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3D replicon distributions arise from stochastic initiation and domino-like DNA replication progression.

Löb D, Lengert N, Chagin VO, Reinhart M, Casas-Delucchi CS, Cardoso MC, Drossel B - Nat Commun (2016)

Bottom Line: Critical model features are: spontaneous stochastic firing of individual origins in euchromatin and facultative heterochromatin, inhibition of firing at distances below the size of chromatin loops and a domino-like effect by which replication forks induce firing of nearby origins.The model reproduces the empirical temporal and chromatin-related properties of DNA replication in human cells.We advance the one-dimensional DNA replication model to a spatial model by taking into account chromatin folding in the nucleus, and we are able to reproduce the spatial and temporal characteristics of the replication foci distribution throughout S-phase.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, Institute for Condensed Matter Physics, Technische Universität Darmstadt, 64289 Darmstadt, Germany.

ABSTRACT
DNA replication dynamics in cells from higher eukaryotes follows very complex but highly efficient mechanisms. However, the principles behind initiation of potential replication origins and emergence of typical patterns of nuclear replication sites remain unclear. Here, we propose a comprehensive model of DNA replication in human cells that is based on stochastic, proximity-induced replication initiation. Critical model features are: spontaneous stochastic firing of individual origins in euchromatin and facultative heterochromatin, inhibition of firing at distances below the size of chromatin loops and a domino-like effect by which replication forks induce firing of nearby origins. The model reproduces the empirical temporal and chromatin-related properties of DNA replication in human cells. We advance the one-dimensional DNA replication model to a spatial model by taking into account chromatin folding in the nucleus, and we are able to reproduce the spatial and temporal characteristics of the replication foci distribution throughout S-phase.

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Several simulated replication characteristics compared with experimental data.(a) Confocal RFi measurements were used to model the initial increase of the limiting factor with a mono-exponential fit L(t)=Lmax(1−e−t/τ) with timescale τ=15 min. (b) Distribution of distances between adjacent fired origins from DNA combing data for HeLa Kyoto cells. The distribution has a peak below 200 kbp and a heavy tail up to 600 kbp. The corresponding distribution, averaged over 100 simulations, displays similar features. (c) Fraction of replicated chromatin as a function of time. Colours are used to distinguish between the chromatin type specific and total replication. Dotted lines show the simulation results, when only induced firing events are allowed. Dashed lines display the other extreme case, where solely spontaneous firing was used. The combined model includes both firing events and the results are shown with solid lines. (d) Time-dependent number of forks in each chromatin type. (e) Comparison of our model with replication timing data for chromosome 6 from the ENCODE project44 (cell type GM12878). Sampling positions are identical to the positions in the experimental data. For individual simulations, the euchromatic peaks start at time zero, but because of the specific sampling positions and averaging over 100 simulations, the displayed peaks are less extreme. The Pearson's correlation coefficient between the theoretical and experimental data shown here is 0.60. The Background indicates the Giemsa staining, where white regions are interpreted as euchromatin and shaded regions as facultative or constitutive heterochromatin. The centromere is indicated as a striped pattern. Analogous figures for other human chromosomes can be found in the Supplementary Figs 4–6.
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f2: Several simulated replication characteristics compared with experimental data.(a) Confocal RFi measurements were used to model the initial increase of the limiting factor with a mono-exponential fit L(t)=Lmax(1−e−t/τ) with timescale τ=15 min. (b) Distribution of distances between adjacent fired origins from DNA combing data for HeLa Kyoto cells. The distribution has a peak below 200 kbp and a heavy tail up to 600 kbp. The corresponding distribution, averaged over 100 simulations, displays similar features. (c) Fraction of replicated chromatin as a function of time. Colours are used to distinguish between the chromatin type specific and total replication. Dotted lines show the simulation results, when only induced firing events are allowed. Dashed lines display the other extreme case, where solely spontaneous firing was used. The combined model includes both firing events and the results are shown with solid lines. (d) Time-dependent number of forks in each chromatin type. (e) Comparison of our model with replication timing data for chromosome 6 from the ENCODE project44 (cell type GM12878). Sampling positions are identical to the positions in the experimental data. For individual simulations, the euchromatic peaks start at time zero, but because of the specific sampling positions and averaging over 100 simulations, the displayed peaks are less extreme. The Pearson's correlation coefficient between the theoretical and experimental data shown here is 0.60. The Background indicates the Giemsa staining, where white regions are interpreted as euchromatin and shaded regions as facultative or constitutive heterochromatin. The centromere is indicated as a striped pattern. Analogous figures for other human chromosomes can be found in the Supplementary Figs 4–6.

Mentions: Due to the induced firing process, the probability for very short distances between firing origins would be much higher than experimentally observed (Fig. 2b). Thus, we introduced a distance around active forks, where firing of potential origins is inhibited (the inhibition distance—di). A range of the di values from 7 to 120 kbp was selected based on the reported correlation of distances between preferentially activated origins2728293031 and average sizes of the chromatin loops in different functional chromatin organization models1432. To find the most probable value for di we compared the experimental distribution of inter-origin distances (Fig. 2b) with the distribution obtained from simulations varying the di value (5 kbp steps) by calculating the χ2 value as well as the Kullback–Leibler divergence. Both measures have a broad minimum for di values between 35 and 55 kb indicating the most probable range. In the simulations presented here, a value of 55 kb was used, because smaller values lead to an increasing total number of origins fired. Figure 1 shows a schematic of the induced firing process in the model. The range of induced firing is determined by the parameter σ, the s.d. of the Gaussian curve, which is used to set the induced firing probabilities of nearby potential origins. Induced firing probabilities below 0.1 are set to zero to avoid the infinite range of the Gaussian curve. Increasing the value of σ broadens the simulated distribution of inter-origin distances shifting the mean towards higher distances and decreasing σ enhances the peak of the distribution below 200 kb. In the range from 100 to 280 kb for the parameter σ there are only minor changes to the distribution of inter-origin distances, therefore it can not be determined more precisely from the given data.


3D replicon distributions arise from stochastic initiation and domino-like DNA replication progression.

Löb D, Lengert N, Chagin VO, Reinhart M, Casas-Delucchi CS, Cardoso MC, Drossel B - Nat Commun (2016)

Several simulated replication characteristics compared with experimental data.(a) Confocal RFi measurements were used to model the initial increase of the limiting factor with a mono-exponential fit L(t)=Lmax(1−e−t/τ) with timescale τ=15 min. (b) Distribution of distances between adjacent fired origins from DNA combing data for HeLa Kyoto cells. The distribution has a peak below 200 kbp and a heavy tail up to 600 kbp. The corresponding distribution, averaged over 100 simulations, displays similar features. (c) Fraction of replicated chromatin as a function of time. Colours are used to distinguish between the chromatin type specific and total replication. Dotted lines show the simulation results, when only induced firing events are allowed. Dashed lines display the other extreme case, where solely spontaneous firing was used. The combined model includes both firing events and the results are shown with solid lines. (d) Time-dependent number of forks in each chromatin type. (e) Comparison of our model with replication timing data for chromosome 6 from the ENCODE project44 (cell type GM12878). Sampling positions are identical to the positions in the experimental data. For individual simulations, the euchromatic peaks start at time zero, but because of the specific sampling positions and averaging over 100 simulations, the displayed peaks are less extreme. The Pearson's correlation coefficient between the theoretical and experimental data shown here is 0.60. The Background indicates the Giemsa staining, where white regions are interpreted as euchromatin and shaded regions as facultative or constitutive heterochromatin. The centromere is indicated as a striped pattern. Analogous figures for other human chromosomes can be found in the Supplementary Figs 4–6.
© Copyright Policy - open-access
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4829661&req=5

f2: Several simulated replication characteristics compared with experimental data.(a) Confocal RFi measurements were used to model the initial increase of the limiting factor with a mono-exponential fit L(t)=Lmax(1−e−t/τ) with timescale τ=15 min. (b) Distribution of distances between adjacent fired origins from DNA combing data for HeLa Kyoto cells. The distribution has a peak below 200 kbp and a heavy tail up to 600 kbp. The corresponding distribution, averaged over 100 simulations, displays similar features. (c) Fraction of replicated chromatin as a function of time. Colours are used to distinguish between the chromatin type specific and total replication. Dotted lines show the simulation results, when only induced firing events are allowed. Dashed lines display the other extreme case, where solely spontaneous firing was used. The combined model includes both firing events and the results are shown with solid lines. (d) Time-dependent number of forks in each chromatin type. (e) Comparison of our model with replication timing data for chromosome 6 from the ENCODE project44 (cell type GM12878). Sampling positions are identical to the positions in the experimental data. For individual simulations, the euchromatic peaks start at time zero, but because of the specific sampling positions and averaging over 100 simulations, the displayed peaks are less extreme. The Pearson's correlation coefficient between the theoretical and experimental data shown here is 0.60. The Background indicates the Giemsa staining, where white regions are interpreted as euchromatin and shaded regions as facultative or constitutive heterochromatin. The centromere is indicated as a striped pattern. Analogous figures for other human chromosomes can be found in the Supplementary Figs 4–6.
Mentions: Due to the induced firing process, the probability for very short distances between firing origins would be much higher than experimentally observed (Fig. 2b). Thus, we introduced a distance around active forks, where firing of potential origins is inhibited (the inhibition distance—di). A range of the di values from 7 to 120 kbp was selected based on the reported correlation of distances between preferentially activated origins2728293031 and average sizes of the chromatin loops in different functional chromatin organization models1432. To find the most probable value for di we compared the experimental distribution of inter-origin distances (Fig. 2b) with the distribution obtained from simulations varying the di value (5 kbp steps) by calculating the χ2 value as well as the Kullback–Leibler divergence. Both measures have a broad minimum for di values between 35 and 55 kb indicating the most probable range. In the simulations presented here, a value of 55 kb was used, because smaller values lead to an increasing total number of origins fired. Figure 1 shows a schematic of the induced firing process in the model. The range of induced firing is determined by the parameter σ, the s.d. of the Gaussian curve, which is used to set the induced firing probabilities of nearby potential origins. Induced firing probabilities below 0.1 are set to zero to avoid the infinite range of the Gaussian curve. Increasing the value of σ broadens the simulated distribution of inter-origin distances shifting the mean towards higher distances and decreasing σ enhances the peak of the distribution below 200 kb. In the range from 100 to 280 kb for the parameter σ there are only minor changes to the distribution of inter-origin distances, therefore it can not be determined more precisely from the given data.

Bottom Line: Critical model features are: spontaneous stochastic firing of individual origins in euchromatin and facultative heterochromatin, inhibition of firing at distances below the size of chromatin loops and a domino-like effect by which replication forks induce firing of nearby origins.The model reproduces the empirical temporal and chromatin-related properties of DNA replication in human cells.We advance the one-dimensional DNA replication model to a spatial model by taking into account chromatin folding in the nucleus, and we are able to reproduce the spatial and temporal characteristics of the replication foci distribution throughout S-phase.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, Institute for Condensed Matter Physics, Technische Universität Darmstadt, 64289 Darmstadt, Germany.

ABSTRACT
DNA replication dynamics in cells from higher eukaryotes follows very complex but highly efficient mechanisms. However, the principles behind initiation of potential replication origins and emergence of typical patterns of nuclear replication sites remain unclear. Here, we propose a comprehensive model of DNA replication in human cells that is based on stochastic, proximity-induced replication initiation. Critical model features are: spontaneous stochastic firing of individual origins in euchromatin and facultative heterochromatin, inhibition of firing at distances below the size of chromatin loops and a domino-like effect by which replication forks induce firing of nearby origins. The model reproduces the empirical temporal and chromatin-related properties of DNA replication in human cells. We advance the one-dimensional DNA replication model to a spatial model by taking into account chromatin folding in the nucleus, and we are able to reproduce the spatial and temporal characteristics of the replication foci distribution throughout S-phase.

Show MeSH