Similar Datasets
Project description:ATAC-seq, ChIP-seq and RNA-seq of breast cancer cell lines post ligand treatment
| PRJNA483771 | ENA
Project description:Goal: study the impact of estrogen receptor ligands on gene expression in HR+ breast cancer cells Methods: RNA sequencing Results: Ligand 4-OH tamoxifen, a selective ER modulator (SERM), promotes transcriptional activation of ER and mimics the transcriptional effect of natural ligand E2 for a subset of ER target genes, consistently across the seven breast cell lines (MCF-7, HCC1500, MDA-MB-330, EFM-19, T-47D, BT-474, and CAMA-1). Selective ER degraders (SERD) fulvestrant and GDC-0927 on the other hand do not induce, or induce very weakly the expression of ER target genes. The effect of GDC-0810 depends on the cellular context.
2019-07-25 | GSE117942 | GEO
Project description:Goal: study the impact of estrogen receptor ligands on gene expression in HR+ breast cancer cells Methods: RNA sequencing Results: Ligand 4-OH tamoxifen, a selective ER modulator (SERM), promotes transcriptional activation of ER and mimics the transcriptional effect of natural ligand E2 for a subset of ER target genes, consistently across the seven breast cell lines (MDA-MB-134 VI, MDA-MB-330, EFM-19, T-47D, and BT-474). Selective ER degraders (SERD) fulvestrant and GDC-0927 on the other hand do not induce, or induce very weakly the expression of ER target genes. The effect of GDC-0810 depends on the cellular context.
2019-07-25 | GSE128911 | GEO
Project description:Changes in cellular chromatin states fine-tune transcriptional output and ultimately lead to phenotypic changes. Here we propose a novel application of our reproducibility-optimized test statistics (ROTS) to detect differential chromatin states (ATAC-seq) or differential chromatin modification states (ChIP-seq) between conditions. We compare the performance of ROTS to existing and widely used methods for ATAC-seq and ChIP-seq data using both synthetic and real datasets. Our results show that ROTS outperformed other commonly used methods when analyzing ATAC-seq data. ROTS also displayed the most accurate detection of small differences when modeling with synthetic data. We observed that two-step methods that require the use of a separate peak caller often more accurately called enrichment borders, whereas one-step methods without a separate peak calling step were more versatile in calling sub-peaks. The top ranked differential regions detected by the methods had marked correlation with transcriptional differences of the closest genes. Overall, our study provides evidence that ROTS is a useful addition to the available differential peak detection methods to study chromatin and performs especially well when applied to study differential chromatin states in ATAC-seq data.
| S-EPMC8253552 | biostudies-literature
Project description:RNA-seq of breast cancer cell lines post ligand treatment II
| PRJNA529360 | ENA
Project description:RNA-seq of breast cancer cell lines post ligand treatment I
| PRJNA483773 | ENA
Project description:DNA accessibility to transcription regulators varies between cells and modulates gene expression patterns. Several "open" chromatin profiling methods that provide valuable insight into the activity of these regulatory regions have been developed. However, their application to clinical samples has been limited despite the discovery that the Analysis of Transposase-Accessible Chromatin followed by sequencing (ATAC-seq) method can be performed using fewer cells than other techniques. Obtaining fresh rather than stored samples and a lack of adequate optimization and quality controls are major barriers to ATAC's clinical implementation. Here, we describe an optimized ATAC protocol in which we varied nuclear preparation conditions and transposase concentrations and applied rigorous quality control measures before testing fresh, flash frozen, and cryopreserved breast cells and tissue. We obtained high quality data from small cell number. Furthermore, the genomic distribution of sequencing reads, their enrichment at transcription start sites, and transcription factor footprint analyses were similar between cryopreserved and fresh samples. This updated method is applicable to clinical samples, including cells from fine needle aspiration and tissues obtained via core needle biopsy or surgery. Chromatin accessibility analysis using patient samples will greatly expand the range of translational research and personalized medicine by identification of clinically-relevant epigenetic features.
| S-EPMC6345852 | biostudies-literature
Project description:Activation of regulatory elements is thought to be inversely correlated with DNA methylation levels. However, it is difficult to determine whether DNA methylation is compatible with chromatin accessibility or transcription factor (TF) binding if assays are performed separately. We developed a fast, low-input, low sequencing depth method, EpiMethylTag, that combines ATAC-seq or ChIP-seq (M-ATAC or M-ChIP) with bisulfite conversion, to simultaneously examine accessibility/TF binding and methylation on the same DNA. Here we demonstrate that EpiMethylTag can be used to study the functional interplay between chromatin accessibility and TF binding (CTCF and KLF4) at methylated sites.
| S-EPMC6868874 | biostudies-literature
Project description:Chromatin immunoprecipitation sequencing (ChIP-seq) and the Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) have become essential technologies to effectively measure protein-DNA interactions and chromatin accessibility. However, there is a need for a scalable and reproducible pipeline that incorporates proper normalization between samples, correction of copy number variations, and integration of new downstream analysis tools. Here we present Containerized Bioinformatics workflow for Reproducible ChIP/ATAC-seq Analysis (CoBRA), a modularized computational workflow which quantifies ChIP-seq and ATAC-seq peak regions and performs unsupervised and supervised analyses. CoBRA provides a comprehensive state-of-the-art ChIP-seq and ATAC-seq analysis pipeline that can be used by scientists with limited computational experience. This enables researchers to gain rapid insight into protein-DNA interactions and chromatin accessibility through sample clustering, differential peak calling, motif enrichment, comparison of sites to a reference database, and pathway analysis. CoBRA is publicly available online at https://bitbucket.org/cfce/cobra.
| S-EPMC9039557 | biostudies-literature
Project description:Extrachromosomal circular DNAs (eccDNAs) are somatically mosaic and contribute to intercellular heterogeneity in normal and tumor cells. Because short eccDNAs are poorly chromatinized, we hypothesized that they are sequenced by tagmentation in ATAC-seq experiments without any enrichment of circular DNA. Indeed, ATAC-seq identified thousands of eccDNAs in cell lines that were validated by inverse PCR and by metaphase FISH. ATAC-seq in gliomas and glioblastomas identify hundreds of eccDNAs, including one containing the well-known EGFR gene amplicon from chr7. More than 18,000 eccDNAs, many carrying known cancer driver genes, are identified in a pan-cancer analysis of ATAC-seq libraries from 23 tumor types. Somatically mosaic eccDNAs are identified by ATAC-seq even before amplification is recognized by genome-wide copy number variation measurements. Thus, ATAC-seq is a sensitive method to detect eccDNA present in a tumor at the pre-amplification stage and can be used to predict resistance to therapy.
| S-EPMC7228742 | biostudies-literature