Biology subjects

Nakato, R.

Publications and source records attributed to Nakato, R..

12 recordsLinked to original sources

bioRxiv2024

ChromBERT: Uncovering Chromatin State Motifs in the Human Genome Using a BERT-based Approach

Chromatin states, which are defined by specific combinations of histone post-translational modifications, are fundamental to gene regulation and cellular identity. Despite their importance, comprehensive patterns within chromatin state sequences, which could provide insights into key biological functions, remain largely unexplored. In this study, we introduce ChromBERT, a BERT-based model specifically designed to detect distinct chromatin state patterns as "motifs." We pre-trained ChromBERT on 15-state chromatin annotations from 127 human cell and tissue types from the ROADMAP consortium. This pre-trained model can be fine-tuned for various downstream tasks, and obtained high-attention chromatin state patterns are extracted as motifs. To account for the variable-length nature of chromatin state motifs, ChromBERT uses Dynamic Time Warping to cluster similar motifs and identify meaningful representative patterns. In this study, we evaluated the performance of the model on several tasks, including binary and quantitative gene expression prediction, cell type classification, and three-dimensional genome feature classification. Our analyses yielded biologically grounded results and revealed the associated chromatin state motifs. This workflow facilitates the discovery of specific chromatin state patterns across different biological contexts and offers a new framework for exploring the dynamics of epigenomic states.

bioinformatics↗

bioRxiv2023

Morc1 re-establishes heterochromatin on activated transposons and shapes the host transcriptome in gonocytes

Following reprogramming of DNA methylation, numerous transposable elements (TEs) are transiently activated in male prenatal gonocytes. Persistent expression of such TEs to adulthood leads to arrest of germ cell development. However, how these TEs are re-silenced has been unexplored. Here, we found that DNA-binding protein Morc1 re-established H3K9me3-marked heterochromatin on activated TEs, which involved methyltransferase SetDB1. Although Morc1 also triggered DNA methylation, the types of Morc1-targeted TEs for each epigenetic modification were different, suggesting that these two mechanisms were largely independent of each other. Significant overlap between TEs targeted by Morc1 and those by Miwi2, a nuclear PIWI protein, indicated that piRNA-loaded Miwi2 conferred target specificity to Morc1. Activated TEs drove transcription of adjacent genes by acting as ectopic cis-regulatory elements. Such a disrupting effect of TEs on the transcriptome was compensated by Morc1. Thus, Morc1 ensures proper interactions of TEs with host genes through re-establishment of heterochromatin in gonocytes.

bioinformatics↗

bioRxiv2023

Loop-extruding Smc5/6 organizes transcription-induced positive DNA supercoils

The Structural Maintenance of Chromosome (SMC) protein complexes cohesin, condensin and the Smc5/6 complex (Smc5/6) are essential for chromosome function. At the molecular level, these complexes fold DNA by loop extrusion. Accordingly, cohesin creates chromosome loops in interphase, and condensin compacts mitotic chromosomes. However, the role of Smc5/6s recently discovered DNA loop extrusion activity is unknown. Here, we uncover that Smc5/6 associates with transcription-induced positively supercoiled chromosomal DNA at cohesin-dependent chromosome loop boundaries. Mechanistically, single-molecule imaging reveals that dimers of Smc5/6 specifically recognize the tip of positively supercoiled DNA plectonemes, and efficiently initiates loop extrusion to gather the supercoiled DNA into a large plectonemic loop. Finally, Hi-C analysis shows that Smc5/6 links chromosomal regions containing transcription-induced positive supercoiling in cis. Altogether, our findings indicate that Smc5/6 controls the three-dimensional organization of chromosomes by recognizing and initiating loop extrusion on positively supercoiled DNA.

molecular biology↗

bioRxiv2023

Nutrient-driven dedifferentiation of enteroendocrine cells promotes adaptive intestinal growth

Post-developmental organ resizing improves organismal fitness under constantly changing nutrient environments. Although stem cell abundance is a fundamental determinant of adaptive resizing, our understanding of its underlying mechanisms remains primarily limited to the regulation of stem cell division. Here we demonstrate that nutrient fluctuation induces dedifferentiation in the Drosophila adult midgut to drive adaptive intestinal growth. From lineage tracing and single-cell RNA-sequencing, we identify a subpopulation of enteroendocrine cells (EEs) that convert into functional intestinal stem cells (ISCs) in response to dietary glucose and amino acids by activating the JAK-STAT pathway. Genetic ablation of EE-derived ISCs severely impairs ISC expansion and midgut growth despite the retention of resident ISCs, and in silico modeling further indicates that EE dedifferentiation enables efficient increase in the midgut cell number while maintaining epithelial cell composition. Our findings uncover a physiologically-induced dedifferentiation that ensures ISC expansion during adaptive organ growth in concert with nutrient conditions.

developmental biology↗

bioRxiv2022

Context-dependent 3D genome regulation by cohesin and related factors

Cohesin plays vital roles in chromatin folding and gene expression regulation, cooperating with such factors as cohesin loaders, unloaders, acetyltransferase, and the insulation factor CTCF. Although various models of regulation have been proposed (e.g., loop extrusion), how cohesin and related factors collectively or individually regulate the hierarchical chromatin structure and gene expression remains unclear. In this study, we have depleted cohesin and related factors and then conducted a comprehensive evaluation of the resulting 3D genome, transcriptome and epigenome data. We observed substantial variation in depletion effects among factors at topologically associating domain (TAD) boundaries and on interTAD interactions, which were partly related to epigenomic status. Gene expression changes were highly correlated with direct cohesin binding and gain of TAD boundaries than with the loss of boundaries. Our results suggested that cohesin positively regulates gene expression, whereas other mechanisms (e.g., cohesin turnover and acetylation) add to the diversity of this pattern of dysregulation. Moreover, cohesin was broadly enriched in active compartment A, but not in compartment B, which were retained even after CTCF depletion. Our rich dataset and the subsequent data-driven analysis support the context-specific regulation of chromatin folding by cohesin and related factors.

genomics↗

bioRxiv2021

Large-scale multi-omics analysis suggests specific roles for intragenic cohesin in transcriptional regulation

Cohesin, an essential protein complex for chromosome segregation, regulates transcription through a variety of mechanisms. It is not a trivial task to genome-widely assign the diverse cohesin functions. Moreover, the context-specific roles of cohesin-mediated interactions, especially on intragenic regions, have not been thoroughly investigated. Here we performed a comprehensive characterization of cohesin binding sites in several human cell types. We integrated epigenomic, transcriptomic and chromatin interaction data with and without transcriptional stimulation, to explore context-specific functions of intragenic cohesin related to gene activation. We identified a new subset of cohesin binding sites, decreased intragenic cohesin sites (DICs), which have a different function from previously known ones. The intron-enriched DICs were negatively correlated with transcriptional regulation: a subgroup of DICs were related to enhancer markers and paused RNA polymerase II, whereas others contributed to chromatin architecture. We implemented machine learning and successfully isolated DICs with distinct genomic features. We observed DICs in various cell types, including cells from cohesinopathy patients. These results suggest a previously unidentified function of cohesin at intragenic regions for transcription regulation.

genomics↗

bioRxiv2021

Codependency and mutual exclusivity for gene community detection from sparse single-cell transcriptome data

Single-cell RNA-seq (scRNA-seq) can be used to characterize cellular heterogeneity in thousands of cells. The reconstruction of a gene network based on coexpression patterns is a fundamental task in scRNA-seq analyses, and the mutual exclusivity of gene expression can be critical for understanding such heterogeneity. Here, we propose an approach for detecting communities from a genetic network constructed on the basis of coexpression properties. The community-based comparison of multiple coexpression networks enables the identification of functionally related gene clusters that cannot be fully captured through differential gene expression-based analysis. We also developed a novel metric referred to as the exclusively expressed index (EEI) that identifies mutually exclusive gene pairs from sparse scRNA-seq data. EEI quantifies and ranks the exclusive expression levels of all gene pairs from binary expression patterns while maintaining robustness against a low sequencing depth. We applied our methods to glioblastoma scRNA-seq data and found that gene communities were partially conserved after serum stimulation despite a considerable number of differentially expressed genes. We also demonstrate that the identification of mutually exclusive gene sets with EEI can improve the sensitivity of capturing cellular heterogeneity. Our methods complement existing approaches and provide new biological insights, even for a large, sparse dataset, in the single-cell analysis field.

bioinformatics↗

bioRxiv2020

Transcription and replication organize cohesin-dependent chromosome loops

Genome function and stability is strictly dependent on regulated folding of chromosomes in space and time. Chromosome loop formation by the protein complex cohesin is a central feature of this multilayer organization1. Accumulating evidence indicates that cohesin creates loops by extruding chromosomal DNA through its ring-like structure in a process that is controlled by the cohesin loading factor Scc2 and the unloader Wpl11-4. Cohesins chromosomal positioning is affected by transcription in both yeast and human cells5,6, and the complex localizes in the vicinity of replication forks7. However, if transcription directly influences chromosome looping remains an unresolved question, and the threedimensional organization of replicating chromosomes is unknown. Here we show that transcription and replication machineries create chromosome loop boundaries. We find that drug-induced depletion of chromosome-bound RNA polymerases triggers a rapid expansion of cohesin-dependent chromosome loops in the budding yeast Saccharomyces cerevisiae. New loop boundaries also form at a few highly expressed genes induced by the cellular stress response caused by the drug. The results also reveal that S-phase chromosomes are shaped by cohesin-dependent loops organized by transcription, with additional loop anchors at replication forks. Together, our results show that replication and transcription control the three-dimensional organization of the genome by blocking the progression of loop-forming cohesin. They also open for the possibility that the resulting positioning of loop-forming cohesin in the vicinity of transcription and replication machineries is part of cohesins functions in transcription control, sister chromatid cohesion and maintenance of fork stability.

molecular biology↗

bioRxiv2019

Comprehensive epigenome characterization reveals diverse transcriptional regulation across human vascular endothelial cells

BackgroundEndothelial cells (ECs) make up the innermost layer throughout the entire vasculature. Their phenotypes and physiological functions are initially regulated by developmental signals and extracellular stimuli. The underlying molecular mechanisms responsible for the diverse phenotypes of ECs from different organs are not well understood.\n\nResultsTo characterize the transcriptomic and epigenomic landscape in the vascular system, we cataloged gene expression and active histone marks in nine types of human ECs (generating 148 genome-wide datasets) and carried out a comprehensive analysis with chromatin interaction data. We identified 3,765 EC-specific enhancers, some of which were associated with disease-associated genetic variations. We also identified various candidate marker genes for each EC type. Notably, reflecting the developmental origins of ECs and their roles in angiogenesis, vasculogenesis and wound healing.\n\nConclusionsWhile the importance of several HOX genes for early vascular development and adult angiogenesis in pathological conditions has been reported, a systematic analysis of the regulation and roles of HOX genes in mature tissue cells has been lacking. These datasets provide a valuable resource for understanding the vascular system and associated diseases.

genomics↗

bioRxiv2019

Dissecting the functions of NIPBL using genome editing: The importance of the N-terminus of NIPBL in transcriptional regulation

Cornelia de Lange syndrome (CdLS) is characterized by craniofacial dysmorphisms, intellectual disabilities, growth retardation, and several other systemic abnormalities. CdLS is caused by heterozygous germline mutations in structural and regulatory components of cohesin. Mutations in NIPBL, which encodes regulatory subunit of cohesin, are frequently found in individuals with CdLS. CdLS is associated with a currently unknown mechanism of global transcriptional dysregulation. In this study, NIPBL mutants were generated using the CRISPR/Cas9 system to study this mechanism. Clones with a biallelic frameshift mutation in exon 3 of NIPBL, resulting in a truncated N-terminus, displayed transcriptional dysregulation without sister chromatid separation defects. Detailed transcriptome analysis revealed the overexpression of genes in NIPBL mutants that are typically expressed at low levels in wild type and the reduced expression of genes that are typically expressed at high levels in wild type. This result suggested that NIPBL plays a role in fine-tuning gene expression levels. MAU2 protein, that closely interacts with NIPBL, was nearly absent in these clones. The reduction of MAU2 observed in NIPBL mutants points to the importance of the NIPBL N-terminus/MAU2 interaction in transcriptional regulatory role of NIPBL.

genetics↗

bioRxiv2019

PHi-C: deciphering Hi-C data into polymer dynamics

Computational modelling methods for Hi-C data have revealed averaged and static features of the 3D genome in cell nuclei. Here, we describe a 4D simulation method, PHi-C (Polymer dynamics deciphered from Hi-C data), that depicts dynamic 3D genome features through polymer modelling. This method allows for demonstrations of dynamic characteristics of genomic loci and chromosomes, as observed in live-cell imaging experiments, and provides physical insights into Hi-C data.

bioinformatics↗

bioRxiv2017

Sensitive and robust assessment of ChIP-seq read distribution using a strand-shift profile

AbstractChromatin immunoprecipitation followed by sequencing (ChIP-seq) can detect read-enriched DNA loci for point-source (e.g., transcription factor binding) and broad-source factors (e.g., various histone modifications). Although numerous quality metrics for ChIP-seq data have been developed, the peaks thus obtained are still difficult to assess with respect to signal-to-noise ratio (S/N) and the percentage of false positives.\n\nWe developed a quality-assessment tool for ChIP-seq data, SSP (strand-shift profile), that quantifies S/N and peak reliability without peak calling. We validated SSP in-depth using [≥] 1,000 publicly available ChIP-seq datasets along with virtual data to demonstrate that SSP is quantifiable and sensitive to different S/Ns for both pointand broad-source factors. Moreover, SSP is consistent among cell types and with respect to variance of sequencing depth, and identifies low-quality samples that cannot be identified by quality metrics currently available. Finally, we show that \"hidden-duplicate reads\" cause aberrantly high S/Ns, and SSP provides an additional metric to avoid them, which can also contribute to estimation of peak mode (pointor broad-source) of samples.\n\nAvailabilityhttps://github.com/rnakato/SSP\"

bioinformatics↗