Chromatin states and genomic organization impact local replication features and timing [Repli-seq]
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA733486 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14678470.fastq.gz | Fastqsanger.gz | |||
| SRR14678471.fastq.gz | Fastqsanger.gz | |||
| SRR14678472.fastq.gz | Fastqsanger.gz | |||
| SRR14678473.fastq.gz | Fastqsanger.gz | |||
| SRR14678474.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 28 |
Similar Datasets
Project description:Chromatin states and genomic organization impact local replication features and timing
| PRJNA733482 | ENA
Project description:Replication timing (RT) control is linked to histone modifications (HMs) and genome architecture. However, HM landscape across cell cycle and its relationship with RT and chromatin modifiers have not been comprehensively assessed. Here we perform detailed replication profiling together with cell cycle profiling of multiple HMs, ATAC-seq, and gene expression. We classify 97% of the genome into four gross chromatin states, including a previously uncharacterized intergenic H3K36me2 state. RT and associated replication features (e.g. initiation zones) quantitatively associate with these chromatin states, HM dynamics, and spatial chromatin structure. Furthermore, overexpression of the histone H3 lysine 9/36 tri-demethylase KDM4A impacts RT across 12% of the genome. RT regulation is strongly linked to KDM4A-associated HMs and enhancer-like elements. Lastly, replication within the intergenic H3K36me2 neighborhoods is sensitive to KDM4A overexpression and is controlled as wide megabase-scale units. In conclusion, these studies establish a critical role for chromatin regulation in directing RT genome-wide.
2021-09-27 | GSE175751 | GEO
Project description:Chromatin states and genomic organization impact local replication features and timing [ChIP-seq]
| PRJNA733485 | ENA
Project description:Chromatin states and genomic organization impact replication timing and local patterns [ATAC-seq]
| PRJNA736434 | ENA
Project description:Allele-specific control of replication timing and genome organization during development [Repli-Seq]
| PRJNA473044 | ENA
Project description:The role of DNA sequence in determining replication timing (RT) and chromatin higher order organization remains elusive. To address this question, we have developed an extra-chromosomal replication system consisting of ~200kb human bacteria artificial chromosomes (BACs) modified with Epstein-Barr virus (EBV) replication origin elements (E-BACs). E-BACs were stably maintained as autonomous mini-chromosomes in both HeLa and human induced pluripotent stem cells (hiPSCs) and established their RT de novo. We applied repli-seq to evaluate E-BACs' replication timing.
2018-01-29 | GSE102522 | GEO
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)].
2012-04-26 | E-GEOD-34399 | biostudies-arrayexpress
Project description:Replication timing (RT) control is linked to histone modifications (HMs) and genome architecture. However, HM landscape across cell cycle and its relationship with RT and chromatin modifiers have not been comprehensively assessed. Here we perform detailed replication profiling together with cell cycle profiling of multiple HMs, ATAC-seq, and gene expression. We classify 97% of the genome into four gross chromatin states, including a previously uncharacterized intergenic H3K36me2 state. RT and associated replication features (e.g. initiation zones) quantitatively associate with these chromatin states, HM dynamics, and spatial chromatin structure. Furthermore, overexpression of the histone H3 lysine 9/36 tri-demethylase KDM4A impacts RT across 12% of the genome. RT regulation is strongly linked to KDM4A-associated HMs and enhancer-like elements. Lastly, replication within the intergenic H3K36me2 neighborhoods is sensitive to KDM4A overexpression and is controlled as wide megabase-scale units. In conclusion, these studies establish a critical role for chromatin regulation in directing RT genome-wide.
2021-09-27 | GSE175750 | GEO
Project description:DNA replication occurs in a defined temporal order known as the replication-timing (RT) program. RT is regulated during development in discrete chromosomal units, coordinated with transcriptional activity and 3D genome organization. Here, we derived distinct cell types from F1 hybrid musculus X castaneus mouse crosses and exploited the high single nucleotide polymorphism (SNP) density to characterize allelic differences in RT (Repli-seq), genome organization (Hi-C and promoter-capture Hi-C), gene expression (nuclear RNA-seq) and chromatin accessibility (ATAC-seq). We also present HARP: a new computational tool for sorting SNPs in phased genomes to efficiently measure allele-specific genome-wide data. Analysis of 6 different hybrid mESC clones with different genomes (C57BL/6, 129/sv and CAST/Ei), parental configurations and gender revealed significant RT asynchrony between alleles across ~12 % of the autosomal genome linked to sub-species genomes but not to parental origin, growth conditions or gender. RT asynchrony in mESCs strongly correlated with changes in Hi-C compartments between alleles but not SNP density, gene expression, imprinting or chromatin accessibility. We then tracked mESC RT asynchronous regions during development by analyzing differentiated cell types including extraembryonic endoderm stem (XEN) cells, 4 male and female primary mouse embryonic fibroblasts (MEFs) and neural precursors (NPCs) differentiated in vitro from mESCs with opposite parental configurations. Surprisingly, we found that RT asynchrony and allelic discordance in Hi-C compartments seen in mESCs was largely lost in all differentiated cell types, coordinated with a more uniform Hi-C compartment arrangement, suggesting that genome organization of homologues converges to similar folding patterns during cell fate commitment.
2018-05-22 | GSE114747 | GEO
Project description:genome-wide analysis of replication timing by repli-chip and repli-seq
| PRJNA376018 | ENA