Biology subjects

Yoshioka, H.

Publications and source records attributed to Yoshioka, H..

17 recordsLinked to original sources

bioRxiv2026

Two closely related RNA helicases, UAP56 and URH49, couple mRNA splicing and export pathways with their distinct complexes

Transcription and mRNA processing are integrated into appropriate mRNA export pathway(s) enabling fine-tuned gene expression. The closely related RNA helicases, UAP56 and URH49, form distinct complexes known as the apo-TREX and the apo-AREX complexes, respectively, which remodel into the ATP-TREX complexes, thus forming multiple mRNA export pathways. However, the mechanisms by which helicases and their complexes shape these pathways remain unclear. Here, we showed that UAP56 and URH49 play general roles in mRNA splicing ahead of export. Further analyses revealed three patterns of splicing regulation and their association with mRNA export: Type I, in which both helicases redundantly or synergistically regulate splicing within the same transcripts, associated with cooperative mRNA export; Type II, in which either helicase preferentially regulates splicing in distinct transcripts; and Type III, in which the helicases exert opposing splicing effects within the same transcripts. Type II and III regulation was associated with selective mRNA export. Moreover, we demonstrated that the distinct complex formation influenced the splicing patterns regulated by the two helicases. Our findings reveal an additional layer of transcriptome regulation mediated by UAP56, URH49, and their complexes, extending beyond their canonical roles in mRNA export.

molecular biology↗

bioRxiv2026

Minimally invasive measurement of maternal transcripts enables predicting the developmental potential of mammalian zygotes

Maternal transcripts are stored in the oocyte cytoplasm during oogenesis and play a pivotal role in early embryonic development after fertilization. However, specific maternal transcripts that reflect the developmental potential of embryos have not been systematically identified, and the use of maternal transcript levels as an indicator of successful development has not been explored. Here, we link the maternal transcriptome to the zygotes developmental potential by examining transcripts in a single polar body. The transcriptome of a zygote or an oocyte was highly similar to that of its accompanying polar body in mouse, cow, and human. We have identified a set of maternal transcripts whose expression levels fluctuate between poor- and good-quality zygotes. Specifically, Sipa1and Zmym6 were identified as marker transcripts that accurately reflect the developmental potential of zygotes. Using these marker genes, combined with machine learning, the development of zygotes to the blastocyst stage was successfully predicted with more than 80% specificity as early as 12 hours after fertilization. Furthermore, our prediction platform significantly improved implantation rates and live births to term. Thus, we have demonstrated a minimally invasive method for identifying maternal transcripts associated with zygote developmental potential. Our developed prediction system provides a generalizable conceptual framework for human infertility treatment to reduce the risk of implantation failure by excluding embryos with low developmental potential, especially when early embryos are transferred, and for livestock propagation to assess selected expressed maternal trait-associated variants before embryo transfer.

developmental biology↗

bioRxiv2025

Reciprocal BLUP: A Predictability-Guided Multi-Omics Framework for Plant Phenotype Prediction

Sustainable improvement of crop performance requires integrative approaches that link genomic variation to phenotypic expression through intermediate molecular layers. Here, we present Reciprocal Best Linear Unbiased Prediction (Reciprocal BLUP), a predictability-guided multi-omics framework that quantifies cross-layer relationships among the genome, metabolome, and microbiome to enhance phenotype prediction. Using a panel of 198 soybean accessions grown under well-watered and drought conditions, we first evaluated four direction-specific prediction models (genome[->]microbiome, genome[->]metabolome, metabolome[->]microbiome, and microbiome[->]metabolome) to estimate the predictability of individual omics features. Then, we evaluated whether subsets of features with high cross-omics predictability improve phenotype prediction. These cross-layer models identify features that play physiologically meaningful roles within multi-omics systems, enabling us to prioritize variables that capture coherent biological signals enriched for phenotype-relevant information. As a result, metabolome features were highly predictable from microbiome data, whereas microbiome predictability from metabolomic data was weaker and more environment-dependent, revealing an asymmetric relationship between these layers. In the subsequent phenotype prediction analysis, the model incorporating predictability-based feature selection substantially outperformed models using randomly selected features and also achieved prediction accuracies comparable to those of the full-feature model. Under drought, phenotype prediction models based on metabolomic or microbiomic kernels (MetBLUP or MicroBLUP) outperformed the genomic baseline (GBLUP) for several biomass-related traits, indicating that environment-responsive omics layers captured phenotypic variation not explained by additive genetic effects. Our results highlight hierarchical interactions among genomic, metabolic, and microbial systems, with the metabolome functioning as an integrative mediator linking genotype, environment, and microbiome composition. The Reciprocal BLUP framework provides a biologically interpretable and practical approach for integrating multi-omics data, improving phenotype prediction, and guiding omics-based feature selection in plant breeding.

bioinformatics↗

bioRxiv2025

Calcium-dependent protein kinases participate in RBOH-mediated sustained ROS burst during plant immune cell death

The sensing of pathogen effector by an intracellular receptor called nucleotide-binding leucine-rich repeat receptor (NLR), induces a robust immune response, effector-triggered immunity (ETI). Sustained reactive oxygen species (ROS) production is accomplished by Nicotiana benthamiana RBOHB, an NADPH oxidase. However, molecular mechanisms connecting effector recognition and ROS production are unclear. Here, we show that calcium-dependent protein kinases (CDPKs) contribute to sustained ROS production downstream of NLR activation. We found that NbCDPK4 and NbCDPK5 directly phosphorylate NbRBOHB Ser-123 and provokes ROS production. In addition, constitutively active NbCDPKs upregulated NbRBOHB transcription. The phosphorylation of Ser-123 was significantly increased in a Ca2+-dependent manner during the ETI-like responses, which execute hypersensitive cell death. Moreover, transient expression of an autoactive helper NLR, NRC4, induced phosphorylation of Ser-123 dependent on its N-terminal conserved motif required for Ca2+ channel activity. These findings uncover a critical role for the NbCDPK-NbRBOHB module in regulating sustained ROS production during ETI.

plant biology↗

bioRxiv2025

Interpretable Machine Learning on Soybean Multi Omics Data Reveals Drought-Driven Shifts of Plant-Microbe Interactions

BackgroundPlant-microbe interactions in the rhizosphere are central to plant growth, nutrient acquisition, and stress resilience. Although multi-omics approaches enable comprehensive profiling of different biological layers, integrating these data to understand the mechanisms underlying plant-microbe symbiosis, particularly under drought stress, remains a challenge. ResultsGenomic, metabolomic, and microbiome data from 198 soybean accessions grown under both control and drought conditions were integrated to identify environment-specific predictive features of the plant phenotypes. We compared best linear unbiased prediction (BLUP), genome-wide association study (GWAS), and a nonlinear machine learning model to evaluate their ability to detect informative features. The machine learning models provided flexible variable selection and outperformed linear models in capturing nonlinear dependencies. Model interpretation using SHapley Additive exPlanations (SHAP) indicated that the isoflavone derivative, daidzin, and the drought-tolerant Candidatus Nitrosocosmicus, were major contributors to phenotypic variation, specifically under drought stress. SHAP-based interaction networks indicated cross-omics links, including connections between daidzin, gamma-aminobutyric acid (GABA), and Paenibacillus. ConclusionThe proposed interpretable machine learning approach for plant phenotype prediction identified multi-omics biomarkers and interactions, providing insights into plant adaptation to drought stress through environment-dependent rhizosphere networks and symbiotic associations.

bioinformatics↗

bioRxiv2025

Ridge Redundancy Analysis for High-Dimensional Omics Data

MotivationRedundancy Analysis (RDA) is a popular reduced rank regression approach for modeling the relationships between two sets of variables. In omics studies, RDA provides a flexible framework for investigating associations between high-dimensional molecular data. However, omics datasets often exhibit strong multicollinearity and suffer from the "large p, small n" problem, where the number of predictor variables p (features) exceeds the number of samples n. Ridge RDA addresses multicollinearity by introducing a ridge penalty in addition to the rank restriction. Despite these advantages, its application to high-dimensional omics data remains challenging due to i) difficulties in manipulating the large coefficient matrix of dimensions p x q, where q represents the number of response variables, and ii) the need to jointly select the rank and the regularization parameter that both influence the performance of the method. ResultsWe propose an efficient computational framework for ridge RDA that overcomes these challenges by leveraging the Singular Value Decomposition of the predictor matrix X. This approach eliminates the need for direct covariance matrix inversion, improving computational efficiency. Furthermore, we introduce a novel strategy that reduces the memory burden associated with the storage of the coefficient matrix from pq to (p + q)r, with r the chosen reduced-rank dimensionality. Our method enables an efficient grid search to jointly select the ridge penalty{lambda} and r via cross-validation. The proposed framework is implemented in the R package rrda, providing a practical and scalable solution for the analysis of high-dimensional omics data. AvailabilityThe R package rrda is available on CRAN: https://CRAN.R-project.org/package=rrda. Scripts and data used for the analysis are available on GitHub: https://github.com/Yoska393/rrda.

bioinformatics↗

bioRxiv2025

Integration of Proxy Intermediate Omics traits into a Nonlinear Two-Step model for accurate phenotypic prediction

Intermediate omics traits, which mediate the effects of genetic variation on phenotypic traits, are increasingly recognised as valuable components of genetic evaluation. In particular, rhizosphere microbiota play a crucial role in plant health and productivity; however, their complex interactions with host genetics remain challenging to model. Although two-step modeling frameworks have been proposed to integrate intermediate omics traits into phenotype prediction, existing approaches do not incorporate nonlinear relationships between different omics layers. To address this, we have proposed a two-step phenotype prediction framework that integrates genomic, rhizosphere microbiome, and metabolome (meta-metabolome) data, while explicitly capturing omicsomics nonlinearities. The first step is to predict meta-metabolome traits from genetic and microbial features, thus effectively isolating them from the environmental noise. In this process, intermediate "proxy" omics traits are generated as general biological information to provide robust models. The second step utilises this "proxy" to enhance the accuracy of the phenotype prediction. We compared the linear model (Best Linear Unbiased Prediction, BLUP) and the nonlinear model (Random Forest, RF) at each step, as demonstrated through simulations and empirical analysis of a multi-omics soybean dataset in which nonlinear modeling captures intricate omics interactions. Notably, our approach enables phenotype prediction without requiring the original meta-metabolome data used in model training, thereby reducing reliance on costly omics measurements. This framework integrates intermediate omics traits into genomic prediction to improve prediction accuracy and provide solutions for deeper insights into plant-microbiome interactions.

bioinformatics↗

bioRxiv2024

Implication of S-1 biomarkers on aging and prognosis in elderly patients with lung cancer treated by adjuvant S-1 chemotherapy: Accompanying results of the Setouchi Lung Cancer Group Study 1201

BACKGROUNDSThe management of elderly patients presents several challenges due to age-related declines; however recent recommendations advocate for age not being the sole determinant for adjuvant treatment decisions in patients with non-small cell lung cancer (NSCLC). Aging may alter expression levels of 5-fluorouracil (5-FU) biomarkers. METHODSExpression changes with aging were explored using The Cancer Genome Atlas (TCGA) database. 5-FU-related biomarker expressions, including thymidylate synthase (TS), dihydropyrimidine dehydrogenase (DPD), orotate phosphoribosyltransferase, epidermal growth factor receptor (EGFR), and excision repair cross-complementation group-1 (ERCC1), were assessed by the quantitative reverse-transcription PCR assays in 89 NSCLCs elderly patients ([≥] 75 years old) receiving adjuvant S-1, an oral fluoropyrimidine agent, therapy in a SLCG1201 trial. RESULTS: TCGA database analysis (n=955) indicated decreased TS expression with aging, particularly in those 75 or older. In the SCLG1201 trial, univariate analysis revealed that high EGFR and low TS expressions correlated with favorable recurrence-free survival (RFS)(p=0.0264) and overall survival (OS)(p=0.0365), respectively. Multivariable analysis confirmed pathological stage as an independent prognostic factor for both RFS and OS (p=0.0052 and 0.0352, respectively). EGFR mutant tumors (n=27) showed significantly higher DPD (p=0.0066) and EGFR (p<0.0001) expressions, and lower TS(p=0.0125) and ERCC1(p=0.0015) expressions. CONCLUSIONDespite pathological stage being an independent prognostic factor, high EGFR and low TS expressions may predict better clinical outcomes in elderly NSCLC patients using adjuvant S-1. The age-related decrease in TS expression supports the potential benefit of 5-FU-based therapy in them compared to younger patients. Further research is warranted to validate these clinical implications.

pharmacology and toxicology↗

bioRxiv2024

In-gel refolding allows fluorescence detection of fully denatured GFPs after SDS-PAGE

Green fluorescent proteins (GFPs) have been widely used as fusion tags, especially to visualize subcellular localization and dynamics of the fused partner proteins. Also, GFPs serve as fluorescent tags in size-exclusion chromatography and native-PAGE, facilitating the evaluation of expression levels and quality of the expressed fusion proteins. However, the fluorescent detection of GFPs is generally incompatible with denaturing SDS-polyacrylamide gel electrophoresis (PAGE), where the samples are heat-denatured before loading. Accordingly, detecting GFP-fused proteins after SDS-PAGE usually relies on western blotting with anti-GFP antibodies. To enable in-gel fluorescence detection of SDS-PAGE-separated GFPs, some protocols employ mild denaturing conditions to keep the GFPs intact. However, such mild denaturation sometimes results in partial denaturation of the proteins and irregular electrophoretic mobility that is not proportional to their molecular weights. Here, we demonstrate that the fully denatured GFPs can be refolded within the gel by cyclodextrin-mediated removal of SDS in the presence of 20% methanol, enabling the in-gel fluorescence detection of the GFP-fused proteins. The protocol is compatible with subsequent total protein staining and western blotting. Although future studies are needed to clarify the scope and generality, the technique developed here would provide a simple, time- and cost-effective alternative to the immunodetection of GFPs. HighlightsO_LIFully denatured GFPs could be in-gel refolded to enable fluorescence detection. C_LIO_LI? cyclodextrin effectively removed SDS to assist in the in-gel refolding of GFPs. C_LIO_LIGFPs amenable for in-gel refolding include GFPuv, EGFP, turboGFP, and sfGFP. C_LIO_LICompatible with total protein staining and western blotting. C_LIO_LIThe in-gel refolding procedure was successfully applied to two turboGFP-fusion proteins. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/615947v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@19fe9b7org.highwire.dtl.DTLVardef@1a927a8org.highwire.dtl.DTLVardef@6aa42borg.highwire.dtl.DTLVardef@1400b78_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2023

NADPH oxidase-mediated sulfenylation of cysteine derivatives is key regulatory events for plant immune responses

Reactive oxygen species (ROS) are rapidly generated during plant immune responses by RBOH, which is a plasma membrane-localizing NADPH oxidase. Although regulatory mechanisms of RBOH activity have been well documented, the ROS-mediated downstream signaling is unclear. We here demonstrated that ROS sensor proteins play a central role in the ROS signaling via oxidative post-translational modification of cysteine residues, sulfenylation. To detect protein sulfenylation, we used dimedone, which specifically and irreversibly binds to sulfenylated proteins. The sulfenylated proteins were labeled by dimedone in Nicotiana benthamiana leaves, and the conjugates were detected by immunoblotting. In addition, a reductant dissociated H2O2-induced conjugates, suggesting that cysteine persulfide and/or polysulfides are involved in sulfenylation. Sulfenylation of cysteine and its derivatives in ROS sensor proteins were continuously increased during both PTI and ETI in an RBOH-dependent manner. Pharmacological inhibition of ROS sensor proteins by dimedone perturbated cell death, ROS accumulation induced by INF1 and MEK2DD, and defense against fungal pathogens. On the other hand, Rpi-blb2-mediated ETI responses were rather enhanced by dimedone. These results suggest that the sulfenylation of cysteine and its derivatives in various ROS sensor proteins are important events in downstream of RBOH-dependent ROS burst to regulate plant immune responses. HighlightNADPH oxidase-mediated ROS production induces sulfenylation of cysteine residues or their derivatives of ROS sensor proteins, which regulates HR cell death, ROS accumulation, and defense against diverse plant pathogens.

immunology↗

bioRxiv2023

A jump-driven self-exciting stochastic fish migration model and its fisheries applications

We introduce a stochastic continuous-time model via a self-exciting process with jumps to describe a seasonal migration event of diadromous fish. The dynamics of the stored population at a point in a river, waiting for their upward migration, increases by the inflow from the downstream/ocean and decreases by the outflow due to their upstream migration. The inflow is assumed to occur at a constant rate until an Erlang-distributed termination time. The outflow is modeled by a self-exciting jump process to incorporate the flocking and social interactions in fish migration. Harvested cases are also studied for fisheries applications. We derive the backward Kolmogorov equations and the associated finite-difference method to compute various performance indices including the mean migration period and harvested populations. Detailed numerical and sensitivity analysis are conducted to study the spring upstream migration of the diadromous Ayu Plecoglossus altivelis altivelis.

ecology↗

bioRxiv2023

The Crucial Role of CTCF in Mitotic Progression during Early Development of Sea Urchin.

CCCTC-binding factor (CTCF), an insulator protein with 11 zinc fingers, is enriched at the boundaries of topologically associated domains (TADs) in eukaryotic genomes. In this study, we isolated and analyzed the cDNAs encoding HpCTCF, the CTCF homolog in the sea urchin Hemicentrotus pulcherrimus, to investigate its expression patterns and functions during early development of sea urchin. HpCTCF contains nine zinc fingers corresponding to fingers 2-10 of the vertebrate CTCF. The expression pattern analysis revealed that HpCTCF mRNA was detected at all developmental stages and in the entire embryo. Upon expressing the HpCTCF-GFP fusion protein in early embryos, we observed its uniform distribution within interphase nuclei. However, during mitosis, it disappeared from the chromosomes and subsequently reassembled on the chromosome during telophase. Moreover, the morpholino-mediated knockdown of HpCTCF resulted in mitotic arrest during the morula-to-blastula stage. Most of the arrested chromosomes were not phospholylated at serine 10 of histone H3, indicating that mitosis was arrested at the telophase by HpCTCF depletion. Furthermore, impaired sister chromatid segregation was observed using time-lapse imaging of HpCTCF-knockdown embryos. Thus, HpCTCF is essential for mitotic progression during the early development of sea urchins, especially during the telophase-to-interphase transition. However, the normal development of pluteus larvae in CRISPR-mediated HpCTCF knockout embryos suggests that disruption of zygotic HpCTCF expression has little effect on embryonic and larval development.

developmental biology↗

bioRxiv2022

Single-cell multi-omics decodes regulatory programs during development of mouse secondary palate

The abnormal perturbation in gene regulation during palatogenesis may lead to cleft palate, a major congenital birth defect in humans and mice. However, a comprehensive multi-omic map of the developing secondary palate at single-cell resolution is lacking. In this study, we performed single-cell multiome sequencing and profiled chromatin accessibility and gene expression simultaneously within the same cells (n = 36,154) isolated from mouse secondary palate across embryonic days (E) 12.5, E13.5, E14.0, and E14.5. Application of optimal transport reconstructed five trajectories, representing continuous differentiation of multipotent cells into different subpopulations in later stages. By linking open chromatin signals to gene expression changes, we discovered a list of lineage-determining transcription factors, such as Shox2 for the anterior and Dlx1/2 for the posterior palatal mesenchymal trajectories. In conclusion, this study charted epigenetic and transcriptional dynamics during palatogenesis, which provides a valuable resource for the community and facilitate future research in cleft palate. HighlightsO_LIThe first report on building a single-cell multi-omics atlas with joint chromatin accessibility and gene expression measurements from the same cells during the development of mouse secondary palate. C_LIO_LIApplication of optimal transport calculated fate probabilities to different terminal states and recovered continuous landscapes during mouse secondary palate development. C_LIO_LIBy linking cis-regulatory DNA elements to target genes, we characterized a series of transcription factors governing the differentiation of cranial neural crest-derived multipotent cells to the anterior and posterior palatal mesenchymal trajectories, respectively. C_LIO_LITranscription factors Shox2 and Dlx1/2 exhibited top regulatory roles for the anterior and posterior palatal mesenchymal trajectories, respectively, showing significant enrichment in both motif accessibility and gene expression. C_LI

developmental biology↗

bioRxiv2021

An efficient polymer cocktail-based transportation method for cartilage tissue, yielding chondrocytes with enhanced hyaline cartilage expression during in vitro culturing

Chondrocytes are used in cell-based therapies such as autologous chondrocyte implantation (ACI) and matrix-associated cartilage implantation (MACI). To transport the cartilage tissue to the laboratory for in vitro culturing, phosphate-buffered saline (PBS), Euro-Collins solution (ECS) and Dulbeccos Modified Eagles Medium (DMEM) are commonly employed at 4-8 {degrees}C. In this study, eight samples of human cartilage biopsy tissues from elderly patients with severe osteoarthritis undergoing arthroscopy, which would otherwise have been discarded, were used. The cartilage tissue samples were compared to assess the cell yield between two transportation groups: i) a thermo-reversible gelation polymer (TGP) based method without cool preservation (~25 {degrees}C) and ii) ECS transport at 4 {degrees}C. These samples were subjected to in vitro culture in a two-dimensional (2D) monolayer for two weeks and subsequently in a three-dimensional (3D) TGP scaffold for six weeks. The cell count obtained from the tissues transported in TGP was higher (0.2 million cells) than those transported in ECS (0.08 million cells) both after initial processing and after in vitro culturing for 2 weeks in 2D (18 million cells compared with 10 million cells). In addition, mRNA quantification demonstrated significantly higher expression of Col2a1 and SOX-9 in 3D-TGP cultured cells and lower expression of COL1a1 in RT-PCR, characteristic of the hyaline cartilage phenotype, than in 2D culture. This study confirms that the TGP cocktail is suitable for both the transport of human cartilage tissue and for in vitro culturing to yield better-quality cells for use in regenerative therapies.

cell biology↗

bioRxiv2020

On a non-standard two-species stochastic competing system and a related degenerate parabolic equation

We propose and analyse a new stochastic competing two-species population dynamics model. Competing algae population dynamics in river environment, important engineering problems, motivate this model. It is a system of stochastic differential equations (SDEs) and has a characteristic that the two populations are competing with each other through the environmental capacities. Unique existence of the uniformly bounded strong solution is proven and an attractor is identified. The Kolmogorov backward equation associated with the population dynamics is formulated and its unique solvability in a Banach space with a weighted norm is discussed. Our mathematical analysis results can be effectively utilized for a base-stone of modelling, analysis, and control of the competing population dynamics.

ecology↗

bioRxiv2019

Acute feeding disorder after oral RNAi exposure results in efficient pest control

Selecting an appropriate target gene is critical to the success of feeding RNA interference (f-RNAi)-based pest control. Gene targets have been chosen based on their ability to induce lethality. However, lethality induction by f-RNAi is slow-acting and crop damage can progress during this time. Here, we show that f-RNAi of death-associated inhibitor of apoptosis protein 1 (diap1), but not two conventional targets vacuolar ATPase subunit A and E, induces acute feeding cessation in the solanaceous pest, Henosepilachna vigintioctopunctata during 24-48 hours. We also found that the feeding cessation by diap1 f-RNAi has species-specificity and occurs with only 1.6 ng dsRNA. Our results suggest that diap1 is an appropriate target in the context of rapid reduction of crop damage. We propose that acute feeding disorder should be assessed as a novel criterion for selecting appropriate target genes for RNAi-based pest control in addition to the conventional criterion based on lethality.

molecular biology↗

bioRxiv2019

Membrane-bounded nucleoid discovered in a cultivated bacterium of the candidate phylum ‘Atribacteria’

A key feature that differentiates prokaryotes from eukaryotes is the absence of an intracellular membrane surrounding the chromosomal DNA. Here, we report isolation of an anaerobic bacterium that possesses an additional intracytoplasmic membrane surrounding a nucleoid, affiliates with the yet-to-be-cultivated ubiquitous phylum Ca. Atribacteria, and possesses unique genomic features likely associated with organization of complex cellular structure. Exploration of the uncharted microorganism overturned the prevailing dogma of prokaryotic cell structure.

microbiology↗