Mouse Hepa1-6 cell line E/L Repli-seq
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB67994 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR12180804_1.fastq.gz | Fastqsanger.gz | |||
| ERR12180804_2.fastq.gz | Fastqsanger.gz | |||
| ERR12180805_1.fastq.gz | Fastqsanger.gz | |||
| ERR12180805_2.fastq.gz | Fastqsanger.gz | |||
| ERR12180806_1.fastq.gz | Fastqsanger.gz |
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Project description:E/L Repli-seq is a powerful tool for detecting cell type-specific replication landscapes in mammalian cells, but its potential to monitor DNA replication under replication stress awaits better understanding. Here, we used E/L Repli-seq to examine the temporal order of DNA replication in human retinal pigment epithelium cells treated with the topoisomerase I inhibitor camptothecin. We found that the replication profiles by E/L Repli-seq exhibits characteristic patterns after replication-stress induction, including the loss of specific initiation zones within individual early replicating timing domains. We also observed global disappearance of the replication timing domain structures in the profiles, which can be explained by checkpoint-dependent suppression of replication initiation. Thus, our results demonstrate the effectiveness of E/L Repli-seq at identifying cells with replication-stress-induced altered DNA replication programs.
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Project description:DNA replication timing and 3D chromatin organisation are associated with epigenomic changes across large domains during human differentiation and cancer progression. However, it is unclear if epigenome changes, in particular cancer-associated DNA hypomethylation, is a consequence or cause of changes observed in higher order genome architecture. Here, we compare replication timing profiles and three dimensional (3D) genome organisation, using Hi-C and single cell Repli-Seq in the DNMT1 and DNMT3B DNA methyltransferases double knockout hypomethylated DKO1 colorectal cancer cell line and its parental HCT116 cell line. We find that the hypomethylated cells show a profound loss of replication timing precision, gain of single cell replication timing heterogeneity and loss of chromatin conformation integrity. Discrete regions, that undergo a large change in replication timing in the hypomethylated cells, are associated with a loss of allelic replication timing and shrinking of late replicating Partially Methylated Domain (PMD) boundaries. In contrast, conservation of replication timing after DNA methylation depletion at PMDs is associated with the formation of new H3K9me3/H3K4me3 bivalent domains which may serve to prevent ectopic transcription and maintain cell viability. Together our results show that a loss of global methylation, a common hallmark of cancer, directly impacts on the precision of replication timing and contribute to deregulation of the 3D chromatin architecture.
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Project description:This track is produced as part of the ENCODE Project. This track shows genome-wide assessment of DNA replication timing in cell lines using the sequencing-based "Repli-seq" methodology (see below). Replication timing is known to be an important feature for epigenetic control of gene expression that usually operates at a higher-order level than at the level of specific genes. For each experiment (cell line, replicate), replication timing was ascertained by the isolation and sequencing of newly replicated DNA from six cell cycle fractions: G1/G1b, S1, S2, S3, S4, G2 (six fraction profile). Replication patterns are visualized as a continuous function based on sequencing tag density (Percentage-normalized Signal) and as a wavelet-smoothed transform of the six fraction profile (Wavelet-smoothed Signal). Replication peaks corresponding to replication initiation zones (Peaks) and valleys corresponding to replication termination zones (Valleys) were determined from local maxima and minima, respectively, in the wavelet-smoothed signal data. A measure of relative copy number at each genomic location (Summed Densities) was determined by summing the normalized tag density values of each cell cycle fraction at that location (equals one replicated genome equivalent). 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. Repli-seq was performed as described by Hansen et al. (2010). Briefly, newly replicated DNA was labeled in vivo with a pulse of 5-bromo-2-deoxyuridine (BrdU), cells were fractionated into six different parts of the cell cycle by flow cytometry according to DNA content, cell cycle fractionated DNA was sonicated and an anti-BrdU monoclonal antibody was used to isolate the newly replicating DNA. Fragment ends were sequenced using the Illumina Genome Analyzer II or HiSeq platforms (36 bp reads). Some experiments (BJ, K562, BG02ES, GM06990) were originally performed and mapped to an earlier version of the human reference genome NCBI36/hg18 (Hansen et al., 2010) and were remapped to the more recent reference genome GRCh37/hg19. Uniquely mapping high-quality reads were mapped to the genome minus the Y chromosome. Replication signals within each six cell cycle fraction were derived from the density of sequence tags mapping within a 50 kb sliding window (stepped 1 kb across the genome); these densities were normalized to 4 million tags per genome. To avoid variation due to copy number or sequence bias, cell cycle-specific replication signals at each location were determined as a percentage of the sum of the six normalized tag density signals (Percentage-normalized Signal). To transform the six fraction replication signals into one track (Wavelet-smoothed Signal), the percentage-normalized signals at each location were used to calculate a weighted average value based on the average DNA content of each fraction according to flow cytometry [higher values correspond to earlier replication; formula=(0.917*G1b)+(0.750*S1)+(0.583*S2)+(0.417*S3)+(0.250*S4)+(0*G2)]. These weighted average data were smoothed by wavelet transformation [J7 level, corresponding to a scale of 128 kb; see Thurman et al. (2007)]. Replication initiation zones were flagged by determining local maxima in the wavelet-smoothed data (Peaks) and, similarly, replication termination zones were flagged by local minima (Valleys). The sum of the 4 million normalized replication tag densities correspond to replication of one genome and can, therefore, be used as a measure of relative genomic copy number (Summed Densities). This is useful for evaluation of unusual replication patterns, such as "biphasic" ones where replication has both early and late components [as described by Hansen et al. (2010)].
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Project description:DNA replication timing is known to facilitate the establishment of the epigenome, however, the intimate connection between replication timing and changes to the genome and epigenome in cancer remain largely uncharacterised. Here, we perform Repli-Seq and integrated epigenome analyses and demonstrate that genomic regions that undergo long-range epigenetic deregulation in prostate cancer also show concordant differences in replication timing. A subset of altered replication timing domains are conserved across cancers from different tissue origins. Notably, late-replicating regions in cancer cells display a loss of DNA methylation, and a switch in heterochromatin features from H3K9me3-marked constitutive to H3K27me3-marked facultative heterochromatin. Finally, analysis of 214 prostate and 35 breast cancer genomes reveal that late-replicating regions are prone to cis and early-replication to trans chromosomal rearrangements. Together, our data suggests that the nature of chromosomal rearrangement in cancer is related to the spatial and temporal positioning and altered epigenetic states of early-replicating compared to late-replicating loci.
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