Search bioRxiv⌕ Search

Biology subjects

Kaizu, K.

Publications and source records attributed to Kaizu, K..

2 recordsLinked to original sources

Replication-dependent histone (Repli-Histo) labeling dissects the physical properties of euchromatin/heterochromatin in living human cells.

A string of nucleosomes, where genomic DNA is wrapped around histones, is organized in the cell as chromatin. Chromatin in the cell varies greatly, from euchromatin to heterochromatin, in its genome functions. It is important to understand how heterochromatin is physically different from euchromatin. However, their specific labeling methods in living cells are limited. To address this, we have developed replication-dependent histone labeling (Repli-Histo labeling) to label nucleosomes in euchromatin and heterochromatin based on DNA replication timing. We investigated local nucleosome motion in the four chromatin classes from euchromatin to heterochromatin of living human and mouse cells. We found that more euchromatic regions (earlier replicated regions) show greater nucleosome motion. Notably, the motion profile in each chromatin class persists throughout interphase. Genome chromatin is essentially replicated from regions with greater nucleosome motions, even though the replication timing program is perturbed. Our findings, combined with computational modeling, suggest that earlier replicated regions have more accessibility and local chromatin motion can be a major determinant of genome-wide replication timing.

cell biology↗

transomics2cytoscape: An automated software for interpretable 2.5-dimensional visualization of trans-omic networks

Biochemical network visualization is one of the essential technologies for mechanistic interpretation of omics data. In particular, recent advances in multi-omics measurement and analysis require the development of visualization methods that encompass multiple omics data. Visualization in 2.5 dimension (2.5D visualization), which is an isometric view of stacked X-Y planes, is a convenient way to interpret multi-omics/trans-omics data in the context of the conventional layouts of biochemical networks drawn on each of the stacked omics layers. However, 2.5D visualization of trans-omics networks is a state-of-the-art method that primarily relies on time-consuming human efforts involving manual drawing. Here, we present an R Bioconductor package transomics2cytoscape for automated visualization of 2.5D trans-omics networks. We confirmed that transomics2cytoscape could be used for rapid visualization of trans-omics networks presented in published papers within a few minutes. Transomics2cytoscape allows for frequent update/redrawing of trans-omics networks in line with the progress in multi-omics/trans-omics data analysis, thereby enabling network-based interpretation of multi-omics data at each research step. The transomics2cytoscape source code is available at https://github.com/ecell/transomics2cytoscape.

systems biology↗