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GRO-seq on MCF7 cells induced with sgRNA vectors targeting CTCF binding elements

ABSTRACT: GRO-seq on MCF7 cells induced with sgRNA vectors targeting CTCF binding elements

PROVIDER: PRJNA512524 | ENA |

REPOSITORIES: ENA

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GRO-seq on MCF7 cells induced with sgRNA vectors targeting CTCF binding elements

Project description:We performed a CRISPR-based functional genetic screen targeting CTCF binding elements (CBEs) located in the vicinity of ERα-bound enhancers. The screen identified four functional CBEs whose targeting resulted in a marked negative effect on the proliferation of MCF-7 cells (ERα-positive cells) but no significant effect on MDA-MB-231 (ERα-negative cells) cells. Here, we carried out GRO-seq analysis on MCF-7 cells induced with an sgRNA vector targeting one of the hits detected by the screen: sgRNA_1118, as well as non-targeting sgRNA and sg1830 as control.

2019-11-01 | GSE124572 | GEO

RNA-Seq and GRO-seq on MCF7 cells induced with sgRNA vectors targeting CTCF binding elements

Project description:RNA-Seq and GRO-seq on MCF7 cells induced with sgRNA vectors targeting CTCF binding elements

| PRJNA512518 | ENA

RNA-seq on MCF7 cells induced with sgRNA vectors targeting CTCF binding elements

Project description:We performed a CRISPR-based functional genetic screen targeting CTCF binding elements (CBEs) located in the vicinity of ERα-bound enhancers. The screen identified four functional CBEs whose targeting resulted in a marked negative effect on the proliferation of MCF-7 cells (ERα-positive cells) but no significant effect on MDA-MB-231 (ERα-negative cells) cells. We then carried out RNA-seq analysis on MCF-7 cells induced with sgRNA vectors targeting these four CBEs: sgRNA_1118, sgRNA_1659, sgRNA_680 and sgRNA_810, as well as non-targeting sgRNA as control.

2019-11-01 | GSE124573 | GEO

RNA-seq on MCF7 cells induced with sgRNA vectors targeting CTCF binding elements

Project description:RNA-seq on MCF7 cells induced with sgRNA vectors targeting CTCF binding elements

| PRJNA512525 | ENA

GRO-seq analysis of MCF7 cells

Project description:We used GRO-seq to examine RNA transcription rates in MCF7 cells.

2017-06-13 | GSE96718 | GEO

RNA-Seq and GRO-seq on MCF7 cells induced with sgRNA vectors targeting CTCF binding elements

Project description:This SuperSeries is composed of the SubSeries listed below.

2019-11-01 | GSE124575 | GEO

GRO-seq from HCT116, MCF7 and SJSA cell lines treated with DMSO and Nutlin

Project description:To identify loci with transcriptionally engaged RNA polymerase, we performed GRO-seq analysis of colorectal carcinoma cell line HCT116, breast carcinoma line MCF7, and osteosarcoma line SJSA treated with MDM2 inhibitor Nutlin.

2017-08-22 | GSE86165 | GEO

GRO-seq on MCF7 and MDA-MB-231 breast cancer cells

Project description:GRO-seq on MCF7 and MDA-MB-231 breast cancer cells

| PRJNA578047 | ENA

Identification of active transcriptional regulatory elements with GRO-seq

Project description:Transcriptional regulatory elements (TREs), including enhancers and promoters, determine the transcription levels of associated genes. We have recently shown that global run-on and sequencing (GRO-seq) with enrichment for 5'-capped RNAs reveals active TREs with high accuracy. Here, we demonstrate that active TREs can be identified by applying sensitive machine-learning methods to standard GRO-seq data. This approach allows TREs to be assayed together with gene expression levels and other transcriptional features in a single experiment. Our prediction method, called discriminative Regulatory Element detection from GRO-seq (dREG), summarizes GRO-seq read counts at multiple scales and uses support vector regression to identify active TREs. The predicted TREs are more strongly enriched for several marks of transcriptional activation, including eQTL, GWAS-associated SNPs, H3K27ac, and transcription factor binding than those identified by alternative functional assays. Using dREG, we survey TREs in eight human cell types and provide new insights into global patterns of TRE function. We analyzed GRO-seq or PRO-seq data from eight human cell lines. Please note that this study comprises new sample data plus reanalysis of old Sample data submitted by another user. Existing PRO-seq or GRO-seq data was combined as detailed in the GSE66031_readme.txt. See GSM1613181 and GSM1613182 Sample records for data processing information.

2015-02-19 | E-GEOD-66031 | biostudies-arrayexpress

Identification of active transcriptional regulatory elements with GRO-seq

2015-02-19 | GSE66031 | GEO

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