Biology subjects

Onimaru, K.

Publications and source records attributed to Onimaru, K..

3 recordsLinked to original sources

bioRxiv2025

RNA Dynamics Regulate Transcriptional Condensate Vivacity to Drive Gene Coordination

Transcriptional condensates (TCs), enriched with Mediator, orchestrate super-enhancer (SE)-driven gene expression critical for cell identity. However, how their dynamic physical properties shape transcriptional activities remains unclear. Here, we reveal a previously unknown regulatory axis wherein dynamic features of enhancer RNA (eRNA), transcribed but rapidly degraded by the RNA exosome, maintain optimal TC fluidity and stability. Depletion of RNA exosome disrupts TC integrity, altering Mediator and Pol II colocalization, in embryonic stem cells. This TC perturbation attenuates proper transcriptional regulator loading and pause-release regulation, enhances transcriptional noise, and diminishes coordinated eRNA-mRNA expression for SE-associated genes. Multi-omics analyses, live-cell imaging, and computational modeling collectively demonstrate that RNA turnover modulates TC vivacity, facilitating widespread chromatin contacts between SE-containing active A compartments and coordinated transcriptional bursts across SE-associated genes. Our findings establish RNA-dependent condensate dynamics as an essential quality-control mechanism that fine-tunes global transcriptional coordination, maintaining cellular homeostasis and cell identity. HighlightsO_LIRNA exosome is required for the homeostasis of transcriptional condensates (TCs) C_LIO_LIRNA synthesis and decay optimize the fluidity and dynamic properties of TCs C_LIO_LITCs maintain the transcriptional consistency of super-enhancer (SE) genes C_LIO_LITCs support contacts of SE-containing A compartments for coordinated transcription C_LI

molecular biology↗

bioRxiv2020

Developmental hourglass and heterochronic shifts in fin and limb development

How genetic changes are linked to morphological novelties and developmental constraints remains elusive. Here we investigate genetic apparatuses that distinguish fish fins from tetrapod limbs by analyzing transcriptomes and open chromatin regions (OCRs). Specifically, we compare mouse forelimb buds with pectoral fin buds of a slowly evolving species, the brown-banded bamboo shark (Chiloscyllium punctatum). A transcriptomic comparison with an accurate orthology map reveals both a mass heterochrony and hourglass-shaped conservation of gene expression between fins and limbs. Furthermore, chromatin-accessibility data indicate that conserved regulatory sequences are most active during mid-stage limb development. During this stage, stage-specific and tissue-specific OCRs are also enriched. Together, early and late stages of fin/limb development are more permissive to mutations, which may have contributed to the major morphological changes during the fin-to-limb evolution. We also hypothesize that the middle stages are constrained by regulatory complexity that results from dynamic and tissue-specific transcriptional controls.

evolutionary biology↗

bioRxiv2018

A regulatory-sequence classifier with a neural network for genomic information processing

Genotype-phenotype mapping is one of the fundamental challenges in biology. The difficulties stem in part from the large amount of sequence information and the puzzling genomic code, particularly of non-protein-coding regions such as gene regulatory sequences. However, recently deep learning-based methods were shown to have the ability to decipher the gene regulatory code of genomes. Still, prediction accuracy needs improvement. Here, we report the design of convolution layers that efficiently process genomic sequence information and developed a software, DeepGMAP, to train and compare different deep learning-based models (https://github.com/koonimaru/DeepGMAP). First, we demonstrate that our convolution layers, termed forward- and reverse-sequence scan (FRSS) layers, enhance the power to predict gene regulatory sequences. Second, we assessed previous studies and identified problems associated with data structures that caused overfitting. Finally, we introduce several visualization methods that provide insights into the syntax of gene regulatory sequences.

bioinformatics↗