Project description:The overall transcriptome changes were discriminated by the radiation dose rather than the radiation type and manifested mainly by DNA damage response (DDR) genes. Transcription levels of major DDR genes were found to increase in a dose-dependent manner but were rarely affected by the radiation type.
Project description:Transcriptome analysis of MCF-7 cells exposed for 48 hours to various concentrations of xenoestrogen chemicals. Although biological effects of endocrine disrupting chemicals (EDCs) are often observed at unexpectedly low doses with occasional non-monotonic dose-response characteristics, transcriptome-wide profiles of sensitivities or dose-dependent behaviors of the EDC responsive genes have remained unexplored. Here, we describe expressome analysis for the comprehensive examination of dose-dependent gene responses and its applications to characterize estrogen responsive genes in MCF-7 cells. Transcriptomes of MCF-7 cells exposed to varying concentrations of representative natural and xenobiotic estrogens for 48 hours were determined by microarray and used for computational calculation of interpolated approximations of estimated transcriptomes for 300 doses uniformly distributed in log space for each chemical. The entire collection of these estimated transcriptomes, designated as the expressome, has provided unique opportunities to profile chemical-specific distributions of ligand sensitivities for large numbers of estrogen responsive genes, revealing that at low concentrations estrogens generally tended to suppress rather than to activate transcription. Gene ontology analysis demonstrated distinct functional enrichment between high- and low-sensitivity estrogen responsive genes, supporting the notion that a single EDC chemical can cause qualitatively distinct biological responses at different doses. Expressomal heatmap visualization of dose-dependent induction of Bisphenol A-inducible genes showed a weak gene activation peak at a very low concentration range (ca. 0.1 nM) in addition to the main, strong gene activation peak at and above 100 nM. Thus, expressome analysis is a powerful approach to understanding the EDC dose-dependent dynamic changes in gene expression at the transcriptomal level, providing important information on the overall profiles of ligand sensitivities and non-monotonic responses. Subconfluent density of MCF-7 cells were exposed to various concentrations of xenoestrogen chemicals for 48 hours and then subjected to transcriptomal analysis using Affymetrix U133 version 2 plus microarray.
Project description:Transcriptome analysis of MCF-7 cells exposed for 48 hours to various concentrations of xenoestrogen chemicals. Although biological effects of endocrine disrupting chemicals (EDCs) are often observed at unexpectedly low doses with occasional non-monotonic dose-response characteristics, transcriptome-wide profiles of sensitivities or dose-dependent behaviors of the EDC responsive genes have remained unexplored. Here, we describe expressome analysis for the comprehensive examination of dose-dependent gene responses and its applications to characterize estrogen responsive genes in MCF-7 cells. Transcriptomes of MCF-7 cells exposed to varying concentrations of representative natural and xenobiotic estrogens for 48 hours were determined by microarray and used for computational calculation of interpolated approximations of estimated transcriptomes for 300 doses uniformly distributed in log space for each chemical. The entire collection of these estimated transcriptomes, designated as the expressome, has provided unique opportunities to profile chemical-specific distributions of ligand sensitivities for large numbers of estrogen responsive genes, revealing that at low concentrations estrogens generally tended to suppress rather than to activate transcription. Gene ontology analysis demonstrated distinct functional enrichment between high- and low-sensitivity estrogen responsive genes, supporting the notion that a single EDC chemical can cause qualitatively distinct biological responses at different doses. Expressomal heatmap visualization of dose-dependent induction of Bisphenol A-inducible genes showed a weak gene activation peak at a very low concentration range (ca. 0.1 nM) in addition to the main, strong gene activation peak at and above 100 nM. Thus, expressome analysis is a powerful approach to understanding the EDC dose-dependent dynamic changes in gene expression at the transcriptomal level, providing important information on the overall profiles of ligand sensitivities and non-monotonic responses.
Project description:Human endogenous retroviruses (HERVs/MaLRs) are distributed among our 24 chromosomes and their long terminal repeats (LTRs) constitute putative regulatory sequences. HERVs have received much attention for their implication in cancer, autoimmunity and placental development. Herein, we used a recently described high-density microarray allowing the exploration of the whole HERVs/MaLRs transcriptome including 353,994 HERVs/MaLRs loci and also 1559 genes related to immunity. We obtained a first view of the HERV transcriptome in peripheral blood mononuclear cells (PBMCs) by using a composite panel of unstimulated, low dose and high dose LPS-stimulated PBMCs from healthy volunteers to mimic inflammatory response or monocyte anergy. About 5.6% of the HERVs/MaLRs repertoire is transcribed in PBMCs. Roughly, one tenth [5.7%-13.1%] of LTRs present a constitutive promoter or polyA function and a quarter [19.5%-27.6%] of LTRs may shift from silent to active LTRs, LTRs being broadly subjected to operational determinism. We provide evidence that some HERVs/MaLRs and genes share similar control of regulation upon LPS stimulation conditions, e.g. presenting a low dose LPS-dependent “tolerizable” profile which can be reversed by INF-g stimulation. Similarly to tissue tropism observed in solid tumors, stimulus-dependent response confirm that the expression of HERVs is tightly regulated in PBMCs. Altogether, these observations allow to integrate 62 HERVs/MaLRs and 26 genes in 11 canonical pathways. We highlight HERVs close to OAS2/3 and IFI44/IFI44L genes. HERV incorporation at the crossroads of immune response pathways, paves the way for further functional studies and analyses of HERV transcriptome in altered immune responses in vivo such as in sepsis.