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

Mitigating Cell Cycle Effects in Multi-Omics Data: Solutions and Analytical Frameworks

Cell cycle structures vary significantly across cell types, which exhibit distinct phase compositions. Asynchronous DNA replication and dynamic cellular characteristics during the cell cycle result in considerable heterogeneity in DNA dosage, chromatin accessibility, methylation, and expression. Nonetheless, the consequences of cell cycle disruption in the interpretation of multi-omics data remain unclear. Here, we systematically assessed the influence of distinct cell phase structures on the interpretation of omics features in proliferating cells, and proposed solutions for each omics dataset. For copy number variation (CNV) calling, asynchronous replication timing (RT) interference induces false CNVs in cells with high S-phase ratio (SPR), which are significantly decreased following replication timing domain (RTD) correction. Similar noise is observed in the chromatin accessibility data. Moreover, for DNA methylation and transcriptomic analyses, cell cycle-sorted data outperformed direct comparison in elucidating the biological features of compared cells. Additionally, we established an integrated pipeline to identify differentially expressed genes (DEGs) after cell cycle phasing. Consequently, our study demonstrated extensive cell-cycle heterogeneity, warranting consideration in future studies involving cells with diverse cell-cycle structures. RTD correction or phase-specific comparison could reduce the influence of cell cycle composition on the analysis of the differences observed between stem and differentiated cells.

Replication-dependent histone labeling dissects the physical properties of euchromatin/heterochromatin in living human cells

A string of nucleosomes, where genomic DNA is wrapped around histones, is organized in the cell as chromatin, ranging from euchromatin to heterochromatin, with distinct genome functions. Understanding physical differences between euchromatin and heterochromatin is crucial, yet specific labeling methods in living cells remain limited. Here, we have developed replication-dependent histone (Repli-Histo) labeling to mark nucleosomes in euchromatin and heterochromatin based on DNA replication timing. Using this approach, we investigated local nucleosome motion in the four known chromatin classes, from euchromatin to heterochromatin, of living human and mouse cells. The more euchromatic (earlier-replicated) and more heterochromatic (later-replicated) regions exhibit greater and lesser nucleosome motions, respectively. Notably, the motion profile in each chromatin class persists throughout interphase. Genome chromatin is essentially replicated from regions with greater nucleosome motions, although the replication timing is perturbed. Our findings, combined with computational modeling, suggest that earlier-replicated regions have more accessibility, and local chromatin motion can be a major determinant of genome-wide replication timing.

The double life of mammalian DNA replication origins

Mammalian DNA replication origins have been historically difficult to identify and their determinants are still unresolved. Here, we first review methods developed over the last decades to map replication initiation sites either directly via initiation intermediates or indirectly via determining replication fork directionality profiles. We also discuss the factors that may specify these sites as replication initiation sites. Second, we address the controversy that has emerged from these results over whether origins are narrowly defined and localized to specific sites or are more dispersed and organized into broad zones. Ample evidence in favor of both scenarios currently creates an impression of unresolved confusion in the field. We attempt to formulate a synthesis of both models and to reconcile discrepant findings. It is evident that not only one approach is sufficient in isolation but that the combination of several is instrumental toward understanding initiation sites in mammalian genomes. We argue that an aggregation of several individual and often inefficient initiation sites into larger initiation zones and the existence of efficient unidirectional initiation sites and fork stalling at the borders of initiation zones can reconcile the different observations.

Unravelling single-cell DNA replication timing dynamics using machine learning reveals heterogeneity in cancer progression

Genomic heterogeneity has largely been overlooked in single-cell replication timing (scRT) studies. Here, we develop MnM, an efficient machine learning-based tool that allows disentangling scRT profiles from heterogenous samples. We use single-cell copy number data to accurately perform missing value imputation, identify cell replication states, and detect genomic heterogeneity. This allows us to separate somatic copy number alterations from copy number changes resulting from DNA replication. Our methodology brings critical insights into chromosomal aberrations and highlights the ubiquitous aneuploidy process during tumorigenesis. The copy number and scRT profiles obtained by analysing >119,000 high-quality human single cells from different cell lines, patient tumours and patient-derived xenograft samples leads to a multi-sample heterogeneity-resolved scRT atlas. This atlas is an important resource for cancer research and demonstrates that scRT profiles can be used to study replication timing heterogeneity in cancer. Our findings also highlight the importance of studying cancer tissue samples to comprehensively grasp the complexities of DNA replication because cell lines, although convenient, lack dynamic environmental factors. These results facilitate future research at the interface of genomic instability and replication stress during cancer progression.

Characterizing the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER

Proliferation is a key hallmark of cancer, but whether it differs between evolutionarily distinct clones co-existing within a tumor is unknown. We introduce the Single-cell Proliferation Rate Inference in Non-homogeneous Tumors through Evolutionary Routes (SPRINTER) algorithm that uses single-cell whole-genome DNA sequencing data to enable accurate identification and clone assignment of S- and G2-phase cells, as assessed by generating accurate ground truth data. Applied to a newly generated longitudinal, primary-metastasis-matched dataset of 14,994 non-small cell lung cancer cells, SPRINTER revealed widespread clone proliferation heterogeneity, orthogonally supported by Ki-67 staining, nuclei imaging and clinical imaging. We further demonstrated that high-proliferation clones have increased metastatic seeding potential, increased circulating tumor DNA shedding and clone-specific altered replication timing in proliferation- or metastasis-related genes associated with expression changes. Applied to previously generated datasets of 61,914 breast and ovarian cancer cells, SPRINTER revealed increased single-cell rates of different genomic variants and enrichment of proliferation-related gene amplifications in high-proliferation clones.

Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data

Dysregulated DNA replication is a cause and a consequence of aneuploidy in cancer, yet the interplay between copy number alterations (CNAs), replication timing (RT) and cell cycle dynamics remain understudied in aneuploid tumors. We developed a probabilistic method, PERT, for simultaneous inference of cell-specific replication and copy number states from single-cell whole genome sequencing (scWGS) data. We used PERT to investigate clone-specific RT and proliferation dynamics in  >50,000 cells obtained from aneuploid and clonally heterogeneous cell lines, xenografts and primary cancers. We observed bidirectional relationships between RT and CNAs, with CNAs affecting X-inactivation producing the largest RT shifts. Additionally, we found that clone-specific S-phase enrichment positively correlated with ground-truth proliferation rates in genomically stable but not unstable cells. Together, these results demonstrate robust computational identification of S-phase cells from scWGS data, and highlight the importance of RT and cell cycle properties in studying the genomic evolution of aneuploid tumors.

Replication initiation sites and zones in the mammalian genome: Where are they located and how are they defined?

Eukaryotic DNA replication is a tightly controlled process that occurs in two main steps, i.e., licensing and firing, which take place in the G1 and S phases of the cell cycle, respectively. In Saccharomyces cerevisiae, the budding yeast, replication origins contain consensus sequences that are recognized and bound by the licensing factor Orc1-6, which then recruits the replicative Mcm2-7 helicase. By contrast, mammalian initiation sites lack such consensus sequences, and the mammalian ORC does not exhibit sequence specificity. Studies performed over the past decades have identified replication initiation sites in the mammalian genome using sequencing-based assays, raising the question of whether replication initiation occurs at confined sites or in broad zones across the genome. Although recent reports have shown that the licensed MCMs in mammalian cells are broadly distributed, suggesting that ORC-dependent licensing may not determine the initiation sites/zones, they are predominantly located upstream of actively transcribed genes. This review compares the mechanism of replication initiation in yeast and mammalian cells, summarizes the sequencing-based technologies used for the identification of initiation sites/zones, and proposes a possible mechanism of initiation-site/zone selection in mammalian cells. Future directions and challenges in this field are also discussed.

Quantifying DNA replication speeds in single cells by scEdU-seq

In a human cell, thousands of replication forks simultaneously coordinate duplication of the entire genome. The rate at which this process occurs might depend on the epigenetic state of the genome and vary between, or even within, cell types. To accurately measure DNA replication speeds, we developed single-cell 5-ethynyl-2'-deoxyuridine sequencing to detect nascent replicated DNA. We observed that the DNA replication speed is not constant but increases during S phase of the cell cycle. Using genetic and pharmacological perturbations we were able to alter this acceleration of replication and conclude that DNA damage inflicted by the process of transcription limits the speed of replication during early S phase. In late S phase, during which less-transcribed regions replicate, replication accelerates and approaches its maximum speed.

Cell cycle gene alterations associate with a redistribution of mutation risk across chromosomal domains in human cancers

Mutations in human cells exhibit increased burden in heterochromatic, late DNA replication time (RT) chromosomal domains, with variation in mutation rates between tissues mirroring variation in heterochromatin and RT. We observed that regional mutation risk further varies between individual tumors in a manner independent of cell type, identifying three signatures of domain-scale mutagenesis in >4,000 tumor genomes. The major signature reflects remodeling of heterochromatin and of the RT program domains seen across tumors, tissues and cultured cells, and is robustly linked with higher expression of cell proliferation genes. Regional mutagenesis is associated with loss of activity of the tumor-suppressor genes RB1 and TP53, consistent with their roles in cell cycle control, with distinct mutational patterns generated by the two genes. Loss of regional heterogeneity in mutagenesis is associated with deficiencies in various DNA repair pathways. These mutation risk redistribution processes modify the mutation supply towards important genes, diverting the course of somatic evolution.

Single-cell DNA replication dynamics in genomically unstable cancers

Dysregulated DNA replication is both a cause and a consequence of aneuploidy, yet the dynamics of DNA replication in aneuploid cell populations remains understudied. We developed a new method, PERT, for inferring cell-specific DNA replication states from single-cell whole genome sequencing, and investigated clone-specific DNA replication dynamics in >50,000 cells obtained from a collection of aneuploid and clonally heterogeneous cell lines, xenografts and primary cancer tissues. Clone replication timing (RT) profiles correlated with future copy number changes in serially passaged cell lines. Cell type was the strongest determinant of RT heterogeneity, while whole genome doubling and mutational process were associated with accumulation of late S-phase cells and weaker RT associations. Copy number changes affecting chromosome X had striking impact on RT, with loss of the inactive X allele shifting replication earlier, and loss of inactive Xq resulting in reactivation of Xp. Finally, analysis of time series xenografts illustrate how cell cycle distributions approximate clone proliferation, recapitulating expected relationships between proliferation and fitness in treatment-naive and chemotherapeutic contexts.

High-throughput microfluidic droplets in biomolecular analytical system: A review

Droplet microfluidic technology has revolutionized biomolecular analytical research, as it has the capability to reserve the genotype-to-phenotype linkage and assist for revealing the heterogeneity. Massive and uniform picolitre droplets feature dividing solution to the level that single cell and single molecule in each droplet can be visualized, barcoded, and analyzed. Then, the droplet assays can unfold intensive genomic data, offer high sensitivity, and screen and sort from a large number of combinations or phenotypes. Based on these unique advantages, this review focuses on up-to-date research concerning diverse screening applications utilizing droplet microfluidic technology. The emerging progress of droplet microfluidic technology is first introduced, including efficient and scaling-up in droplets encapsulation, and prevalent batch operations. Then the new implementations of droplet-based digital detection assays and single-cell muti-omics sequencing are briefly examined, along with related applications such as drug susceptibility testing, multiplexing for cancer subtype identification, interactions of virus-to-host, and multimodal and spatiotemporal analysis. Meanwhile, we specialize in droplet-based large-scale combinational screening regarding desired phenotypes, with an emphasis on sorting for immune cells, antibodies, enzymatic properties, and proteins produced by directed evolution methods. Finally, some challenges, deployment and future perspective of droplet microfluidics technology in practice are also discussed.

OKseqHMM: a genome-wide replication fork directionality analysis toolkit

During each cell division, tens of thousands of DNA replication origins are co-ordinately activated to ensure the complete duplication of the human genome. However, replication fork progression can be challenged by many factors, including co-directional and head-on transcription-replication conflicts (TRC). Head-on TRCs are more dangerous for genome integrity. To study the direction of replication fork movement and TRCs, we developed a bioinformatics toolkit called OKseqHMM (https://github.com/CL-CHEN-Lab/OK-Seq, https://doi.org/10.5281/zenodo.7428883). Then, we used OKseqHMM to analyse a large number of datasets obtained by Okazaki fragment sequencing to directly measure the genome-wide replication fork directionality (RFD) and to accurately predict replication initiation and termination at a fine resolution in organisms including yeast, mouse and human. We also successfully applied our analysis to other genome-wide sequencing techniques that also contain RFD information (e.g. eSPAN, TrAEL-seq). Our toolkit can be used to predict replication initiation and fork progression direction genome-wide in a wide range of cell models and growth conditions. Comparing the replication and transcription directions allows identifying loci at risk of TRCs, particularly head-on TRCs, and investigating their role in genome instability by checking DNA damage data, which is of prime importance for human health.

Optimized Repli-seq: improved DNA replication timing analysis by next-generation sequencing

The human genome is divided into functional units that replicate at specific times during S-phase. This temporal program is known as replication timing (RT) and is coordinated with the spatial organization of the genome and transcriptional activity. RT is also cell type-specific, dynamically regulated during development, and alterations in RT are observed in multiple diseases. Thus, the precise measure of RT is critical to understand the role of RT in gene function regulation. Distinct methods for assaying the RT program exist; however, conventional methods require thousands of cells as input, prohibiting its applicability to samples with limited cell numbers such as those from disease patients or from early developing embryos. Although single-cell RT analyses have been developed, these methods are low throughput, require generation of numerous libraries, increased sequencing costs, and produce low resolution data. Here, we developed an improved method to measure RT genome-wide that enables high-resolution analysis of low input samples. This method incorporates direct cell sorting into lysis buffer, as well as DNA fragmentation and library preparation in a single tube, resulting in higher yields, increased quality, and reproducibility with decreased costs. We also performed a systematic data processing analysis to provide standardized parameters for RT measurement. This optimized method facilitates RT analysis and will enable its application to a broad range of studies investigating the role of RT in gene expression, nuclear architecture, and disease.

High-throughput analysis of single human cells reveals the complex nature of DNA replication timing control

DNA replication initiates from replication origins firing throughout S phase. Debate remains about whether origins are a fixed set of loci, or a loose agglomeration of potential sites used stochastically in individual cells, and about how consistent their firing time is. We develop an approach to profile DNA replication from whole-genome sequencing of thousands of single cells, which includes in silico flow cytometry, a method for discriminating replicating and non-replicating cells. Using two microfluidic platforms, we analyze up to 2437 replicating cells from a single sample. The resolution and scale of the data allow focused analysis of replication initiation sites, demonstrating that most occur in confined genomic regions. While initiation order is remarkably similar across cells, we unexpectedly identify several subtypes of initiation regions in late-replicating regions. Taken together, high throughput, high resolution sequencing of individual cells reveals previously underappreciated variability in replication initiation and progression.