Coupling of replisome movement with nucleosome dynamics can contribute to the parent–daughter information transfer
Nucleic Acids Research
Coupling of replisome movement with nucleosome dynamics can contribute to the parent-daughter information transfer
Tripti Bameta 2
Dibyendu Das 1
Ranjith Padinhateeri 0
0 Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay , Mumbai 400076 , India
1 Department of Physics, Indian Institute of Technology Bombay , Mumbai 400076 , India
2 UM-DAE Centre for Excellence in Basic Sciences, University of Mumbai , Vidhyanagari Campus, Mumbai 400098 , India
Positioning of nucleosomes along the genomic DNA is crucial for many cellular processes that include gene regulation and higher order packaging of chromatin. The question of how nucleosome-positioning information from a parent chromatin gets transferred to the daughter chromatin is highly intriguing. Accounting for experimentally known coupling between replisome movement and nucleosome dynamics, we propose a model that can obtain de novo nucleosome assembly similar to what is observed in recent experiments. Simulating nucleosome dynamics during replication, we argue that short pausing of the replication fork, associated with nucleosome disassembly, can be a event crucial for communicating nucleosome positioning information from parent to daughter. We show that the interplay of timescales between nucleosome disassembly ( p) at the replication fork and nucleosome sliding behind the fork ( s) can give rise to a rich 'phase diagram' having different inherited patterns of nucleosome organization. Our model predicts that only when p ≥ s the daughter chromatin can inherit nucleosome positioning of the parent.
The fate of a cell is controlled not just by the DNA sequence
alone but also by the organization and the kinetics of
proteins along the DNA. In most eukaryotes, a huge fraction of
the genomic DNA (e.g. >80% in yeast gene regions) is
covered by histone proteins leading to formation of a chromatin
that appears like a ‘string of beads’ (
). Advances made
in the last many years have confirmed that nucleosomes and
their organization play an important role in nearly all
cellular processes. For example, nucleosomes are known to cover
transcription factor binding sites and restrict proteins from
accessing those crucial sites along the genome and, hence,
regulate gene expression (
). There are very different
nucleosome organizations in coding regions and promoter
regions of genes, indicating the importance of the high
diversity in nucleosome organization (
nucleosome organization is also crucial for higher order packaging
of DNA as the polymorphic chromatin structure depends
on linker length distribution (
Since the precise positioning of nucleosomes is
important, the natural question is, how do cells transfer this
information about nucleosome positioning from one
generation to another? How do daughter cells know about the
nature of nucleosome positioning in the parent cells? This is
an intriguing question for which we do not know the precise
answer. One hypothesis argues that the DNA sequence
determines the nucleosome positioning along the genome, and
hence, the information is transferred with the DNA (
However, various experiments have indicated that the DNA
sequence alone would not determine the nucleosome
positioning in the genome (
remodelling, statistical positioning and other factors play
equally important role (
). Moreover, different cell
types (neuronal, muscle, epithelial cells etc) have exactly the
same DNA, but they have very different organization of the
chromatin, gene expression pattern and function (
Another major drawback of the sequence-dictated model of
self-organization of nucleosomes is that attaining an
‘equilibrium’ (steady state) nucleosome organization may take
long time (
), and hence, regulation of genes prior to
attaining a desired nucleosome distribution may fail. An
alternative hypothesis is that nucleosome positioning needs to be
inherited, somehow, during replication so that the
daughter cells can appropriately regulate their gene expression in
an independent manner (
). This hypothesis is partially
strengthened by recent experiments (
) which show that
nucleosome positions are conserved at inactive sites behind
the replication fork.
How does the de novo nucleosome assembly happen
during DNA replication? Experiments have been giving us
major insights into the de novo nucleosome assembly in
the various gene regions (
). For example, Lucchini
et al. have shown that nucleosomes are properly organized
shortly after passage of the replication machinery and
propose that the nucleosome positioning is the initial step of
chromosome maturation (24). Recently, Alabert et al have
shown that not just nucleosome positioning, but
nucleosome modifications are also inherited from the parent to
). Additionally, Blythe et al have shown that
chromatin accessibility is also conserved throughout the
cell cycle (
). Moreover, experiments from different groups
over the years have shown that DNA replication is coupled
with nucleosome assembly (
). In a recent publication
), Smith and Whitehouse have shown that nascent
chromatin plays a role in termination of Okazaki fragment
synthesis. This indicates the importance of nucleosome
positioning immediately behind the fork during replication. In
another paper, Yadav and Whitehouse showed that the
nucleosomes behind the replication fork also get repositioned
via ATP-dependent chromatin remodeling machines, and
such remodeling is essential for obtaining certain features
associated to nucleosome organization (
of ATP-dependent chromatin remodelling enzymes to
reorganize nucleosomes, after replication, is also proposed
by Fennessy et al. (
). Recently, in yeast, Vassuer et al.
studied the maturation of nucleosome organization
following genome replication (
) and analysed the role of
transcription in the maturation of nucleosome organization to
their mid log position of active gene region. They showed
that soon after replication, in downstream TSS, the
nucleosome organization is not proper and it takes time to
maturate. Ramachandran and Henikoff found that after
replication nucleosome occupancy at active gene regions may
differ from steady-state pattern owing to the competition
between nucleosomes and various regulatory factors that
bind DNA (
). However, they also found that nucleosome
occupancy in the inactive region is very similar to the
nucleosome of the parent chromatin, suggesting that
inheritance of nucleosome positioning after replication at
certain locations along the genome. There has been hardly any
theoretical/computational study investigating the de novo
nucleosome assembly. To the best of our knowledge, only
the work of Osberg et al. (
) investigates some aspects of
the de novo nucleosome assembly. However, they do not
address the question of inheritance of precise nucleosome
positioning from parent chromatin to the daughter.
In this work, we investigate the nucleosome organization
immediately after replication, accounting for various
experimentally known facts. We present a kinetic model
incorporating replisome (replication fork) movement, nucleosome
disassembly ahead of the fork, and nucleosome deposition
and repositioning (sliding) of nucleosomes behind the fork.
We show that pausing of the fork during disassembly of
nucleosomes on parental chromatin and sliding/repositioning
of nucleosomes on daughter chromatin behind the fork are
crucial events dictating the nucleosome positioning after
replication. We systematically explore the parameter space
in the model and point out the parameter regime where
inheritance of nucleosome positioning may be observed. We
also study the competition between nucleosomes and
nonhistone proteins, and how they affect the nucleosome
positioning during replication.
MATERIALS AND METHODS
Model for nucleosome kinetics during replication
Here we present a model to study the nucleosome
reorganization following gene replication. In this model we
start by considering an initial (parental) chromatin––DNA
bound with nucleosomes––having a specific nucleosome
organization. The DNA is considered as a one-dimensional
lattice with each base pair marked with an index i. The
nucleosome is modelled as a hard-core particle sitting on the
lattice, occupying a space of k = 150 lattice sites (see
Figure 1). At t = 0, the replisome starts replication process from
the replication origin (i = 0), and it moves with a bare rate
vr (rate of fork movement unhindered by nucleosomes) in
the forward direction. As the replisome moves forward, it
may encounter a nucleosome. Given that the nucleosome
is a stable complex, there can be delays in fork progression
as the remodeling enzymes try to disassembly the
nucleosome ahead of the fork. This delay in fork progression will
be referred to as a ‘pause’ event. This is a pause in fork
progression and not in other processes. We consider p as
the typical timescale of this pause event (
). In other
words, 1/ p is the eviction rate of nucleosomes at the
replication fork. The replisome, as it moves, creates new
doublestranded DNA (dsDNA) behind it; whenever the length of
the newly synthesized dsDNA is larger than the size of a
nucleosome (>150 bp), a new nucleosome can occupy that
space with an intrinsic rate of kon. The effective nucleosome
binding rate is proportional to the freely available space ( f)
on the dsDNA for nucleosomes to bind, i.e, koefnf = kon × f
(see Supporting Information (SI)). As the replisome moves
further, the process repeats. At this point, it is important to
note that, as mentioned earlier, recent experiments have
indicated that the nucleosome deposition behind the fork
happens soon after the fork movement (
) and is crucial
for efficient replication (27).
It has also been shown that the the newly deposited
nucleosomes get slid/repositioned with the help of appropriate
ATP-dependent chromatin remodelers, and this is crucial
for the formation of proper nucleosome positioning (
In the model, taking cues from recent experiments (
we assume that a nucleosome gets slid back and forth until
it settles down at the middle of the available free dsDNA.
To achieve this repositioning, we do the following exercise:
each nucleosome has a rate of sliding given by rs = rs0|(i −
i0)| toward the mid position i0, from the current location i,
with a step of size 10 bp. Here, rs0 is the intrinsic rate of
sliding and i0 is the mid position of the locally available free
(linker) dsDNA at that instant; i0 will evolve as the nearest
nucleosome or the fork is displaced. However, the
nucleosome does not slide for ever; it stops sliding after a time s.
The sliding could stop because the ATPase that facilitates
sliding can disassemble or stop functioning after a certain
What is given above is our basic model that describes
nucleosome assembly dynamics. However, we have also
extended the model to introduce binding of non-histone
proteins such as gene regulatory factors (GRFs) or proteins
that bind near replication origins. These proteins are
considered as sterically interacting particles like a nucleosome,
but with different sizes and different parameter values. For
example, GRFs will have size lesser than a nucleosome while
their sliding rate will be zero. Using the same simulation set
up we have developed here, we investigate the role of
different non-histone protein factors and how they affect
nucleosome organization post replication.
Parameters and their numerical values. There are five
parameters (rates or timescales) in the model. However, many
of them are constrained by known experimental data. The
bare rate of replication (vr) and the pausing timescale of
the replication fork are constrained by the time it takes to
complete replication over a stretch. These rates are taken
such a way that 1.5−2 kb of dsDNA is replicated in a
). Similarly, nucleosome density of the parent
constrains the nucleosome deposition rate, and the fork
velocity. In our simulations we have used a nucleosome
density range of 60–90% as known in vivo (
). Apart from the
above constraints, various experiments published in the
literature also give us relevant ranges of parameter values. The
forward movement rate of the replication fork is estimated
in the range 10−500 bp/s (36). The binding rate of
nucleosomes (kon) is estimated to be ≈0.1−10 (bp s)−1 (
The fork pausing timescale, p, which happens due to
delay in nucleosome disassembly ahead of the fork, can be
estimated to many seconds/tens of seconds (
is also comparable to the known timescale of similar
pausing during transcription (
). In (
disassembly timescale ahead of the replication fork (the
pausing timescale) is estimated as 7 s, assuming a uniform
disassembly rate everywhere. However, there will be
heterogeneity (due to DNA sequence/nucleosome stability) and it may
vary over a range ∼7 s depending on the location/cell-type.
Hence we have done our simulations for a wide range of
p values. We do not know the sliding parameters precisely.
Hence in this work, we vary the sliding duration
parameter ( s) over a wide range and examine how this would
affect nucleosome organization during replication. The other
sliding parameter rs0 is also varied from 0.05 to 1 bp−1 s−1.
Details of simulation. In this paper, given the events and
rates, we simulate the system using kinetic Monte Carlo
methods (Gillespie algorithm) (
). We start from a
specified parental nucleosome profile (occupancy pattern), and
simulate replication, as per the events discussed above, and
produce nucleosome organization in the daughter
chromatin. We repeat this many times (typically 5000) and
compute average occupancy of nucleosomes on the daughter
cells. Occupancy at any position i is defined as the
probability that the site is covered by a nucleosome. Rates used
for each figure is given in the text.
A minimal model and its limitations
The simplest (or minimal) model for replication is to
consider only two processes, namely the replisome movement
and the nucleosome deposition. That is, imagine a
onedimensional problem of a replication fork moving at a rate
vr and nucleosomes being deposited behind the fork with a
rate kon. This problem was considered by Osberg et al. (
As a start, we also simulated replication with only these two
processes and the results are presented in the SI text
(Supplementary Figure S1). Our main findings from this simple
study are (i) the average density of nucleosomes, within this
minimal model, is determined by the ratio of vr to kon (ii)
within this model, the density of the nucleosomes (the
fraction of DNA covered by nucleosomes) has to be between
75% and 100% (iii) the occupancy pattern in this simple
model will always be uniform, one will never obtain a
heterogeneous (space-dependent) nucleosome organization on
an average (see Figure 2A). The last two points are major
limitations of the minimal model. Within this model, there
is no mechanism that transfers the positional information
from the parent to the daughter.
Heterogeneous nucleosome organization : role of fork pausing and nucleosome sliding
In the simulation of the minimal model, we did not account
for the experimentally observed (
repositioning (sliding). We also assumed that nucleosomes ahead
of the replication fork get disassembled infinitely fast,
resulting in unhindered (no pause) movement of the fork.
However, in reality the replication might pause until the
nucleosome ahead of the fork is removed. Given that
nucleosome insertion behind the fork is strongly coupled with
the movement of the fork (
), we hypothesise that the
timescale of such pausing, and hence, the pausing in
movement of the replication machinery, can be important in
determining the nucleosome organization behind the fork.
Therefore, as discussed in the model section, we introduce
both sliding of nucleosomes behind the fork and pausing of
the fork due to the removal of nucleosomes ahead of the
fork. Each nucleosome, after deposition behind the fork,
will be slid for a time s as discussed in the Model section.
As the fork reaches a nucleosome on the parent strand, the
fork will pause until a time p which is the time needed for
clearing the way for the machinery to go forward by
removing the nucleosome ahead. Since we do not know the precise
values of these two parameters, we will vary them
systematically and investigate the parameter regime under which one
can observe experimentally sensible results. We, first, take
the bare sliding rate as rs0 = 1.0 bp−1 s−1. The precise value
of rs0 may not be important as we discuss later.
We start our simulation with only three moves: replisome
movement, nucleosome deposition and nucleosome sliding
(i.e. minimal model + nucleosome sliding; assume pausing
is negligible). The results are given in Figure 2B. One can see
that, with sliding and no pausing, the resulting average
occupancy is homogeneous in space, and looks very different
from the parental nucleosome positioning. This means that
sliding cannot produce heterogenous nucleosome
positioning. Then, we simulate another limit with no sliding but with
pausing (i.e. minimal model + nucleosome pausing; assume
sliding is negligible). The results are in Figure 2C. Here, we
find that the introduction of pausing brings some signature
of the parental nucleosome organization. However, the
occupancy pattern is not very similar to that of the parent.
Further, we simulate the model by introducing all the four
events: fork movement, nucleosome deposition, sliding and
pausing events simultaneously. First, we take the pausing
timescale longer than the sliding timescale ( p = 10 s, s
= 1 s). In this parameter regime, the parental nucleosome
occupancy is nicely replicated in the daughter (Figure 2D).
Note that even the heterogeneity in spacing is inherited in
the next generation. For example, near position 200, the gap
between two nucleosomes in the parent is small (≈50 bp),
and near position 800, the gap is large (≈100 bp). One can
see that in the daughter cell (even after averaging over many
cells) the gap variation is reproduced (Figure 2D).
In Figure 3A, we present a natural scenario where
nucleosome positioning on chromosome-1 of Saccharomyces
cerevisiae starting at location 2708 bp is replicated. We started
with data obtained from Kaplan et al.’s study (
) (blue curve
Figure 3A) as the parental nucleosome positioning profile,
and performed the replication simulation on an ensemble
of configurations; the resulting nucleosome occupancy of
the daughter chromatin is shown as red curve in Figure 3A
(also see Figure 3B). Comparing the parental and
daughter nucleosome occupancy, we note the following points:
the daughter occupancy is not exactly the same as the
parent; however, there is a good amount of similarity where
the daughter occupancy profile captures essential signatures
of the parent. For example, the peak positions (high
occupancy regions) are largely similar, even though the height of
the peaks (and depth of the troughs) do not match well. This
is qualitatively comparable to some of the recent
experimental studies where there are some signatures of inheritance
but the inheritance is not perfect (
Further, we examined the promoter region of PHO5 gene
which is known to show diverse behaviour (
example, if the TATA protein binding site is covered with a
nucleosome, the promoter will mostly be in the ‘off ’ (inactive)
state; on the other hand if TATA site is exposed, then the
promoter will mostly be in the ‘on’ (active) state. Based on
the recent experimental data (41), we started with a
nucleosome occupancy pattern that represents the inactive (off)
state of the promoter (see Figure 3C)––that is, TATA site is
covered. After replication, if the nucleosome positioning is
not faithfully inherited, it may lead to unwanted spurious
gene expression. In our simulations, we find that with large
enough pausing, the nucleosome positioning can be
inherited keeping the TATA box covered with a probability 0.9,
and hence the promoter is inactive. In comparison, in the
absence of pausing and sliding, the inheritance is poor––it
leads to reduced coverage of TATA box (see Figure 3C). In
our simulations, we rarely got configurations that are devoid
of nucleosomes implying that such nucleosome free states
are only possible with active remodeling (
Going beyond single genes, to understand how
parameters values affect the inheritance, we have systematically
studied the inheritance of nucleosome positioning by taking
a few different values of p and s. In Figure 4A, we have
compared nucleosome occupancies in parent and daughter
chromatins for different values of p and s. We observe
that whenever both p and s are non-zero, and p ≥ s
the daughter cell inherits the parent positioning reasonably
well. To compare the nucleosome occupancies, we define
deviation, , as a measure of the difference in nucleosome
occupancy between the daughter and the parent,
where mi and di are occupancy of ith site in parent and
daughter strand, respectively. If the nucleosome occupancy
pattern between the parent and daughter is identical, then
we expect the → 0; if the occupancy patterns are very
different we expect a large value of close to 1. In
Figure 4B, the deviation ( ) is plotted for different values of
p and s as a heat-map with small values of represented
by a dark violet color and large values of represented by
a yellow color(see the colourbar on the side). This further
verifies that for the parameter regime, 0 < s ≤ p, the
deviation is small. That is, for 0 < s ≤ p the daughter
somewhat faithfully inherits parental nucleosome occupancy. In
SI Text (Supplementary Figure S2) we present similar
results for a different set of parameter values, and it suggests
that the phenomena of nucleosome positioning inheritance
due to the pausing is independent of the precise parameter
values we use. Please note that even for the best inheritance,
the deviation is non-zero suggesting that the inheritance is
not perfect. However, the process lays down a pattern of
nucleosome positioning similar to the parent and this may help
the post-replication maturating events in achieving a proper
steady-state nucleosome organization.
Role of strongly positioned nucleosomes and barrier-like proteins
In certain parts of chromatin, it is known that there are
regions where nucleosomes are ‘strongly’ positioned,
while other regions have weakly positioned
). Even though the DNA sequence may
influence the regions with strong positioning, it is well
known that factors beyond the sequence also affect
nucleosome stability. For example, action (or the lack of action)
of certain remodellers, histone variants (H2A.Z, H3.3),
various nucleosome-binding proteins (like H1 or HMG
family proteins) and histone modifications are all known
to affect the stability and positioning strength of
). Does stability/positioning-strength of
nucleosomes have any role in transferring the nucleosome
positioning information into the daughter cells?
We investigate the effect of strong vs weak nucleosome
positioning and how they influence the occupancy pattern
in daughter chromatin. Strongly positioned nucleosomes
are defined as those nucleosomes that are more difficult to
be disassembled ahead of the fork – that is, nucleosomes
having a higher value of p are strongly positioned, while
low p would imply weakly positioned nucleosomes. We
simulate such a system with heterogeneous (high and low)
p values 0.01 s (weak) and 10 s (strong) keeping s (=1 s)
fixed. In a long stretch of DNA, we consider two special
regions with strongly positioned nucleosomes. In Figure 5A,
the two grey-shaded regions (each of length 365 bp)
contain two strongly positioned nucleosomes each, while the
rest of the DNA has weakly positioned nucleosomes. All
nucleosomes are arranged with a uniform linker length of
65bp. The resulting nucleosome positioning in the daughter
cells (averaged over 5000 cells) is shown as a red curve. We
observe that strongly positioned parental nucleosomes give
rise to regions in daughter chromatin with high nucleosome
occupancy inheriting the strong positioning. Also note that
there is a statistical positioning on either side of the strongly
positioned nucleosomes implying that the strongly
positioned nucleosomes can influence the positioning of the
neighboring nucleosomes like in the case of the well-known
statistical positioning near a strong ‘barrier’ (
). In SI
text (Supplementary Figure S3), we show that a similar
inheritance of nucleosome positioning is applicable even when
just one nucleosome is strongly positioned (also see
Supplementary Figure S4).
Another aspect of such local nucleosome positioning
influenced by various proteins happens in the context of
generegulatory factors (GRF). We consider a situation where
there is certain non-histone GRF present in the parental
gene. It is known that when a bound GRF is highly
stable, it can act like a ‘barrier’ and cause statistical
) of nucleosomes. Typically, it is known that
the coding region will have the statistical positioning of
nucleosomes, while the regions upstream to TSS often show
different kinds of nucleosome organization (9). How the
nucleosome positioning is inherited near a GRF is an
interesting question, and recent works have probed this
). Here, we examine the prediction of our
model given certain nucleosome organization reminiscent
of GRF locations on the parent DNA.
On the parent DNA, on the left side of the GRF we start
with the statistical positioning of nucleosomes, and on the
right side with uniformly positioned nucleosomes (flat
occupancy) with mean density ≈85% (see top panel of
Figure 5B). We start with 5000 parent copies of the same gene,
each having nucleosomes organized near the GRF in such a
way that the mean of the occupancy of the parents as given
in the top panel of Figure 5B. Each of these 5000 copy is
replicated once, and we look at the nucleosome positioning
on each of the gene and compute the average occupancy,
which is plotted as red continuous curve in Figure 5B.
When we carry out the replication from left to right with
regard to the GRF (in the parent, the left side has
statistical positioning, the right side has uniform occupancy),
we find that on the left side the statistical positioning gets
parent to daughter nucleosomal organization. The parameters used to generate daughter cell nucleosome occupancy are vr = 500 bp/s, kon = 0.1 bp−1 s−1,
rs0 = 1 bp−1 s−1. For a different parameter value of rs0 = 0.05 bp−1 s−1, the results are shown in SI Supplementary Figure S2.
replicated fairly well (see middle panel of Figure 5B).
However, on the right side, even though there was a flat
positioning in the parent, the daughter chromatin has
nucleosomes with non-uniform oscillatory occupancy in space.
The physical reason for this is the following: on the left side,
daughter gene inherits the parental occupancy via pausing
and sliding; Whereas, on the right side, due to the effect of
the GRF barrier, one obtains oscillatory positioning––it is
well known that nucleosomes near a barrier will have spatial
oscillations in occupancy. This also indicates that physical
barriers will have influence near the barrier site, even with
pausing and sliding. In our simulations, since the GRF is
bound immediately behind the replication fork, the
nucleosome depositing after the GRF ‘feels’ (via steric exclusion)
the GRF barrier, and hence, the generation of the
oscillatory pattern. Please note that ATPase activity (here, sliding
of nucleosomes) is an important factor in producing the
oscillatory pattern as known in other contexts (
When we carry out the replication from right to left with
respect to GRF, we get the result as shown in Figure 5B,
bottom panel. Since the machinery that is moving towards
GRF is unaware of the presence of GRF until it reaches the
location, the replicated chromatin will have very little
influence of the barrier. However, after the GRF, the statistical
positioning is reproduced. Within the short span of sliding,
the nucleosome very close to the GRF feels the barrier and
hence, one obtains a single peak on the right side (Figure 5B,
bottom panel). We observe that the nucleosome
organization immediately after the replication in the vicinity of GRF
is tied to the replication fork progression direction (see
Figure 5B). This positioning may change long after replication
under the influence of other events such as transcription or
action of various remodellers (
). These local remodelling
events may destroy the spontaneous peak formed in
Figure 5B and lead to parent-like nucleosome positioning as a
result of these extra events.
So far we have assumed that non-histone proteins like
GRFs bind in the nucleosome depleted region (NDR) with
large affinity and occupy their precise locations on the
DNA. However, many of the recent experiments indicate
that nucleosomes compete with non-histone protein
binding and this may result in gain of nucleosomes in NDR
). To test this, we introduced the competition
between nucleosome binding and binding of non-histone
proteins (binding factors near replication origin and GRFs
near promoters) in the following way. Whenever a
nonhistone protein binding region is replicated, that newly
replicated region is free to be occupied by nucleosome and
non-histone protein with probabilities (1 − ) and ( ),
respectively. Typical transcription factor binding free energy
(≈5−15 kcal/mol) can be comparable to the nucleosome
binding free energy at certain sequences (
Experiments have also shown that, at biologically relevant
concentrations, typical transcription factors can have binding rates
comparable to that of nucleosomes (
). Hence we consider
= 0.5 here. In Figure 5C, we present our results of
nucleosome positioning near origin of replication and find that
the inheritance is poor when the non-histone protein
binding probability is small. This is similar to the
experimental observations made by Ramachandran and Heinikoff in
their recent paper (
). We also find that the competition
mostly leads to nucleosome gain in the nucleosome depleted
regions and it influences the inheritance. A similar picture is
also obtained at promoter region where a GRF is
competing with nucleosomes (see Figure 5D). This suggests that
the inheritance of nucleosome positioning also depends on
other factors such as action of non-histone proteins.
Therefore, in some context, transcription may also play an
important role in ‘maturation’ of nucleosome positioning as
indicated in (
In this paper, we have addressed the question of inheritance
of nucleosome organization from parent to daughter,
instantly after replication, by simulating a plausible physical
model. We have used various known information from
published experiments and constructed a model to study the
effect of different replication-related processes on
nucleosome organization in daughter cells. We have first studied
a bare minimum model of the fork movement and
nucleosome deposition behind the fork, which can only produce a
homogeneous nucleosome distribution in the daughter cell
irrespective of parental organization. Since the bare
minimum model has no mechanism to transfer information of
the heterogeneous parental nucleosome organization to the
next generation, we have introduced another physically
important process, which is the pausing of the replication fork
on encountering a nucleosome on the parental chromatin.
This interaction of the fork with nucleosomes have given
some signature of parental organization in the daughter
strand, but the signature has not been precise enough.
Consequently, we introduced sliding of the newly deposited
nucleosomes as reported in recent experiments (
computer simulation we explore the parameter-space and
show that when one has a finite pausing and sliding with
comparable timescales, one gets replicated daughter
chromatin that has similar nucleosome occupancy as that of the
parental chromatin. Our model argues that strongly
positioned nucleosomes act as ‘barriers’ that will make the
replication fork pause for a short period (a period comparable to
the nucleosome sliding timescale) at the site of the strongly
positioned nucleosomes, and this pause will help
transferring the positioning information from parent to daughter.
Nucleosome positioning inheritance at ‘inactive’ gene regions
In the first part of our paper, we have only accounted for
events that would typically occur in an ‘inactive’ gene
region, namely, nucleosome disassembly and related pausing
ahead of the fork, DNA replication, nucleosome
deposition behind the fork and nucleosome sliding. With these
events, we find that the nucleosome positioning can be
inherited given that the pausing timescale is sufficiently big
( p ≥ s). As discussed in the context of Figure 3, a
randomly selected typical gene region with no extra activity due
to non-histone proteins, and an inactive (off) gene promoter
region (e.g. PHO5) can inherit nucleosome positioning from
the parental chromatin. This is consistent with recent
experimental observation that ‘nucleosome positions are
conserved at inactive sites behind replication fork’ (
Our results do not imply that, with pausing, the
inheritance is perfect. There is always some finite amount of
deviation (e.g. Figures 3A and 5B). What our work
suggests is that if pausing happens, it allows the chromatin to
pass some information about the nucleosome positioning to
the daughter chromatin. The duration of pausing will
crucially depend on the local nucleosome stability and hence it
maybe highly heterogeneous. As our results show, if the
nucleosomes are not stable, the pausing and inheritance will
be negligible. Interestingly, nearly all the experiments that
study nucleosome positioning behind the fork report
nonhomogeneous (having peaks and troughs) nucleosome
occupancy pattern immediately after replication (
we show in our work, a minimal model would not give rise
to this heterogeneity (Figure 2). Our results suggest that
nucleosome pausing would lead to inheritance of the
inhomogeneity seen in the parental chromatin. Therefore, one of the
interesting predictions of our model is that pausing would
play a role in giving rise to heterogeneity in nucleosome
Lack of nucleosome positioning inheritance at ‘active’ gene regions
At ‘active’ gene regions, non-histone proteins play
important role––for example, gene regulatory factors. In the
second part of the paper, we extended our model
incorporating binding of different non-histone proteins that compete
with nucleosomes to occupy certain specific sites along the
genome. Our results show that this competition will lead to
imperfect inheritance of nucleosome positioning (Figure 5C
and D). This is also consistent with (
) where they find a
lack of inheritance in nucleosome positioning at such
active sites. This again suggests that many other factors could
influence the positioning of nucleosomes in the daughter
chromatin. Depending on the gene location and the factors
involved the precise nature of nucleosome positioning
inheritance may vary.
Strength and limitations of the model
The strength of our model is that it incorporates various
known experimental features such as nucleosome
deposition behind the replication fork, sliding of newly deposited
nucleosomes, and physically plausible events like
nucleosome pausing. In our work we do not distinguish between
replication of leading versus lagging strand. We find that if
fork pauses for sufficiently long time and there is sufficient
time for remodelling machines to position nucleosomes, the
results that we obtain should be similar for both the strands.
Since the mechanism of replication is different for the
lagging strand, we tried to mimic that in a modified
simulation relevant for the lagging strand (see SI text section 5
and Supplementary Figure S6). We find that results do not
change significantly. However, the model has various
limitations or drawbacks: the first drawback is that we have not
considered the extended size of replisome, which is ≈55 bp
). One reason we did not put in the size of a
replisome is that, during the pause, it may happen that the
replisome would partially unwrap or partially disassemble the
nucleosome (which can be of a few tens of basepairs
comparable to the size of the replisome) before pausing close
to the dyad; this will offset the effect due to the finite size
of the replisome and we will end up with a scenario that is
very similar to what we have obtained here. In other words,
we have not considered the size of a replisome, while we
have assumed that the nucleosome at the fork will occupy
full 150 bp; however, the reality might be that the
nucleosome may unwrap occupying only <100 bp, while the rest
of the space might be occupied by the replisome. In the case
of transcription, it has been reported that the RNA
Polymerase pauses inside the unwrapped nucleosome near the
dyad region (
). This would be mathematically equivalent
of what we did and it will not change our results. The second
limitation is that we have considered nucleosomes as stable
hard-core particles––that is, particles with strong steric
repulsion disfavouring any amount of overlap. However,
partial unwrapping of DNA from nucleosomes has been
observed experimentally (
); this feature as discussed in
earlier works (
) is not included in the current model
and may be addressed in a future work. Another limitation
is that the rates of processes in vivo might be very different
from what we have taken for our simulations. However, we
have explored the parameter-space, and found that our
results will not depend on the precise value of rates; rather,
the results will be true for a range of rates.
One possibility would be to make appropriate modifications
to histones that would stabilise/destabilise the nucleosomes.
This may be achieved by using appropriate histone variants
or by using suitable chemical modifications along the
histone tails. It can be tested whether a less stable (more
stable) nucleosome positioning is poorly (better) inherited or
not. Another way would be to stabilise nucleosomes on the
parent chromatin by inserting artificial sequences (like the
601 sequence). Since the sliding machinery is known to slide
nucleosomes away even from 601-like strongly positioning
), the pause will contribute to the inheritance
of nucleosome positioning at such strongly positioned
Our study can be a first step in the direction of
understanding the mechanism of inheritance of epigenetic information
from parent to daughter, and it introduces strong physical
arguments with predictive power. With our model we have
been able to reproduce the parental nucleosome
organization in the daughter cell with reasonable precision after
disruption due to replication. While in some regions, the
remodeling after replication (e.g. nucleosome rearrangement
related to transcription (
)) might play important role, for
some other regions (like heterochromatin or regions where
the gene is ‘off ’) the positioning of nucleosomes after
replication may not change much. Hence, the inheritance of
precise nucleosome positioning in these regions can be crucial;
an erroneous gene activation due to incorrect epigenetic
information transfer during replication may lead to various
abnormalities and diseases (
). Our results will certainly
be important for these latter regions. Even for regions that
may change their nucleosome positioning after
transcription, it is important to have a proper nucleosome
positioning at all times as incorrect nucleosome positioning may
expose promoters leading to unwanted transcription. We
know that there are many other factors, such as DNA
sequence and chemical modifications of histones, which also
play significant roles in deciding the nucleosome
organization. Further study is required to quantify the significance
of these factors at various stages of the cell cycle.
Supplementary Data are available at NAR Online.
We acknowledge useful discussions with Iestyn Whitehouse,
Geeta Narlikar and Swati Patankar. We also thank
DSTINSPIRE(TB), CSIR(DD), IIT Bombay(RP) for financial
Suggestions for new experiments to test our predictions
Our work predicts that strongly positioned nucleosomes
will induce a pause in the progression of the replication fork,
and this pause will help in transferring nucleosome
positioning information from parent to daughter. One way to
test our predictions is to do experiments with and without
strongly positioned nucleosomes in the parent chromatin.
Indian Institute of Technology Bombay [13IRAWD005];
Council of Scientific and Industrial Research
[03(1326)/14/EMR-II]; Department of Science and
Technology, Ministry of Science and Technology [IFA-13
PH-64]. Funding for open access charge: Department of
Science and Technology, India.
Conflict of interest statement. None declared.
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