Cell-to-cell variability and robustness in S-phase duration from genome replication kinetics

Single molecule MATAC-seq reveals key determinants of DNA replication origin efficiency

Stochastic origin activation gives rise to significant cell-to-cell variability in the pattern of genome replication. The molecular basis for heterogeneity in efficiency and timing of individual origins is a long-standing question. Here, we developed Methylation Accessibility of TArgeted Chromatin domain Sequencing (MATAC-Seq) to determine single-molecule chromatin accessibility of four specific genomic loci. MATAC-Seq relies on preferential modification of accessible DNA by methyltransferases combined with Nanopore-Sequencing for direct readout of methylated DNA-bases. Applying MATAC-Seq to selected early-efficient and late-inefficient yeast replication origins revealed large heterogeneity of chromatin states. Disruption of INO80 or ISW2 chromatin remodeling complexes leads to changes at individual nucleosomal positions that correlate with changes in their replication efficiency. We found a chromatin state with an accessible nucleosome-free region in combination with well-positioned +1 and +2 nucleosomes as a strong predictor for efficient origin activation. Thus, MATAC-Seq identifies the large spectrum of alternative chromatin states that co-exist on a given locus previously masked in population-based experiments and provides a mechanistic basis for origin activation heterogeneity during eukaryotic DNA replication. Consequently, our single-molecule chromatin accessibility assay will be ideal to define single-molecule heterogeneity across many fundamental biological processes such as transcription, replication, or DNA repair in vitro and ex vivo.

DEK oncoprotein participates in heterochromatin replication via SUMO-dependent nuclear bodies

The correct inheritance of chromatin structure is key for maintaining genome function and cell identity and preventing cellular transformation. DEK, a conserved non-histone chromatin protein, has recognized tumor-promoting properties, its overexpression being associated with poor prognosis in various cancer types. At the cellular level, DEK displays pleiotropic functions, influencing differentiation, apoptosis and stemness, but a characteristic oncogenic mechanism has remained elusive. Here, we report the identification of DEK bodies, focal assemblies of DEK that regularly occur at specific, yet unidentified, sites of heterochromatin replication exclusively in late S-phase. In these bodies, DEK localizes in direct proximity to active replisomes in agreement with a function in the early maturation of heterochromatin. A high-throughput siRNA screen, supported by mutational and biochemical analyses, identifies SUMO as one regulator of DEK body formation, linking DEK to the complex SUMO protein network that controls chromatin states and cell fate. This work combines and refines our previous data on DEK as a factor essential for heterochromatin integrity and facilitating replication under stress, and delineates an avenue of further study for unraveling the contribution of DEK to cancer development.

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.

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

Mammalian genomes are replicated in a cell type-specific order and in coordination with transcription and chromatin organization. Currently, single-cell replication studies require individual processing of sorted cells, yielding a limited number (<100) of cells. Here, we develop Kronos scRT, a software for single-cell Replication Timing (scRT) analysis. Kronos scRT does not require a specific platform or cell sorting, which allows investigating large datasets obtained from asynchronous cells. By applying our tool to published data as well as droplet-based single-cell whole-genome sequencing data generated in this study, we exploit scRT from thousands of cells for different mouse and human cell lines. Our results demonstrate that although genomic regions are frequently replicated around their population average RT, replication can occur stochastically throughout S phase. Altogether, Kronos scRT allows fast and comprehensive investigations of the RT programme at the single-cell resolution for both homogeneous and heterogeneous cell populations.

A scalable approach to explore DNA replication in single cells reveals that although aneuploidy does not have a major impact on the pattern of replication, different cell types and sub-populations display distinguished replication paths.

An evolutionary model identifies the main evolutionary biases for the evolution of genome-replication profiles

Recent results comparing the temporal program of genome replication of yeast species belonging to the Lachancea clade support the scenario that the evolution of the replication timing program could be mainly driven by correlated acquisition and loss events of active replication origins. Using these results as a benchmark, we develop an evolutionary model defined as birth-death process for replication origins and use it to identify the evolutionary biases that shape the replication timing profiles. Comparing different evolutionary models with data, we find that replication origin birth and death events are mainly driven by two evolutionary pressures, the first imposes that events leading to higher double-stall probability of replication forks are penalized, while the second makes less efficient origins more prone to evolutionary loss. This analysis provides an empirically grounded predictive framework for quantitative evolutionary studies of the replication timing program.

Data Driven Cell Cycle Model to Quantify the Efficacy of Cancer Therapeutics Targeting Specific Cell-Cycle Phases From Flow Cytometry Results

Many chemotherapeutic drugs target cell processes in specific cell cycle phases. Determining the specific phases targeted is key to understanding drug mechanism of action and efficacy against specific cancer types. Flow cytometry experiments, combined with cell cycle phase and division round specific staining, can be used to quantify the current cell cycle phase and number of mitotic events of each cell within a population. However, quantification of cell interphase times and the efficacy of cytotoxic drugs targeting specific cell cycle phases cannot be determined directly. We present a data driven computational cell population model for interpreting experimental results, where in-silico populations are initialized to match observable results from experimental populations. A two-stage approach is used to determine the efficacy of cytotoxic drugs in blocking cell-cycle phase transitions. In the first stage, our model is fitted to experimental multi-parameter flow cytometry results from untreated cell populations to identify parameters defining probability density functions for phase transitions. In the second stage, we introduce a blocking routine to the model which blocks a percentage of attempted transitions between cell-cycle phases due to therapeutic treatment. The resulting model closely matches the percentage of cells from experiment in each cell-cycle phase and division round. From untreated cell populations, interphase and intermitotic times can be inferred. We then identify the specific cell-cycle phases that cytotoxic compounds target and quantify the percentages of cell transitions that are blocked compared with the untreated population, which will lead to improved understanding of drug efficacy and mechanism of action.

Estimation of the Minimum Number of Replication Origins Per Chromosome in any Organism

Eukaryote nuclear genomes predominantly replicate through multiple replication origins. The number of replication origins activated per chromosome during the S-phase duration may vary according to many factors, but the predominant one is replication stress. Several studies have applied different approaches to estimate the number and map the positions of the replication origins in various organisms. However, without a parameter to restrict the minimum of necessary origins, less sensitive techniques may suggest conflicting results. The estimation of the minimum number of replication origins (MO) per chromosome is an innovative method that allows the establishment of a threshold, which serves as a parameter for genomic approaches that map origins. For this, the MO can be easily obtained through a formula that requires as parameters: chromosome size, S-phase duration, and replication rate. The chromosome size for any organism can be acquired in genomic databanks (such as NCBI), the S-phase duration can be estimated by monitoring DNA replication, and the replication rate is obtained through the DNA combing approach. The estimation of MO is a simple, quick, and easy method that provides a new methodological framework to assist studies of mapping replication origins in any organism.

Comparative Analysis of the Minimum Number of Replication Origins in Trypanosomatids and Yeasts

Single-celled eukaryote genomes predominantly replicate through multiple origins. Although origin usage during the S-phase has been elucidated in some of these organisms, few studies have comparatively approached this dynamic. Here, we developed a user-friendly website able to calculate the length of the cell cycle phases for any organism. Next, using a formula developed by our group, we showed a comparative analysis among the minimum number of replication origins (MO) required to duplicate an entire chromosome within the S-phase duration in trypanosomatids (Trypanosoma cruzi, Leishmania major, and Trypanosoma brucei) and yeasts (Saccharomyces cerevisiae and Schizosaccharomyces pombe). Using the data obtained by our analysis, it was possible to predict the MO required in a situation of replication stress. Also, our findings allow establishing a threshold for the number of origins, which serves as a parameter for genome approaches that map origins. Moreover, our data suggest that when compared to yeasts, trypanosomatids use much more origins than the minimum needed. This is the first time a comparative analysis of the minimum number of origins has been successfully applied. These data may provide new insight into the understanding of the replication mechanism and a new methodological framework for studying single-celled eukaryote genomes.

Transcription activity contributes to the firing of non-constitutive origins in African trypanosomes helping to maintain robustness in S-phase duration

The co-synthesis of DNA and RNA potentially generates conflicts between replication and transcription, which can lead to genomic instability. In trypanosomatids, eukaryotic parasites that perform polycistronic transcription, this phenomenon and its consequences are still little studied. Here, we showed that the number of constitutive origins mapped in the Trypanosoma brucei genome is less than the minimum required to complete replication within S-phase duration. By the development of a mechanistic model of DNA replication considering replication-transcription conflicts and using immunofluorescence assays and DNA combing approaches, we demonstrated that the activation of non-constitutive (backup) origins are indispensable for replication to be completed within S-phase period. Together, our findings suggest that transcription activity during S phase generates R-loops, which contributes to the emergence of DNA lesions, leading to the firing of backup origins that help maintain robustness in S-phase duration. The usage of this increased pool of origins, contributing to the maintenance of DNA replication, seems to be of paramount importance for the survival of this parasite that affects million people around the world.

Evidence that the human cell cycle is a series of uncoupled, memoryless phases

The cell cycle is canonically described as a series of four consecutive phases: G1, S, G2, and M. In single cells, the duration of each phase varies, but the quantitative laws that govern phase durations are not well understood. Using time-lapse microscopy, we found that each phase duration follows an Erlang distribution and is statistically independent from other phases. We challenged this observation by perturbing phase durations through oncogene activation, inhibition of DNA synthesis, reduced temperature, and DNA damage. Despite large changes in durations in cell populations, phase durations remained uncoupled in individual cells. These results suggested that the independence of phase durations may arise from a large number of molecular factors that each exerts a minor influence on the rate of cell cycle progression. We tested this model by experimentally forcing phase coupling through inhibition of cyclin-dependent kinase 2 (CDK2) or overexpression of cyclin D. Our work provides an explanation for the historical observation that phase durations are both inherited and independent and suggests how cell cycle progression may be altered in disease states.

The evolution of the temporal program of genome replication

Genome replication is highly regulated in time and space, but the rules governing the remodeling of these programs during evolution remain largely unknown. We generated genome-wide replication timing profiles for ten Lachancea yeasts, covering a continuous evolutionary range from closely related to more divergent species. We show that replication programs primarily evolve through a highly dynamic evolutionary renewal of the cohort of active replication origins. We found that gained origins appear with low activity yet become more efficient and fire earlier as they evolutionarily age. By contrast, origins that are lost comprise the complete range of firing strength. Additionally, they preferentially occur in close vicinity to strong origins. Interestingly, despite high evolutionary turnover, active replication origins remain regularly spaced along chromosomes in all species, suggesting that origin distribution is optimized to limit large inter-origin intervals. We propose a model on the evolutionary birth, death, and conservation of active replication origins.

Temporal programs of genome replication show different levels of conservation between closely or distantly related species. Here, the authors generate genome-wide replication timing profiles for ten yeast species, and analyze their evolutionary dynamics.