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The Japanese encephalitis virus (JEV) is one of the vector borne causes of encephalitis found in southeastern Asia. This positive single-stranded RNA virus is a member of the Flaviviridae family, which notably includes dengue, tick-borne, West Nile, Zika as well as yellow fever, and transmits to humans by infected mosquitos. The main site of interactions for antibodies against this virus is the envelope protein domain III (ED3). The present report investigates the time-dependent structural and conformational changes of JEV ED3 functional epitopes and escape mutants by computer simulations. The results indicate the presence of significant structural differences between the functional epitopes and the escape mutants. Mutation-induced structural/conformational instabilities of this type can decrease the antibody neutralization activity. Among the different escape mutants studied here, Ser40Lys/Asp41Arg appear to be most unstable, while Ser40Glu/Asp41Leu exhibit the lowest structural variations. The highest level of escape mutation observed in Ser40Lys is linked to the relatively higher values of root mean square deviation/fluctuation found in the molecular dynamics simulation of this protein. Secondary-structure deviations and depletion of H bonding are other contributing factors to the protein's increased instability. Overall, the proteins with residue 41 mutations are found to be structurally more ordered than those with residue 40 mutations. The detailed time-based structural assessment of the mutant epitopes described here may contribute to the development of novel vaccines and antiviral drugs necessary to defend against future outbreaks of JEV escape mutants.Background Preterm birth (PTB) is a major adverse pregnancy outcome and largely contributes to increasing neonatal and maternal mortality. Genetic and environmental factors may play an important role in the development of PTB. Numerous studies have shown that immune genes related to the immune system, such as IL-6, IL-10, and TNFα, are associated with the occurrence of PTB. Objective We examined genetic associations between IL-6 rs1800796, IL-10 rs1800872, and TNFα rs1800630 polymorphisms and PTB in Korean women. Methods In this study, 115 PTB patients and 147 controls were analyzed. The genotyping of three SNPs was performed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Results Our result showed that the rs1800872 polymorphism was significantly associated with the development of PTB in genotype frequency (odds ratio (OR) 1.71, 95% confidence interval (CI) 1.01-2.90, p = 0.046). We also found a significant association in an analysis of combined genotypes (rs1800796 CC, rs1800872 CA, and rs1800630 CA) (OR 7.43, 95% CI 2.06-26.84, p = 0.001). In a correlation analysis, rs1800630 A allele was significantly related with the increased birth weight (g) within PTB patients (p = 0.005). Conclusion Our results imply possible relationships between the rs1800796, rs1800872, and rs1800630 polymorphisms and the development of PTB.Background The apparent disconnection between biological complexity and both genome size (C-value) and gene number (G-value) is one of the long-standing biological puzzles. Gene-dense genomic sequences in prokaryotes or simple eukaryotes are highly constrained during selection, whereas gene-sparse genomic sequences in higher eukaryotes have low selection constraints. This review discusses the correlations of the C-value and G-value with genome architecture, polyploidy, repeatomes, introns, cell economy and phenomes. Discussion Eukaryotic chromosomes carry an assortment of various repeated DNA sequences (repeatomes). Expansion of copies of repeatomes together with polyploidization or whole-genome duplication (WGD) are major players in genome size (C-value) bloating, but genomes are equipped with counterbalancing systems such as diploidization, illegitimate recombination, and nonhomologous end joining (NHEJ) after double-strand breaks (DSBs). The lack of these efficient purging systems allowed the accumulation have been constructed. However, basic questions have not yet been fully resolved. Why have some species retained small genomes yet some closely related species have large genomes? Random genetic drift and mutational pressure might have affected for genome size in the limited population size during evolution; thus, genome size may be quasiadaptable rather than the best adaptive trait.Background Fertility is the most important economic trait in sows, as it is critical for profitability. Considerable phenotypic variation in litter size exists in Large White sows. However, relatively little is known about the underlying molecular and genetic bases. read more Objective An experiment was conducted to screen key genes that affect the fecundity of pigs during the luteal (L) and follicular phases (F) of the estrous cycle. Methods Eight sows (n = 4 for high fertility sows and n = 4 for low fertility sows) were sacrificed on day 14 (day 1 = first day of estrus) after estrus in the L phase. Another eight sows were slaughtered on day 20 of the estrous cycle in the F phase. Sixteen ovarian tissue samples were collected at the different sacrifice time points. Total RNA extracted was used to construct the library and then sequence on an Illumina HiSeq X10 system. Differentially expressed genes (DEGs) between high and low fertility in Large White sows were identified, and their potential biological functions were analyzed using bioinformatics analysis. Results In total, 457 DEGs (161 up-regulated and 296 down-regulated genes) were detected in the ovarian tissues of the high and low fertility groups in the L phase of the estrous cycle. Furthermore, 475 DEGs (253 up-regulated and 222 down-regulated genes) were identified in the F phase. Twenty-nine DEGs were common to both comparisons. Kyoto Encyclopedia of Genes and Genomes enrichment analysis showed that the DEGs were mainly associated with steroid biosynthesis, the Hippo signaling pathway, and lysosomes. Others, such as MSMO1, CYP27B1, and CTSB, were related to reproduction. Conclusion These results will contribute to a better understanding of the individual differences in fertility at the transcriptome level, which may provide useful information to explore new ways to improve fertility in pigs.
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