High-resolution Hi-C analyses have traditionally leaned on hundreds of millions of sequenced read pairs, a convention driven more by precedent than by evidence. The problem is that no one had systematically established the minimum depth required for the different classes of features that researchers routinely compute from contact maps. Granovsky and Polovnikov tackled this by performing progressive random subsampling of twelve Hi-C libraries spanning multiple cell types and experimental protocols. By repeatedly downsampling each library to different depths, they could track how each derived metric fluctuated as data became sparser, effectively simulating dozens of cheaper experiments from every expensive one already in hand.

The crucial innovation lies in how the authors defined sufficiency. Rather than declaring a depth adequate when a metric reached some arbitrary fraction of its full-depth value, they introduced a biologically motivated criterion grounded in the variability between independent biological replicates. The logic is elegant: if the scatter in a metric caused by reducing sequencing depth falls below the scatter observed between genuine replicate experiments, then adding more reads cannot improve the estimate any further, because biological noise has become the dominant source of variation. The required depth for each metric, then, is the point at which subsampling-induced scatter first reaches that replicate-level floor.

Applying this criterion across their panel of libraries produced strikingly different thresholds for different metrics. The genome-average loop-density estimate, derived from the log-derivative of the contact probability function P(s), reached its biological floor at approximately seven million read pairs. The genome-average loop-size estimate required roughly twenty million. Insulation scores, which quantify the depletion of contacts at boundaries between chromatin domains, needed around eighty million read pairs. And compartment eigenvectors, the principal descriptors of active versus inactive chromatin organization, demanded approximately one hundred ten million read pairs when computed at one-hundred-kilobase resolution. Compartment, insulation, and boundary analyses were performed on a subset of nine libraries with comparable full-depth coverage, while loop inference was evaluated across all twelve.

These numbers carry real weight for experimental design. Loop density and loop size, which reflect the fingerprint of the loop-extrusion process that shapes chromatin into loops anchored by CTCF and cohesin, turn out to be remarkably cheap to measure accurately at the genome-wide level. A lab interested primarily in global extrusion characteristics can obtain biologically saturated estimates with a small fraction of the sequencing typically deployed. In contrast, compartment eigenvectors at kilobase resolution sit at the expensive end of the spectrum, approaching the very depths that have become standard practice in high-resolution studies. The hierarchy of requirements means that a one-size-fits-all sequencing budget inevitably overpays for some measurements and may still underdeliver on others.

Perhaps the most consequential finding is that for every metric examined, depth-induced variability fell below biological replicate variability well before full sequencing depth was reached. In other words, the marginal value of additional reads on a single library diminishes to zero long before the deepest libraries stop yielding information. Once the subsampling scatter hits the replicate floor, extra sequencing refines nothing that matters, because the remaining uncertainty reflects genuine biological variation between cell populations rather than statistical noise. This reframes the entire question of depth: the ceiling is set not by the sequencer but by the biology itself.

The authors are careful to delineate the scope of their conclusions. The thresholds they report apply to genome-averaged characteristics, not to local metrics at specific genomic loci. A researcher hunting for a boundary shift at a particular disease-associated locus, or validating a single enhancer-promoter loop, faces a different statistical regime in which rare contacts must be sampled densely enough to resolve one narrow window of the genome. Genome-wide averages benefit from the law of large numbers across millions of loci, which is precisely why they saturate at comparatively modest depths, while locus-specific calls cannot borrow strength from the rest of the map in the same way.

The practical upshot for the field is a reallocation argument. If global biophysical features are the goal, the analysis suggests that increasing the number of biological replicates is likely to improve inference more effectively than sequencing individual libraries to greater depth. Multiple shallower libraries sample the true biological heterogeneity of a cell type, whereas one ultra-deep library samples a single biological state with precision that quickly becomes redundant. For groups planning Hi-C campaigns, this means the sequencing budget conversation should begin with the specific metrics to be computed, not with a blanket target of hundreds of millions of read pairs per sample.

The study also carries methodological significance for how the community benchmarks genomics pipelines. Subsampling-based calibration against replicate variability offers a general template that could be extended to other contact-map assays, such as Micro-C, and to other classes of derived quantities beyond those examined here. Because the work relied entirely on publicly available sequencing datasets, with no new human or animal data generated, it demonstrates how reanalysis of existing archives can yield design guidance of immediate value to the field. The research was supported by the Russian Science Foundation, with additional support to Polovnikov from the Alexander von Humboldt Foundation.

As Hi-C and its descendants become routine tools in chromatin biology, genome assembly, and disease genomics, the economics of sequencing decisions increasingly shape what questions laboratories can afford to ask. Granovsky and Polovnikov have converted a folk assumption about depth into a quantified, metric-by-metric benchmark, and in doing so they have handed experimentalists a map of where each additional million read pairs stops buying accuracy and starts buying only cost. For a field that has often equated more data with better science, the message is a bracing one: sometimes the deepest insight comes from knowing exactly when to stop sequencing.

Subject of Research: Sequencing depth requirements for Hi-C-derived chromatin metrics

Article Title: Systematic assessment of sequencing depth requirements for Hi-C-derived metrics

Article References: Systematic assessment of sequencing depth requirements for Hi-C-derived metrics. (n.d.). https://doi.org/10.1186/s12864-026-13455-7

Image Credits: AI Generated

DOI: 10.1186/s12864-026-13455-7

Keywords: Hi-C, sequencing depth, chromatin organization, A/B compartments, insulation score, loop extrusion, contact probability, biological replicates, benchmark, genomics, next-generation sequencing, chromatin structure

A study published on September 22 in the journal Molecular Cell by researchers at The Ohio State University and the University of Zurich shows that linker histone H1 wanders aimlessly inside the cell even when its target, a nucleosome with spooled-up segments of DNA, is directly in front of it. Although H1 binds readily to two DNA strands that stick out from the nucleosome, it struggles to bind to the nucleosome itself. Only when a chaperone protein escorts it does H1 successfully load onto the nucleosome and carry out its gene-silencing role. The finding fills a long-standing gap in scientists’ understanding of how one of the genome’s most important architectural proteins finds its proper place.

The research team, led by first author Ehsan Akbari, a research scientist in the laboratory of senior author Michael Poirier, professor of physics at The Ohio State University, tackled the question with single-molecule experiments. Rather than averaging the behavior of millions of molecules together, single-molecule methods allow researchers to quantify molecular motions and interactions one molecule at a time, watching individual H1 proteins and their nucleosome targets before, during and after H1 bound to the DNA and to the center of the nucleosome. The team combined optical tweezer instrumentation, which uses highly focused laser light to manipulate and measure single molecules, with single-molecule fluorescence measurements to visualize the process in real time.

“Many proteins are dynamic, and the way you get at mechanistic dynamic information is by doing these single-molecule studies where you literally can watch in real time what individual molecules are doing,” Poirier said. This approach proved essential for a protein whose behavior defied expectations. When the researchers observed H1 in action, they found that the protein continues to move around even after it binds to DNA. More strikingly, instead of loading onto the nucleosome by way of the DNA it had attached to, the protein reflects away from the nucleosome entirely.

“It moves around and doesn’t even go to the nucleosome, which I didn’t believe,” Poirier said. That unexpected observation prompted the team to hypothesize that a chaperone protein might be the missing link in the loading process. Chaperone proteins are known to assist other proteins in folding, targeting and assembly, and three linker histone chaperone proteins were already known to science. When the researchers added these chaperones to their experiments, the results were dramatic.

“Amazingly, the chaperones did a bunch of things to regulate how H1 goes around and how it actually finds and gets onto nucleosomes. And that’s the main point, that people have not understood how H1 loads and gets onto a nucleosome,” Poirier said. “What we found was that it actually will directly load and likes to slide along DNA – we also didn’t even know that it would do that – but it needs a chaperone to help get onto the actual nucleosome.” The experiments revealed that H1 can load directly onto DNA and slide along it, a previously unknown behavior, but the final step of binding to the nucleosome core requires chaperone assistance.

The biological stakes of this process are considerable. Every cell in a plant, animal or human contains the organism’s entire genome, and nucleosomes fold in on each other, clumping together to form chromatin. Linker histone H1’s job is to facilitate chromatin compaction, ensuring that DNA segments containing genes the cell is not using stay wrapped up and unavailable for expression. “We know that H1 is important for compacting the genome, which is important for regulating gene expression,” Poirier said. “In the genome, regions that are going to be compacted are loaded with a lot of H1, while regions that are more open are going to have less H1.”

Most genes in any given cell are turned off at any moment, because only a small fraction of the genome is active in a particular cell type. Maintaining the silent majority in compacted states is therefore a fundamental requirement of cellular life, and H1 is a central player in that maintenance. “H1 is a key regulator of which genes are being used by a cell and which genes are not,” Poirier said. “If you want to understand how disease develops because gene expression is no longer working properly, then you need to understand how H1 works. Once you understand this, then you open up the possibility for new therapies that counteract this cause of disease.”

The connection to disease is not hypothetical. H1 is well known for its role in compacting genes and for its connection to cancer when it undergoes mutation. Mutations in linker histone genes and alterations in how H1 is deployed across the genome can disrupt the careful balance between open, active chromatin and closed, silent chromatin, contributing to the misregulated gene expression that characterizes cancer cells. Understanding the mechanics of how H1 reaches nucleosomes in the first place gives researchers a new handle on where this process could go wrong.

Though the work does not tell the entire H1 story, the step-by-step visualizations offer concrete directions for future research. Poirier’s laboratory has previously studied H1 variants and the post-translational modifications that can change H1 targeting and function after the protein has been fabricated by the cell. “One very natural thing to do next is to look at how these variants, post-translational modifications, and, most importantly, cancer-relevant mutations influence H1 properties and function that we are now in a position to measure,” he said. With single-molecule tools now capable of watching H1’s loading pathway in detail, the effects of disease-linked alterations can be tested directly.

The study, titled “Linker histone H1.0 loads onto nucleosomes through multiple pathways that are facilitated by histone chaperones,” was funded by the National Institutes of Health and the U.S. National Science Foundation. In addition to Akbari and Poirier, the co-authors included Nathaniel Burge of Ohio State and Matti Valdimarsson, Aritra Chowdhury and Benjamin Schuler of the University of Zurich. Together, their findings reframe a seemingly simple question – how does a protein find its binding site? – into a multi-step journey involving DNA sliding, unexpected reflection away from targets, and an essential chaperone handoff, deepening the mechanistic picture of how cells keep their vast genomes organized and their genes properly silenced.

Subject of Research: How linker histone H1 is targeted to nucleosomes with the help of histone chaperone proteins

Article Title: Protein key to cells’ gene regulation needs a chaperone to do its job

Article References: Protein key to cells’ gene regulation needs a chaperone to do its job. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: linker histone H1, nucleosome, chromatin compaction, gene regulation, histone chaperones, single-molecule imaging, optical tweezers, epigenetics, cancer mutations, Molecular Cell, Ohio State University, DNA packaging

The technical hurdle the team faced is one that has haunted genome biologists for years: the three-dimensional arrangement of enhancers and promoters at the scale of individual nucleosomes—the fundamental spools around which DNA wraps—has remained essentially invisible. Popular chromosome conformation capture methods such as Hi-C average over millions of cells and blur out anything smaller than tens of kilobases. Super-resolution imaging can reach the nanoscale, but only for a handful of selected loci at a time. To bridge the gap, the researchers developed a simulation framework that leverages region-capture Micro-C contact maps, an assay that zooms in on megabase-scale windows with nucleosome-level resolution, to infer full conformational ensembles of genomic regions.

A central innovation of the work is a data-processing step the authors call neighbor balancing. Standard Micro-C analysis assumes that contact density is uniform across the genome, an assumption that quietly erases one of the most biologically meaningful signals: the fact that some stretches of DNA are simply more densely packed, and therefore more frequently in contact, than others. The new balancing strategy identifies variation in contact density instead of normalizing it away. When the team applied the method, sharp dips in contact density appeared precisely at active promoters and enhancers—places where the chromatin fiber opens up and nucleosomes thin out. These dips had been smoothed over in coarser, genome-wide datasets, but region-capture data preserved them, and neighbor balancing made them interpretable.

With the corrected contact maps in hand, the researchers turned to a maximum-entropy inversion approach, a technique rooted in statistical mechanics that finds the least-biased set of polymer structures consistent with the experimental constraints. The resulting simulated ensembles were then put through a battery of validation tests. The simulated structures reproduced pairwise distance distributions measured independently by chromatin tracing, a super-resolution imaging method that follows the positions of dozens of genomic loci in single cells. The simulations also contained packing domains and nucleosome clutches—discrete clusters of neighboring nucleosomes—matching structures that electron microscopy and super-resolution imaging studies had previously observed directly in cells. In other words, the model did not merely fit the data it was trained on; it recovered structural features seen by entirely different experimental techniques.

The most striking finding emerged when the team examined what those structures actually look like. Far from being uniformly open, euchromatin generally forms condensed domains with packing densities comparable to those of heterochromatin. The difference lies in scale: euchromatic domains are smaller than their heterochromatic counterparts, but the chromatin fiber inside them is nearly as tightly packed. Local nucleosome concentrations inside domain interiors frequently exceeded 400 micromolar, an extraordinarily crowded environment for DNA. This result aligns with a growing body of imaging evidence suggesting that so-called open chromatin is condensed but liquid-like in living cells, and it forces a rethinking of what the light and dark bands of classical cytology actually represent.

If euchromatin is mostly dense, how do genes get read? The answer, according to the simulations, lies in the geometry of the domain surfaces. Kilobase-scale regions at promoters and enhancers often protrude from the condensed domains, extending outward into the surrounding nuclear space where they become highly accessible. The team found that protrusion probability, the positions of clutch boundaries, and local contact density all correlate closely with ATAC-seq coverage, a genome-wide measure of chromatin accessibility. Where the fiber pokes out of a domain, transcription factors can find their binding sites; where it is buried inside, it cannot. Accessibility, in this picture, is not a bulk property of open chromatin but a surface phenomenon.

This arrangement effectively compartmentalizes regulatory elements from the surrounding chromatin, and the authors argue that the geometry serves a functional purpose. By lifting enhancers and promoters onto domain surfaces, the cell facilitates protein binding and enhancer–promoter communication, the long-range conversations between distant regulatory elements that switch genes on. The condensed cores may act as scaffolds that keep related regulatory elements in physical proximity, while the exposed protrusions provide the docking sites. The study also found that both packing domains and clutches tend to be smaller around ATAC-seq peaks, suggesting that local accessibility reshapes chromatin organization at multiple scales simultaneously.

The hierarchical picture that emerges runs from nucleosomes to clutches to domains, and it holds across species and cell types. The team validated their framework in mouse embryonic stem cells and in several human cell lines, finding condensed domains throughout. Even when the researchers examined data from cells depleted of cohesin, the ring-shaped protein complex that extrudes DNA loops, the local structure was largely maintained: chromatin expanded at large scales, but clutch-scale organization and the correlation between protrusions and accessibility persisted. This indicates that the condensed-domain architecture of euchromatin is not simply a byproduct of loop extrusion but reflects more fundamental physicochemical interactions within the chromatin fiber itself.

The implications reach well beyond structural biology. Misregulated enhancer–promoter communication underlies many developmental disorders and cancers, and drugs that target chromatin regulators, such as bromodomain inhibitors, are already in clinical use. A model in which accessibility depends on whether a regulatory element sits on a domain surface offers a concrete structural hypothesis for how such drugs work and why their effects are so context-dependent. It also reframes a long-standing question in the field: rather than asking how euchromatin stays open, biologists may now ask how specific regulatory elements are actively extruded or maintained on domain surfaces, and what molecular machinery performs that positioning.

The study’s computational framework, along with its simulation trajectories and analysis code, has been made publicly available, allowing other groups to apply the approach to their own region-capture datasets. As region-capture Micro-C spreads through the genomics community, the MIT team’s method could become a standard tool for converting contact maps into physically realistic, nucleosome-resolution structures. What began as a technical exercise in matrix balancing has delivered a conceptual shift: the active genome is not a loose tangle waiting to be read, but a dense, well-organized material whose most important working parts hang, deliberately and accessibly, on the outside.

Subject of Research: Three-dimensional organization of euchromatin and regulatory elements at nucleosome resolution

Article Title: Euchromatin forms condensed domains with short active regions on the surface

Article References: Paggi, J. M., Long, L. Y., & Zhang, B. (2026). Euchromatin forms condensed domains with short active regions on the surface. Nature Genetics. https://doi.org/10.1038/s41588-026-02775-9

Image Credits: AI Generated

DOI: 10.1038/s41588-026-02775-9

Keywords: chromatin, euchromatin, heterochromatin, nucleosomes, Micro-C, enhancers, promoters, gene regulation, 3D genome organization, polymer simulations, chromatin accessibility, super-resolution imaging

Chromatin is the molecular framework that determines how DNA is packaged and interpreted inside a cell. Long strands of DNA are wrapped around proteins called histones, and chemical modifications attached to those histones help identify regions that should be read, paused or silenced. This system enables cells carrying the same genome to develop into radically different forms, such as neurons, liver cells, roots or leaves. When chromatin regulation fails, genes can become active or inactive at the wrong time, contributing to conditions including cancer and other diseases.

The chemical marks involved in this process are thought to have been present in the Last Eukaryotic Common Ancestor, or LECA, a single-celled organism that lived approximately two billion years ago and gave rise to modern animals, plants, fungi and protists. Many of the enzymes that add or remove histone modifications are still shared across these lineages. Yet most detailed knowledge of how the system works has come from a small collection of laboratory organisms, including humans, mice, fruit flies, baker’s yeast and the model plant Arabidopsis thaliana. The new study extends that view to branches of the eukaryotic tree that have largely been missing from chromatin research.

“The cell’s instructions for activating genes are essentially the same in a human, a sea anemone and a soil amoeba,” says Arnau Sebé-Pedrós, an ICREA Research Professor at the CRG and senior author of the study. “But the instructions for silencing genes and other genomic elements like transposons have been continuously evolving since our last common eukaryotic ancestor. Different branches of life have developed different molecular toolkits to do the same thing.”

To make the comparison possible, the researchers developed iChIP2, an expanded version of a chromatin-profiling method. The technique uses molecular barcodes to label chromatin from multiple species and analyze the samples together in a single experiment. This design makes it possible to compare histone modifications under consistent experimental conditions while working with very small quantities of biological material. The approach is particularly valuable for organisms that are difficult to grow or that have not previously had their epigenetic states mapped.

The team used iChIP2 to examine twelve histone modifications across twelve phylogenetically diverse species. The collection included the soil amoeba Acanthamoeba castellanii, the freshwater amoeba Naegleria gruberi, the ciliate Tetrahymena thermophila, the chytrid fungus Spizellomyces punctatus, baker’s yeast Saccharomyces cerevisiae, the ichthyosporean Creolimax fragrantissima, the marine predator Bigelowiella natans, the alga Guillardia theta, the plants Arabidopsis thaliana and Physcomitrium patens, the social amoeba Dictyostelium discoideum and the sea anemone Nematostella vectensis. Several of these species had never undergone detailed chromatin mapping.

Across the organisms, active genes carried a highly similar chromatin signature. Histone modifications associated with transcription tended to cluster around the beginning of a gene and extend across the gene body, indicating that the basic molecular language for gene activation has remained stable since early eukaryotic evolution. Repressed genes, however, displayed strikingly different patterns. Some species used separate modifications to silence transposable elements and inactive genes, while others combined multiple repressive marks on the same stretches of DNA. In Acanthamoeba, a modification commonly associated with active genes in animals appeared to have been repurposed for gene repression.

The researchers propose that much of this diversity reflects an evolutionary struggle between host genomes and parasitic genetic material. Transposable elements, often called jumping genes, can copy or move themselves to new positions in a genome, potentially disrupting genes or altering chromosome structure. Endogenized viruses and other mobile sequences can also persist within genetic material and evolve ways to escape cellular defenses. In humans, transposable-element-derived sequences make up approximately half of the genome. Because these elements differ between lineages, the systems used to suppress them may also have diverged.

“If a species loses its repressive mechanisms completely, it can’t tolerate parasitic elements like transposable elements or endogenized viruses,” Sebé-Pedrós says. “The result is that it’s no longer there. It’s dead.” Over hundreds of millions of years, this pressure may have produced a series of lineage-specific solutions, with chromatin marks and the enzymes that control them repeatedly adapted, combined or reassigned. Some mechanisms originally evolved to restrain mobile DNA may later have been recruited to regulate ordinary genes and other genomic regions.

The results arrive as projects such as the Earth BioGenome Project and the Wellcome Sanger Institute’s Tree of Life programme accelerate the sequencing of species from across the planet. Genome sequences reveal an organism’s genetic parts list, but they do not fully explain when those genes are active or how potentially harmful sequences are controlled. By enabling chromatin comparisons across unfamiliar species, iChIP2 could help add this regulatory layer to future biodiversity studies. The researchers say that examining more branches of life may reveal additional strategies for controlling DNA—and clarify how the molecular systems underlying health, disease and genome stability evolved.

Subject of Research: Comparative evolution of chromatin regulation and histone modifications across diverse eukaryotic species.

Article Title: Diversity and evolution of chromatin regulatory states across eukaryotes

Web References: https://doi.org/10.1038/s41588-026-02672-1

References: Nature Genetics, “Diversity and evolution of chromatin regulatory states across eukaryotes,” DOI: 10.1038/s41588-026-02672-1.

Image Credits: Sean Montgomery/Centro de Regulación Genómica

Keywords: chromatin, histone modifications, gene regulation, epigenetics, eukaryotes, transposable elements, endogenized viruses, genome evolution, iChIP2, comparative genomics