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Background: Comprehensively understanding the dynamics of biological systems is among the biggest current challenges in biology and medicine. To acquire this understanding, researchers have measured the time-series expression profiles of cell lines of various organisms. Biological technologies have also drastically improved, providing a huge amount of information with support from bioinformatics and systems biology. However, the transitions between the activation and inactivation of gene regulations, at the temporal resolution of single time points, are difficult to extract from time-course gene expression profiles. Results: Our proposed method reports the activation period of each gene regulation from gene expression profiles and a gene regulatory network. The correctness and effectiveness of the method were validated by analyzing the diauxic shift from glucose to lactose in Escherichia coli. The method completely detected the three periods of the shift; 1) consumption of glucose as nutrient source, 2) the period of seeking another nutrient source and 3) consumption of lactose as nutrient source. We then applied the method to mouse adipocyte differentiation data. Cell differentiation into adipocytes is known to involve two waves of the gene regulation cascade, and sub-waves are predicted. From the gene expression profiles of the cell differentiation process from ES to adipose cells (62 time points), our method acquired four periods; three periods covering the two known waves of the cascade, and a final period of gene regulations when the differentiation to adipocytes was completed. Conclusions: Our proposed method identifies the transitions of gene regulations from time-series gene expression profiles. Dynamic analyses are essential for deep understanding of biological systems and for identifying the causes of the onset of diseases such as diabetes and osteoporosis. The proposed method can greatly contribute to the progress of biology and medicine. [ABSTRACT FROM AUTHOR]

Background: Epigenetic factors associated with the development of autoimmune diseases are unclear. Monozygotic twin pairs discordant for positive antithyroglobulin autoantibodies (TgAb) are useful to examine the epigenetic factors because of their identical genetic background. This study aimed to clarify the discordant epigenetic differences affecting the development of TgAb. Methods: Subjects were selected from 257 Japanese monozygotic twins, recruited from the registry established by the Center for Twin Research at Osaka University. TgAb positive concordant (PC) pairs were 5.7% (four pairs) and 9.6% (18 pairs) of male and female pairs, respectively. TgAb discordant (DC) pairs were 11.4% (eight pairs) and 8.0% (15 pairs) of male and female pairs, respectively. TgAb negative concordant (NC) pairs were 78.6% (55 pairs) of male pairs and 74.3% (139 pairs) of female pairs. To perform stricter grouping, the cut-off value for positive TgAb was set to 50.0 IU/mL (TgAb negative: <28.0 IU/mL; TgAb positive: ≥50.0 IU/mL; TgAb borderline: ≥28.0 IU/mL and <50.0 IU/mL). Nineteen discordant (6 male and 13 female pairs) and 185 concordant pairs (48 male and 137 female pairs) for TgAb positivity were finally examined. DNA methylation levels of genomic DNA were evaluated using the Infinium HumanMethylation450 BeadChip Kit. Gene polymorphisms were also genotyped using the Omni5-4 BeadChip Kit to clarify genetic background specific for discordant twins. Results: No CpG sites were found with significant within-pair differences of methylation levels in TgAb DC pairs after correction for multiple comparisons. However, 155 polymorphisms specific for TgAb DC pairs were significantly different in genotype frequencies from those of concordant pairs, and none of them were located on the HLA region of chromosome 6. In TgAb DC pairs with some specific genotypes of these polymorphisms, four CpG sites were observed exhibiting significant within-pair differences in each DC pair, even after correction for multiple comparisons. Conclusions: This study found that the genetic background specific for TgAb DC twins who are susceptible to epigenetic changes are different from that specific for TgAb PC twins, and it clarified the genotype-based epigenetic differences in TgAb DC monozygotic twins. [ABSTRACT FROM AUTHOR]

Background/objectives: The dynamic interaction between genomic DNA, epigenetic modifications, and phenotypic traits was examined in identical twins. Environmental perturbations can induce epigenetic changes in DNA methylation, influencing gene expression and phenotypes. Although DNA methylation mediates gene-environment correlations, the quantitative effects of external factors on DNA methylation remain underexplored. This study aimed to quantify these effects using a novel approach., Methods: A cohort study was conducted on healthy monozygotic twins to evaluate the influence of environmental stimuli on DNA methylation. We developed the Environmental Factor Index (EFI) to identify methylation sites showing statistically significant changes in response to environmental stimuli. We analyzed the identified sites for associations with disorders, DNA methylation markers, and CpG islands., Results: The EFI identified methylation sites that exhibited significant associations with genes linked to various disorders, particularly cancer. These sites were overrepresented on CpG islands compared to other genomic features, highlighting their regulatory importance., Conclusions: The EFI is a valuable tool for understanding the molecular mechanisms underlying disease pathogenesis. It provides insights into the development of preventive and therapeutic strategies and offers a new perspective on the role of environmental factors in epigenetic regulation.