Biology subjects

Polovnikov, K. E.

Publications and source records attributed to Polovnikov, K. E..

5 recordsLinked to original sources

bioRxiv2026

Loop statistics and fountain geometry reveal effective two-sided cohesin extrusion and crowding-induced arm desynchronization

Cohesin-driven loop extrusion shapes chromosome organization, yet what determines loop lengths and coordination between the extruding arms in vivo remains unclear. Broad extrusion "fountains" in Hi-C maps point to arm desynchronization, whose physical origin is unknown. Here we develop a kinetic theory of extrusion through transient chromatin roadblocks and neighbouring cohesins. Roadblock abundance, lifetime and partial permeability, together with cohesin crowding, combine into an effective obstacle density that renormalizes processivity and sets the mean loop length. Full loop-length distributions reveal extrusion symmetry: one-sided extrusion remains exponential, whereas effectively two-sided extrusion can generate a finite-length peak. ChIA-PET and MNase HiChIP data match the two-sided predictions, disfavouring purely one-sided extrusion. Cohesin crowding further desynchronizes the arms while leaving a residual correlation approaching {rho}=1/4. Fountain anisotropy across three vertebrates yields correlations near this value, consistent with local cohesin crowding as a sufficient mechanism for fountain formation. Fits further reveal 30-100-kb cohesin-loading regions and, in Danio rerio, a loading width comparable to the extent of enhancer enrichment, motivating a model in which an enhancer-rich loading platform acts as a collective barrier sustaining outward extrusion toward surrounding promoters. Our framework shows how cohesin and roadblock kinetics jointly determine loop statistics, shape chromosome-contact patterns, and may facilitate enhancer-promoter search.

biophysics↗

bioRxiv2026

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

BackgroundHi-C experiments produce genome-wide chromatin contact maps from which structural features can be quantified across multiple genomic scales, ranging from megabase-scale compartments to kilobase-scale boundaries and chromatin loops. Although high-resolution analyses commonly rely on hundreds of millions of sequenced read pairs, the minimum sequencing depth required for different classes of Hi-C-derived features has not been systematically established. We therefore sought to determine these depth requirements systematically. ResultsWe performed progressive random subsampling of twelve Hi-C libraries representing multiple cell types and experimental protocols. Loop-density and loop-size inference from the P(s) log-derivative was evaluated across all libraries, whereas compartment, insulation, and boundary analyses were performed on a subset of nine libraries with comparable full-depth coverage. Rather than defining sufficient depth as an arbitrary fraction of the full-depth value, we introduced a biologically motivated criterion based on the variability between independent biological replicates. The required sequencing depth for each metric was defined as the point at which subsampling scatter first reached the variability observed between independent biological replicates, representing the accuracy that additional sequencing cannot improve upon. Using this criterion, loop-density estimation reached its biological floor at approximately 10 million read pairs, loop-size estimation at approximately 20 million, insulation scores and boundary detection at approximately 30 million, and compartment eigenvectors at 100-kilobase resolution at approximately 60 million read pairs. ConclusionsDifferent Hi-C-derived metrics require substantially different sequencing depths to achieve biologically meaningful accuracy. For all metrics, depth-induced variability fell below biological replicate variability well before full sequencing depth was reached. These thresholds provide practical guidance for experimental design and sequencing budget allocation, suggesting that, in many studies, increasing the number of biological replicates is likely to improve reproducibility more effectively than sequencing individual libraries to greater depth.

bioinformatics↗

bioRxiv2025

Hyperspherical geometry positions the lipidome as a partly independent axis of human brain organization

The brains transcriptome is well mapped, but the spatial organization of lipids--over half of brain dry mass--remains poorly defined. We profiled lipidomic (419 species) and transcriptomic (15,013 genes) signatures from 35 anatomically defined regions in four healthy adult donors, measured from the same tissue samples. Both modalities recapitulate major neuroanatomical divisions, yet the lipidome shows distinctive features: a pronounced white-gray asymmetry, a smooth neocortical rostrocaudal gradient, and limbic-specific lipid clusters absent in transcriptomic space. Using regression against gene-expression principal components and two null models (random and anatomy-aware), we define three data-driven classes of lipid-gene relationships: Synchronizers (10%) tightly coupled to gene programs, Anchors (67%) predictable at levels expected from gross anatomy and cell-type composition, and Drifters (23%) largely transcription-independent. A simple geometric framework unifies these patterns: after centering and normalization, molecular profiles lie on a hypersphere where two interpretable coordinates--polar latitude relative to transcriptome-defined white/gray poles and nearest-gene angular distance--jointly index coupling; an analytical null quantitatively explains the observed scaling. Key effects are robust in leave-one-donor-out analyses and position the lipidome as a partly independent organizational axis of the human brain. Broadly, our results provide an interpretable geometric framework for multi-omics integration, supported by an interactive platform.

neuroscience↗

bioRxiv2025

Universal contact statistics of looped polymers resolve cohesin density and stoichiometry in vivo

Cohesin organizes mammalian chromosomes by extruding DNA loops, but whether this process involves single cohesin complexes or paired "dimers" in vivo has remained controversial. Here, we identify a universal physical signature of cohesin loop density in Hi-C contact statistics at short genomic separations. In this regime, contact statistics simplify dramatically and loops can be treated as static, enabling an analytically solvable equilibrium polymer theory for a looped chain with finite contact detection. The theory predicts a characteristic dip in the slope of the contact probability curve that depends only on two parameters: cohesin loop density and the contact capture radius determined by the experimental protocol. Applying this framework to diverse mammalian Hi-C datasets, we infer a conserved loop density of approximately six loops per megabase. Independent cohesin copy-number measurements from quantitative imaging and mass spectrometry match this value, indicating that loop extrusion is predominantly monomeric in vivo, although rare or transient higher-order assemblies cannot be excluded. More broadly, this framework integrates Hi-C, imaging, and biochemical measurements within a single physical model, providing new mechanistic insight into how motor proteins organize chromatin in vivo. Significance StatementHow many cohesin complexes are required to extrude a chromatin loop in living cells remains a central question in genome biology. We develop a polymer-physics framework that links short-range Hi-C features to the density of cohesin-mediated loops in vivo. The theory explains a characteristic contact signature that depends solely on loop density. Applying this readout across mammalian datasets, we infer [~] sixloops per megabase in interphase chromatin, implying that [~] 60 - 70% of the genome is folded within cohesin-mediated loops. Independent imaging and biochemical measurements yield comparable values, supporting a predominantly monomeric mode of loop extrusion in vivo while not excluding rare or transient dimeric events. By bridging polymer physics with genome-wide contact maps, this framework provides a quantitative route to dissect how motor proteins organize chromosomes.

biophysics↗

bioRxiv2022

A fractal polymer with loops recapitulates key features of chromosome organization

Chromosomes are exceedingly long topologically-constrained polymers compacted in a cell nucleus. We recently suggested that chromosomes are organized into loops by an active process of loop extrusion. Yet loops remain elusive to direct observations in living cells; detection and characterization of myriads of such loops is a major challenge. The lack of a tractable physical model of a polymer folded into loops limits our ability to interpret experimental data and detect loops. Here, we introduce a new physical model - a polymer folded into a sequence of loops, and solve it analytically. Our model and a simple geometrical argument show how loops affect statistics of contacts in a polymer across different scales, explaining universally observed shapes of the contact probability. Moreover, we reveal that folding into loops reduces the density of topological entanglements, a novel phenomenon we refer as "the dilution of entanglements". Supported by simulations this finding suggests that up to [~] 1 - 2Mb chromosomes with loops are not topologically constrained, yet become crumpled at larger scales. Our theoretical framework allows inference of loop characteristics, draws a new picture of chromosome organization, and shows how folding into loops affects topological properties of crumpled polymers.

biophysics↗