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Kronos scRT: a uniform framework for single-cell replication timing analysis

ABSTRACT: Mammalian genomes are replicated in a cell-type specific order and in coordination with transcription and chromatin organization. Although the field of replication is also entering the singlecell era, current studies require cell sorting, individual cell processing and have yielded a limited number (<100) of cells. Here, we have developed Kronos scRT (https://github.com/CL-CHEN-Lab/Kronos_scRT), a software for single-cell Replication Timing (scRT) analysis. Kronos scRT does not require a specific platform nor cell sorting, allowing the investigation of large datasets obtained from asynchronous cells. Analysis of published available data and droplet-based scWGS data generated in the current study, allows exploitation of scRT data from thousands of cells for different mouse and human cell lines. Our results demonstrate that, although most cells replicate within a close timing range for a given genomic region, replication can also occur stochastically throughout S phase. Altogether, Kronos scRT allows investigating the RT program at a single-cell resolution for both homogeneous and heterogeneous cell populations in a fast and comprehensive manner.

ORGANISM(S): Homo sapiens

PROVIDER: GSE186173 | GEO | 2022/03/29

REPOSITORIES: GEO

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Project description:The organization of mammalian DNA replication is poorly understood. We have produced genome-wide high-resolution dynamic maps of the timing of replication in human erythroid, mesenchymal and embryonic stem cells using TimEX, a method that relies on gaussian convolution of massive, highly redundant determinations of DNA copy number variations during S phase obtained using either high-density oligonucleotide tiling arrays or massively-parallel sequencing to produce replication timing profiles. We show that in untransformed human cells, timing of replication is highly regulated and highly synchronous, and that many genomic segments are replicated in temporal transition regions devoid of initiation where replication forks progress unidirectionally from origins that can be hundreds of kilobases away. Absence of initiation in one transition region is shown at the molecular level by SMARD analysis. Comparison of ES and erythroid cells replication patterns revealed that these cells replicate about 20% of their genome in different quarter of S phase and that ES cells replicate a larger proportion of their genome in early S phase than erythroid cells. Importantly, we detected a strong inverse relationship between timing of replication and distance to the closest expressed gene. This relationship can be used to predict tissue specific timing of replication profiles from expression data and genomic annotations. We also provide evidence that early origins of replication are preferentially located near highly expressed genes, that mid firing origins are located near moderately expressed genes and that late firing origins are located far from genes. Comparison of S/G1 from ES cells, MSCs and erythroid cells The purpose of the study was to measure replication timing by taking advantage of the fact that copy number of DNA increases from 2 two 4 during replication. Specifically, the study was designed to compare the number of copies of DNA of cells in the G1 phase of the cell cycle with the number of copies of DNA of cells in the S phase of the cell cycle. The cells in G1 and S of the cell cycle were obtained by sorting cells based on DNA content after staining with propidium iodide, a fluorescent compound that binds to DNA. We first tested the strategy with Nimblegen tiling arrays representing about 3% of the genome and found that it was indeed possible to measure such a small difference of copy number if a high-level of redundancy was used. We then extended the study genome-wide using massively parallel sequencing on either the SolID or the Illumina platform. Both platforms were tested and we found that for that application, both platforms were equivalent and provided sufficient number of reads to measure timing of replication genome-wide. We then attempted to better understand the correlation between timing of replication and transcription. We therefore obtained RNA from hESC and from erythroblast and hybridized them to standard Affymetrix U133plus2 arrays. This analysis revealed that it was possible to predict the replication timing patterns with relatively good accuracy (r=0.8) using expression data and distance of every genomic windows to express genes.

Project description:We have characterized allele-specific regulation of replication in human cultured primary basophilic erythroblasts using TimEX-seq. We show that in most of the genome the timing of replication of the two chromosome homologs is robustly and tightly regulated since the two alleles replicate almost at the same time. We also show that small genetic differences such as SNPs and indels do not affect replication timing. We identify two major causes of replication asynchrony: the presence of large structural variants and parental imprinting. Both are associated with the formation of asynchronously replicated domains that can reach several megabases in size. We also report that replication timing domains have a previously undetected fine structure. Compare DNA content in cells in S and G1 phase of cell cycle using TimEX-seq The goal of these experiments was to measure the timing of replication in human basophilic erythroblasts in an allele-specific manner by comparing DNA content in cells in S and G1 phase of cell cycle using TimEX-seq. Cells in S phase were obtained by sorting propidium iodide stained exponentially growing basophilic erythroblasts produce after 14 days of culture of circulating peripheral blood stem and progenitor cells. The cells in G1, which are used to normalize the results from the cells in S phase for mapability, were circulating mononuclear cells (WBCs) which are in the G1 cell for the cell cycle at 99.5%. The processed files represent S/G1 ratio values which are surrogate values for the timing of replication. Allele-specific TimEX-seq profiles and hi-resolution non-allele specific profiles are provided at different smoothing levels. The following processed files are derived from the multiple files as indicated below; >FNY01_3_2_Ery_MAT_S.bed is generated from FNY01_3_2_Ery_round *_S_Phase.bed >FNY01_3_2_Ery_PAT_S.bed is generated from FNY01_3_2_Ery_round *_S_Phase.bed >FNY01_3_2_Ery_MAT_G1.bed is generated from FNY01_3_2_WBC_round *_G1_600.bed FNY01_3_2_WBC_round *_G1_300.bed >FNY01_3_2_WBC_PAT_G1.bed is generated from FNY01_3_2_WBC_round *_G1_600.bed FNY01_3_2_WBC_round *_G1_300.bed >FNY01_3_2_Ery_S_G1 ratio_MAT_100kb_smooth.bedGraph is from FNY01_3_2_Ery_MAT_S.bed FNY01_3_2_Ery_MAT_G1.bed >FNY01_3_2_Ery_S_G1 ratio_PAT_100kb_smooth.bedGraph is from FNY01_3_2_Ery_PAT_S.bed FNY01_3_2_Ery_PAT_G1.bed >FNY01_3_2_Ery_S_G1 ratio_unsmooth.bedGraph, FNY01_3_2_Ery_S_G1 ratio_20Kb_smooth.bedGraph, and FNY01_3_2_Ery_S_G1 ratio_100Kb_smooth.bedGraph are from FNY01_3_2_Ery_round *_S_Phase.bed FNY01_3_2_WBC_round *_G1_600.bed FNY01_3_2_WBC_round *_G1_300.bed >FNY01_3_2&3_3_Ery* files are generated from 14 .bed files linked to the corresponding sample records. Please note that *3_3* files follow the same pattern as *3_2*

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Kronos scRT: a uniform framework for single-cell replication timing analysis

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