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.

			Action	DRS
	SRR9002460.fastq.gz	Fastqsanger.gz
	SRR9002470.fastq.gz	Fastqsanger.gz
	SRR9002461.fastq.gz	Fastqsanger.gz
	SRR9002471.fastq.gz	Fastqsanger.gz
	SRR9002462.fastq.gz	Fastqsanger.gz

Dataset Information

SHY2-dose dependent transcriptome analysis

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets