Biology subjects

Fiorillo, L.

Publications and source records attributed to Fiorillo, L..

5 recordsLinked to original sources

bioRxiv2025

Specialised super-enhancer networks in stem cells and neurons

Super-enhancers (SEs) are clusters of enhancers with high transcriptional activity that play essential roles in defining cell identity through regulation of nearby genes. SEs preferentially form multiway chromatin interactions with other SEs and highly transcribed regions in embryonic stem cells. However, the properties of the interacting SEs and their specific contributions to complex regulatory interactions in differentiated cell types remain poorly understood. Here, we compare the structural and functional properties of SEs between embryonic stem cells (ESCs) and dopaminergic neurons (DNs) by combining Genome Architecture Mapping (GAM), chromatin accessibility, histone modification, and transcriptome data. Most SEs are cell-type specific and establish extensive pairwise and multiway chromatin interactions with other SEs and genes with cell-type specific expression. SE interactions span megabase genomic distances and frequently connect distant topologically associating domains. By applying network centrality analyses, we detected SEs with different hierarchical importance. Highest network centrality SEs contain binding motifs for cell-type specific transcription factors, and are candidate regulatory hubs. The functional heterogeneity of SEs is also highlighted by their organisation into modular sub-networks that differ in structure and spatial scale between ESCs and DNs, with more specific and strongly connected SE modules in post-mitotic neurons. Our results uncover both the high complexity and specificity of SE-based 3D regulatory networks and provide a resource for prioritizing SEs with potential roles in transcriptional regulation and disease.

genomics↗

bioRxiv2021

Polymer physics and machine learning reveal a combinatorial code linking chromatin 3D architecture to 1D epigenetics

The mammalian genome has a complex 3D organization, serving vital functional purposes, yet it remains largely unknown how the multitude of specific DNA contacts, e.g., between transcribed and regulatory regions, is orchestrated by chromatin organizers, such as Transcription Factors. Here, we implement a method combining machine learning and polymer physics to infer from only Hi-C data the genomic 1D arrangement of the minimal set of binding sites sufficient to recapitulate, through only physics, 3D contact patterns genome-wide in human and mouse cells. The inferred binding sites are validated by their predictions on how chromatin refolds in a set of duplications at the Sox9 locus against available independent cHi-C data, showing that their different phenotypes originate from distinct enhancer hijackings in their 3D structure. Albeit derived from only Hi-C, our binding sites fall in epigenetic classes that well match chromatin states from epigenetic segmentation studies, such as active, poised and repressed states. However, the inferred binding domains have an overlapping, combinatorial organization along chromosomes, missing in epigenetic segmentations, which is required to explain Hi-C contact specificity with high accuracy. In a reverse approach, the epigenetic profile of binding domains provides a code to derive from only epigenetic marks the DNA binding sites and, hence, the 3D architecture, as validated by successful predictions of Hi-C matrices in an independent set of chromosomes. Overall, our results shed light on how complex 3D architectural information is encrypted in 1D epigenetics via the related, combinatorial arrangement of specific binding sites along the genome.

molecular biology↗

bioRxiv2020

Chromatin folding variability across single-cells results from state degeneracy in phase-separation

Chromosome spatial organization controls functional interactions between genes and regulators, yet the molecular and physical mechanisms underlying folding at the single DNA molecule level remain to be understood. Here we employ models of polymer physics to investigate the conformations of two 2Mb-wide DNA loci in human HCT116 and IMR90 wild-type and cohesin depleted cells. Model predictions on the 3D structure of single-molecules are consistently validated against super-resolution single-cell imaging data, providing evidence that the architecture of the studied loci is controlled by a thermodynamics mechanism of polymer phase separation whereby chromatin self-assembles in segregated globules. The process is driven by interactions between distinct types of cognate binding sites, correlating each with a different combination of chromatin factors, including CTCF, cohesin and histone marks. The intrinsic thermodynamics degeneracy of conformations results in a broad structural and time variability of single-molecules, reflected in their varying TAD-like contact patterns. Globules breathe in time, inducing stochastic unspecific interactions, yet they produce stable, compact environments where specific contacts become highly favored between regions enriched for cognate binding sites, albeit characterized by weak biochemical affinities. Cohesin depletion tends to reverse globule phase separation into a coil, randomly folded state, resulting in much more variable contacts across single-molecules, hence erasing population-averaged patterns. Overall, globule phase separation appears to be a robust, reversible mechanism of chromatin organization, where stochasticity and specificity coexist.

molecular biology↗

bioRxiv2020

Comparison of the Hi-C, GAM and SPRITE methods by use of polymer models of chromatin

Powerful technologies have been developed to probe chromatin 3D physical interactions genome-wide, such as Hi-C, GAM and SPRITE. Due to their intrinsic differences and without a benchmarking reference, it is currently difficult to assess how well each method represents the genome 3D structure and their relative performance. Here, we develop a computational approach to implement Hi-C, GAM and SPRITE in-silico to compare the three methods in a simplified, yet controlled framework against known polymer 3D structures. We test our approach on models of three 6-Mb genomic regions, around the Sox9 and the HoxD genes in mouse ES cells, and around the Epha4 gene in mouse CHLX-12 cells. The model-derived contact matrices consistently match Hi-C, GAM and SPRITE experiments. We show that in-silico Hi-C, GAM and SPRITE average data are overall faithful to the 3D structures of the polymer models. We find that the inherent variability of model single-molecule 3D conformations and experimental efficiency differently affect the contact data of the different methods. Similarly, the noise-to-signal levels vary with genomic distance differently in in-silico Hi-C, SPRITE and GAM. We benchmark the performance of each technology in bulk and in single-cell experiments, and identify the minimal number of cells required for replicates to return statistically consistent chromatin contact measures. Under the same experimental conditions, SPRITE requires the lowest number of cells, Hi-C is close to SPRITE, while GAM is the most reproducible method to capture interactions at large genomic distances.

biophysics↗

bioRxiv2020

Cell-type specialization in the brain is encoded by specific long-range chromatin topologies

Neurons and oligodendrocytes are terminally differentiated cells that sustain cascades of gene activation and repression to execute highly specialized functions, while retaining homeostatic control. To study long-range chromatin folding without disturbing the native tissue environment, we developed Genome Architecture Mapping in combination with immunoselection (immunoGAM), and applied it to three cell types from the adult murine brain: dopaminergic neurons (DNs) from the midbrain, pyramidal glutamatergic neurons (PGNs) from the hippocampus, and oligodendroglia (OLGs) from the cortex. We find cell-type specific 3D chromatin structures that relate with patterns of gene expression at multiple genomic scales, including extensive reorganization of topological domains (TADs) and chromatin compartments. We discover the loss of TAD insulation, or TAD melting, at long genes (>400 kb) when they are highly transcribed. We find many neuron-specific contacts which contain accessible chromatin regions enriched for putative binding sites for multiple neuronal transcription factors, and which connect cell-type specific genes that are associated with neurodegenerative disorders such as Parkinsons disease, or specialized functions such as synaptic plasticity and memory. Lastly, sensory receptor genes exhibit increased membership in heterochromatic compartments that establish strong contacts in brain cells. However, their silencing is compromised in a subpopulation of PGNs with molecular signatures of long-term potentiation. Overall, our work shows that the 3D organization of the genome is highly cell-type specific, and essential to better understand mechanisms of gene regulation in highly specialized tissues such as the brain.

molecular biology↗