Sex biases in the genome-wide distribution of DNA methylation and gene expression levels are some of the manifestations of sexual dimorphism in mammals. To advance our understanding of the mechanisms that contribute to sex biases in DNA methylation and gene expression, we conducted whole genome bisulfite sequencing (WGBS) as well as RNA-seq on liver samples from mice with different combinations of sex phenotype and sex-chromosome complement. We compared groups of animals with different sex phenotypes, but the same genetic sexes, and vice versa, same sex phenotypes, but different sex-chromosome complements. We also compared sex-biased DNA methylation in mouse and human livers. Our data show that sex phenotype, X-chromosome dosage, and the presence of Y chromosome shape the differences in DNA methylation between males and females. We also demonstrate that sex bias in autosomal methylation is associated with sex bias in gene expression, whereas X-chromosome dosage-dependent methylation differences are not, as expected for a dosage-compensation mechanism. Furthermore, we find partial conservation between the repertoires of mouse and human genes that are associated with sex-biased methylation, an indication that gene function is likely to be an important factor in this phenomenon.
Bisphenol A (BPA) is a chemical widely used both in plastics production as a food and beverage container and in thermal papers as a color developer. Dietary consumption is the main route of human exposure to BPA, but dermal absorption through handling different papers might be underestimated or ignored. In this study, BPA in different paper products, including different types of papers, receipts and Chinese currencies, were investigated. BPA was detected in receipts (n = 87) and Chinese currencies (n = 46) with concentrations of 0.17-2.675 × 10(4) μg per g paper and 0.09-288.55 μg per g paper, respectively. Except for parchment papers (n = 3), copy papers (n = 3) and food contact papers (n = 3), BPA was measured in all of the other paper products, with levels of 0.01-6.67 μg per g paper. BPA transferred from thermal papers to common papers increased with the increasing contact pressure. Compared with that in water, the migration speed of BPA was doubled in the synthetic sweat. Washing hands could reduce BPA dermal exposure, and washing hands with lotion was the most efficient way. However, about 19-47% of BPA was still found on hands after different washing methods. Dermal absorption via handling of receipts and papers was estimated to be 36.45 ng per day for the general population and 1.54 × 10(-3) to 248.73 μg per day for a cashier. These values are below the maximum doses recommended by the U.S. Environmental Protection Agency and the European Food Safety Authority. However, due to its uncertain adverse effects on human beings, long-term BPA exposure through dermal absorption should be paid more attention, particularly for some occupational populations.
Background: In systems biology, the dynamics of biological networks are often modeled with ordinary differential equations (ODEs) that encode interacting components in the systems, resulting in highly complex models. In contrast, the amount of experimentally available data is almost always limited, and insufficient to constrain the parameters. In this situation, parameter estimation is a very challenging problem. To address this challenge, two intuitive approaches are to perform experimental design to generate more data, and to perform model reduction to simplify the model. Experimental design and model reduction have been traditionally viewed as two distinct areas, and an extensive literature and excellent reviews exist on each of the two areas. Intriguingly, however, the intrinsic connections between the two areas have not been recognized. Results: Experimental design and model reduction are deeply related, and can be considered as one unified framework. There are two recent methods that can tackle both areas, one based on model manifold and the other based on profile likelihood. We use a simple sum-of-two-exponentials example to discuss the concepts and algorithmic details of both methods, and provide Matlab-based code and implementation which are useful resources for the dissemination and adoption of experimental design and model reduction in the biology community. Conclusions: From a geometric perspective, we consider the experimental data as a point in a high-dimensional data space and the mathematical model as a manifold living in this space. Parameter estimation can be viewed as a projection of the data point onto the manifold. By examining the singularity around the projected point on the manifold, we can perform both experimental design and model reduction. Experimental design identifies new experiments that expand the manifold and remove the singularity, whereas model reduction identifies the nearest boundary, which is the nearest singularity that suggests an appropriate form of a reduced model. This geometric interpretation represents one step toward the convergence of experimental design and model reduction as a unified framework.
Sexual dimorphism in gene regulation, including DNA methylation, is the main driver of sexual dimorphism in phenotypes. However, the questions of how and when sex shapes DNA methylation remain unresolved. Recently, using mice with different combinations of genetic and phenotypic sex, we identified sex-associated differentially methylated regions (sDMRs) that depended on the sex phenotype. Focusing on a panel of validated sex-phenotype dependent male- and female-biased sDMRs, we tested the developmental dynamics of sex bias in liver methylation and the impacts of mutations in the androgen receptor, estrogen receptor alpha, or the transcriptional repressor Bcl6 gene. True hermaphrodites that carry both unilateral ovaries and contralateral testes were also tested. Our data show that sex bias in methylation either coincides with or follows sex bias in the expression of sDMR-proximal genes, suggesting that sex bias in gene expression may be required for demethylation at certain sDMRs. Global ablation of AR, ESR1, or a liver-specific loss of BCL6, all alter sDMR methylation, whereas presence of both an ovary and a testis delays the establishment of male-type methylation levels in hermaphrodites. Moreover, the Bcl6-LKO shows dissociation between expression and methylation, suggesting a distinct role of BCL6 in demethylation of intragenic sDMRs.
1Proteases are pleiotropic, promiscuous enzymes that degrade proteins and peptides, which drive 2 important processes in health and disease. The ability to quantify the activity of protease signatures by 3 sampling with Massively Multiplexed Activity (MMA) libraries will provide unparalleled biological 4 information. Under such a framework, a designed library of peptide substrates is exposed to a cocktail 5 of proteases, the cleavage velocity of each substrate is measured, and individual protease activity levels 6 are inferred from the data. Previous studies have developed individual protease sensors, but 7 multiplexed substrate cleavage data becomes difficult to interpret as the number of cross-cutting 8 proteases increases. Computational methods for parsing this data to estimate individual protease 9 activities primarily use an extensive compendium of all possible protease-substrate combinations, 10 which require impractical amounts of training data when scaling up to MMA libraries. Here we 11 provide a computational method for estimating protease activities efficiently by reducing the number 12 of substrates and clustering proteases with similar cleavage activities into families. This method is 13 scalable and will enable the future use of MMA libraries with applications spanning therapeutic and 14 diagnostic biotechnology.15 16
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