Dataset Information

Transcriptomic analysis identifies gene networks regulated by estrogen receptor ? (ER?) and ER? that control distinct effects of different botanical estrogens.

ABSTRACT: The estrogen receptors (ERs) ER? and ER? mediate the actions of endogenous estrogens as well as those of botanical estrogens (BEs) present in plants. BEs are ingested in the diet and also widely consumed by postmenopausal women as dietary supplements, often as a substitute for the loss of endogenous estrogens at menopause. However, their activities and efficacies, and similarities and differences in gene expression programs with respect to endogenous estrogens such as estradiol (E2) are not fully understood. Because gene expression patterns underlie and control the broad physiological effects of estrogens, we have investigated and compared the gene networks that are regulated by different BEs and by E2. Our aim was to determine if the soy and licorice BEs control similar or different gene expression programs and to compare their gene regulations with that of E2. Gene expression was examined by RNA-Seq in human breast cancer (MCF7) cells treated with control vehicle, BE or E2. These cells contained three different complements of ERs, ER? only, ER?+ER?, or ER? only, reflecting the different ratios of these two receptors in different human breast cancers and in different estrogen target cells. Using principal component, hierarchical clustering, and gene ontology and interactome analyses, we found that BEs regulated many of the same genes as did E2. The genes regulated by each BE, however, were somewhat different from one another, with some genes being regulated uniquely by each compound. The overlap with E2 in regulated genes was greatest for the soy isoflavones genistein and S-equol, while the greatest difference from E2 in gene expression pattern was observed for the licorice root BE liquiritigenin. The gene expression pattern of each ligand depended greatly on the cell background of ERs present. Despite similarities in gene expression pattern with E2, the BEs were generally less stimulatory of genes promoting proliferation and were more pro-apoptotic in their gene regulations than E2. The distinctive patterns of gene regulation by the individual BEs and E2 may underlie differences in the activities of these soy and licorice-derived BEs in estrogen target cells containing different levels of the two ERs.

SUBMITTER: Gong P

PROVIDER: S-EPMC4193135 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Transcriptomic analysis identifies gene networks regulated by estrogen receptor α (ERα) and ERβ that control distinct effects of different botanical estrogens.

Gong Ping P Madak-Erdogan Zeynep Z Li Jilong J Cheng Jianlin J Greenlief C Michael CM Helferich William W Katzenellenbogen John A JA Katzenellenbogen Benita S BS

Nuclear receptor signaling 20140912

The estrogen receptors (ERs) ERα and ERβ mediate the actions of endogenous estrogens as well as those of botanical estrogens (BEs) present in plants. BEs are ingested in the diet and also widely consumed by postmenopausal women as dietary supplements, often as a substitute for the loss of endogenous estrogens at menopause. However, their activities and efficacies, and similarities and differences in gene expression programs with respect to endogenous estrogens such as estradiol (E2) are not full ...[more]

PMID: 25363786

Similar Datasets

Project description:The two estrogen receptors ERα and ERβ are nuclear receptors that bind estrogen (E2) and function as ligand-inducible transcription factors. They are homologues and can form dimers with each other and bind to the same estrogen-response element motifs in the DNA. ERα drives breast cancer growth whereas ERβ has been reported to be anti-proliferative. However, they are rarely expressed in the same cells, and it is not fully investigated to which extent their functions are different because of inherent differences or because of different cellular context. To dissect their similarities and differences, we here generated a novel estrogen-dependent cell model where ERα homodimers can be directly compared to ERβ homodimers within the identical cellular context. By using CRISPR-cas9 to delete ERα in breast cancer MCF7 cells with Tet-Off-inducible ERβ expression, we generated MCF7 cells that express ERβ but not ERα. MCF7 (ERβ only) cells exhibited regulation of estrogen-responsive targets in a ligand-dependent manner. We demonstrated that either ER was required for MCF7 proliferation, but while E2 increased proliferation via ERα, it reduced proliferation through a G2/M arrest via ERβ. The two ERs also impacted migration differently. In absence of ligand, ERβ increased migration, but upon E2 treatment, ERβ reduced migration. E2 via ERα, on the other hand, had no significant impact on migration. RNA sequencing revealed that E2 regulated a transcriptome of around 800 genes via each receptor, but over half were specific for either ERα or ERβ (417 and 503 genes, respectively). Functional gene ontology enrichment analysis reinforced that E2 regulated cell proliferation in opposite directions depending on the ER, and that ERβ specifically impacted extracellular matrix organization. We corroborated that ERβ bound to cis-regulatory chromatin of its unique proposed migration-related direct targets ANXA9 and TFAP2C. In conclusion, we demonstrate that within the same cellular context, the two ERs regulate cell proliferation in the opposite manner, impact migration differently, and each receptor also regulates a distinct set of target genes in response to E2. The developed cell model provides a novel and valuable resource to further complement the mechanistic understanding of the two different ER isoforms.

Project description:BackgroundChondroclasts and osteoclasts have been previously identified as the cells capable of resorbing mineralized cartilage and bone matrices, respectively. While both cell types appear morphologically similar, contain comparable ultrastructural features, and express tartrate-resistant acid phosphatase (TRAP), however, no information is available about the genomic similarities and differences between osteoclasts and chondroclasts.MethodsTo address this question, we laser captured homogeneous populations of TRAP-positive cells that interact with bone (osteoclasts) and TRAP-positive cells that interact with mineralized cartilage (chondroclasts) on the same plane from murine femoral fracture callus sections. We then performed a global transcriptome profiling of chondroclasts and osteoclasts by utilizing a mouse genome Agilent GE 4X44K V2 microarray platform. Multiple computational approaches and interaction networks were used to analyze the transcriptomic landscape of osteoclasts and chondroclasts.ResultsOur systematic and comprehensive analyses using hierarchical clustering and principal component analysis (PCA) demonstrate that chondroclasts and osteoclasts are transcriptionally distinct cell populations and exhibit discrete transcriptomic signatures as revealed by multivariate analysis involving scatter plot, volcano plot, and heatmap analysis. TaqMan qPCR was used to validate the microarray results. Intriguingly, the functional enrichment and integrated network analyses revealed distinct Gene Ontology terms and molecular pathways specific to chondroclasts and osteoclasts and further suggest that subsets of metabolic genes were specific to chondroclasts. Protein-protein interaction (PPI) network analysis showed an abundance of structured networks of metabolic pathways, ATP synthesis, and proteasome pathways in chondroclasts. The regulatory network analysis using transcription factor-target gene network predicted a pool of genes including ETV6, SIRT1, and ATF1 as chondroclast-specific gene signature.ConclusionsOur study provides an important genetic resource for further exploration of chondroclast function in vivo. To our knowledge, this is the first demonstration of genetic landscape of osteoclasts from chondroclasts identifying unique molecular signatures, functional clustering, and interaction network.

Dataset Information

Transcriptomic analysis identifies gene networks regulated by estrogen receptor ? (ER?) and ER? that control distinct effects of different botanical estrogens.

Publications

Transcriptomic analysis identifies gene networks regulated by estrogen receptor α (ERα) and ERβ that control distinct effects of different botanical estrogens.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets