Biology subjects

Tsugama, D.

Publications and source records attributed to Tsugama, D..

6 recordsLinked to original sources

bioRxiv2026

DEAR-OWL: a fully browser-based hybrid resource for instant or precise differential gene expression analysis

MotivationDifferential gene expression analysis (DEA) via RNA sequencing (RNA-seq) is essential but remains challenging for wet-lab biologists due to command-line complexities. Centralized web platforms democratize this process but suffer from server congestion, long queuing delays, data privacy risks with proprietary datasets, and limited long-term sustainability due to hosting fees. ResultsWe present DEAR-OWL (Differential Expression Analysis Resource on the Web (Lite)), a fully serverless, privacy-preserving web application that performs the DEA locally inside the users web browser. To combine instant exploratory speed with rigorous verification, the application runs two distinct analysis options. The first option is a fast screening tool written in native browser language (JavaScript) that delivers immediate, genome-wide fold-change calculations and statistical screening based on an edgeR-equivalent logic. The second option is a heavy-duty statistical tool that brings the standard R package (DESeq2) directly into the browser using WebR and WebAssembly technology, ensuring publication-grade validation without needing server power. Interactive visual plots (volcano plots, minus-average plots, and heatmaps) are seamlessly generated from the results of either analysis choice. Benchmarking proved its hardware compatibility: the browser-based DESeq2 engine completed the analysis in [~]30 seconds on a 64 GB RAM workstation and in [~]3 minutes on an 8 GB RAM laptop without crashing. DEAR-OWL can utilize the Grass Expression Atlas (GExA) data as built-in and supports secure local file uploads, ensuring total data privacy with neither queuing delays nor cloud infrastructure costs. Availability and implementationDEAR-OWL is freely accessible at https://webpark2116.sakura.ne.jp/deseq2/. The source code is available at https://github.com/kota200/DEAR-OWL.

bioinformatics↗

bioRxiv2026

Decoding universal principles of codon-mediated regulation of gene expression

Codon usage determines gene expression levels, yet its universal principles remain elusive. Here, we developed a regression-based model to derive "codon weights" from transcriptomic data, enabling improved prediction of mRNA and protein abundance across diverse taxa, including plants, mammals, insects, and microbes. Ribosome profiling (Ribo-seq) data analysis revealed that these codon weights correlate with Ribo-seq-weighted cumulative codon frequencies specifically in ribosome-unoccupied regions, rather than at stalling sites, across all seven model species. Experimental validation using species-specific optimization confirmed that our method effectively modulates gene expression in Escherichia coli and terrestrial plants. These findings demonstrate that species-specific environments for gene expression are encoded in codon weights, which can be deduced through a universal, species-independent framework, providing a new foundation for synthetic biology.

genomics↗

bioRxiv2026

Generation of promoters enabling high-level constitutive gene expression in both plants and Escherichia coli

Functional validation of genetic components in plants often requires cloning them separately into both plant and bacterial expression vectors, a process that is both time-consuming and laborious. This study aimed to simplify this workflow by developing plant-bacteria dual-host promoter systems that drive high-level constitutive expression in both environments. To achieve this, two variants of the chloramphenicol acetyltransferase promoter (PCAT), a bacterial {sigma} factor-dependent promoter, were integrated into the cauliflower mosaic virus 35S promoter (P35S), and their performance was evaluated using a hygromycin phosphotransferase (HPT)-GFP fusion reporter. One of these variants, PCAT1, conferred hygromycin resistance to Escherichia coli (DH5 and BL21 (DE3)) and maintained high-level expression comparable to the original P35S in onion epidermal cells. A hybrid P35S enhancer-PNOS system also conferred hygromycin resistance to E. coli, but its activity in inducing GFP signals in onion cells remained lower than that of P35S. Due to its compact size (89 bp) and efficiency, PCAT1 can serve as a module for converting standard plant vectors into dual-host systems, accelerating gene characterization and the development of new gene-based tools.

plant biology↗

bioRxiv2026

Rapid and flexible assessment of gene functions in plant cells with particle bombardment and linear DNA

Biolistic transformation is a versatile tool in plant science, yet high equipment costs and tissue damage from high-pressure gas remain significant barriers. Building on our previously developed "TSGMAC", a low-cost, helium-free biolistic system, we report three major advancements to enhance its throughput, delivery quality, and quantitative capability. First, a "guide barrel" assembled from commercial DIY fittings was developed; it effectively eliminates physical tissue damage and ensures uniform particle distribution, even in soft tissues like bok choy (Brassica rapa subsp. chinensis). Second, a rapid gene expression platform using PCR products was characterized. Results demonstrate that linear DNA constructs are efficiently circularized via non-homologous end joining (NHEJ) in plant cells, and protein expression is robust regardless of the relative positions of the promoter, coding sequence, and terminator. This system bypasses time-consuming cloning. Third, a cost-effective, highly sensitive dual-luciferase assay system utilizing teal Luc (teLuc) and inexpensive firefly luciferase (FLuc) inhibitors was established. This integrated workflow enables rapid, quantitative molecular biology using supermarket-obtained materials and standard PCR reagents. Our findings provide a practical foundation for plant scientists, synergistically accelerating gene functional analysis and genetic tool development.

plant biology↗

bioRxiv2026

A tool to shoot genes with massive air from a compressor (TSGMAC)

Particle bombardment systems are widely used for plant transformation, but commercial devices are expensive and rely on high-pressure helium gas. This study aimed to develop a cost-effective and helium gas-free alternative using an air duster gun connected to a commercial compressor. A nozzle (for DNA with transgenes), gold particles (as DNA carriers), nozzle-to-sample distance, and a method for coating gold particles with DNA were optimized to yield better transformation efficiency in targeting onion epidermal cells and rice calli. From the rice calli transformed with the newly developed system (a tool to shoot genes with massive air from a compressor: TSGMAC), stable transgenic plants could be obtained. TSGMAC offers a low-cost and helium gas-free solution for plant transformation and genome editing and can enhance accessibility to particle bombardment-based techniques.

plant biology↗

bioRxiv2026

Grass Expression Atlas: an RNA-seq-based expression resource for grass species.

Grass Expression Atlas (GExA) is an interactive web-based resource for rapid exploration of gene expression across diverse tissues, developmental stages, and conditions in grass species. GExA integrates publicly available RNA sequencing (RNA-seq) datasets for four millets: pearl millet (Cenchrus americanus), foxtail millet (Setaria italica), proso millet (Panicum miliaceum), and finger millet (Eleusine coracana), and includes barley (Hordeum vulgare) and sorghum (Sorghum bicolor) as reference species. Datasets were processed using a unified processing workflow to generate expression values in transcripts per million (TPM). The current release comprises 4,673 samples from 442 BioProjects, including 987 pearl millet samples and 2,216 foxtail millet samples, and is provided through a user-friendly web interface. GExA is designed for scalable expansion to additional species via the pipeline used in this study. GExA is freely available at https://webpark2116.sakura.ne.jp/RNADB.

bioinformatics↗