Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 63,068 bioRxiv papers from 279,747 authors.
Most downloaded bioRxiv papers, since beginning of last month
61,421 results found. For more information, click each entry to expand.
952 downloads developmental biology
Size trade-offs of visual versus olfactory organs is a pervasive feature of animal evolution. Comparing Drosophila species, we find that larger eyes correlate with smaller antennae, where olfactory organs reside, and narrower faces. We demonstrate that this trade-off arises through differential subdivision of the head primordium into visual versus non-visual fields. Specification of the visual field requires a highly-conserved eye development gene called eyeless in flies and Pax6 in humans. We discover that changes in the temporal regulation of eyeless expression during development is a conserved mechanism for sensory trade-offs within and between Drosophila species. We identify a natural single nucleotide polymorphism in the cis-regulatory region of eyeless that is sufficient to alter its temporal regulation and eye size. Because Pax6 is a conserved regulator of sensory placode subdivision, we propose that alterations in the mutual repression between sensory territories is a conserved mechanism for sensory trade-offs in animals.
937 downloads bioinformatics
Analysis of single-cell RNA-seq data begins with pre-processing of sequencing reads to generate count matrices. We investigate algorithm choices for the challenges of pre-processing, and describe a workflow that balances efficiency and accuracy. Our workflow is based on the kallisto (<https://pachterlab.github.io/kallisto/>) and bustools (<https://bustools.github.io/>) programs, and is near-optimal in speed and memory. The workflow is modular, and we demonstrate its flexibility by showing how it can be used for RNA velocity analyses. Documentation and tutorials for using the kallisto | bus workflow are available at <https://www.kallistobus.tools/>.
928 downloads neuroscience
Or A. Shemesh, Changyang Linghu, Kiryl D. Piatkevich, Daniel Goodwin, Howard Gritton, Michael F. Romano, Cody A Siciliano, Ruixuan Gao, Chi-Chieh (Jay) Yu, Hua-an Tseng, Seth Bensussen, Sujatha Narayan, Chao-Tsung Yang, Limor Freifeld, Ishan Gupta, Habiba Noamany, Nikita Pak, Young-Gyu Yoon, Jeremy F.P. Ullmann, Burcu Guner-Ataman, Zoe R. Sheinkopf, Won Min Park, Shoh Asano, Amy Keating, James Trimmer, Jacob Reimer, Andreas Tolias, Kay M Tye, Xue Han, Misha B Ahrens, Edward S Boyden
Methods for one-photon fluorescent imaging of calcium dynamics in vivo are popular due to their ability to simultaneously capture the dynamics of hundreds of neurons across large fields of view, at a low equipment complexity and cost. In contrast to two-photon methods, however, one-photon methods suffer from higher levels of crosstalk between cell bodies and the surrounding neuropil, resulting in decreased signal-to-noise and artifactual correlations of neural activity. Here, we address this problem by engineering cell body-targeted variants of the fluorescent calcium indicator GCaMP6f. We screened fusions of GCaMP6f to both natural as well as engineered peptides, and identified fusions that localized GCaMP6f to within approximately 50 microns of the cell body of neurons in live mice and larval zebrafish. One-photon imaging of soma-targeted GCaMP6f in dense neural circuits reported fewer artifactual spikes from neuropil, increased signal-to-noise ratio, and decreased artifactual correlation across neurons. Thus, soma-targeting of fluorescent calcium indicators increases neuronal signal fidelity and may facilitate even greater usage of simple, powerful, one-photon methods of population imaging of neural calcium dynamics.
918 downloads neuroscience
Noninvasive behavioral tracking of animals during experiments is crucial to many scientific pursuits. Extracting the poses of animals without using markers is often essential for measuring behavioral effects in biomechanics, genetics, ethology & neuroscience. Yet, extracting detailed poses without markers in dynamically changing backgrounds has been challenging. We recently introduced an open source toolbox called DeepLabCut that builds on a state-of-the-art human pose estimation algorithm to allow a user to train a deep neural network using limited training data to precisely track user-defined features that matches human labeling accuracy. Here, with this paper we provide an updated toolbox that is self contained within a Python package that includes new features such as graphical user interfaces and active-learning based network refinement. Lastly, we provide a step-by-step guide for using DeepLabCut.
918 downloads genetics
Ashot Margaryan, Daniel Lawson, Martin Sikora, Fernando Racimo, Simon Rasmussen, Ida Moltke, Lara Cassidy, Emil Jørsboe, Andrés Ingason, Mikkel Pedersen, Thorfinn Korneliussen, Helene Wilhelmson, Magdalena Buś, Peter de Barros Damgaard, Rui Martiniano, Gabriel Renaud, Claude Bhérer, J. Víctor Moreno-Mayar, Anna Fotakis, Marie Allen, Martyna Molak, Enrico Cappellini, Gabriele Scorrano, Alexandra Buzhilova, Allison Fox, Anders Albrechtsen, Berit Schütz, Birgitte Skar, Caroline Arcini, Ceri Falys, Charlotte Hedenstierna Jonson, Dariusz Błaszczyk, Denis Pezhemsky, Gordon Turner-Walker, Hildur Gestsdóttir, Inge Lundstrøm, Ingrid Gustin, Ingrid Mainland, Inna Potekhina, Italo Muntoni, Jade Cheng, Jesper Stenderup, Jilong Ma, Julie Gibson, Jüri Peets, Jörgen Gustafsson, Katrine Iversen, Linzi Simpson, Lisa Strand, Louise Loe, Maeve Sikora, Marek Florek, Maria Vretemark, Mark Redknap, Monika Bajka, Tamara Pushkina, Morten Søvsø, Natalia Grigoreva, Tom Christensen, Ole Kastholm, Otto Uldum, Pasquale Favia, Per Holck, Raili Allmäe, Sabine Sten, Símun Arge, Sturla Ellingvåg, Vayacheslav Moiseyev, Wiesław Bogdanowicz, Yvonne Magnusson, Ludovic Orlando, Daniel Bradley, Marie Louise Jørkov, Jette Arneborg, Niels Lynnerup, Neil Price, M. Thomas Gilbert, Morten Allentoft, Jan Bill, Søren Sindbæk, Lotte Hedeager, Kristian Kristiansen, Rasmus Nielsen, Thomas Werge, Eske Willerslev
The Viking maritime expansion from Scandinavia (Denmark, Norway, and Sweden) marks one of the swiftest and most far-flung cultural transformations in global history. During this time (c. 750 to 1050 CE), the Vikings reached most of western Eurasia, Greenland, and North America, and left a cultural legacy that persists till today. To understand the genetic structure and influence of the Viking expansion, we sequenced the genomes of 442 ancient humans from across Europe and Greenland ranging from the Bronze Age (c. 2400 BC) to the early Modern period (c. 1600 CE), with particular emphasis on the Viking Age. We find that the period preceding the Viking Age was accompanied by foreign gene flow into Scandinavia from the south and east: spreading from Denmark and eastern Sweden to the rest of Scandinavia. Despite the close linguistic similarities of modern Scandinavian languages, we observe genetic structure within Scandinavia, suggesting that regional population differences were already present 1,000 years ago. We find evidence for a majority of Danish Viking presence in England, Swedish Viking presence in the Baltic, and Norwegian Viking presence in Ireland, Iceland, and Greenland. Additionally, we see substantial foreign European ancestry entering Scandinavia during the Viking Age. We also find that several of the members of the only archaeologically well-attested Viking expedition were close family members. By comparing Viking Scandinavian genomes with present-day Scandinavian genomes, we find that pigmentation-associated loci have undergone strong population differentiation during the last millennia. Finally, we are able to trace the allele frequency dynamics of positively selected loci with unprecedented detail, including the lactase persistence allele and various alleles associated with the immune response. We conclude that the Viking diaspora was characterized by substantial foreign engagement: distinct Viking populations influenced the genomic makeup of different regions of Europe, while Scandinavia also experienced increased contact with the rest of the continent.
917 downloads plant biology
Background: Wheat (Triticum aestivum) is one of the most important crops worldwide. Given a growing global population coupled with increasingly challenging climate and cultivation conditions, facilitating wheat breeding by fine-tuning important traits such as stress resistance, yield and plant architecture is of great importance. Since they are involved in virtually all aspects of plant development and stress responses, prime candidates for improving these traits are MIKC-type (type II) MADS-box genes. Results: We present a detailed overview of number, phylogeny, and expression of 201 wheat MIKC-type MADS-box genes, which can be assigned to 15 subfamilies. Homoeolog retention is significantly above the average genome-wide retention rate for wheat genes, indicating that many MIKC-type homoeologs are functionally important and not redundant. Gene expression is generally in agreement with the expected subfamily-specific expression pattern, indicating broad conservation of function of MIKC-type genes during wheat evolution. We find the extensive expansion of some MIKC-type subfamilies to be correlated with their chromosomal location and propose a link between MADS-box gene duplications and the adaptability of wheat. A number of MIKC-type genes encode for truncated proteins that lack either the DNA-binding or protein-protein interaction domain and occasionally show novel expression patterns, possibly pointing towards neofunctionalization. Conclusions: Conserved and neofunctionalized MIKC-type genes may have played an important role in the adaptation of wheat to a diversity of conditions, hence contributing to its importance as a global staple food. Therefore, we propose that MIKC-type MADS-box genes are especially well suited for targeted breeding approaches and phenotypic fine tuning.
910 downloads bioinformatics
Single-cell RNA sequencing enables researchers to study the gene expression of individual cells. However, in high-throughput methods the portrait of each individual cell is noisy, representing thousands of the hundreds of thousands of mRNA molecules originally present. While many methods for denoising single-cell data have been proposed, a principled procedure for selecting and calibrating the best method for a given dataset has been lacking. We present "molecular cross-validation," a statistically principled and data-driven approach for estimating the accuracy of any denoising method without the need for ground-truth. We validate this approach for three denoising methods--principal component analysis, network diffusion, and a deep autoencoder--on a dataset of deeply-sequenced neurons. We show that molecular cross-validation correctly selects the optimal parameters for each method and identifies the best method for the dataset.
900 downloads developmental biology
A fundamental question in developmental biology is how the early embryo breaks initial symmetry to establish the spatial coordinate system later important for the organisation of the embryonic body plan. In zebrafish, this is thought to depend on the inheritance of maternal mRNAs [–], cortical rotation to generate a dorsal pole of beta-catenin activity [–] and the release of Nodal signals from the yolk syncytial layer (YSL) [–]. Recent work aggregating mouse embryonic stem cells has shown that symmetry breaking can occur in the absence of extra-embryonic tissue [,]. To test whether this is also true in zebrafish, we separated embryonic cells from the yolk and allowed them to develop as aggregates. These aggregates break symmetry autonomously to form elongated structures with an anterior-posterior pattern. Extensive cell mixing shows that any pre-existing asymmetry is lost prior to the breaking morphological symmetry, revealing that the maternal pre-pattern is not strictly required for early embryo patterning. Following early signalling events after isolation of embryonic cells reveals that a pole of Nodal activity precedes and is required for elongation. The blocking of PCP-dependent convergence and extension movements disrupts the establishment of opposing poles of BMP and Wnt/TCF activity and the patterning of anterior-posterior neural tissue. These results lead us to suggest that convergence and extension plays a causal role in the establishment of morphogen gradients and pattern formation during zebrafish gastrulation. : #ref-1 : #ref-3 : #ref-4 : #ref-8 : #ref-9 : #ref-12 : #ref-19 : #ref-20
899 downloads bioinformatics
Background: Recent innovations in single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands of individual cells. scATAC-seq data analysis presents unique methodological challenges. scATAC-seq experiments sample DNA, which, due to low copy numbers (diploid in humans) lead to inherent data sparsity (1-10% of peaks detected per cell) compared to transcriptomic (scRNA-seq) data (20-50% of expressed genes detected per cell). Such challenges in data generation emphasize the need for informative features to assess cell heterogeneity at the chromatin level. Results: We present a benchmarking framework that was applied to 10 computational methods for scATAC-seq on 13 synthetic and real datasets from different assays, profiling cell types from diverse tissues and organisms. Methods for processing and featurizing scATAC-seq data were evaluated by their ability to discriminate cell types when combined with common unsupervised clustering approaches. We rank evaluated methods and discuss computational challenges associated with scATAC-seq analysis including inherently sparse data, determination of features, peak calling, the effects of sequencing coverage and noise, and clustering performance. Running times and memory requirements are also discussed. Conclusions: This reference summary of scATAC-seq methods offers recommendations for best practices with consideration for both the non-expert user and the methods developer. Despite variation across methods and datasets, SnapATAC, Cusanovich2018, and cisTopic outperform other methods in separating cell populations of different coverages and noise levels in both synthetic and real datasets. Notably, SnapATAC was the only method able to analyze a large dataset (> 80,000 cells).
897 downloads genomics
Elisabetta Mereu, Atefeh Lafzi, Catia Moutinho, Christoph Ziegenhain, Davis J. MacCarthy, Adrian Alvarez, Eduard Batlle, Sagar, Dominic Grün, Julia K. Lau, Stéphane C Boutet, Chad Sanada, Aik Ooi, Robert C. Jones, Kelly Kaihara, Chris Brampton, Yasha Talaga, Yohei Sasagawa, Kaori Tanaka, Tetsutaro Hayashi, Itoshi Nikaido, Cornelius Fischer, Sascha Sauer, Timo Trefzer, Christian Conrad, Xian Adiconis, Lan T. Nguyen, Aviv Regev, Joshua Z Levin, Swati Parekh, Aleksandar Janjic, Lucas E. Wange, Johannes W. Bagnoli, Wolfgang Enard, Ivo G Gut, Rickard Sandberg, Ivo Gut, Oliver Stegle, Holger Heyn
Single-cell RNA sequencing (scRNA-seq) is the leading technique for charting the molecular properties of individual cells. The latest methods are scalable to thousands of cells, enabling in-depth characterization of sample composition without prior knowledge. However, there are important differences between scRNA-seq techniques, and it remains unclear which are the most suitable protocols for drawing cell atlases of tissues, organs and organisms. We have generated benchmark datasets to systematically evaluate techniques in terms of their power to comprehensively describe cell types and states. We performed a multi-center study comparing 13 commonly used single-cell and single-nucleus RNA-seq protocols using a highly heterogeneous reference sample resource. Comparative and integrative analysis at cell type and state level revealed marked differences in protocol performance, highlighting a series of key features for cell atlas projects. These should be considered when defining guidelines and standards for international consortia, such as the Human Cell Atlas project.
896 downloads molecular biology
Tissue-specific gene expression requires coordinated control of gene-proximal and -distal cis-regulatory elements (CREs), yet functional analysis of gene-distal CREs such as enhancers remains challenging. Here we describe enhanced CRISPR/dCas9-based epigenetic editing systems, enCRISPRa and enCRISPRi, for multiplexed analysis of enhancer function in situ and in vivo. Using dual effectors capable of re-writing enhancer-associated chromatin modifications, we show that enCRISPRa and enCRISPRi modulate gene transcription by remodeling local epigenetic landscapes at sgRNA-targeted enhancers and associated genes. Comparing with existing methods, the new systems display more robust perturbation of enhancer activity and gene transcription with minimal off-targets. Allele-specific targeting of enCRISPRa to oncogenic TAL1 super-enhancer modulates TAL1 expression and cancer progression in xenotransplants. Multiplexed perturbations of lineage-specific enhancers using an enCRISPRi knock-in mouse establish in vivo evidence for lineage-restricted essentiality of developmental enhancers during hematopoietic lineage specification. Hence, enhanced CRSIPR epigenetic editing provides opportunities for interrogating enhancer function in native biological contexts.
884 downloads genomics
Ansuman T. Satpathy, Jeffrey M. Granja, Kathryn E Yost, Yanyan Qi, Francesca Meschi, Geoffrey P McDermott, Brett N Olsen, Maxwell R. Mumbach, Sarah E Pierce, M. Ryan Corces, Preyas Shah, Jason C. Bell, Darisha Jhutty, Corey M Nemec, Jean Wang, Li Wang, Yifeng Yin, Paul G Giresi, Anne Lynn S. Chang, Grace X.Y. Zheng, William J. Greenleaf, Howard Y. Chang
Understanding complex tissues requires single-cell deconstruction of gene regulation with precision and scale. Here we present a massively parallel droplet-based platform for mapping transposase-accessible chromatin in tens of thousands of single cells per sample (scATAC-seq). We obtain and analyze chromatin profiles of over 200,000 single cells in two primary human systems. In blood, scATAC-seq allows marker-free identification of cell type-specific cis- and trans-regulatory elements, mapping of disease-associated enhancer activity, and reconstruction of trajectories of differentiation from progenitors to diverse and rare immune cell types. In basal cell carcinoma, scATAC-seq reveals regulatory landscapes of malignant, stromal, and immune cell types in the tumor microenvironment. Moreover, scATAC-seq of serial tumor biopsies before and after PD-1 blockade allows identification of chromatin regulators and differentiation trajectories of therapy-responsive intratumoral T cell subsets, revealing a shared regulatory program driving CD8+ T cell exhaustion and CD4+ T follicular helper cell development. We anticipate that droplet-based single-cell chromatin accessibility will provide a broadly applicable means of identifying regulatory factors and elements that underlie cell type and function.
864 downloads microbiology
We recently introduced the Genome Taxonomy Database (GTDB), a phylogenetically consistent, genome-based taxonomy providing rank normalized classifications for nearly 150,000 genomes from domain to genus. However, nearly 40% of the genomes used to infer the GTDB reference tree lack a species name, reflecting the large number of genomes in public repositories without complete taxonomic assignments. Here we address this limitation by proposing 24,706 species clusters which encompass all publicly available bacterial and archaeal genomes when using commonly accepted average nucleotide identity (ANI) criteria for circumscribing species. In contrast to previous ANI studies, we selected a single representative genome to serve as the nomenclatural type for circumscribing each species with type strains used where available. We complemented the 8,792 species clusters with validly or effectively published names with 15,914 de novo species clusters in order to assign placeholder names to the growing number of genomes from uncultivated species. This provides the first complete domain to species taxonomic framework which will improve communication of scientific results.
855 downloads neuroscience
Peter H Li, Larry F. Lindsey, Michal Januszewski, Zhihao Zheng, Alexander Shakeel Bates, István Taisz, Mike Tyka, Matthew Nichols, Feng Li, Eric Perlman, Jeremy Maitin-Shepard, Tim Blakely, Laramie Leavitt, Gregory S.X.E. Jefferis, Davi Bock, Viren Jain
Reconstruction of neural circuitry at single-synapse resolution is an attractive target for improving understanding of the nervous system in health and disease. Serial section transmission electron microscopy (ssTEM) is among the most prolific imaging methods employed in pursuit of such reconstructions. We demonstrate how Flood-Filling Networks (FFNs) can be used to computationally segment a forty-teravoxel whole-brain Drosophila ssTEM volume. To compensate for data irregularities and imperfect global alignment, FFNs were combined with procedures that locally re-align serial sections and dynamically adjust image content. The proposed approach produced a largely merger-free segmentation of the entire ssTEM Drosophila brain, which we make freely available. As compared to manual tracing using an efficient skeletonization strategy, the segmentation enabled circuit reconstruction and analysis workflows that were an order of magnitude faster.
853 downloads systems biology
Determining protein levels in each tissue and how they compare with RNA levels is important for understanding human biology and disease as well as regulatory processes that control protein levels. We quantified the relative protein levels from 12,627 genes across 32 normal human tissue types prepared by the GTEx project. Known and new tissue specific or enriched proteins (5,499) were identified and compared to transcriptome data. Many ubiquitous transcripts are found to encode highly tissue specific proteins. Discordance in the sites of RNA expression and protein detection also revealed potential sites of synthesis and action of protein signaling molecules. Overall, these results provide an extraordinary resource, and demonstrate that understanding protein levels can provide insights into metabolism, regulation, secretome, and human diseases. Summary Quantitative proteome study of 32 human tissues and integrated analysis with transcriptome data revealed that understanding protein levels could provide in-depth knowledge to post transcriptional or translational regulations, human metabolism, secretome, and diseases.
847 downloads biochemistry
Nearly all mitochondrial proteins are encoded by the nuclear genome and imported into mitochondria following synthesis on cytosolic ribosomes. These precursor proteins are translocated into mitochondria by the TOM complex, a protein-conducting channel in the mitochondrial outer membrane. Using cryo-EM, we have obtained high-resolution structures of both apo and presequence-bound core TOM complexes from Saccharomyces cerevisiae in dimeric and tetrameric forms. Dimeric TOM consists of two copies each of five proteins arranged in two-fold symmetry--Tom40, a pore-forming beta-barrel with an overall negatively-charged inner surface, and four auxiliary alpha-helical transmembrane proteins. The structure suggests that presequences for mitochondrial targeting insert into the Tom40 channel mainly by electrostatic and polar interactions. The tetrameric complex is essentially a dimer of dimeric TOM, which may be capable of forming higher-order oligomers. Our study reveals the molecular organization of the TOM complex and provides new insights about the mechanism of protein translocation into mitochondria.
845 downloads neuroscience
Evolution is a blind fitting process by which organisms, over generations, adapt to the niches of an ever-changing environment. Does the mammalian brain use similar brute-force fitting processes to learn how to perceive and act upon the world? Recent advances in training deep neural networks has exposed the power of optimizing millions of synaptic weights to map millions of observations along ecologically relevant objective functions. This class of models has dramatically outstripped simpler, more intuitive models, operating robustly in real-life contexts spanning perception, language, and action coordination. These models do not learn an explicit, human-interpretable representation of the underlying structure of the data; rather, they use local computations to interpolate over task-relevant manifolds in a high-dimensional parameter space. Furthermore, counterintuitively, over-parameterized models, similarly to evolutionary processes, can be simple and parsimonious as they provide a versatile, robust solution for learning a diverse set of functions. In contrast to traditional scientific models, where the ultimate goal is interpretability, over-parameterized models eschew interpretability in favor of solving real-life problems or tasks. We contend that over-parameterized blind fitting presents a radical challenge to many of the underlying assumptions and practices in computational neuroscience and cognitive psychology. At the same time, this shift in perspective informs longstanding debates and establishes unexpected links with evolution, ecological psychology, and artificial life.
841 downloads cell biology
Aging of the mammary gland is closely associated with increased susceptibility to diseases such as cancer, but there have been limited systematic studies of aging-induced alterations within this organ. We performed high-throughput single-cell RNA-sequencing (scRNA-seq) profiling of mammary tissues from young and old nulliparous mice, including both epithelial and stromal cell types. Our analysis identified altered proportions and distinct gene expression patterns in numerous cell populations as a consequence of the aging process, independent of parity and lactation. In addition, we detected a subset of luminal cells that express both hormone-sensing and alveolar markers and decrease in relative abundance with age. These data provide a high-resolution landscape of aging mammary tissues, with potential implications for normal tissue functions and cancer predisposition.
830 downloads systems biology
Benoit Lehallier, David Gate, Nicholas Schaum, Tibor Nanasi, Song Eun Lee, Hanadie Yousef, Patricia Moran Losada, Daniela Berdnik, Andreas Keller, Joe Verghese, Sanish Sathyan, Claudio Franceschi, Sofiya Milman, Nir Barzilai, Tony Wyss-Coray
Aging is the predominant risk factor for numerous chronic diseases that limit healthspan. Mechanisms of aging are thus increasingly recognized as therapeutic targets. Blood from young mice reverses aspects of aging and disease across multiple tissues, pointing to the intriguing possibility that age-related molecular changes in blood can provide novel insight into disease biology. We measured 2,925 plasma proteins from 4,331 young adults to nonagenarians and developed a novel bioinformatics approach which uncovered profound non-linear alterations in the human plasma proteome with age. Waves of changes in the proteome in the fourth, seventh, and eighth decades of life reflected distinct biological pathways, and revealed differential associations with the genome and proteome of age-related diseases and phenotypic traits. This new approach to the study of aging led to the identification of unexpected signatures and pathways of aging and disease and offers potential pathways for aging interventions.
823 downloads genomics
In addition to its known roles in protein synthesis and enzyme catalysis, RNA has been proposed to stabilize higher-order chromatin structure. To distinguish presumed architectural roles of RNA from other functions, we applied a ribonuclease digestion strategy to our CUT&RUN in situ chromatin profiling method (CUT&RUN.RNase). We find that depletion of RNA compromises association of the murine nucleolar protein Nucleophosmin with pericentric heterochromatin and alters the chromatin environment of CCCTC-binding factor (CTCF) bound regions. Strikingly, we find that RNA maintains the integrity of both constitutive (H3K9me3 marked) and facultative (H3K27me3 marked) heterochromatic regions as compact domains, but only moderately stabilizes euchromatin. To establish the specificity of heterochromatin stabilization by RNA, we performed CUT&RUN on cells deleted for the Firre long non-coding RNA and observed disruption of H3K27me3 domains on several chromosomes. We conclude that RNA maintains local and global chromatin organization by acting as a structural scaffold for heterochromatic domains.
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