Biology subjects

Gupta, S.

Publications and source records attributed to Gupta, S..

At least 145 records · Page 8Linked to original sources

bioRxiv2024

BoMBR: An Annotated Bone Marrow Biopsy Dataset for Segmentation of Reticulin Fibers

Bone marrow reticulin fibrosis is associated with varied benign as well as malignant hematological conditions. The assessment of reticulin fibrosis is important in the diagnosis, prognostication and management of such disorders. The current methods for quantification of reticulin fibrosis are inefficient and prone to errors. Therefore, there is a need for automated tools for accurate and consistent quantification of reticulin. However, the lack of standardized datasets has hindered the development of such tools. In this study, we present a comprehensive dataset that comprises of 201 Bone Marrow Biopsy images for Reticulin (BoMBR) quantification. These images were meticulously annotated for semantic segmentation, with the focus on performing reticulin fiber quantification. This annotation was done by two trained hematopathologists who were aided by Deep Learning (DL) models and image processing techniques that generated a rough automated annotation for them to start with. This ensured precise delineation of the reticulin fibers alongside other cellular components such as bony trabeculae, fat, and cells. This is the first publicly available dataset in this domain with the aim to catalyze advancements the development of computational models for improved reticulin quantification. Further, we show that our annotated dataset can be used to train a DL model for a multi-class semantic segmentation task for robust reticulin fiber detection task (Mean Dice score: 0.92). We use these model outputs for the Marrow Fibrosis (MF) grade detection and obtained a Mean Weighted Average F1 score of 0.656 with our trained model. Our code for preprocessing the dataset is available at https://github.com/AI-in-Medicine-IIT-Ropar/BoMBR_dataset_preprocessing.

pathology↗

bioRxiv2024

BaMBo: An Annotated Bone Marrow Biopsy Dataset for Segmentation Task

Bone marrow examination has become increasingly important for the diagnosis and treatment of hematologic and other illnesses. The present methods for analyzing bone marrow biopsy samples involve subjective and inaccurate assessments by visual estimation by pathologists. Thus, there is a need to develop automated tools to assist in the analysis of bone marrow samples. However, there is a lack of publicly available standardized and high-quality datasets that can aid in the research and development of automated tools that can provide consistent and objective measurements. In this paper, we present a comprehensive Bone Marrow Biopsy (BaMBo) dataset consisting 185 semantic-segmented bone marrow biopsy images, specifically designed for the automated calculation of bone marrow cellularity. Our dataset comprises high-resolution, generalized images of bone marrow biopsies, each annotated with precise semantic segmentation of different haematological components. These components are divided into 4 classes: Bony trabeculae, adipocytes, cellular region and Background (BG). The annotations were performed with the help of two experienced hematopathologists that were supported by state-of-the-art Deep Learning (DL) models and image processing techniques. We then used our dataset to train a custom U-Net based DL model that performs multi-class semantic segmentation of the images (Dice Score: 0.831 {+/-} 0.099) and predicts the cellularity of these images with an error of 5.9% {+/-} 8.8%. This shows the applicability of our data for future research in this domain. Our code is available at https://github.com/AI-in-Medicine-IIT-Ropar/BaMbo-Bone-Marrow-Biopsy.

pathology↗

bioRxiv2024

TECPR2 is a Rab5 effector that regulates endosomal cargo recycling

Small GTP-binding (G) proteins of the Rabs, Arfs, and Arls (Arf-like) family mediate the recruitment of their effectors to subcellular membrane-bound compartments, which in turn mediates vesicle budding, motility, and tethering. Here, we report that Tectonin-{beta}-propeller repeat containing protein 2 (TECPR2), a protein mutated in a form of hereditary sensory and autonomic neuropathy (HSAN), is an effector of early endosomal Rab protein, Rab5, and interacts with Rab5 via its C-terminal TECPR repeats. The HSAN-associated TECPR2 (R1336W) missense variant was deficient in Rab5-binding and, consequently, in membrane recruitment. TECPR2-depletion led to perinuclear collapse of recycling endosomes and increased overlap of sorting and degradative subdomain markers on early endosomes. Consistent with a possible role in endocytic recycling, we observed impaired recycling and increased lysosomal degradation of 5{beta}1 integrin receptors upon TECPR2 knockdown. TECPR2 regulates the early endosomal localization of the cargo adaptor for {beta}1 integrins, SNX17, and its-associated protein complex WASH, which mediates actin polymerization on early endosomes. Finally, TECPR2 depletion in the zebrafish model resulted in delayed motility and changes in the neuromuscular junction. Our study supports an early endosomal role for TECPR2 in cargo recycling and provides insights into how its loss-of- function results in a neurodegenerative genetic disorder.

cell biology↗

bioRxiv2024

scaLR: a low-resource deep neural network-based platform for single cell analysis and biomarker discovery

PurposeSingle-cell RNA sequencing (scRNA-seq) is producing vast amounts of individual cell profiling data. Analysis of such datasets presents a significant challenge in accurately annotating cell types and their associated biomarkers. scRNA-seq datasets analysis will help us understand diseases such as Alzheimers, Cancer, Diabetes, Coronavirus disease 2019 (COVID-19), Systemic Lupus Ery-thematosus (SLE), etc. Recently different pipelines based on machine learning (ML) and Deep Neural Network (DNN) methods have been employed to tackle these issues utilizing scRNA-seq datasets. These pipelines have arisen as a promising resource and are capable of extracting meaningful and concise features from noisy, diverse, and high-dimensional data to enhance annotations and subsequent analysis. Existing tools require high computational resources to execute large sample datasets. MethodsWe have developed a cutting-edge platform known as scaLR (Single Cell Analysis using Low Resource) that efficiently processes data in batches, and reduces the required resources for processing large datasets and running NN models. scaLR is equipped with data processing, feature extraction, training, evaluation, and downstream analysis. The data processing module consists of sample-wise & standard scaler normalization and splitting of data. Its novel feature extraction algorithm, first trains the model on a feature subset and stores feature importance for all the features in that subset. At the end of this process, top K features are selected based on their importance. The model is trained on top K features, its performance evaluation and associated downstream analysis provide significant biomarkers for different cell types and diseases/traits. ResultsTo showcase the capabilities of scaLR, we utilized several scRNA-seq datasets of Peripheral Blood Mononuclear Cells (PBMCs), Alzheimers patients, and large datasets from human and mouse embryonic development. Our findings indicate that scaLR offers comparable prediction accuracy and requires less model training time and compute resources than existing Python-based pipelines and frameworks. Moreover, scaLR efficiently handles large sample datasets (>11.4 million cells) with minimal resource usage (29GB RAM, 12GB GPU, and 8 CPUs) while maintaining high prediction accuracy and being capable of ranking the biomarker association with specific cell types and diseases. ConclusionWe present scaLR a Python-based platform, engineered to utilize minimal computational resources while maintaining comparable execution times to existing frameworks. It is highly scalable and capable of efficiently handling datasets containing millions of cell samples and providing their classification and important biomarkers.

bioinformatics↗

bioRxiv2024

NucBalancer: Streamlining Barcode Sequence Selection for Optimal Sample Pooling for Sequencing

Recent advancements in next-generation sequencing (NGS) technologies have brought to the forefront the necessity for versatile, cost-effective tools capable of adapting to a rapidly evolving landscape. The emergence of numerous new sequencing platforms, each with unique sample preparation and sequencing requirements, underscores the importance of efficient barcode balancing for successful pooling and accurate demultiplexing of samples. Recently launched new sequencing systems claim better affordability comparable to more established platforms further exemplifies these challenges, especially when libraries originally prepared for one platform need conversion to another. In response to this dynamic environment, we introduce NucBalancer, a Shiny app developed for the optimal selection of barcode sequences. While initially tailored to meet the nucleotide, composition challenges specific to G400 and T7 series sequencers, NucBalancers utility significantly broadens to accommodate the varied demands of these new sequencing technologies. Its application is particularly crucial in single-cell genomics, enabling the adaptation of libraries, such as those prepared for 10x technology, to various sequencers including G400 and T7 series sequencers. By facilitating the efficient balancing of nucleotide composition and the accommodation of differing sample concentrations, NucBalancer plays a pivotal role in reducing biases in nucleotide composition. This enhances the fidelity and reliability of NGS data across multiple platforms. As the NGS field continues to expand with the introduction of new sequencing technologies, the adaptability and wide-ranging applicability of NucBalancer render it an invaluable asset in genomic research. This tool addresses the current sequencing challenges ensuring that researchers can effectively balance barcodes for sample pooling regardless of the sequencing platform used. Availability and implementationNucBalancer is implemented in R and is available at https://github.com/ersgupta/NucBalancer. Additionally, a shiny interface is made available at https://ersgupta.shinyapps.io/NucBalancer/.

bioinformatics↗

bioRxiv2024

flt1 inactivation promotes zebrafish cardiac regeneration by enhancing endothelial activity and limiting the fibrotic response

Summary statementflt1 inactivation promotes zebrafish cardiac regeneration by enhancing coronary revascularization and endocardial expansion, while limiting myofibroblast differentiation. VEGFA administration has been explored as a pro-angiogenic therapy for cardiovascular diseases including heart failure for several years, but with little success. Here we investigate a different approach to augment VEGFA bioavailability: by deleting the VEGFA decoy receptor VEGFR1/FLT1, one can achieve more physiological VEGFA concentrations. We find that following cryoinjury, zebrafish flt1 mutant hearts display enhanced coronary revascularization and endocardial expansion, increased cardiomyocyte dedifferentiation and proliferation, and decreased scarring. Suppressing Vegfa signaling in flt1 mutants abrogates these beneficial effects of flt1 deletion. Transcriptomic analyses of cryoinjured flt1 mutant hearts reveal enhanced endothelial MAPK/ERK signaling and downregulation of the transcription factor gene egr3. Using newly generated genetic tools, we observe egr3 upregulation in the regenerating endocardium, and find that Egr3 promotes myofibroblast differentiation. These data indicate that with enhanced Vegfa bioavailability, the endocardium limits myofibroblast differentiation via egr3 downregulation, thereby providing a more permissive microenvironment for cardiomyocyte replenishment after injury.

molecular biology↗

bioRxiv2024

The transmembrane glycoprotein Gpnmb is required for the immune and fibrotic responses during zebrafish heart regeneration

Myocardial infarction occurs when coronary supply of oxygen and nutrients to part of the heart is interrupted. In contrast to adult mammals, adult zebrafish have a unique ability to regenerate their heart after cardiac injury. Several processes are involved in this regenerative response including inflammation, coronary endothelial cell proliferation and revascularization, endocardial expansion, cardiomyocyte repopulation, and transient scar formation. To identify potential regulators of zebrafish cardiac regeneration, we profiled the transcriptome of regenerating coronary endothelial cells at 7 days post cryoinjury (dpci) and observed the significant upregulation of dozens of genes including gpnmb. Gpnmb (glycoprotein non-metastatic melanoma protein B) is a transmembrane glycoprotein implicated in inflammation resolution and tissue regeneration. Transcriptomic profiling data of cryoinjured zebrafish hearts reveal that gpnmb is mostly expressed by macrophages. To investigate gpnmb function during zebrafish cardiac regeneration, we generated a full locus deletion (FLD) allele. We find that after cardiac cryoinjury, animals lacking gpnmb exhibit neutrophil retention and decreased macrophage recruitment as well as reduced myofibroblast numbers. Moreover, loss of gpnmb impairs coronary endothelial cell regeneration and cardiomyocyte dedifferentiation. Transcriptomic analyses of cryoinjured gpnmb mutant hearts identified enhanced collagen gene expression and the activation of extracellular matrix (ECM) related pathways. Furthermore, gpnmb mutant hearts exhibit larger fibrotic scars revealing additional defects in cardiac regeneration. Altogether, these data indicate that gpnmb expressing macrophages modulate inflammation and ECM deposition after cardiac cryoinjury in zebrafish and further highlight the importance of this subset of immune cells to support a regenerative response.

molecular biology↗

bioRxiv2024

A combination of systemic mannitol administration and mannitol-modified polyester nanoparticles facilitate gene delivery to the brain through caveolae-mediated endocytosis

Overcoming the blood-brain barrier (BBB) remains a significant challenge for nucleic acid delivery to the brain. We have explored a combination of mannitol-modified poly ({beta}-amino ester) (PBAE) nanoparticles and systemic mannitol injection for crossing the BBB. We incorporated mannitol in the PBAE polymer for caveolae targeting and also selected monomers that may help avoid delivery to the liver. We also induced caveolae at the BBB through systemic mannitol injection in order to create an opportunity for the caveolae-targeting nanoparticles (M30 D90)containing plasmid DNA to cross the BBB. When a clinically relevant dose was administered intravenously in this caveolae induction model, M30 D90 demonstrated significant transgene expression of a reporter plasmid in the brain, with selective uptake by neuronal cells and minimal liver accumulation. We also demonstrate that both caveolae modulation using systemic mannitol administration and caveolae targeting using designed nanoparticles are necessary for efficient delivery to the brain. This delivery platform offers a simple, scalable, and controlled delivery solution and holds promise for treating central nervous system diseases with functional targets.

bioengineering↗

bioRxiv2024

Nociceptor Neurons Control Pollution-Mediated Neutrophilic Asthma

The immune and sensory nervous systems, having evolved in parallel, communicate through shared receptors and transmitters to maintain homeostasis and respond to both external and internal disruptions. Although neural responses often confer protective benefits, they can also exacerbate inflammation during allergic reactions such as asthma. In our study, we modeled pollution-exacerbated asthma by exposing mice to ambient PM2.5 particles alongside ovalbumin. Compared to exposure to ovalbumin alone, this co-exposure significantly increased the numbers of neutrophils and {gamma}{delta} T cells in bronchoalveolar lavage fluid. We found that silencing nociceptor neurons at the peak of inflammation using intranasal QX-314 or ablating TRPV1-expressing neurons reduced lung neutrophil accumulation. Live in vivo intravital imaging confirmed that neuronal ablation reduced neutrophil numbers and increased their net displacement capacity. In neurons isolated from mice with pollution-exacerbated asthma, the chemical-sensing TRPA1 channel exhibited heightened sensitivity to its cognate ligand. Elevated levels of artemin were detected in the bronchoalveolar lavage fluid of pollution-exposed mice but returned to baseline in mice with ablated nociceptor neurons. Alveolar macrophages expressing the pollution-sensing aryl hydrocarbon receptor were identified as a putative source of artemin following exposure to PM2.5. This molecule enhanced TRPA1 responsiveness and, in turn, drove nociceptor-mediated neutrophil recruitment, revealing a novel mechanism by which lung-innervating neurons respond to air pollution in the context of allergy. Overall, our findings suggest that targeting artemin-driven pathways could provide a therapeutic strategy for controlling neutrophilic airway inflammation in asthma, a clinical condition typically refractory to treatment.

immunology↗

bioRxiv2024

Dynamins combine mechano-constriction and membrane remodeling to enable two-step mitochondrial fission via a snap-through instability.

Mitochondrial fission is controlled by dynamin proteins, the dysregulation of which is correlated with diverse diseases. Fission dynamins are GTP hydrolysis-driven mechanoenzymes that self-oligomerize into helical structures that constrict membrane to achieve fission, but details are not well understood. However, dynamins can also remodel membranes by inducing negative Gaussian curvature, the type of curvature required for completion of fission. Here, we examine how these drastically different mechanisms synergistically exert their influences on a membrane, via a mechanical model calibrated with small-angle X-ray scattering structural data. We find that free dynamin can trigger a "snap-through instability" that enforces a shape transition from an oligomer-confined cylindrical membrane to a drastically narrower catenoid-shaped neck within the spontaneous hemi-fission regime, in a manner that depends critically on the length of the confined tube. These results indicate how the combination of dynamin assembly, and paradoxically disassembly, can lead to diverse pathways to scission. TeaserDynamin mechano-constriction by assembly and curvature-driven instability by free monomers synergistically drive mitochondrial fission.

biophysics↗

bioRxiv2024

Traffic Jam activates the Flamenco piRNA cluster locus and the Piwi pathway to ensure transposon silencing and Drosophila fertility.

Flamenco (Flam) is the most prominent piRNA cluster locus expressed in Drosophila ovarian follicle cells, and it is required for female fertility to silence gypsy/mdg4 transposons. To determine how Flam is regulated, we used promoter-bashing reporter assays in OSS cells to uncover novel enhancer sequences within the first exons of Flam. We confirmed the enhancer sequence relevance in vivo with new Drosophila Flam deletion mutants of these regions that compromised Flam piRNA expression and lowered female fertility from activated transposons. Our proteomic analysis of proteins associated with these enhancer sequences discovered the transcription factor Traffic Jam (TJ). Tj knockdowns in OSS cells caused a decrease in Flam transcripts, Flam piRNAs, and multiple Piwi pathway genes. A TJ ChIP-seq analysis from whole flies and OSS cells confirmed TJ binding exactly at the enhancer that was deleted in the new Flam mutant as well as at multiple Piwi pathway gene enhancers. Interestingly, TJ also bound the Long Terminal Repeats of transposons that had decreased expression after Tj knockdowns in OSS cells. Our study reveals the integral role TJ plays in the on-going arms race between selfish transposons and their suppression by the host Piwi pathway and the Flam piRNA cluster locus.

genetics↗

bioRxiv2024

Beyond Differential Expression: Embracing Cell-to-Cell Variability in Single-Cell Gene Expression Data Analysis

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular variability by capturing gene expression profiles of individual cells. The importance of cell-to-cell variability in determining and shaping cell function has been widely appreciated. Nevertheless, differential expression (DE) analysis remains a cornerstone method in analytic practice, by focusing exclusively on mean expressional differences, current computational analyses overlook the rich information encoded by variability within the single-cell gene expression data. Thus, there is a need for more relevant approaches to assess data variability rather than the mean in order to offer a deeper understanding of cellular systems. Here we present spline-DV, a novel statistical framework for differential variability (DV) analysis using scRNA-seq data. The spline-DV method identifies genes exhibiting significantly increased or decreased expression variability among cells derived from two experimental conditions. Case studies show that DV genes identified using spline-DV are representative, and functionally relevant in the tested cellular conditions including obesity, fibrosis, and cancer.

bioinformatics↗

bioRxiv2024

Re-analysis of mobile mRNA datasets highlights challenges in the detection of mobile transcripts from short-read RNA-Seq data

Short-read RNA-Seq analyses of grafted plants have led to the proposal that large numbers of mRNAs move over long distances between plant tissues, acting as potential signals. The detection of transported transcripts by RNA-Seq is both experimentally and computationally challenging, requiring successful grafting, delicate harvesting, rigorous contamination controls and data processing approaches that can identify rare events in inherently noisy data. Here, we perform a meta-analysis of existing datasets and examine the associated bioinformatic pipelines. Our analysis reveals that technological noise, biological variation and incomplete genome assemblies give rise to features in the data that can distort the interpretation. Taking these considerations into account, we find that a substantial number of transcripts that are currently annotated as mobile are left without support from the available RNA-Seq data. Whilst several annotated mobile mRNAs have been validated, we cannot exclude that others may be false positives. The identified issues may also impact other RNA-Seq studies, in particular those using single nucleotide polymorphisms (SNPs) to detect variants.

plant biology↗

bioRxiv2024

Inseparable/IER3IP1 are essential for cytokinesis in Drosophila neuroblast and human cells

To unveil the molecular players that maintain neural stem cell homeostasis, we conducted a genetic screen in Drosophila and isolated an uncharacterized gene that we named Inseparable (Insep). Insep is the Drosophila homologue of human IER3IP1, a gene associated with Microcephaly, Epilepsy, and Neonatal Diabetes Syndrome (MEDS-1). We show that Insep loss leads to early larval lethality with small brains and these phenotypes can be rescued by expressing IER3IP1 indicating that their biological function is conserved through evolution. The Insep deficient neuroblasts fail to complete cytokinesis and show excessive accumulation of Rab11 vesicles in the cytoplasm. Similarly, IER3IP1 depletion in human cells leads to cytokinesis failure and accumulation of Rab11 vesicles. Insep and IER3IP1 localize to Rab11 vesicles and interact with Rab11. The pathogenic mutations in IER3IP1 perturb its localization to Rab11 vesicles and interaction with Rab11. These results suggest that Insep and IER3IP1 work along with Rab11 and may regulate fusion of Rab11 vesicles to the advancing furrow during cytokinesis.

cell biology↗

bioRxiv2024

High-yield production of recombinant human myelin oligodendrocyte glycoprotein in SHuffle bacteria without a refolding step

1.1Experimental autoimmune encephalomyelitis (EAE) is a model for central nervous system (CNS) autoimmune demyelinating diseases such as multiple sclerosis (MS) and MOG antibody-associated disease (MOGAD). Immunization with the extracellular domain of recombinant human MOG (rhMOG), which contains pathogenic antibody and T cell epitopes, induces B cell-dependent EAE for studies in mice. However, these studies have been hampered by rhMOG availability due to its insolubility when overexpressed in bacterial cells, and the requirement for inefficient denaturation and refolding. Here, we describe a new protocol for the high-yield production of soluble rhMOG in SHuffle cells, a commercially available E. coli strain engineered to facilitate disulfide bond formation in the cytoplasm. SHuffle cells can produce a soluble fraction of rhMOG yielding >100 mg/L. Analytical size exclusion chromatography multi-angle light scattering (SEC-MALS) and differential scanning fluorimetry of purified rhMOG reveals a homogeneous monomer with a high melting temperature, indicative of a well-folded protein. An in vitro proliferation assay establishes that purified rhMOG can be processed and recognized by T cells expressing a T cell receptor (TCR) specific for the immunodominant MOG35-55 peptide epitope. Lastly, immunization of wild-type, but not B cell deficient, mice with rhMOG resulted in robust induction of EAE, indicating a B cell-dependent induction. Our SHuffle cell method greatly simplifies rhMOG production by combining the high yield and speed of bacterial cell expression with enhanced disulfide bond formation and folding, which will enable further investigation of B cell-dependent EAE and expand human research of MOG in CNS demyelinating diseases.

biochemistry↗

bioRxiv2024

Gene Function Revealed at the Moment of Stochastic Gene Silencing

Gene expression is a dynamic and stochastic process characterized by transcriptional bursting followed by periods of silence. Single-cell RNA sequencing (scRNA-seq) is a powerful tool to measure transcriptional bursting and silencing at the individual cell level. In this study, we introduce the single-cell Stochastic Gene Silencing (scSGS) method, which leverages the natural variability in single-cell gene expression to decipher gene function. For a target gene g under investigation, scSGS classifies cells into transcriptionally active (g+) and silenced (g-) samples. It then compares these cell samples to identify differentially expressed genes, referred to as SGS-responsive genes, which are used to infer the function of the target gene g. Analysis of real data demonstrates that scSGS can reveal regulatory relationships up- and downstream of target genes, circumventing the survivorship bias that often affects gene knockout and perturbation studies. scSGS thus offers an efficient approach for gene function prediction, with significant potential to reduce the use of genetically modified animals in gene function research.

bioinformatics↗

bioRxiv2024

Electrochemical cofactor recycling of bacterial microcompartments

Bacterial microcompartments (BMCs) are prokaryotic organelles that consist of a protein shell which sequesters metabolic reactions in its interior. While most of the substrates and products are relatively small and can permeate the shell, many of the encapsulated enzymes require cofactors that must be regenerated inside. We have analyzed the occurrence of an enzyme previously assigned as a cobalamin (vitamin B12) reductase and, curiously, found it in many unrelated BMC types that do not employ B12 cofactors. We propose NAD+ regeneration as a new function of this enzyme and name it MNdh, for Metabolosome NADH dehydrogenase. Its partner shell protein BMC-TSE assists in passing the generated electrons to the outside. We support this hypothesis with bioinformatic analysis, functional assays, EPR spectroscopy, protein voltammetry and structural modeling verified with X-ray footprinting. This discovery represents a new paradigm for the BMC field, identifying a new, widely occurring route for cofactor recycling and a new function for the shell as separating redox environments.

microbiology↗

bioRxiv2024

NPM1 mediates genome-nucleolus interactions and the establishment of their repressive chromatin states

Repressive chromatin domains are often located at the nuclear lamina (NL) or nucleolus. Although nucleolar associated domains (NADs) have been recently mapped, the mechanisms of NAD association with nucleoli and the functional significance of their localization remain unclear. Here, we show that NAD association with nucleoli is mediated by nucleophosmin (NPM1), a factor located within the granular component, the outer layer of the nucleolus. NPM1 binds NADs, interacts with the histone lysine methyltransferase G9a (EHMT2), and is required for establishing H3K9me2 at NADs. Loss of NPM1 or expression of NPM1 mutant lacking the DNA binding domain (NPM1{Delta}DBD) caused NAD dissociation from nucleoli and H3K9me2 reduction specifically at NADs. G9a is dispensable for NAD contacts with nucleoli and interacts with NPM1{Delta}DBD, indicating that NADs acquire G9a-mediated H3K9me2 only after associating with NPM1 at nucleoli. The results provide mechanistic insights into how genomic domains associate with nucleoli and acquire their repressive chromatin state. Additionally, our findings suggest that the nucleolus not only serves as a scaffold for positioning repressive chromatin domains but also plays a direct role in establishing these chromatin states.

molecular biology↗