Biology subjects

Takizawa, S.

Publications and source records attributed to Takizawa, S..

7 recordsLinked to original sources

bioRxiv2026

The human RNA-DNA interactome is cell type-specific and dynamic

More than twenty years ago, the FANTOM consortium uncovered that mammalian genomes are pervasively transcribed, revealing multitudes of RNAs with unknown functions. A subset of these transcripts has since then been linked to transcriptional control and to chromatin organization via their ability to interact with DNA, suggesting that chromatin-associated RNAs could be key players in genome regulation. Although recent technological advances now enable the mapping of genome-wide RNA-DNA contacts, a lack of analyses integrating these methods with other genomic features and across multiple cellular contexts hinders our comprehensive understanding of the principles underlying RNA-DNA interactions and of their biological importance. As part of the FANTOM6 project, we thus generated RNA-DNA interaction maps in 16 different human cell types, then combined these contacts with multiple layers of other genomic data to investigate how patterns of interaction between RNA and DNA relate to chromatin organization and function. We show that the RNA-DNA interactome is highly dynamic yet reproducibly organized in cell-type specific networks, constituted of a great diversity of interactions that vary in function of their distance, the nature of their sources and the chromatin state of their targets. In particular, we detected numerous regulatory elements that exhibit marked changes in activity when differentially bound by transcripts, implying that thousands of RNA-DNA interactions can play a mechanistic role in gene expression. This regulatory function correlates with RNA-protein interactions and significantly associates with cell type-relevant and disorder-related traits. In addition to providing essential resources for future research in RNA-mediated chromatin regulation, cellular biology and human diseases, our study thus establishes the RNA-DNA interactome as a new genome regulatory layer that defines and maintains cellular identity and behavior.

genomics↗

bioRxiv2025

Speed-controlled visual stimuli modulate fish collective dynamics

Fish navigation is modulated by visual stimulation and associated parameters, such as size, speed, and orientation, yet the regulatory mechanisms remain unclear. Here, we experimentally investigate how systematically controlled stimulus speed influences the temporal and spatial collective dynamics of Hemigrammus bleheri. Using a simple and customisable top-down projection setup, we displayed clockwise-rotating black-dot patterns at three distinct speeds to simulate complex environmental motion cues. We quantified individual temporal responsiveness through angular movements, and evaluated group-level spatial organisation. Fish angular movements positively tracked the rotation direction of the visual patterns. Lower stimulus speeds elicited predominantly exploratory behaviour, while higher speeds induced a transition to strong motion-tracking behaviour, aligning fish orientation with the rotating patterns. Increasing stimulus speed also corresponded with greater nearest-neighbour distance, indicating reduced spatial cohesion. Notably, we observed transient schooling episodes not aligned with the rotational stimulus, reflecting periods in which internal social interactions outweighed stimulus-driven coordination. Using a newly defined free-schooling index, we show that such internally driven episodes were frequent at lower stimulus speeds but markedly reduced at higher speeds. Overall, these results demonstrate that speed-controlled visual stimuli modulate both individual navigation and group coherence, offering new insights into how visual cues shape fish collective behaviour dynamics.

animal behavior and cognition↗

bioRxiv2024

RADIP technology comprehensively identifies H3K27me3-mediated RNA-chromatin interactions

Many RNAs associate with chromatin, either directly or indirectly. Several technologies for mapping regions where RNAs interact across the genome have been developed to investigate the function of these RNAs. Obtaining information on the proteins involved in these RNA-chromatin interactions is critical for further analysis. Here, we developed RADIP (RNA and DNA interacting complexes ligated and sequenced (RADICL-seq) with immunoprecipitation), a novel technology that combines RADICL-seq technology with chromatin immunoprecipitation to characterize RNA-chromatin interactions mediated by individual proteins. Building upon the foundational principles of RADICL-seq, RADIP extends its advantages by increasing genomic coverage and unique mapping rate efficiency compared to existing methods. To demonstrate its effectiveness, we applied an anti-H3K27me3 antibody to the RADIP technology and generated libraries from mouse embryonic stem cells (mESCs). We identified a multitude of RNAs, including RNAs from protein-coding genes and non-coding RNAs, that are associated with chromatin via H3K27me3 and that likely facilitate the spread of Polycomb repressive complexes over broad regions of the mammalian genome, thereby affecting gene expression, chromatin structures and pluripotency of mESCs. Our study demonstrates the applicability of RADIP to investigations of the functions of chromatin-associated RNAs. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/597497v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@c41e0forg.highwire.dtl.DTLVardef@1919e78org.highwire.dtl.DTLVardef@13adc29org.highwire.dtl.DTLVardef@14c3db8_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2022

xcore: an R package for inference of gene expression regulators

Elucidating the Transcription Factors (TFs) that drive the gene expression changes in a given experiment is one of the most common questions asked by researchers. The existing methods rely on the predicted Transcription Factor Binding Site (TFBS) to model the changes in the motif activity. Such methods only work for TFs that have a motif and assume the TF binding profile is the same in all cell types. Given the wealth of the ChIP-seq data available for a wide range of the TFs in various cell types, we propose that the modeling can be done using ChiP-seq "signatures" directly, effectively skipping the motif finding and TFBS prediction steps. We present xcore, an R package that allows Transcription Factor activity modeling based on their ChiP-seq signatures and users gene expression data. We also provide xcoredata a companion data package that provides a collection of preprocessed ChiP-seq signatures. We demonstrate that xcore leads to biologically relevant predictions using TGF-beta induced epithelial-mesenchymal transition and rinderpest infection time-course CAGE data as examples. Availability and Implementationxcore and xcoredata R packages are freely available at www.github.com/bkaczkowski/xcore and www.github.com/mcjmigdal/xcoredata. xcore user guide is available www.bkaczkowski.github.io/xcore/articles/xcore_vignette.html. Contactb.kaczkowski@gmail.com

bioinformatics↗

bioRxiv2021

ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation

Regulatory elements control gene expression through transcription initiation (promoters) and by enhancing transcription at distant regions (enhancers). Accurate identification of regulatory elements is fundamental for annotating genomes and understanding gene expression patterns. While there are many attempts to develop computational promoter and enhancer identification methods, reliable tools to analyze long genomic sequences are still lacking. Prediction methods often perform poorly on the genome-wide scale because the number of negatives is much higher than that in the training sets. To address this issue, we propose a dynamic negative set updating scheme with a two-model approach, using one model for scanning the genome and the other one for testing candidate positions. The developed method achieves good genome-level performance and maintains robust performance when applied to other species, without re-training. Moreover, the unannotated predicted regulatory regions made on the human genome are enriched for disease-associated variants, suggesting them to be potentially true regulatory elements rather than false positives. We validated high scoring "false positive" predictions using reporter assay and all tested candidates were successfully validated, demonstrating the ability of our method to discover novel human regulatory regions.

bioinformatics↗

bioRxiv2020

Efficient Development of Platform Cell Lines Using CRISPR-Cas9 1 and Transcriptomics Analysis

Antibody-drug conjugates offers many advantages as a drug delivery platform that allows for highly specific targeting of cell types and genes. Ideally, testing the efficacy of these systems requires two cell types to be different only in the gene targeted by the drug, with the rest of the cellular machinery unchanged, in order to minimize other potential differences from obscuring the effects of the drug. In this study, we created multiple variants of U87MG cells with targeted mutation in the TP53 gene using the CRISPR-Cas9 system, and determined that their major transcriptional differences stem from the loss of p53 function. Using the transcriptome data, we predicted which mutant clones would have less divergent phenotypes from the wild type and thereby serve as the best candidates to be used as drug delivery testing platforms. Further in vitro and in vivo assays of cell morphology, proliferation rate and target antigen-mediated uptake supported our predictions. Based on the combined analysis results, we successfully selected the best qualifying mutant clone. This study serves as proof-of-principle of the approach and paves the way for extending to additional cell types and target genes.

bioengineering↗

bioRxiv2018

C1 CAGE detects transcription start sites and enhancer activity at single-cell resolution

Single-cell transcriptomic profiling is a powerful tool to explore cellular heterogeneity. However, most of these methods focus on the 3-end of polyadenylated transcripts and provide only a partial view of the transcriptome. We introduce C1 CAGE, a method for the detection of transcript 5-ends with an original sample multiplexing strategy in the C1 microfluidic system. We first quantified the performance of C1 CAGE and found it as accurate and sensitive as other methods in C1 system. We then used it to profile promoter and enhancer activities in the cellular response to TGF-{beta} of lung cancer cells and discovered subpopulations of cells differing in their response. We also describe enhancer RNA dynamics revealing transcriptional bursts in subsets of cells with transcripts arising from either strand within a single-cell in a mutually exclusive manner, which was validated using single molecule fluorescence in-situ hybridization.

genomics↗