Effects of endocrine disruptors on imprinted gene expression in the mouse embryo
Abstract
Environmental endocrine disruptors (EDs) are synthetic chemicals that resemble natural hormones and are known to cause epigenetic perturbations. EDs have profound effects on development and fertility. Imprinted genes had been identified as susceptible loci to environmental insults by EDs because they are functionally haploid, and because the imprints undergo epigenetic resetting between generations. To screen for possible epigenetic perturbations caused by EDs at imprinted loci, we treated pregnant mice daily between 8.5 and 12.5 days post coitum (dpc) with di-(2-ethylhexyl)-phthalate (DEHP), bisphenol A (BPA), vinclozolin (VZ), or control oil vehicle. After isolating RNA from the placenta, yolk sac, amnion, head, body, heart, liver, lung, stomach, and intestines of 13.5 dpc embryos we measured the allele-specific expression of 38 imprinted transcripts using multiplex single nucleotide primer extension (SNuPE) assays. In this representative data set we identified only a small number of transcripts that exhibited a substantial relaxation of imprinted expression with statistical significance: Slc22a18 with 10% relaxation in the embryo after BPA treatment; Rtl1as with 11 and 16% relaxation in the lung and placenta, respectively after BPA treatment; and Rtl1 with 12% relaxation in the yolk sac after DEHP treatment. Additionally, the standard deviation of allele-specificity increased in various organs after ED treatment for several transcripts including Igf2r, Rasgrf1, Usp29,…
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.