GBLUP improved accuracy of prediction by 0.02 for EMA and up to 0.05 for BFT, CWT, and MS, compared to a 50 k standard SNP array that gave accuracies of 0.50, 0.47, 0.58, and 0.47, respectively. Accuracy of prediction of BFT and CWT increased when BayesR was applied with the 50 k SNP array (0.02 and 0.03, respectively) and was further improved by combining the 50 k array with the top-SNPs (0.06 and 0.04, respectively). By contrast, using BayesR resulted in limited improvement for EMA and MS. wGBLUP did not improve accuracy but increased prediction bias. Based on the RNA-seq experiment, we identified informative expression quantitative trait loci, which, when used in GBLUP, improved the accuracy of prediction slightly, i.e. between 0.01 and 0.02. SNPs that were located in genes, the expression of which was associated with differences in trait phenotype, did not contribute to a higher prediction accuracy. Conclusions: Our results show that, in Hanwoo beef cattle, when SNPs are pre-selected from GWAS on imputed sequence data, the accuracy of prediction improves only slightly whereas the contribution of SNPs that are selected based on gene expression is not significant. The benefit of statistical models to prioritize selected SNPs for estimating genomic breeding values is trait-specific and depends on the genetic architecture of each trait.

Chicken is important livestock that serves as a vital food source which remain largely affected by heat stress. Therefore, we performed the transcriptome analysis to help understand the mechanisms of heat stress response in chickens. In the animal experiments, we grouped them into a normal and severe at 21 and 33 °C, with identified physiologic parameters for 2-weeks. Subsequently, RNA-seq analysis was performed to identify DEGs with a false discovery rate < 0.05 and a fold change ≥ 1.5. In the physiological parameters, we observed average daily gain was declined, rectal temperature and respiration rate was increased in severe group. Among total 245 DEGs, 230 and 15 genes were upregulated and downregulated, respectively. In upregulated DEGs, HSPs, MYLK2, and BDKRB1 genes were identified as key genes in heat stress. The KEGG pathway analysis showed involvement in the ATP metabolic process, MAPK signaling pathway and calcium signaling pathway with related protein processing and synthesis. In conclusion, with induced heat stress, such changes in physiologic parameters alter the neuroendocrine system, and we observed that the heat stress environment regulates such Heat shock protein genes to protect the cells and proteins from an altered metabolism. These findings provide a more comprehensive understanding of the heat stress response in poultry.

Probiotics can modulate the composition of gut microbiota and benefit the host animal health in multiple ways. Lactic acid bacteria (LAB), mainly Lactobacillus and Bifidobacterium species, are well-known microbes with probiotic potential. In the present study, 88 microbial strains were isolated from canine feces and annotated. Among these, the four strains CACC517, 537, 558, and 566 were tested for probiotic characteristics, and their beneficial effects on hosts were evaluated both in vitro and in vivo; these strains exhibited antibiosis, antibiotic activity, acid and bile tolerance, and relative cell adhesion to the HT-29 monolayer cell line. Byproducts of these strains increased the viability and decreased oxidative stress in mouse and dog cell lines (RAW264.7 and DH82, respectively). Subsequently, when the probiotics were applied to the clinical trial, changes in microbial composition and relative abundance of bacterial strains were clearly observed in the experimental animals. Experimental groups before and after the application were obviously separated from PCA analysis of clinical results. Conclusively, these results could provide comprehensive understanding of the effects of probiotic strains (CACC517, 537, 558, and 566) and their industrial applications.

Climate change increases global temperatures, which is lethal to both livestock and humans. Heat stress is known as one of the various livestock stresses, and dairy cows react sensitively to high-temperature stress. We aimed to better understand the effects of heat stress on the health of dairy cows and observing biological changes. Individual cows were divided into normal (21–22 °C, 50–60% humidity) and high temperature (31–32 °C, 80–95% humidity), respectively, for 7-days. We performed metabolomic and transcriptome analyses of the blood and gut microbiomes of feces. In the high-temperature group, nine metabolites including linoleic acid and fructose were downregulated, and 154 upregulated and 72 downregulated DEGs (Differentially Expressed Genes) were identified, and eighteen microbes including Intestinimonas and Pseudoflavonifractor in genus level were significantly different from normal group. Linoleic acid and fructose have confirmed that associated with various stresses, and functional analysis of DEG and microorganisms showing significant differences confirmed that high-temperature stress is related to the inflammatory response, immune system, cellular energy mechanism, and microbial butyrate production. These biological changes were likely to withstand high-temperature stress. Immune and inflammatory responses are known to be induced by heat stress, which has been identified to maintain homeostasis through modulation at metabolome, transcriptome and microbiome levels. In these findings, heat stress condition can trigger alteration of immune system and cellular energy metabolism, which is shown as reduced metabolites, pathway enrichment and differential microbes. As results of this study did not include direct phenotypic data, we believe that additional validation is required in the future. In conclusion, high-temperature stress contributed to the reduction of metabolites, changes in gene expression patterns and composition of gut microbiota, which are thought to support dairy cows in withstanding high-temperature stress via modulating immune-related genes, and cellular energy metabolism to maintain homeostasis.

Although pork quality traits are important commercially, genome-wide association studies (GWASs) have not well considered Landrace and Yorkshire pigs worldwide. Landrace and Yorkshire pigs are important pork-providing breeds. Although quantitative trait loci of pigs are well-developed, significant genes in GWASs of pigs in Korea must be studied. Through a GWAS using the PLINK program, study of the significant genes in Korean pigs was performed. We conducted a GWAS and surveyed the gene ontology (GO) terms associated with the backfat thickness (BF) trait of these pigs. We included the breed information (Yorkshire and Landrace pigs) as a covariate. The significant genes after false discovery rate (＜0.01) correction were AFG1L, SCAI, RIMS1, and SPDEF. The major GO terms for the top 5% of genes were related to neuronal genes, cell morphogenesis and actin cytoskeleton organization. The neuronal genes were previously reported as being associated with backfat thickness. However, the genes in our results were novel, and they included ZNF280D, BAIAP2, LRTM2, GABRA5, PCDH15, HERC1, DTNBP1, SLIT2, TRAPPC9, NGFR, APBB2, RBPJ, and ABL2. These novel genes might have roles in important cellular and physiological functions related to BF accumulation. The genes related to cell morphogenesis were NOX4, MKLN1, ZNF280D, BAIAP2, DNAAF1, LRTM2, PCDH15, NGFR, RBPJ, MYH9, APBB2, DTNBP1, TRIM62, and SLIT2. The genes that belonged to actin cytoskeleton organization were MKLN1, BAIAP2, PCDH15, BCAS3, MYH9, DTNBP1, ABL2, ADD2, and SLIT2.