Biology subjects

Di Pierro, M.

Publications and source records attributed to Di Pierro, M..

15 recordsLinked to original sources

bioRxiv2026

3D genome architecture regulates the traffic of transcription factors throughout human chromosomes

Transcription factors (TFs) control the rate of transcription of genetic information by binding to specific DNA sequences. The time needed for a TF to find its specific target sites is a bottleneck to the genetic response mechanism. While TF target site search is a well-studied problem, the effect of genome 3D architecture on the TF target search times is poorly understood. Here, we use accurate and cell-specific 3D structural ensembles of human chromosomes to investigate how the spatial organization of binding sites on chromosomes influences the dynamics of TFs. We use Chromatin Immuno-Precipitation data to map the position of binding sites for several TFs on chromosomal structures and simulate the dynamics of individual TF within chromosomal territories. We find that the distribution of binding sites along chromosomes cooperates with the 3D folding of the chromatin fiber to induce dynamics in which TFs tend to visit sites distributed sequentially along the genome. In this way, genome 3D architecture appears to reduce the time each TF spends in the unbound state while commuting from one target site to the other. At the same time, genome 3D architecture further reduces the flux of TFs between binding sites already well separated along the genome, effectively isolating distant clusters of binding sites. We compare the TF traffic patterns generated by the 3D structures of human chromosomes with those generated by several alternative structural models characterized by increasing randomness. Finally, we study the effect of lengthwise compaction and phase separation, known architectural features of the human genome, in TFs target search. In short, our analysis demonstrates that genome architecture regulates the traffic of TFs within chromosomal territories and reduces the time each TF spends commuting between binding sites.

biophysics↗

bioRxiv2025

Random, fragile, or correlated: Mechanisms of synteny decay in mammals

We formalize three models of genome evolution, yielding analytical distributions of synteny block sizes between pairs of genomes. To evaluate each model, we fit theoretical synteny block size distributions to empirical distributions from a comparative analysis of nearly 200 mammalian genomes. Between the random breakage model (RBM), with uniformly distributed breakpoints, the fragile breakage model (FBM) with breakpoint hotspots, and what we term the correlated breakage model (CBM) with pairs of nearby breakpoints, we find that the FBM and CBM are far more consistent with mammalian genome evolution than the RBM. Inferred parameters of each model qualitatively agree with previous characterizations of mammalian genome evolution. The FBM and CBM perform comparably with each other, suggesting that either model could serve as an improved null model of genome evolution to use in statistical tests for syntenic regions that are unlikely to exist due to random chance.

evolutionary biology↗

bioRxiv2025

Understanding the physical processes behind DNA-DNA proximity ligation assays

In the last decade, DNA-DNA proximity ligation assays opened powerful new ways to study the 3D organization of genomes and have become a mainstay experimental technology. Yet many aspects of these experiments remain poorly understood. We study the inner workings of DNA-DNA proximity ligation assays through numerical experiments and theoretical modeling. Chromosomes are modeled at nucleosome resolution and evolved in time via molecular dynamics. A virtual Hi-C experiment reproduces, in-silico, the different steps of the Hi-C protocol, including: crosslinking of chromatin to an underlying proteic matrix, enzymatic digestion of DNA, and subsequent proximity ligation of DNA open ends. The protocol is simulated on ensembles of different structures as well as individual structures, enabling the construction of ligation maps and the calculation of ligation probabilities as functions of genomic and Euclidean distance. The methods help to assess the effect of the many variables of the Hi-C experiment and of subsequent data processing methods on the quality of the final results.

biophysics↗

bioRxiv2025

Quantifying the influence of genetic context on duplicated mammalian genes

Gene duplication is a fundamental part of evolutionary innovation. While single-gene duplications frequently exhibit asymmetric evolutionary rates between paralogs, the extent to which this applies to multi-gene duplications remains unclear. In this study, we investigate the role of genetic context in shaping evolutionary divergence within multi-gene duplications, leveraging microsynteny to differentiate source and target copies. Using a dataset of 193 mammalian genome assemblies and a bird outgroup, we systematically analyze patterns of sequence divergence between duplicated genes and reference orthologs. We find that target copies, those relocated to new genomic environments, exhibit elevated evolutionary rates compared to source copies in the ancestral location. This asymmetry is influenced by the distance between copies and the size of the target copy. We also demonstrate that the polarization of rate asymmetry in paralogs, the "choice" of the slowly evolving copy, is biased towards collective, block-wise polarization in multi-gene duplications. Our findings highlight the importance of genetic context in modulating post-duplication divergence, where differences in cis-regulatory elements and co-expressed gene clusters between source and target copies may be responsible. This study presents a large-scale test of asymmetric evolution in multi-gene duplications, offering new insight into how genome architecture shapes functional diversification of paralogs. Significance statementAfter a gene is duplicated, reduced selective constraints can lead the two copies to rapidly diverge, with one copy often evolving faster and occasionally gaining a new function. We quantify the influence of genetic context in choosing which copy of a duplicated gene has an elevated substitution rate. In a representative dataset of 193 mammalian genomes, we found strong evidence that gene copies pasted into new genomic locations tend to evolve faster than the corresponding copies in ancestral locations, suggesting an important role for the regulatory environment. The asymmetry in evolutionary rates of duplicated genes persists even for very large multigenic duplications, up to the scale of megabases, indicating that regulatory interactions frequently reach farther than previously thought.

evolutionary biology↗

bioRxiv2023

4D Mesoscale liquid model of nucleus resolves chromatin's radial organization

Recent chromatin capture, imaging techniques, and polymer modeling advancements have dramatically enhanced our quantitative understanding of chromosomal folding. However, the dynamism inherent in genome architectures due to physical and biochemical forces and their impact on nuclear architecture and cellular functions remains elusive. While imaging techniques capable of probing the physical properties of chromatin in 4D are growing, there is a conspicuous lack of physics-based computational tools appropriate for revealing the underlying forces that shape nuclear architecture and dynamics. To this end, we have developed a multi-phase liquid model of the nucleus, which can resolve chromosomal territories, compartments, and nuclear lamina using a physics-based and data-informed free energy function. The model enables rapid hypothesis-driven prototyping of nuclear dynamics in 4D, thereby facilitating comparison with whole nucleus imaging experiments. As an application, we model the Drosophila nucleus spanning the interphase and map phase diagram of nuclear morphologies. We shed light on the interplay of adhesive and cohesive interactions within the nucleus, giving rise to distinct radial organization seen in conventional, inverted, and senescent nuclear architectures. The results also show the highly dynamic nature of the radial organization, the disruption of which leads to significant variability in domain coarsening dynamics and, consequently, variability of chromatin architecture. The model also highlights the impact of oblate nuclear geometry and heterochromatin sub-type interactions on the global chromatin architecture and local asymmetry of chromatin compartments.

biophysics↗

bioRxiv2022

An Associative Memory Hamiltonian Model for DNA and Nucleosomes

A model for DNA and nucleosomes is introduced with the goal of studying chromosomes from a single base level all the way to higher-order chromatin structures. This model, dubbed the Widely Editable Chromatin Model (WEChroM), is able to reproduce the complex mechanics of the double helix including its bending persistence length and twisting persistence length, and their respective temperature dependence. The WEChroM Hamiltonian is composed of chain connectivity, steric interactions, and associative memory terms representing all remaining interactions leading to the structure, dynamics, and mechanical characteristics of the B-DNA. Several applications of this model are discussed to demonstrate its applicability. WEChroM is used to investigate the behavior of circular DNA in the presence of positive and negative supercoiling. We show that it recapitulates the formation of plectonemes and of structural defects that relax mechanical stress. The model spontaneously manifests an asymmetric behavior with respect to positive or negative supercoiling, similarly to what was previously observed in experiments. Additionally, we show that the associative memory Hamiltonian is also capable of reproducing the free energy of partial DNA unwrapping from nucleosomes. WEChroM can readily emulate the continuously variable mechanical properties of the 10nm fiber and, by virtue of its simplicity, allows the simulation of molecular systems large enough to study the structural ensembles of genes. WEChroM is implemented in the OpenMM simulation toolkits and is freely available for public use. Author SummaryThe structural ensembles of genes have been so far out of the reach of theoretical and computational investigations because genes are molecular complexes too big to be tackled with even the most efficient computational chemistry approaches and yet too strongly affected by heterogeneous molecular factors to be effectively modeled as a simple polymer. In this work, we develop a computationally efficient, easy-to-use, and widely editable chromatin model to study the principles of DNA folding at the gene scale. Using the framework of Associative Memory Hamiltonians, this model reproduces the structural and mechanical properties of double-stranded DNA and accounts for the effects of nucleosome-forming histone octamers and other proteins bound to DNA. Our results open the path to studying the structural and mechanical ensembles of genetic systems as large as tens of kilobases of chromatin, i.e., the size of mammalian genes.

biophysics↗

bioRxiv2022

Structural Reorganization and Relaxation Dynamics of Axially Stressed Chromosomes

Micromechanical studies of mitotic chromosomes have revealed them to be remarkably extensible objects and informed early models of mitotic chromosome organization. We use a data-driven, coarsegrained polymer modeling approach, capable of generating ensembles of chromosome structures that are quantitatively consistent with experiments, to explore the relationship between the spatial organization of individual chromosomes and their emergent mechanical properties. In particular, we investigate the mechanical properties of our model chromosomes by axially stretching them. Simulated stretching led to a linear force-extension curve for small strain, with mitotic chromosomes behaving about ten-fold stiffer than interphase chromosomes. Studying the relaxation dynamics we found that chromosomes are viscoelastic solids, with a highly liquid-like, viscous behavior in interphase that becomes solid-like in mitosis. This emergent mechanical stiffness in our model originates from lengthwise compaction, an effective potential capturing the activity of loop-extruding SMC complexes. Chromosomes denature under large strains via unraveling, which is characterized by opening of large-scale folding patterns. By quantifying the effect of mechanical perturbations on the chromosomes structural features, our model provides a nuanced understanding of in vivo mechanics of chromosomes.

biophysics↗

bioRxiv2022

Shaping the Genome via Lengthwise Compaction, Phase Separation, and Lamina Adhesion

The link between genomic structure and biological function is yet to be consolidated, it is, however, clear that physical manipulation of the genome, driven by the activity of a variety of proteins, is a crucial step. To understand the consequences of the physical forces underlying genome organization, we build a coarse-grained polymer model of the genome, featuring three fundamentally distinct classes of interactions: lengthwise compaction, i.e., compaction of chromosomes along its contour, self-adhesion among epigenetically similar genomic segments, and adhesion of chromosome segments to the nuclear envelope or lamina. We postulate that these three types of interactions sufficiently represent the concerted action of the different proteins organizing the genome architecture and show that an interplay among these interactions can recapitulate the architectural variants observed across the tree of life. The model elucidates how an interplay of forces arising from the three classes of genomic interactions can drive drastic, yet predictable, changes in the global genome architecture, and makes testable predictions. We posit that precise control over these interactions in vivo is key to the regulation of genome architecture.

biophysics↗

bioRxiv2022

Interphase chromosomes of the Aedes aegypti mosquito are liquid crystalline and can sense mechanical cues

We use data-driven physical simulations to study the three-dimensional architecture of the Aedes aegypti genome. Hi-C maps exhibit both a broad diagonal and compart-mentalization with telomeres and centromeres clustering together. Physical modeling reveals that these observations correspond to an ensemble of 3D chromosomal structures that are folded over and partially condensed. Clustering of the centromeres and telomeres near the nuclear lamina appears to be a necessary condition for the formation of the observed structures. Further analysis of the mechanical properties of the genome reveals that the chromosomes of Aedes aegypti, by virtue of their atypical structural organization, are highly sensitive to the deformation of the nuclei. This last finding provides a possible physical mechanism linking mechanical cues to gene regulation.

genomics↗

bioRxiv2021

Evolutionary differences in the ACE2 reveals the molecular origins of COVID-19 susceptibility

We explore the energetic frustration patterns associated with the binding between the SARS-CoV-2 spike protein and the ACE2 receptor protein in a broad selection of animals. Using energy landscape theory and the concept of energy frustration--theoretical tools originally developed to study protein folding--we are able to identify interactions among residues of the spike protein and ACE2 that result in COVID-19 resistance. This allows us to identify whether or not a particular animal is susceptible to COVID-19 from the protein sequence of ACE2 alone. Our analysis predicts a number of experimental observations regarding COVID-19 susceptibility, demonstrating that this feature can be explained, at least partially, on the basis of theoretical means.

biophysics↗

bioRxiv2021

The interplay of chromatin phase separation and lamina interactions in nuclear organisation

The genetic material of eukaryotes is segregated into transcriptionally active euchromatin and silent heterochromatin compartments. The spatial arrangement of chromatin compartments evolves over the course of cellular life in a process that remains poorly understood. The latest nuclear imaging experiments reveal a number of dynamical signatures of chromatin which are reminiscent of active multi-phase liquids. This includes the observations of viscoelastic response, coherent motions, Ostwald ripening and coalescence of chromatin compartments. There is also growing evidence that liquid-liquid phase separation of protein and nucleic acid components is the underlying mechanism for the dynamical behavior of chromatin. In order to dissect the organizational and dynamical implications of chromatins liquid behavior, we have devised a phenomenological field-theoretic model of nucleus as a multi-phase condensate of liquid chromatin types. Employing the liquid chromatin model of Drosophila nucleus, we have carried out an extensive set of simulations with an objective to shed light on the dynamics and chromatin patterning observed in the latest nuclear imaging experiments. Our simulations reveal the emergence of experimentally detected mesoscale chromatin channels and spheroidal droplets which arise from the dynamic interplay of chromatin type to type interactions and intermingling of chromosomal territories. We also quantitatively reproduce coherent motions of chromatin domains observed in displacement correlation spectroscopy measurements which are explained within the framework of our model by phase separation of chromatin types operating within constrained intra-chromosomal and inter-chromosomal boundaries. Finally, we illuminate the role of heterochromatin-lamina interactions in the nuclear organization by showing that these interactions enhance the mobility of euchromatin and indirectly introduce correlated motions of heterochromatin droplets. SIGNIFICANCE STATEMENTThe latest super-resolution imaging experiments have revealed a surprisingly dynamic and stochastic nature of chromatin in eukaryotic nuclei which is reminiscent of multi-phase fluid behavior. As a result, the concepts from the theory of complex fluids such as phase separation, viscoelasticity, and droplet nucleation have found widespread utility in understanding salient features of nuclear organization. In order to understand and disentangle the complex interplay of forces that contribute to the emergent patterns of organization and dynamics, we have devised a phenomenological field-theoretic model of nucleus as a multi-phase condensate of liquid chromatin types. Armed with a mesoscopic model of nuclear chromatin, we have shed light on the distinct dynamical and structural contributions of chromatin type interactions intermingling of chromosomal territories and lamina binding. We also shed light on the dynamical heterogeneity and coherent motions of chromatin domains which are fully captured by an interplay of micro-phase separation of chromatin types and lamina binding.

biophysics↗

bioRxiv2020

Exploring Chromosomal Structural Heterogeneity AcrossMultiple Cell Lines

We study the structural ensembles of human chromosomes across different cell types. Using computer simulations, we generate cell-specific 3D chromosomal structures and compare them to recently published chromatin structures obtained through microscopy. We demonstrate using a combination of machine learning and polymer physics simulations that epigenetic information can be used to predict the structural ensembles of multiple human cell lines. The chromosomal structures obtained in silico are quantitatively consistent with those obtained through microscopy as well as DNA-DNA proximity ligation assays. Theory predicts that chromosome structures are fluid and can only be described by an ensemble, which is consistent with the observation that chromosomes exhibit no unique fold. Nevertheless, our analysis of both structures from simulation and microscopy reveals that short segments of chromatin make transitions between a closed conformation and an open dumbbell conformation. This conformational transition appears to be consistent with a two-state process with an effective free energy cost of about four times the effective information theoretic temperature. Finally, we study the conformational changes associated with the switching of genomic compartments observed in human cell lines. Genetically identical but epigenetically distinct cell types appear to rearrange their respective structural ensembles to expose segments of transcriptionally active chromatin, belonging to the A genomic compartment, towards the surface of the chromosome, while inactive segments, belonging to the B compartment, move to the interior. The formation of genomic compartments resembles hydrophobic collapse in protein folding, with the aggregation of denser and predominantly inactive chromatin driving the positioning of active chromatin toward the surface of individual chromosomal territories.

biophysics↗

bioRxiv2019

The Nucleome Data Bank: Web-based Resources to Simulate and Analyze the Three-Dimensional Genome

We introduce the Nucleome Data Bank, a web-based platform to simulate and analyze the three-dimensional organization of genomes. The Nucleome Data Bank enables physics-based simulation of chromosomal structural dynamics through the MEGABASE + MiChroM computational pipeline. The input of the pipeline consists of epigenetic information sourced from the Encode database; the output consists of the trajectories of chromosomal motions that accurately predict Hi-C and FISH data, as well as multiple observations of chromosomal dynamics in vivo. As an intermediate step, users can also generate chromosomal sub-compartment annotations directly from the same epigenetic input, without the use of any DNA-DNA proximity ligation data. Additionally, the Nucleome Data Bank freely hosts both experimental and computational structural genomics data. Besides being able to perform their own genome simulations and download the hosted data, users can also analyze and visualize the same data through custom-designed web-based tools. In particular, the one-dimensional genetic and epigenetic data can be overlaid onto accurate three-dimensional structures of chromosomes, to study the spatial distribution of genetic and epigenetic features. The Nucleome Data Bank aims to be a shared resource to biologists, biophysicists, and all genome scientists. The Nucleome Data Bank (NDB) is available at https://ndb.rice.edu.

bioinformatics↗

bioRxiv2018

Walking along chromosomes with super-resolution imaging, contact maps, and integrative modeling

Chromosome structure is thought to be crucial for proper functioning of the nucleus. Here, we present a method for visualizing chromosomal DNA at super-resolution and then integrating Hi-C data to produce three-dimensional models of chromosome organization. We begin by applying Oligopaint probes and the single-molecule localization microscopy methods of OligoSTORM and OligoDNA-PAINT to image 8 megabases of human chromosome 19, discovering that chromosomal regions contributing to compartments can form distinct structures. Intriguingly, our data also suggest that homologous maternal and paternal regions may be differentially organized. Finally, we integrate imaging data with Hi-C and restraint-based modeling using a method called integrative modeling of genomic regions (IMGR) to increase the genomic resolution of our traces to 10 kb.\n\nOne Sentence SummarySuper-resolution genome tracing, contact maps, and integrative modeling enable 10 kb resolution glimpses of chromosome folding.

genetics↗

bioRxiv2017

De Novo Prediction of Human Chromosome Structures: Epigenetic Marking Patterns Encode Genome Architecture

Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from ChIP-Seq. We exploit the idea that chromosomes encode a one-dimensional sequence of chromatin structural types. Interactions between these chromatin types determine the three-dimensional (3D) structural ensemble of chromosomes through a process similar to phase separation. First, a recurrent neural network is used to infer the relation between the epigenetic marks present at a locus, as assayed by ChIP-Seq, and the genomic compartment in which those loci reside, as measured by DNA-DNA proximity ligation (Hi-C). Next, types inferred from this neural network are used as an input to an energy landscape model for chromatin organization (MiChroM) in order to generate an ensemble of 3D chromosome conformations. After training the model, dubbed MEGABASE (Maximum Entropy Genomic Annotation from Biomarkers Associated to Structural Ensembles), on odd numbered chromosomes, we predict the chromatin type sequences and the subsequent 3D conformational ensembles for the even chromosomes. We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C maps as well as distances measured using 3D FISH experiments. Both sets of experiments support the hypothesis of phase separation being the driving process behind compartmentalization. These findings strongly suggest that epigenetic marking patterns encode sufficient information to determine the global architecture of chromosomes and that de novo structure prediction for whole genomes may be increasingly possible.

biophysics↗