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Chromatin is a polymer complex of DNA and proteins that regulates gene expression. The three-dimensional (3D) structure and organization of chromatin controls DNA transcription and replication. High-throughput chromatin conformation capture techniques generate Hi-C maps that can provide insight into the 3D structure of chromatin. Hi-C maps can be represented as a symmetric matrix ${\mathcal{A}}_{ij}$, where each element represents the average contact probability or number of contacts between chromatin lociiandj. Previous studies have detected topologically associating domains (TADs), or self-interacting regions in ${\mathcal{A}}_{ij}$within which the contact probability is greater than that outside the region. Many algorithms have been developed to identify TADs within Hi-C maps. However, most TAD identification algorithms are unable to identify nested or overlapping TADs and for a given Hi-C map there is significant variation in the location and number of TADs identified by different methods. We develop a novel method to identify TADs, KerTAD, using a kernel-based technique from computer vision and image processing that is able to accurately identify nested and overlapping TADs. We benchmark this method against state-of-the-art TAD identification methods on both synthetic and experimental data sets. We find that the new method consistently has higher true positive rates (TPR) and lower false discovery rates (FDR) than all tested methods for both synthetic and manually annotated experimental Hi-C maps. The TPR for KerTAD is also largely insensitive to increasing noise and sparsity, in contrast to the other methods. We also find that KerTAD is consistent in the number and size of TADs identified across replicate experimental Hi-C maps for several organisms. Thus, KerTAD will improve automated TAD identification and enable researchers to better correlate changes in TADs to biological phenomena, such as enhancer-promoter interactions and disease states. 

Biomolecular condensates have emerged as major drivers of cellular organization. It remains largely unexplored, however, whether these condensates can impart mechanical function(s) to the cell. The heterochromatin protein HP1α (Swi6 in Schizosaccharomyces pombe) crosslinks histone H3K9 methylated nucleosomes and has been proposed to undergo condensation to drive the liquid-like clustering of heterochromatin domains. Here, we leverage the genetically tractable S. pombe model and a separation-of-function allele to elucidate a mechanical function imparted by Swi6 condensation. Using single-molecule imaging, force spectroscopy, and high-resolution live-cell imaging, we show that Swi6 is critical for nuclear resistance to external force. Strikingly, it is the condensed yet dynamic pool of Swi6, rather than the chromatin-bound molecules, that is essential to imparting mechanical stiffness. Our findings suggest that Swi6 condensates embedded in the chromatin meshwork establish the emergent mechanical behavior of the nucleus as a whole, revealing that biomolecular condensation can influence organelle and cell mechanics. 

The chromosomes—DNA polymers and their binding proteins—are compacted into a spatially organized, yet dynamic, three-dimensional structure. Recent genome-wide chromatin conformation capture experiments reveal a hierarchical organization of the DNA structure that is imposed, at least in part, by looping interactions arising from the activity of loop extrusion factors. The dynamics of chromatin reflects the response of the polymer to a combination of thermal fluctuations and active processes. However, how chromosome structure and enzymes acting on chromatin together define its dynamics remains poorly understood. To gain insight into the structure-dynamics relationship of chromatin, we combine high-precision microscopy in living Schizosaccharomyces pombe cells with systematic genetic perturbations and Rouse model polymer simulations. We first investigated how the activity of two loop extrusion factors, the cohesin and condensin complexes, influences chromatin dynamics. We observed that deactivating cohesin, or to a lesser extent condensin, increased chromatin mobility, suggesting that loop extrusion constrains rather than agitates chromatin motion. Our corresponding simulations reveal that the introduction of loops is sufficient to explain the constraining activity of loop extrusion factors, highlighting that the conformation adopted by the polymer plays a key role in defining its dynamics. Moreover, we find that the number of loops or residence times of loop extrusion factors influence the dynamic behavior of the chromatin polymer. Last, we observe that the activity of the INO80 chromatin remodeler, but not the SWI/SNF or RSC complexes, is critical for ATP-dependent chromatin mobility in fission yeast. Taking the data together, we suggest that thermal and INO80-dependent activities exert forces that drive chromatin fluctuations, which are constrained by the organization of the chromosome into loops. 

Abstract PremisePteridophytes—vascular land plants that disperse by spores—are a powerful system for studying plant evolution, particularly with respect to the impact of abiotic factors on evolutionary trajectories through deep time. However, our ability to use pteridophytes to investigate such questions—or to capitalize on the ecological and conservation‐related applications of the group—has been impaired by the relative isolation of the neo‐ and paleobotanical research communities and by the absence of large‐scale biodiversity data sources. MethodsHere we present the Pteridophyte Collections Consortium (PCC), an interdisciplinary community uniting neo‐ and paleobotanists, and the associated PteridoPortal, a publicly accessible online portal that serves over three million pteridophyte records, including herbarium specimens, paleontological museum specimens, and iNaturalist observations. We demonstrate the utility of the PteridoPortal through discussion of three example PteridoPortal‐enabled research projects. ResultsThe data within the PteridoPortal are global in scope and are queryable in a flexible manner. The PteridoPortal contains a taxonomic thesaurus (a digital version of a Linnaean classification) that includes both extant and extinct pteridophytes in a common phylogenetic framework. The PteridoPortal allows applications such as greatly accelerated classic floristics, entirely new “next‐generation” floristic approaches, and the study of environmentally mediated evolution of functional morphology across deep time. DiscussionThe PCC and PteridoPortal provide a comprehensive resource enabling novel research into plant evolution, ecology, and conservation across deep time, facilitating rapid floristic analyses and other biodiversity‐related investigations, and providing new opportunities for education and community engagement. 

Brain age (BA), distinct from chronological age (CA), can be estimated from MRIs to evaluate neuroanatomic aging in cognitively normal (CN) individuals. BA, however, is a cross-sectional measure that summarizes cumulative neuroanatomic aging since birth. Thus, it conveys poorly recent or contemporaneous aging trends, which can be better quantified by the (temporal) pace P of brain aging. Many approaches to map P, however, rely on quantifying DNA methylation in whole-blood cells, which the blood–brain barrier separates from neural brain cells. We introduce a three-dimensional convolutional neural network (3D-CNN) to estimate P noninvasively from longitudinal MRI. Our longitudinal model (LM) is trained on MRIs from 2,055 CN adults, validated in 1,304 CN adults, and further applied to an independent cohort of 104 CN adults and 140 patients with Alzheimer’s disease (AD). In its test set, the LM computes P with a mean absolute error (MAE) of 0.16 y (7% mean error). This significantly outperforms the most accurate cross-sectional model, whose MAE of 1.85 y has 83% error. By synergizing the LM with an interpretable CNN saliency approach, we map anatomic variations in regional brain aging rates that differ according to sex, decade of life, and neurocognitive status. LM estimates of P are significantly associated with changes in cognitive functioning across domains. This underscores the LM’s ability to estimate P in a way that captures the relationship between neuroanatomic and neurocognitive aging. This research complements existing strategies for AD risk assessment that estimate individuals’ rates of adverse cognitive change with age.