# Bridging spatial and temporal scales of developmental gene regulation

Andres Hernan Cardona Echeverry, Márcia Mesquita Peixoto, Tohn Borjigin, Thomas Gregor

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Andres Hernan Cardona Echeverry, Márcia Mesquita Peixoto, Tohn Borjigin, Thomas Gregor. Bridg- ing spatial and temporal scales of developmental gene regulation. Current Opinion in Genetics and Development, 2025, 92, pp.102328. 10.1016/j.gde.2025.102328. pasteur-04914954v2

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Review

# Bridging spatial and temporal scales of developmental gene regulation

Andrés H Cardona<fnref n="1" />,*, Márcia M Peixoto<fnref n="1" />,*, Tohn Borjigin<fnref n="2" /> and Thomas Gregor<fnref n="1" />,<fnref n="2" />,<fnref n="3" />

<figure><img src="image_3.png" /></figure>

The development of multicellular organisms relies on the precise coordination of molecular events across multiple spatial and temporal scales. Understanding how information flows from molecular interactions to cellular processes and tissue organization during development is crucial for explaining the remarkable reproducibility of complex organisms. This review explores how chromatin-encoded information is transduced from localized transcriptional events to global gene expression patterns, highlighting the challenge of bridging these scales. We discuss recent experimental findings and theoretical frameworks, emphasizing polymer physics as a tool for describing the relationship between chromatin structure and dynamics across scales. By integrating these perspectives, we aim to clarify how gene regulation is coordinated across levels of biological organization and suggest strategies for future experimental approaches.

## Addresses

Corresponding author: Gregor, Thomas (thomas.gregor@pasteur.fr), Gregor, Thomas (@thomasgregor.bsky.social)

**Current Opinion in Genetics & Development** 2025, **92**:102328

This review comes from a themed issue on **Genome Architecture and Expression**

Edited by Anders Sejr Hansen and Marcelo Nollmann

Available online xxxx

https://doi.org/10.1016/j.gde.2025.102328

0959-437X/© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

## Introduction

The development of complex organisms — from a single cell to multicellular tissues — unfolds over extended periods, yet it is driven by molecular events occurring on

much faster, smaller spatiotemporal scales. How information from these rapid, localized events guides organismal development remains poorly understood, requiring a dissection of intermediate steps and their connections.

Transcriptional regulation provides a framework to explore how molecular dynamics influence cellular behaviors and tissue-level processes. Nanometer-scale chromatin interactions with regulatory effectors occur within seconds to minutes (Figure 1a) and, together with micrometer-scale chromatin reorganization over minutes to hours (Figure 1b), shape developmental processes at the tissue and organism levels (Figure 1c). Clarifying how rapid molecular events drive broader changes is essential for resolving the ‘black boxes’ in gene regulation.

At the molecular level, transcription often depends on spatial interactions between gene promoters and cis-regulatory elements (CREs), such as enhancers, located thousands (kb) to millions (Mb) of base pairs apart (Figure 1a). Yet, the precise spatiotemporal nature of enhancer-promoter (E-P) interactions remains unclear, underscoring the complexity of the three-dimensional (3D) chromatin architecture [1]. Advances in high-throughput chromosome conformation capture technologies have revealed multiple levels of chromatin organization — including loops, topologically associating domains (TADs), compartments (A/B), and chromosome territories (Figure 1a,b) [2] — which are increasingly recognized as key regulators of gene expression during development [3]. Understanding how chromatin structure regulates transcription across scales is crucial for linking molecular mechanisms to developmental outcomes (Figure 1c).

This review examines gene regulation at three scales: (1) the locus scale, connecting transcription effectors, E-P interactions, and transcriptional dynamics; (2) the chromatin scale, focusing on the random search process, chromatin structure, and polymeric behavior in long-distance regulation; and (3) the organism scale, where transcriptional programs and genome organization are coordinated across cell populations and tissues. Bridging these scales remains challenging and requires complex model systems, high-resolution techniques, and methods to capture ‘4D’ genome-scale data. While current approaches often trade spatial or temporal

<footnote n="1">¹Department of Stem Cell and Developmental Biology, CNRS UMR3738 Paris Cité, Institut Pasteur, 25 Rue du Docteur Roux, 75015 Paris, France</footnote>

<footnote n="2">²Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA</footnote>

<footnote n="3">³Joseph Henry Laboratories of Physics, Princeton University, Princeton, NJ 08544, USA</footnote>

<footnote>*These authors contributed equally.</footnote>
<figure><img src="image_4.png" /><figcaption>Figure 1</figcaption></figure>

Spatiotemporal scales of gene regulation during development. (a) E-P interactions at the locus scale. Enhancers (blue) and their target promoters (red) interact dynamically through loops that bring them into close proximity (~200 nm) but not direct contact. These E-P loops facilitate transcription initiation, typically occurring in short, stochastic bursts lasting minutes. TF binding, which occurs on even shorter timescales (seconds), contributes to transcriptional activation. Together, these rapid interactions establish the first layer of gene regulation, localized at individual loci. (b) Higher-order chromatin structures at the chromatin scale. Chromatin is organized into TADs, which are megabase-sized regions of increased self-interaction. TADs are further segregated into A and B compartments, reflecting differences in genomic activity and accessibility. Chromosomes occupy distinct, noninterlaced nuclear territories. Chromatin reorganization at this scale occurs over minutes to hours, enabling dynamic adjustments in gene regulation. (c) Gene expression patterns at the organism scale. The coordinated activity of E-P interactions at the locus scale and the dynamic restructuring of chromatin at the chromatin scale together generate spatially and temporally regulated gene expression patterns across tissues and developmental stages. This coordination unfolds over extended timescales, from hours to days, synchronizing gene expression programs across multiple loci and cell types. Shown are examples of the even-skipped (eve) gene in the *Drosophila* embryo at nuclear cycle (n.c.) 14 and the *Brachyury* (*Bra*) gene in the mouse embryo at embryonic (E) days E8 and E9, where gene activity patterns guide tissue formation and body axis specification.

resolution or focus on specific loci — potentially obscuring the full picture — recent publications have discussed these technical biases [1,2,4].

Polymer models offer a promising method to link chromatin structure with dynamic regulatory processes. However, discrepancies between experimental observations and theoretical models underscore the need for a unified framework that integrates transcriptional dynamics and chromatin behavior across scales. Moreover, species-specific characteristics must be considered when extrapolating findings between model organisms. Here, we discuss how polymer models can bridge spatial and temporal dimensions of gene regulation and address the challenges of modeling chromatin, emphasizing the importance of incorporating species-specific factors for a comprehensive understanding of how molecular information integrates during development.

## Integrating molecular dynamics at the gene locus

At the gene locus scale, transcriptional regulation integrates molecular events such as the assembly of transcriptional machinery and RNA polymerase II (Pol II) binding with physical processes like chromatin folding and steric hindrance across diverse spatiotemporal dimensions. Yet, the mechanisms bridging these scales

remain elusive. To initiate transcription, transcription factors (TFs), and other effectors must traverse the crowded nuclear environment to find CREs. Spatial strategies — including condensates and transcriptional hubs — concentrate these effectors, facilitating the assembly of active gene loci [1,5–7].

Once at their targets, the challenge shifts to coordinating rapid TF binding (lasting seconds) with transcriptional bursts that persist for minutes [1,8,9]. Studies of promoters with multiple TF-binding sites reveal that co-operative TF exchange maintains high promoter occupancy, effectively linking the brief TF binding events with longer transcriptional bursts [9,10] (Figure 2a).

E-P communication is central to gene regulation [1,2] (Figure 1a). Although models invoking direct contact or action-at-a-distance have been proposed [1], the transient nature of chromatin configurations complicates this view [11]. Recent studies in mouse embryonic stem cells (mESCs) show that fully extruded loops grouping regulatory units are rare (~3% of the time, lasting 10–30 min), while partially extruded configurations are common (~92% of the time) [12,13]. Constraints imposed by cohesin and CCCTC-binding factor (CTCF) may stabilize chromatin interactions, though whether
<figure><img src="image_5.png" /><figcaption>Figure 2</figcaption></figure>

Mechanisms bridging temporal and spatial scales in transcriptional regulation. (a) Cooperative TF binding and transcriptional bursts. TFs bind and unbind promoters on short timescales (seconds). However, transcriptional bursts typically persist for longer periods (minutes). Continuous TF exchange, particularly at promoters with multiple binding sites, maintains high promoter occupancy, bridging short binding events with transcriptional bursts timescales. Adapted from Pomp et al. [10]. (b) E-P interactions and regulatory steps. Zuin et al. [14] observed a sigmoidal (nonlinear) relationship between E-P contact probabilities and transcription levels, rather than a direct linear correlation. This finding suggests that physical E-P proximity alone does not directly translate to transcriptional output. Instead, a series of intermediate regulatory steps, such as TF recruitment, Mediator complex assembly, pre-initiation complex formation, and RNA polymerase pausing/release, collectively modulate transcription activity. These steps intervene in the integration of rapid E-P interactions with slower transcriptional bursts. (c) Condensates and transcriptional hubs. Transcriptional condensates and microenvironments (~200 nm) concentrate TFs, coactivators, and RNA Pol II, potentially mediating E-P proximity and facilitating the assembly of active transcriptional machinery. Such hubs may influence transcriptional bursting dynamics. (d) Transcription-dependent chromatin reorganization. Hypothetical model illustrating transcription-dependent chromatin decompaction and reorganization. In the inactive state, the locus is highly compacted, limiting regulatory interactions. Chromatin decompaction enhances genome accessibility and allows regulatory elements to reorganize into proximity. This process could stabilize a more confined and reorganized locus configuration, potentially reinforced by transcription. For instance, loci with paired E-P often exhibit smaller E-P separations when transcriptionally active compared to their silent state, where dissociation occurs more rapidly [16].

productive E-P communication persists throughout
transcription or occurs briefly remains open [13,14]. In
fact, the nonlinear, sigmoidal relationship between E-P
contact probabilities and transcription suggests inter-
mediate regulatory steps bridging short-lived E-P con-
tacts and transcriptional bursts [14] (Figure 2b). These
steps, while abstract may represent a combination of
stochastic regulatory processes — possibly involving TF
recruitment, Mediator assembly, pre-initiation complex
formation, and Pol II pausing/release — contributing to
transcriptional activity [14].

Live-cell imaging further indicates that sustained
proximity, rather than direct physical contact, between
E-P pairs is crucial for transcriptional activity. E-P pairs
are typically 150–300 nm apart [15–20], and transcrip-
tional output drops significantly when this proximity is

disrupted [15,16]. However, the molecular signals
transmitted during E-P interactions remain elusive,
particularly given the small size of transcription com-
plexes (10–20 nm) [1].

Emerging evidence suggests that transcriptional hubs,
condensates, and clusters facilitate E-P communication
and influence bursting dynamics [1,5,18,21,22] (Figure
2c). Bursts can be modulated via changes in frequency
(OFF periods) and size (ON periods) [23]. For instance,
embedding promoters within enhancer-associated clus-
ters of Pol II general transcription factors (GTFs) in-
creases burst frequency, implying that nanoscale
clustering extends productive E-P communication [18].
Condensates are also implicated in superenhancer-
driven bursting [21] and may support dynamic contact
models of productive E-P interactions (e.g. ‘hit-and-run’
and ‘kiss-and-kick’: brief E-P encounter phase followed by dissociation) [1,7,21,24]. In mESCs, transcriptional burst size and frequency increase when Pol II condensate is spatially proximal (< 1 µm) to the enhancer and gene locus (‘three-way kissing’), with transcriptional activity decreasing as the condensate moves away [21]. Real-time measurements in Drosophila further suggest that low-transcribing regimes modulate burst frequency, whereas mid-to-high regimes adjust burst size [23].

Transcriptional hubs and condensates do not remain static [8]. In *Drosophila*, hubs mature progressively through compositional changes into Pol II-enriched clusters that drive transcriptional activation. Each compositional transition is both selective and tightly regulated, determining the number of active hubs [25,26]. Notably, these hubs are transient and dispersive, with transcription itself acting as a negative feedback mechanism that limits burst duration by dispersing hub components [25]. For instance, in zebrafish, transcriptional elongation can release E-P contacts, further emphasizing the dynamic nature of these structures [24]. It has also been proposed that hubs can retain a compositional footprint, which may serve as a ‘molecular memory’ to facilitate rapid reactivation [26].

Transcriptional activity also influences larger chromatin structures at the gene locus (Figure 2d). Locus decompaction is commonly associated with transcriptional activity, though its relationship with transcription varies across species. In yeast, highly transcribed genes tend to be less compact [27]. In contrast, mammalian systems show positive correlations between gene activity and locus compaction [28]. Fixed-imaging studies in *Drosophila* embryos suggest that inactive loci are more compact, while active loci show spatial decompaction with enhancers physically closest to the promoter [17]. These findings align with the observation that transcription-associated topologies, such as promoter-promoter and E-P contacts, are more prominent within highly active loci [17,28]. Chromatin decompaction could facilitate regulatory element proximity, which stabilizes a confined, reorganized locus configuration (Figure 2d) [16]. Some models propose that hubs and condensates promote bursting despite increased E-P distances, potentially reflecting spacing mechanisms [6,7,20].

Connecting the spatiotemporal parameters of molecular events, transcription, and E-P dynamics is crucial for uncovering general principles of transcriptional regulation. Key questions include: How frequently do E-P pairs form productive interactions? How long do these interactions last? How do they relate to transcription bursts and locus conformation? Clarifying these mechanisms will be essential for understanding how genetic information is transmitted, integrated, and regulated at the gene locus level.

## Chromatin dynamics across scales: polymer models as bridging tools

At the gene locus scale, transcriptional regulation relies on the coordinated integration of molecular signals and E-P interactions. However, a complete understanding requires examining larger organizational scales, particularly how genes and regulatory elements are positioned within the genome. This section focuses on chromatin dynamics and how spatial organization impacts the search process for regulatory interactions, ultimately shaping transcriptional control.

Certain enhancers, such as the ZRS enhancer located approximately 850 kb from the Shh promoter, can regulate gene expression over vast genomic distances. However, enhancer relocation studies have demonstrated significant distance-dependent effects on transcriptional activation. For instance, as the genomic separation between enhancer and promoter increases, interactions may occur less frequently or with limited functionality [14,15,29–32]. The probability of E-P contact is proposed to follow a nonlinear, sigmoidal relationship with transcriptional output [4,14], where genomic distance influences the frequency of interactions (interburst duration) but has minimal impact on burst size or duration [14]. This nonlinearity helps reconcile the statistical nature of TADs with the moderate transcriptional control exerted by contact probabilities, as recently reviewed [33].

Interestingly, enhancer activity over long distances may be modulated by specific regulatory sequences distinct from those governing cell-type specificity. When such long-range elements are incorporated, short-range enhancers can extend their functional range [30]. Several studies suggest that enhancers possess an intrinsic ‘action radius’ or ‘sphere of influence’, governed by their regulatory strength, which can be expanded by specific regulatory DNA sequences [30] or by forming cooperative networks with other enhancers in multi-enhancer clusters [29]. These mechanisms may allow enhancers to bypass some spatial constraints and gain flexibly to control gene activity over varying distances.

Beyond sequence-based regulation, dynamic processes shaping chromatin architecture also influence long-range regulatory interactions. Mechanisms such as cohesin-and CTCF-mediated loop extrusion help organize chromatin into spatially favorable configurations, bringing distant regulatory elements into proximity [31,34]. Understanding chromatin’s physical organization and dynamics is therefore crucial for elucidating how distal regulatory elements regulate gene expression.

A central challenge in chromatin biology is understanding how a polymer as long as the genome (centimeters to meters) folds into a nucleus only 5–20 µm in
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Modeling approach</th><th>Model</th><th>Description</th><th>Strengths</th><th>Weaknesses</th><th>Data fitting?</th><th>Input</th><th>Output</th><th>Refs.</th></tr></thead><tbody><tr><td rowspan="2">Highly predictive heteromorphic polymer (HIP-HoP)</td><td rowspan="2"></td><td>developed to considering extrusion without an active, ATP-dependent motor but driven by thermal diffusion of transcription-induced supercoiling</td><td>predictions about the dynamics of loop formation</td><td>intensive for large genomic regions</td><td></td><td></td><td></td><td rowspan="2">[11,90]</td></tr><tr><td>Represents chromatin with different levels of compaction (heteromorphic), combined with diffusing protein bridges and loop extrusion</td><td>Accounts for heterogeneity in chromatin properties</td><td>Computationally intensive</td><td>Requires integration of multiple types of experimental data</td><td>No</td><td>CTCF/cohesin binding<br>Epigenetic modifications<br>DNA accessibility</td><td>Simulated contact probabilities maps, FISH</td></tr></tbody></table>

diameter. Chromatin achieves this through a complex interplay of physical forces and biochemical interactions, forming distinct functional domains while remaining dynamic. To address this complexity, polymer physics models and simulations have proven valuable by providing simplified but predictive frameworks to describe chromatin behavior ([35], Table 1).

Polymer models typically reduce molecular detail while preserving essential physical properties (coarse grained). They can be divided into two main classes: data-driven models, which reconstruct 3D chromatin conformations based on experimental data with minimal assumptions, and mechanistic models, which incorporate physical principles and specific hypotheses about chromatin organization, such as loop extrusion and phase separation. Key polymer physics metrics derived from imaging and sequencing studies help characterize chromatin behavior quantitatively: (1) physical distance, *R*(*s*): the average separation between two loci at genomic distance *s*; (2) contact probability, *P*(*s*): the likelihood of physical interaction between loci separated by *s*; (3) mean squared displacement (*MSD*)(*t*): the average movement of chromatin segments over time (*t*), reflecting chromatin diffusion and mobility. Comparing these metrics with polymer models such as the ideal chain, self-avoiding walk, equilibrium globule, and fractal globule can reveal how chromatin is organized and moves within the nucleus (reviewed in [36–38]; Figure 3a).

In a human cell line, contact probability measurements showed an exponent of $\alpha \approx 1$, which is not found in equilibrium polymer states but fits a fractal globule polymer — a knot-free, crumpled polymer state where chromosomes segregate into compact territories and limit interchromosomal contacts (Figure 1b) [39–41]. Subsequent studies have shown $\alpha$ to be system dependent, varying between different chromosomes and species [42].

Simultaneously, chromatin exhibits dynamic properties consistent with the Rouse polymer model, describing chromatin as a flexible, entropic chain driven by thermal fluctuations and entropy [11–13,15,43,44]. This apparent paradox — where chromatin exhibits both fractal compaction and Rouse-like dynamics — was highlighted in recent studies in *Drosophila* embryos. Live imaging of ectopic E-P pairs across genomic distances (50 kb to 3 Mb) revealed that physical distances and interaction probabilities scaled with genomic distance according to the fractal globule model, while *MSD* measurements followed the predictions of an ideal Rouse chain [15]. This anomalous combination of compaction and dynamics has profound implications for transcriptional regulation. For E-P pairs separated by ~3 Mb, the DNA polymer's relaxation time (the time for the polymer to reconfigure) was measured to be 100 times shorter than
<figure><img src="image_6.png" /><figcaption>**Figure 3**</figcaption></figure>

Integrating chromatin dynamics across spatial scales. (a) Scaling relationships predicted by polymer models. The end-to-end distance (R), contact probability (P), and mean square displacement (MSD) are shown as functions of genomic distance (s) and time (t) for two widely used polymer physics models: the Rouse model (green) and the fractal globule model (red). The scaling coefficients for each model are indicated, highlighting the differences in chromatin behavior predicted by these theoretical frameworks. D in the MSD equation represents the diffusion quotient, which reflects the average rate of loci movement and the distance moved over time. (b) Experimental measurements of chromatin mobility. Summary of studies measuring chromatin dynamics using different cell types and genomic contexts. Diffusion exponents (α) and coefficients (D) vary across systems. On the left, the genomic segment sizes tracked in each study are indicated. Studies that simultaneously tracked two regions (e.g. E-P pairs or TAD boundaries) are represented with blue and violet dots. Variations in α and D reveal scale-dependent chromatin dynamics, but differences in experimental methodologies and genomic contexts caution against overgeneralization. (c) Simulations of chromatin mobility across scales. The top panel shows simulated MSD curves for different genomic distances (from 40 kb to 1 Mb) in a polymer with loop extrusion, where smaller distances exhibit higher MSD values and greater constraints [13]. The bottom panel shows MSD values for the center of mass of chromatin segments measured with different probe sizes, indicating higher mobility in smaller regions, as shown by Forte et al. [15]. (d) Dynamic polymer modeling and chromatin behavior. Experimental results suggest that larger chromatin regions exhibit slower dynamics, while smaller scales display more rapid movement. However, as scales approach sub-kilobase resolution, additional factors such as loop extrusion, E-P interactions, transcription, and macromolecular crowding significantly influence chromatin mobility, making predictions more complex. This complexity, represented by the black box with a question mark, underscores the need for dynamic polymer models that incorporate multiple species, scales, and genomic contexts. A more comprehensive model would account for chromatin accessibility, loop density, folding mechanisms, molecular crowding, and transcriptional interference to capture chromatin behavior accurately. n.s. – not shown.

Adapted from Keizer et al., 2022 [43]; Mach et al., 2022 [13]; Brückner et al., 2023 [15]; Gabriele et al., 2022 [12]; Forte et al., 2023 [11]
predicted by either model alone, suggesting active me-
chanisms might assist long-range E-P interactions in
driving gene regulation.

Multiple live imaging studies have consistently shown that chromatin behaves according to the Rouse model ([11–13,15,43,44], Figure 3b). These studies are beginning to shed light on both the slow and fast structural changes of chromatin depending on the spatial scale under investigation (Figure 3b). For example, a 4 Mb subtelomeric region in human cells exhibited subdiffusive motion (α ~ 0.5), being only moderately constrained by nuclear factors such as chromatin interfaces and nuclear landmarks when displaced magnetically [43]. Meanwhile, smaller regions (~8 kb) randomly inserted into mESCs showed similar subdiffusive behavior but with higher effective diffusion coefficient (D), suggesting faster local chromatin movement [13,43]. In *Drosophila* embryos, 5 kb regions separated by ~550 kb exhibited similar dynamics (Figure 3b) [15]. However, tracking the boundaries of a 550 kb TAD in mESCs revealed more restricted motion potentially due to loop extrusion, with *D* values 20-fold lower [12]. Such variations indicate that mobility is strongly influenced by the genomic context in question [45], such as differences in the processes underlying CTCF boundary interactions and E-P search but might also reflect effects of transcription on chromatin mobility or species-specific differences.

Within TADs, physical constraints imposed by loop
extrusion and chromatin compaction can influence reg-
ulatory dynamics by stabilizing regulatory interactions
such as E-P pairing. For example, tracking 8 kb regions
within a neutral TAD in mESCs revealed constrained
subdiffusive motion (α ~ 0.2; Figure 3b) [13]. However,
theoretical models suggest that as genomic regions ap-
proach subkilobase scales, their mobility may either in-
crease or decrease depending on local chromatin
architecture and biochemical interactions [11,13] (Figure
3c). While chromatin can display both slow and fast
dynamic changes, the behavior of chromatin at inter-
mediate scales, such as TADs, remains poorly under-
stood (Figure 3d). These dynamics are critical to
transcriptional regulation, as they likely influence how
enhancers and promoters encounter each other and in-
itiate transcription.

Integrating classical polymer physics models with live-
cell imaging and genome-wide assays has proven in-
valuable for describing chromatin behavior (Table 1).
However, capturing both local and global chromatin
organizations, while integrating E-P dynamics and
transcriptional activity, remains a significant chal-
lenge. Moving forward, combining high-resolution
imaging, advanced polymer simulations, and quanti-
tative models will be crucial for dissecting the multi-
scale regulation of chromatin during gene expression
(Figure 3d).

Coordinating genome organization with
developmental timing

Development is an intricately choreographed multi-
cellular process requiring cells to integrate diverse sig-
nals and coordinate genomic activities with precision to
guide tissue patterning and morphogenesis. While pre-
vious sections have focused on gene regulation at the
individual cell level, development requires scaling up to
the tissue level, where genomic processes must be syn-
chronized across groups of cells. Tracking chromatin
dynamics across cell types is crucial for understanding
how chromatin organization influences cell fate decisions
and drives cellular diversification during development.

Single-cell atlases of *Drosophila* early embryogenesis, integrating chromatin accessibility (ATAC-Seq) and gene expression (RNA-Seq), have revealed that chromatin accessibility often precedes gene expression. This suggests a ‘priming’ mechanism where regulatory regions become accessible before transcription initiates [46]. Consistent with this, loops and CRE hubs form early in cells with distinct fates, preceding both TAD formation and transcriptional activation [47,48].

In mouse embryos, most postgastrulation cells exhibit mild heterogeneity in chromatin conformation at the TAD and A/B compartment levels. However, terminally differentiated cells, such as primitive erythrocytes, display compact, highly organized chromatin folding and strongly demarcated compartments [49]. This suggests that while large-scale chromatin architecture remains relatively stable during early development to maintain cellular plasticity, finer-scale features like E-P contacts may decisively influence cell fate decisions and lineage specification [49–53].

Chromatin in pluripotent cells appears primed for flex-
ibility. Many enhancer regions are pre-accessible, in-
dicating that the genome is organized to support a range
of developmental pathways [52] and allowing rapid re-
sponses to differentiation cues while preserving plasti-
city. As differentiation progresses, chromatin becomes
more specialized. Higher-order chromatin in un-
differentiated mESCs is less compact, more dynamic,
and more homogeneous than in differentiated neuronal
cells, which exhibit greater structural and dynamic het-
erogeneity [54]. *In vivo* studies measuring chromatin’s
viscoelastic properties reveal that undifferentiated
chromatin behaves as a Maxwell fluid, while differ-
entiated chromatin shows both fluid-like and solid-like
phases [54,55]. Euchromatin activity in differentiated
states further promotes segregation and heterochromatin
compaction, potentially stabilizing nuclear architecture
[56]. Yet, the extent to which chromatin structure drives
or responds to differentiation remains an open question.

Two pivotal processes exemplify how development
bridges molecular and organismal scales: zygotic gene
activation (ZGA) and gene patterning. ZGA marks a
critical transition in early development when maternal
signals trigger genome-wide transcription and chromatin
reorganization across the embryo. The earliest com-
partmentalization signals during ZGA typically emerge
at the TAD level — a conserved pattern — though the
timing of A/B compartment formation and loop extrusion
varies across species [57]. For example, A/B compart-
ments appear later in humans than in mice and Droso-
phila. Gene patterning further illustrates this bridging of
scales. In Drosophila, the Bicoid morphogen gradient
initiates a cascade of transcriptional responses across the
embryo. The localized transcriptional readouts of Bicoid
integrate to produce a step-like gradient of hunchback, a
downstream TF that regulates subsequent develop-
mental processes [58]. This integration ensures co-
ordinated patterns of gene expression for body
segmentation and tissue formation, with further refine-
ment provided by cross-regulation and feedback me-
chanisms.

Post-transcriptional regulation is also critical across
scales. RNA metabolism — including transcript diffu-
sion, localization, and fate — significantly contributes to
patterning and morphogenesis. In many organisms, early
developmental decisions rely on the post-transcriptional
control of maternal mRNAs preloaded into the cyto-
plasm before zygotic transcription begins. Additionally,
RNA diffusion and localized translation can modulate
transcript distribution and promote cross-regulation; for
example, localized mRNA translation is involved in sy-
napse formation and asymmetric cell fate decisions
[59,60]. These mechanisms help spatially restricted gene
products influence tissue-wide patterning, further
linking molecular events to organism-scale outcomes.

Taken together, these examples illustrate how devel-
opment achieves precise coordination of gene regulatory
networks across spatial and temporal scales. From
priming of chromatin in pluripotent cells to genome-
wide reprogramming during ZGA and orchestrated gene
expression during tissue patterning, chromatin archi-
tecture emerges as a dynamic regulatory scaffold.
Moving forward, investigating how chromatin structure
and transcriptional activity reinforce each other across
scales will deepen our understanding of development.

**Discussion and future perspectives**

Challenges for modeling scale-dependent chromatin
dynamics

Chromatin displays a broad spectrum of dynamic beha-
viors, from rapid local reorganizations occurring within
seconds to minutes [9–11,15,16] to slower, large-scale
structural changes unfolding over hours to days [3,47,49].
Unraveling the mechanisms bridging these fast and slow
timescales remains essential for linking chromatin

structure with transcriptional regulation and gene ex-
pression control.

The interplay between gene loci dynamics and chro-
matin reorganization highlights the complexity of tran-
scriptional regulation across spatial and temporal scales.
Transcriptional activity can influence chromatin folding
within TADs [11,16,17,28,61] and near TAD boundaries
[62–67]. In turn, chromatin organization impacts tran-
scription through mechanisms such as tethering ele-
ments and insulators [68,69]. Disruptions in these
elements can alter transcriptional regulation, though ef-
fects often appear limited to local chromatin structures
[69]. This emphasizes the challenge of reconciling
higher-order chromatin structure with dynamic tran-
scriptional activity, especially given observations of
large-scale chromatin structure appearing decoupled
from gene expression output [28,47,70–73].

Despite progress in polymer models of chromatin organ-
nization, no single theoretical framework accurately de-
scribes all aspects of chromatin behavior across scales,
and polymer models that incorporate transcription are
only starting to emerge [44]. Existing models often
struggle to incorporate both the dynamic aspects of
transcription and large-scale structural changes. Lever-
aging polymer physics to develop models that integrate
global chromatin dynamics, local CRE activity, and
transcriptional bursts remains a key area for exploration.

A significant barrier to generalizing chromatin behavior
lies in variations across chromatin regions and experi-
mental contexts. Dynamic behaviors can differ de-
pending on region size, simulation scale, and local
chromatin properties, such as loop density, chromatin
accessibility, and macromolecular crowding
[11,13,74,75]. For example, recent loop extrusion
polymer models showed how simulating different
looping mechanisms, topological (where cohesin em-
braces DNA) and nontopological (cohesin acts as a cross-
linker), impacts the observed contact probabilities and
polymer behaviors [75,76]. In the nontopological model,
loops form a comb-like polymer structure with a rigid
central backbone and short, unentangled loops [75].
Conversely, the topological model preserves a linear
polymer structure with more flexible chromatin
loops [76].

The observed discrepancies between chromatin's
structural and dynamic properties underscore the lim-
itations of purely scale-free polymer models [38]. In-
corporating the viscoelasticity of the nucleoplasm [38,77]
and refining heteropolymer models to account for var-
iation along the chromatin fiber, transcription activity,
and regulatory interactions could enhance model accu-
racy. Mechanistic polymer models that integrate these
properties could generate testable predictions, guiding
experimental strategies to better capture chromatin's multiscale behavior.

## Insights into phenotypic and species complexity

The complexity of chromatin architecture highlights that phenotypic diversity and species complexity arise not solely from genomic expansion but from the diversification and refinement of gene regulatory strategies. Though gene expression principles appear highly conserved, species-specific differences in genome organization can significantly influence chromatin structure and transcriptional dynamics. For instance, substantial variation in chromosome size and number between species might influence chromatin compaction mechanisms. Differences in cell cycle duration, particularly during early developmental stages, can further affect or be the consequence of the temporal dynamics of chromatin organization and transcriptional regulation.

Metazoan genomes rely on a combination of loop extrusion and focal DNA-DNA contacts. Vertebrates tend to rely more on loop extrusion [3,68,69], potentially resulting in a more linear chromosomal organization with slower relaxation dynamics due to persistent long-range correlations [75,76]. In contrast, invertebrates like flies exhibit more focal contacts [68,69], which may lead to a comb-like chromatin organization at smaller scales, allowing for faster domain dynamics as predicted by loop extrusion simulations [75,76].

Throughout development, cells must synchronize rapid changes in genome architecture with transcriptional programs. Elements such as CTCF binding and cohesin-mediated extrusion likely act as temporal regulators [3], facilitating genome compartmentalization while preserving nuclear organization. Species-specific differences in these regulatory mechanisms could influence the timing of chromatin reorganization and developmental progression, adding a layer of complexity to cross-species comparisons of gene regulation.

## Concluding remarks and open questions

Despite substantial progress, several critical questions remain regarding the interplay between chromatin dynamics and gene regulation:

* Plasticity and precision: How do chromatin dynamics maintain both regulatory flexibility and precise developmental coordination across scales?

* Temporal control: What additional mechanisms contribute to the temporal regulation of chromatin and transcriptional programs?

* Species-specific variation: How do species-specific differences in genome organization impact regulatory complexity and developmental timing?

* Feedback mechanisms: To what extent do transcriptional bursts actively reshape chromatin architecture?

Addressing these questions will require continued exploration of both experimental and theoretical approaches that capture the temporal and spatial dimensions of chromatin regulation during development. Advancing multiscale models, while integrating insights from polymer physics, will be critical for uncovering generalizable principles of gene regulation across species.

## Data Availability

No data were used for the research described in the article.

## Declaration of Competing Interest

Thomas Gregor reports financial support was provided by Institut Pasteur. Thomas Gregor reports financial support was provided by Princeton University. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

We thank D. Brückner and B. Zoller for careful reading and comments on the manuscript.

This work was supported in part by the European Research Council grant DynaTrans (101118866); by U.S. National Science Foundation (NSF), through the Center for the Physics of Biological Function (PHY-1734030); and by U.S. National Institutes of Health (NIH) Grants R01GM097275, U01DA047730, and U01DK127429.

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