ChIP-seq. analysis of pan-histone 3 acetylation in Romidepsin treated TCam-2
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Daniel Nettersheim
PROVIDER: E-GEOD-78262 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Illumina 450k DNA methylation microarray analysis of seminoma-like TCam-2 cells xenografted in nude mice. 2120EP embryonal carcinoma cells served as control. TCam-2 cells acquire pluripotency and become epigenetically reprogrammed to an embryonal carcinoma-like state during in vivo growth. This analysis is part of the article 'BMP inhibition in seminomas initiates acquisition of pluripotency via NODAL signaling resulting in reprogramming to an embryonal carcinoma' by Nettersheim et al., 2015. PLoS Genetics Genomic DNA was isolated from tumors of TCam-2 and 2102EP cells xenografted for 1, 2, 4 and 6 weeks as well as 4 and 8 weeks, respectively. In vivo samples of TCam-2 cells were analyzed in biological duplicates. In vitro cultivated TCam-2 / 2102EP cells as well as 2102EP xenografted for 4 and 8 weeks were analyzed once.
2015-08-01 | E-GEOD-60787 | biostudies-arrayexpress
Project description:Illumina cDNA expression microarray analysis of seminoma-like TCam-2 cells xenografted in nude mice. 2120EP embryonal carcinoma cells served as control. TCam-2 cells acquire pluripotency and become epigenetically reprogrammed to an embryonal carcinoma-like state during in vivo growth. This analysis is part of the article 'BMP inhibition in seminomas initiates acquisition of pluripotency via NODAL signaling resulting in reprogramming to an embryonal carcinoma' by Nettersheim et al., 2015. PLoS Genetics Total RNA was isolated from tumors of TCam-2 and 2102EP cells xenografted for 1, 2, 4 and 6 weeks as well as 4 and 8 weeks, respectively. 1x10^7 cells were xenografted. In vivo samples of TCam-2 cells were analyzed in biological duplicates. In vitro cultivated TCam-2 / 2102EP cells as well as 2102EP xenografted for 4 and 8 weeks were analyzed once.
2015-08-01 | E-GEOD-60698 | biostudies-arrayexpress
Project description:Germ cell tumors (GCT) originate from germ cells at different developmental stages (GCT type I – V) They are thought to inherit their methylation profile from (early embryonic) germ cells which undergo a characteristic epigenetic “reset” during maturation. This study aims to provide insight into the developmental timing and underlying biology of the various subtypes of GCTs and their (embryonic) cells of origin by identifying specific and global methylation differences between GCT subtypes. In total, 91 type I-IV GCTs and four cell lines were profiled using the Illumina HumanMethylation450 BeadChip (450K) platform. The data were pre-processed using a validated pipeline and analyzed using an in-house generated extension of the annotation manifest. Marked methylation differences were identified between GCT subtypes both on the global and local level (i.e. differentially methylated regions, imprinting control regions, promoters, etc). GCT subtypes indeed show major similarities to specific stages of (early) developing embryonic germ cells with regard to their methylation profile. The extended annotation manifest for the Illumina 450K platform and methylation datasets are readily available on GEO (GEO accession: GSE58538, GPL18809), providing an integrated hypothesis generating data source for future research. 91 germ cell tumors of various histologies were investigated for their methylation profile. Methylation detection was performed using Illumina’s HumanMethylation450 BeadChip. 14 type I teratomas (TE) were included of which 6 were located sacral (3 male: I.TE.s.m; 3 female: I.TE.s.f), 4 were located in the testis (I.TE.t) and 3 were located in the ovary (I.TE.o). 30 pure embryonal carcinomas (EC) were included as well as 21 mixed non seminomas (mNS). 12 seminomas of the testis (SE) were included as well as 4 dysgerminomas (their couterpart in the ovary). Finally, 4 spermatocytic seminomas (SS) and three dermoid cysts were analyzed. For a detailed overview the histological classification of germ cell tumors please see the publication linked to this data or associated literature [1-3]. Four cell lines were included, al modelling type II GCTs. Cell lines derived from EC include NT2[4-8], NCCIT [5, 9] and 2102EP[4-8]. TCam-2 closely resembles SE [10-12]. 1. Oosterhuis, J.W. and L.H. Looijenga, Testicular germ-cell tumours in a broader perspective. Nat Rev Cancer, 2005. 5(3): p. 210-22. 2. Looijenga, L.H., Human testicular (non)seminomatous germ cell tumours: the clinical implications of recent pathobiological insights. J Pathol, 2009. 218(2): p. 146-62. 3. Woodward, P.J., et al., Testicular germ cell tumors, in World Health Organization Classification of Tumours Pathology and Genetics of the Urinary System and Male Genital Organs., J.N. Eble, et al., Editors. 2004, IARC Press: Lyon. p. 17-278. 4. Andrews, P.W., et al., A comparative study of eight cell lines derived from human testicular teratocarcinoma. Int J Cancer, 1980. 26(3): p. 269-80. 5. Andrews, P.W., et al., Comparative analysis of cell surface antigens expressed by cell lines derived from human germ cell tumours. Int J Cancer, 1996. 66(6): p. 806-16. 6. Wang, N., et al., Nonrandom abnormalities in chromosome 1 in human testicular cancers. Cancer Res, 1980. 40(3): p. 796-802. 7. Fogh, J. and G. Trempe, New Human Tumor Cell Lines, in Human Tumor Cells in Vitro, J. Fogh, Editor. 1975, Springer US. p. 115-159. 8. Fogh, J., Cultivation, characterization, and identification of human tumor cells with emphasis on kidney, testis, and bladder tumors. Natl Cancer Inst Monogr, 1978(49): p. 5-9. 9. Teshima, S., et al., Four new human germ cell tumor cell lines. Lab Invest, 1988. 59(3): p. 328-36. 10. Eckert, D., et al., TCam-2 but not JKT-1 cells resemble seminoma in cell culture. Cell Tissue Res, 2008. 331(2): p. 529-38. 11. de Jong, J., et al., Further characterization of the first seminoma cell line TCam-2. Genes Chromosomes Cancer, 2008. 47(3): p. 185-96. 12. Mizuno, Y., et al., [Establishment and characterization of a new human testicular germ cell tumor cell line (TCam-2)]. Nihon Hinyokika Gakkai Zasshi, 1993. 84(7): p. 1211-8.
2015-02-26 | E-GEOD-58538 | biostudies-arrayexpress
Project description:To investigate the exact locations of CCTT-chromatin interaction on a genome-wide scale, we modified previously reported ChIRP-seq (chromatin isolation by RNA purification followed by deep-sequencing) with a crosslinker 4’- aminomethyltrioxalen (AMT, a psoralen derivative), which allows fixation of nucleic acid interaction by ultraviolet light without crosslinking proteins. We designed 8 complementary DNA oligonucleotides that tiled the Alu-depleted part of CCTT. Affinity-purified CCTT-binding DNAs were sequenced and mapped to the HuRef genome hg38, which contains human α-satellite sequence models in each centromeric region. In contrast with 5.38% of input reads mapping to α-satellite sequence, 16.89% of CCTT-binding reads were enriched at α-satellites. Peaks bound by lnc-CCTT were identified by MACS2 algorithm, which compared the reads in CCTT-captured samples with that in input ones. CCTT-binding peaks mapped across the centromeric regions of all 23 reference centromeres. Next, we validated the enrichment of centromeric peaks located at all chromosomes via ChIRP-qPCR. To validate our ChIRP-seq results, we selected representatives of three major subpopulations: multimapping peaks in one specific chromosome and several chromosomes, as well as single-copy peaks. We performed ChIRP-qPCR and found abundant CCTT-binding centromeric peaks throughout all 23 chromosomes. Importantly, CCTT ChIRP-seq profile was highly correlated with the previously reported ChIP-seq profiles of CENP-C (Pearson correlation R = 0.82), both of which showed very strong, extensive signals across entire centromeric regions in HeLa cells.
2022-04-20 | GSE149532 | GEO
Project description:ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with high-throughput massively parallel sequencing, is increasingly being used for identification of proteinM-bM-^@M-^SDNA interactions in-vivo in the genome. In general, current algorithms for ChIP-seq reads employ artificial estimation of the average length of DNA fragments for peak finding, leading to uncertain prediction of DNA-protein binding sites. Here, we present SIPeS (Site Identification from Paired-end Sequencing), a novel algorithm for precise identification of binding sites from short reads generated from paired-end Solexa ChIP-Seq technology. SIPeS uses a dynamic baseline directly via M-bM-^@M-^Xpiling upM-bM-^@M-^Y the corresponding fragments defined by the paired reads to efficiently find peaks corresponding to binding sites. The performance of SIPeS is demonstrated by analyzing the ChIP-Seq data of the Arabidopsis basic helix-loop-helix transcription factor ABORTED MICROSPORES (AMS). The robustness of SIPeS was demonstrated in higher sensitivity and spatial resolution in peak finding compared to three existing peak detection algorithms. Keywords: transcription factors (protein-DNA interactions) Examination of protein-DNA interactions in buds of Arabidopsis anther cell
2010-06-04 | E-GEOD-16940 | biostudies-arrayexpress
Project description:To identify sGCβ1 binding sites to chromatin DNA, we performed ChIP analysis by using anti-sGCβ1 antibody (Sigma G4405). We have successfully identified 4169 intervals. In this study, sGCβ1 was found to bind to many genes' promoter region. We used U-87 MG (ATCC® HTB-14) glioma cells which overexpress sGCβ1 (generated by us) to perform ChIP assay by using anti-sGCβ1 antibody (Sigma G4405) and genome-wide sGCβ1 binding was determined with sequencing. The ChIP DNA was processed into a standard Illumina ChIP-Seq library and sequence. The 75-nt sequence reads generated by Illumina sequencing (using NextSeq 500) are mapped to the hg19 genome using the BWA algorithm with default settings. Only reads that pass Illuminaâs purity filter, align with no more than 2 mismatches, and map uniquely to the genome are used in the subsequent analysis. Intervals (= Peaks) were determined using the MACS peak finding algorithm.
2016-06-16 | E-GEOD-83419 | biostudies-arrayexpress
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Richard Sandstrom mailto:sull@u.washington.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track is produced as part of the ENCODE Project. This track shows DNaseI sensitivity measured genome-wide in different cell lines using the Digital DNaseI methodology (see below), and DNaseI hypersensitive sites. DNaseI has long been used to map general chromatin accessibility and DNaseI hypersensitivity is a universal feature of active cis-regulatory sequences. The use of this method has led to the discovery of functional regulatory elements that include enhancers, insulators, promotors, locus control regions and novel elements. For each experiment (cell type) this track shows DNaseI sensitivity as a continuous function using sequencing tag density (Raw Signal), and discrete loci of DNaseI sensitive zones (HotSpots) and hypersensitive sites (Peaks)." For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols. Digital DNaseI was performed by DNaseI digestion of intact nuclei, isolating DNaseI 'double-hit' fragments as described in Sabo et al. (2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Solexa platform (36 bp reads). Uniquely mapping high-quality reads were mapped to the genome. DNaseI sensitivity is directly reflected in raw tag density (Raw Signal), which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI sensitive zones (HotSpots) were identified using the HotSpot algorithm described in Sabo et al. (2004). 1.0% false discovery rate thresholds (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within FDR 1.0% hypersensitive zones using a peak-finding algorithm.
2011-06-03 | E-GEOD-29692 | biostudies-arrayexpress
Project description:This track is produced as part of the mouse ENCODE Project. This track shows DNaseI sensitivity measured genome-wide in mouse tissues and cell lines using the Digital DNaseI methodology (see below), and DNaseI hypersensitive sites. DNaseI has long been used to map general chromatin accessibility and DNaseI hypersensitivity is a universal feature of active cis-regulatory sequences. The use of this method has led to the discovery of functional regulatory elements that include enhancers, insulators, promotors, locus control regions and novel elements. For each experiment (tissue/cell type) this track shows DNaseI sensitivity as a continuous function using sequencing tag density (Signal), and discrete loci of DNaseI sensitive zones (HotSpots) and hypersensitive sites (Peaks). For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Fresh tissues were harvested from mice and the nuclei prepared according to the tissue appropriate protocol (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Digital DNaseI was performed by DNaseI digestion of intact nuclei, isolating DNaseI 'double-hit' fragments as described in Sabo et al. (2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Illumina IIx (and Illumina HiSeq by early 2011) platform (36 bp reads). Uniquely mapping high-quality reads were mapped to the genome using the bowtie aligner. DNaseI sensitivity is directly reflected in raw tag density, which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI sensitive zones (HotSpots) were identified using the HotSpot algorithm described in Sabo et al. (2004). 1.0% false discovery rate thresholds (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within FDR 1.0% hypersensitive zones using a peak-finding algorithm (I-max).
2012-10-03 | E-GEOD-37074 | biostudies-arrayexpress
Project description:The PAF complex (Paf1C) has been shown to regulate chromatin modifications, gene transcription, and PolII elongation. Here, we provide the first genome-wide analysis of chromatin occupancy by the entire PAF complex in mammalian cells. We show that Paf1C is recruited not only to promoters and gene bodies, but also to regions downstream of cleavage/polyadenylation (pA) sites at 3â ends, a profile that sharply contrasted with the yeast complex. Remarkably, our studies identified novel, subunit-specific links between Paf1C and regulation of alternative cleavage and polyadenylation (APA) and upstream antisense transcription. Moreover, we found that depletion of Paf1C subunits also resulted in the accumulation of RNA polymerase II (PolII) over gene bodies, which coincided with APA. Depletion of specific Paf1C subunits leads to global loss of histone H2B ubiquitylation, but surprisingly, there is little impact of Paf1C depletion on other histone modifications, including the tri-methylation of histone H3 on lysines 4 and 36 (H3K4me3 and H3K36me3), previously associated with this complex. Our results provide surprising differences with yeast, while unifying observations that link Paf1C with PolII elongation and RNA processing, and suggest that Paf1C could play a role in protecting transcripts from premature cleavage by preventing PolII accumulation at TSS-proximal pA sites. ChIP-seq, RNA-seq and 3'READS of Paf1C factors in mouse C2C12 myoblast cells
2016-01-15 | E-GEOD-72574 | biostudies-arrayexpress
Project description:10^7 HL-60 cells were treated with 10 uM ATRA for two and five days. 10% whole cell lysates were saved as input after genomic DNA was broken into 200-500 bp by sonication. 1 μg IP grade antibodies of CTCF, H3K4me3 or H3K27me3 (CST, Boston, USA) were incubated with the rest of the lysate overnight, followed by 2 h protein-A beads incubation at 4 °C for target protein pull down. The CTCF enriched or H3K4/27me3 modified DNA or input DNA were repaired to 3’-dA overhang and added the ligated adapter. The DNA library was eliminated the unligated adapters and selected the appropriate size for sequence using an Illumina X Ten platform. The raw sequence reads of input and IP were trimmed adaptors and filter out low quality reads using Cutadapt (v1.9.1) and Trimmomatic (v0.35), and checked the quality of clean reads using Fastqc. Next, clean reads were mapped to the human genome (assembly hg38) using the Bowtie 2 (v2.2.6) algorithm. The process of peak calling (p<0.01) were performed by MACS 2 (v2.1.1) and analyzed the different binding domains based on FDR value less than 0.05 and annotated by DiffBind. De novo motif were analyzed using the R language and MEME. The peaks on certain genomic loci were visualized by Integrative Genomics Viewer (IGV). Gene ontology (GO) Analysis was used to interpret the biological function of the genes associated with differential peaks.
2020-05-07 | E-MTAB-8558 | biostudies-arrayexpress