scholarly journals EREFinder: Genome-wide detection of estrogen response elements

2018 ◽  
Author(s):  
Andrew P. Anderson ◽  
Adam G. Jones
Keyword(s):  
Dna Sequences ◽  
Target Genes ◽  
Response Elements ◽  
Data Manipulation ◽  
Link Type ◽  
Estrogen Response ◽  
Genome Wide ◽  
Wide Range ◽  
Estrogen Response Elements ◽  
Excellent Tool

AbstractMotivationEstrogen response elements (EREs) are specific DNA sequences to which ligand-bound estrogen receptors (ERs) physically bind, allowing them to act as transcription factors for target genes. Locating EREs and ER responsive regions is therefore a potentially important component of the study of estrogen-regulated pathways.ResultsWe tested and demonstrated the ability of EREFinder, a novel algorithm we developed, to locate regions of ER-binding across the human genome and show that these regions designated by the program occur more frequently near estrogen responsive genes. EREFinder can handle large input files, has settings to allow for broad and narrow searches, and provides the full output to allow for greater data manipulation. These features facilitate a wide range of hypothesis testing for researchers and make EREFinder an excellent tool to aid in estrogen-related research.Availability and ImplementationSource code and binaries freely available for download at https://github.com/JonesLabIdaho/EREfinder, implemented in C++ and supported on Linux and MS [email protected] MaterialsR scripts can be found at https://github.com/JonesLabIdaho/EREfinder

scholarly journals Amplification of Distant Estrogen Response Elements Deregulates Target Genes Associated with Tamoxifen Resistance in Breast Cancer

Cancer Cell ◽  
2013 ◽  
Vol 24 (2) ◽  
pp. 197-212 ◽  
Author(s):  
Pei-Yin Hsu ◽  
Hang-Kai Hsu ◽  
Xun Lan ◽  
Liran Juan ◽  
Pearlly S. Yan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Target Genes ◽  
Tamoxifen Resistance ◽  
Response Elements ◽  
Estrogen Response ◽  
Estrogen Response Elements

scholarly journals Genome-Wide Identification of High-Affinity Estrogen Response Elements in Human and Mouse

2004 ◽  
Vol 18 (6) ◽  
pp. 1411-1427 ◽  
Author(s):  
Véronique Bourdeau ◽  
Julie Deschênes ◽  
Raphaël Métivier ◽  
Yoshihiko Nagai ◽  
Denis Nguyen ◽  
...  
Keyword(s):  
Response Elements ◽  
High Affinity ◽  
Estrogen Response ◽  
Genome Wide ◽  
Estrogen Response Elements ◽  
Human And Mouse

scholarly journals Two functional estrogen response elements are located upstream of the major chicken vitellogenin gene.

1988 ◽  
Vol 8 (3) ◽  
pp. 1123-1131 ◽  
Author(s):  
J B Burch ◽  
M I Evans ◽  
T M Friedman ◽  
P J O'Malley
Keyword(s):  
Essential Feature ◽  
Coding Region ◽  
Transient Expression Assay ◽  
Specific Expression ◽  
Response Elements ◽  
Estrogen Response ◽  
Pair Sequence ◽  
Estrogen Response Elements ◽  
Vitellogenin Gene ◽  
Simplex Virus

We used a transient-expression assay to identify two estrogen response elements (EREs) associated with the major chicken vitellogenin gene (VTGII). Each element was characterized by its ability to confer estrogen responsiveness when cloned in either orientation next to a chimeric reporter gene consisting of the herpes simplex virus thymidine kinase promoter and the chloramphenicol acetyl transferase-coding region. Deletion analyses indicated that sequences necessary for the distal ERE resided within the region from -626 to -613 (nucleotide positions relative to the VTGII start site) whereas those necessary for the proximal ERE were within the region from -358 to -335. These distal and proximal elements contain, respectively, a perfect copy and an imperfect copy of the 13-base-pair sequence that is an essential feature of the EREs associated with two frog vitellogenin genes. These chicken VTGII EREs mapped near regions that were restructured at the chromatin level when the endogenous VTGII gene was expressed in the liver in response to estradiol. These data suggest a model for the tissue-specific expression of this estrogen-responsive gene.

scholarly journals HCR-FlowFISH: A flexible CRISPR screening method to identify cis-regulatory elements and their target genes

2020 ◽  
Author(s):  
SK Reilly ◽  
SJ Gosai ◽  
A Gutierrez ◽  
JC Ulirsch ◽  
M Kanai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Screening Method ◽  
Cell Types ◽  
Regulatory Elements ◽  
Hybridization Chain Reaction ◽  
Genome Wide ◽  
Wide Range ◽  
Causal Variants ◽  
Endogenous Loci

AbstractCRISPR screens for cis-regulatory elements (CREs) have shown unprecedented power to endogenously characterize the non-coding genome. To characterize CREs we developed HCR-FlowFISH (Hybridization Chain Reaction Fluorescent In-Situ Hybridization coupled with Flow Cytometry), which directly quantifies native transcripts within their endogenous loci following CRISPR perturbations of regulatory elements, eliminating the need for restrictive phenotypic assays such as growth or transcript-tagging. HCR-FlowFISH accurately quantifies gene expression across a wide range of transcript levels and cell types. We also developed CASA (CRISPR Activity Screen Analysis), a hierarchical Bayesian model to identify and quantify CRE activity. Using >270,000 perturbations, we identified CREs for GATA1, HDAC6, ERP29, LMO2, MEF2C, CD164, NMU, FEN1 and the FADS gene cluster. Our methods detect subtle gene expression changes and identify CREs regulating multiple genes, sometimes at different magnitudes and directions. We demonstrate the power of HCR-FlowFISH to parse genome-wide association signals by nominating causal variants and target genes.

scholarly journals Human URAT1/SLC22A12 gene promoter is regulated by 27-hydroxycholesterol through estrogen response elements

2019 ◽  
Author(s):  
Masaya Matsubayashi ◽  
Yoshihiko M. Sakaguchi ◽  
Yoshiki Sahara ◽  
Hitoki Nanaura ◽  
Sotaro Kikuchi ◽  
...  
Keyword(s):  
Uric Acid ◽  
Serum Uric Acid ◽  
Cholesterol Metabolism ◽  
Gene Promoter ◽  
Human Kidney ◽  
Response Elements ◽  
Estrogen Response ◽  
Uric Acid Transporters ◽  
Estrogen Response Elements ◽  
Phylogenic Relationship

AbstractElevated levels of uric acid, a metabolite of purine in humans, is related to various diseases, such as gout, atherosclerosis and renal dysfunction. The excretion and reabsorption of uric acid to/from urine is tightly regulated by uric acid transporters. The amino acid sequences of uric acid reabsorption transporters, URAT1/SLC22A12, OAT4/SLC22A11, and OAT10/SLC22A13, share closer phylogenic relationship, whereas the gene promoter sequences are distant phylogenic relationship. Through the single-cell RNA-sequencing analysis of an adult human kidney, we found that only a small number of cells express these transporters, despite their role in the regulation of serum uric acid levels. Transcriptional motif analysis on these transporter genes, revealed that the URAT1/SLC22A12 gene promoter displayed the most conserved estrogen response elements (EREs) among the three transporters. The endogenous selective estrogen receptor modulator (SERM) 27-hydroxycholesterol (27HC) had positive effects on the transcriptional activity of URAT1/SLC22A12. We also found that 27HC increased the protein and gene expression of URAT1/SLC22A12 in mouse kidneys and human kidney organoids, respectively. These results strongly suggest the role of 27HC for URAT1/SLC22A12 expression in renal proximal tubules and upregulation of serum uric acid levels and also show the relationship between cholesterol metabolism and serum uric acid regulation.Significance StatementThe elevated levels of serum uric acid cause various diseases, and the excretion/reabsorption of uric acid to/from urine is tightly regulated by the uric acid transporters. We found that despite the role in serum uric acid regulation, only a small number of cells express URAT1/SLC22A12. We also found that URAT1/SLC22A12 gene promoter region has effective estrogen response elements, and endogenous selective estrogen receptor (ER) modulator 27-hydroxycholesterol (27HC) increased URAT1/SLC22A12 expression in the mice kidneys and human kidney organoids. These suggest that 27HC increases URAT1/SLC22A12 expression and upregulate serum uric acid levels. Since 27HC connects cholesterol metabolism, our study indicates the important link between cholesterol metabolism and serum uric acid regulation, and also provides a novel therapeutic approach to hyperuricemia.

scholarly journals Qtlizer: comprehensive QTL annotation of GWAS results

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Matthias Munz ◽  
Inken Wohlers ◽  
Eric Simon ◽  
Tobias Reinberger ◽  
Hauke Busch ◽  
...  
Keyword(s):  
Association Studies ◽  
Housekeeping Genes ◽  
R Package ◽  
Genome Wide Association Studies ◽  
Protein Abundance ◽  
Base Pairs ◽  
Link Type ◽  
Genome Wide ◽  
Wide Range ◽  
Distance Limit

AbstractExploration of genetic variant-to-gene relationships by quantitative trait loci such as expression QTLs is a frequently used tool in genome-wide association studies. However, the wide range of public QTL databases and the lack of batch annotation features complicate a comprehensive annotation of GWAS results. In this work, we introduce the tool “Qtlizer” for annotating lists of variants in human with associated changes in gene expression and protein abundance using an integrated database of published QTLs. Features include incorporation of variants in linkage disequilibrium and reverse search by gene names. Analyzing the database for base pair distances between best significant eQTLs and their affected genes suggests that the commonly used cis-distance limit of 1,000,000 base pairs might be too restrictive, implicating a substantial amount of wrongly and yet undetected eQTLs. We also ranked genes with respect to the maximum number of tissue-specific eQTL studies in which a most significant eQTL signal was consistent. For the top 100 genes we observed the strongest enrichment with housekeeping genes (P = 2 × 10–6) and with the 10% highest expressed genes (P = 0.005) after grouping eQTLs by r2 > 0.95, underlining the relevance of LD information in eQTL analyses. Qtlizer can be accessed via https://genehopper.de/qtlizer or by using the respective Bioconductor R-package (https://doi.org/10.18129/B9.bioc.Qtlizer).

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