Chordoma ATAC-Seq
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Charles Lin
PROVIDER: E-GEOD-70771 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Cell-to-cell variation is a universal feature of life that impacts a wide range of biological phenomena, from developmental plasticity to tumor heterogeneity. While recent advances have improved our ability to document cellular phenotypic variation the fundamental mechanisms that generate variability from identical DNA sequences remain elusive. Here we reveal the landscape and principles of cellular DNA regulatory variation by developing a robust method for mapping the accessible genome of individual cells via assay of transposase accessible chromatin sequencing (ATAC-seq). Single-cell ATAC-seq (scATAC-seq) maps from hundreds of single-cells in aggregate closely resemble accessibility profiles from tens of millions of cells and provides insights into cell-to-cell variation. Accessibility variance is systematically associated with specific trans-factors and cis-elements, and we discover combinations of trans-factors associated with either induction or suppression of cell-to-cell variability. We further identify sets of trans-factors associated with cell-type specific accessibility variance across 6 cell types. Targeted perturbations of cell cycle or transcription factor signaling evoke stimulus-specific changes in this observed variability. The pattern of accessibility variation in cis across the genome recapitulates chromosome topological domains de novo, linking single-cell accessibility variation to three-dimensional genome organization. All together, single-cell analysis of DNA accessibility provides new insight into cellular variation of the “regulome.” Profiles of single cell epigenomes, assayed using scATAC-seq, across 8 cell types and 4 targeted cell manipulations. The complete data set contains a total of 1,632 assayed wells.
2015-06-17 | E-GEOD-65360 | biostudies-arrayexpress
Project description:shRNA-mediated brachyury knockdown was performed on the chordoma cell line U-CH1 as replicates. RNA was extracted, labelled and hybridised to Human Gene 1.0ST chips followed by gene expression microarray analysis.This was followed by a ChIP-seq experiment using a specific brachyury antibody, the data for which are stored in Raw ChIP-seq reads are stored under: European Nucleotide Archive accession ERP000953 and Array Express accession E-ERAD-23.
2012-10-08 | E-MEXP-3716 | biostudies-arrayexpress
Project description:The histological grade of carcinomas describes the ability of tumor cells to organize differentiated epithelial structures and has prognostic impact. Molecular control of differentiation in normal and cancer cells relies on lineage-determining transcription factors (TFs) that activate the repertoire of cis-regulatory elements controlling cell type-specific transcriptional outputs. TF recruitment to cognate genomic DNA binding sites results in the deposition of histone marks characteristic of enhancers and other cis-regulatory elements. Here we integrated transcriptomics and genome-wide analysis of chromatin marks in human pancreatic ductal adenocarcinoma (PDAC) cells of different grade to identify first, and then experimentally validate the sequence-specific TFs controlling grade-specific gene expression. We identified a core set of TFs with a pervasive binding to the enhancer repertoire characteristic of differentiated PDACs and controlling different modules of the epithelial gene expression program. Defining the regulatory networks that control the maintenance of epithelial differentiation of PDAC cells will help determine the molecular basis of PDAC heterogeneity and progression. Poly(A) fraction of the total RNA from human pancreatic ductal adenocarcinoma cell lines was extracted and subjected to by multiparallel sequencing. Experiments were carried out in unmodified cells in duplicate, genome edited clonal CFPAC1 cells (2 KLF5-deleted CRISPR-Cas9 clones, 3 ELF3-deleted CRISPR-Cas9 clones and 2 wt clones) and CFPAC1 cells ectopically expressing ZEB1 or empty vector control (in duplicate).
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Project description:Gene regulatory networks that govern hematopoietic stem cells (HSC) and leukemia–initiating cells (L-IC) are deeply entangled. Thus, the discovery of compounds that target L-IC while sparing HSC is an attractive but difficult endeavor. Presently, most drug discovery approaches fail to counter-screen compounds against normal hematopoietic stem/progenitor cells (HSPC) to assess therapeutic index. Here, we present a combined in vitro and in vivo strategy to identify compounds specific to L-IC in acute myeloid leukemia (AML). A high-throughput screen of 4000 compounds on novel leukemia cell lines derived from human experimental leukemogenesis models yielded 80 hits, of which most were toxic to normal HSPC. Of the 10 compounds that passed this initial filter, we chose to characterize a single compound, kinetic riboside (KR), on AML L-IC and HSPC. KR demonstrated comparable efficacy to standard therapies against 63 primary AMLs. In vitro, KR effectively targeted the L-IC-enriched CD34+CD38- AML fraction, while sparing normal HSPC enriched fractions, although these effects were mitigated on HSC assayed in vivo, and highlights the importance of in vivo L-IC and HSC assays to measure function. Overall, we provide a novel approach to screen large drug libraries for the discovery of anti-L-IC compounds for human leukemias. The gene expression profile of TEX and M9-ENL1 cells were compared to HL-60 (Series GSE16160, GSE28185) and THP1 (Series GSE28185), to determine if TEX and M9-ENL1 cells were more enriched in stem cell (embryonic, adult, leukemia, and cancer) gene sets using Gene Set Enrichment Analysis (GSEA). TEX and M9-ENL1 cells were treated with DMSO in triplicate. Total RNA was harvested and analyzed with the Affymetrix Human Genome U133A 2.0 Array. Raw data was background corrected with RMA, normalized using quantiles method, corrected using only PM values, and median polished to generate log2 values. Published HL-60 and THP-1 raw data using the same Affymetrix array were processed identically. To account for batch variation, the log2 values were adjusted using ComBat in GenePattern with a parametric Empirical Bayes priors distribution estimation method and without covariate analysis.
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Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2016-01-18 | E-GEOD-64560 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE33653: Direct Recruitment of Polycomb Repressive Complex 1 (PRC1) to Chromatin by Core Binding Transcription Factors (ChIP-Seq) GSE33659: Direct Recruitment of Polycomb Repressive Complex 1 (PRC1) to Chromatin by Core Binding Transcription Factors (microarray) Refer to individual Series
2012-02-10 | E-GEOD-33660 | biostudies-arrayexpress
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