Biology subjects

Kambara, K.

Publications and source records attributed to Kambara, K..

6 recordsLinked to original sources

bioRxiv2026

Genotype imputation improves GWAS resolution and facilitates candidate gene identification in pearl millet

Pearl millet (Cenchrus americanus; syn. Pennisetum glaucum (L.) R. Br.) is an important cereal crop mainly grown in semi-arid areas. However, in pearl millet, genes underlying many agronomic traits remain unknown. Our previous genome-wide association study (GWAS) was based primarily on genotype data derived from restriction site-associated DNA sequencing (RAD-seq), which contained a high proportion of missing genotypes and may have limited mapping resolution. To address this limitation, we used whole-genome sequencing (WGS)-derived genotype data from 21 elite lines as a reference panel to impute missing genotypes in the RAD-seq-derived dataset. Genotype imputation reduced the proportion of missing genotypes from 82.42% to 0% and increased the mean density of non-missing genotypes from 569.61 to 1,158.09 genotypes/Mb. Leave-one-out validation yielded a mean genotype concordance of 89.9% (SD = 4.6%). GWAS using the imputed dataset showed more localized association signals for several traits. Homologs of rice SHORT INTERNODES1, Arabidopsis FLOWERING LOCUS Y, and rice EPIDERMAL PATTERNING FACTOR 2 were identified as candidates for genes regulating culm height, days to panicle emergence, and awn growth, respectively. These results demonstrate that reference-panel-based genotype imputation can increase the utility of reduced-representation genotype datasets and facilitate candidate gene identification in pearl millet.

genomics↗

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

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↗

bioRxiv2021

A cationic lipid site at the outward transmembrane face of a pentameric ligand-gated ion channel

Pentameric ligand-gated ion channels (pLGICs) are crucial mediators of electrochemical signal transduction from bacteria to humans. Lipids play an important role in regulating pLGIC function, yet the structural basis for specific pLGIC-lipid interactions remains poorly understood. The bacterial channel ELIC recapitulates several properties of eukaryotic pLGICs, including activation by the neurotransmitter GABA and sensitivity to lipids, offering a simplified model system for structure-function studies. In this study, functional effects of non-canonical amino acid substitution of W206 at the top of the M1-helix, combined with detergent interactions observed in recent X-ray structures, are consistent with this region being the location of a lipid binding site on the outward face of the ELIC transmembrane domain. Coarse-grained and atomistic molecular dynamics simulations revealed preferential binding of lipids containing a positive charge, particularly involving interactions with residue W206 consistent with cation-{pi} binding. Polar contacts from the principal subunit, particularly M3 residue Q264, further supported lipid binding via headgroup ester linkages. Aromatic residues were identified at analogous sites in a handful of eukaryotic family members, including the human GABAA receptor subunit {varepsilon}, suggesting conservation of relevant interactions in other evolutionary branches. Further mutagenesis experiments indicated that mutations at this site in {varepsilon}-containing GABAA receptors can change the apparent affinity of the agonist response to GABA, consistent with a potential role of this site in channel gating. In conclusion, this work is a detailed case study in type-specific lipid interactions at an evolutionarily distinctive pLGIC site, with implications for lipid modulation and lipophilic drug design.

biophysics↗

bioRxiv2019

A functionally conserved mechanism of modulation via a vestibule site in pentameric ligand-gated ion channels

Pentameric ligand-gated ion channels (pLGICs) belong to a class of ion channels involved in fast synaptic signaling in the central and peripheral nervous systems. Molecules acting as allosteric modulators target binding sites that are remote from the neurotransmitter binding site, but functionally affect coupling of ligand binding to channel opening. Here, we investigated an allosteric binding site in the ion channel vestibule, which has converged from a series of studies on prokaryote and eukaryote channel homologs. We discovered single domain antibodies, called nanobodies, which are functionally active as allosteric modulators, and solved co-crystal structures of the prokaryote channel ELIC bound either to a positive (PAM) or a negative (NAM) allosteric modulator. We extrapolate the functional importance of the vestibule binding site to eukaryote ion channels, suggesting a conserved mechanism of allosteric modulation. This work identifies key elements of allosteric binding sites and extends drug design possibilities in pLGICs using nanobodies.

neuroscience↗