Biology subjects

Bono, H.

Publications and source records attributed to Bono, H..

At least 19 recordsLinked to original sources

bioRxiv2026

tWhEEL: a transcript-aware workflow for quantifying CRISPR knockout feasibility using transcriptome assembly

Gene redundancy can complicate loss-of-function experiments (knockout), and its extent varies among organisms and biological functions. Relating variation in gene redundancy to the availability of genome-editing targets can help researchers select tractable biological functions and experimental organisms. Here, we present the transcript-aware Whole-genomic Evaluation for Editing Locus (tWhEEL), a pipeline that infers redundancy in silico from transcript information and cross-references it with specific guide RNA designs. tWhEEL integrates CRISPR-Cas9 guide design with Gene Ontology (GO) and pathway annotations to compute a knockout feasibility index (KFI) for individual genes and functional categories. Interactive HTML reports link GO-associated KFI and pathway-associated KFI summaries to the contributing groups, genes, and guide candidates with links to QuickGO or WikiPathways. By linking sequence-level guide candidates to functional-level targetability, tWhEEL can support the selection of biological functions and organisms for reverse-genetic experiments. Applications to model and nonmodel datasets revealed distinct targetability profiles, including high full targetability in yeast and query-protein-set dependence in zebrafish. A zebrafish Fanconi anemia case study recovered 14 of 19 published target-site designs. By connecting sequence-level guide candidates with function-level experimental planning, tWhEEL provides a framework for comparing reverse genetic tractability and prioritizing biological functions and organisms for further study.

bioinformatics↗

bioRxiv2026

Genome sequence data of Ascogaster reticulata (Hymenoptera: Braconidae)

Parasitoid wasps develop in or on other arthropods and have evolved a wide range of strategies for exploiting their hosts. Ascogaster reticulata is a solitary egg to larval endoparasitoid wasp belonging to the subfamily Cheloninae of Braconidae. We constructed a genome assembly using long-read sequence data. The assembled genome was 280.5 Mbp, consisting of 209 contigs. The N50 value and GC content ratio were 13.9 Mbp and 30.43%, respectively. The percentage of transposable elements and repetitive regions was 52.43%. The predicted number of genes is 27,261. Merqury revealed that the QV value and completeness of the genome were 61.79 and 99.3917%, respectively. BUSCO analysis detected approximately 99% of the core genes. These results suggest that the genome data were of sufficient quality for use as a reference genome. Therefore, these data can be utilized as a genomic resource for comparative studies within Braconidae and for future investigations into the biology and evolution of Cheloninae parasitoid wasps.

genomics↗

bioRxiv2026

Transcriptome-based genome-wide analysis reveals hybridization dynamics and genetic structure of Japanese giant salamanders

AbstractsThe Japanese giant salamander (Andrias japonicus), an apex predator and a Special Natural Monument in Japan, is threatened by hybridization with introduced Chinese giant salamanders (Andrias davidianus). This hybridization has caused genetic introgression and expansion of hybrid populations, posing a serious conservation risk. Because morphological identification of hybrids is occasionally unreliable and current genetic methods rely on limited markers, a genome-wide approach is required. However, the extremely large genome ([~]50 Gb) of giant salamanders has hindered whole-genome analyses. In this study, we conducted transcriptome-based analyses of Japanese giant salamanders, Chinese giant salamanders, and their hybrids, generating RNA-seq data from 34 individuals. A total of over 419,000 SNP candidates were identified, from which 4,457 high-confidence SNPs in highly expressed genes were selected for analysis. Population structure analyses for Nabari colony revealed that hybrid individuals form two major groups, corresponding to different degrees of genetic contribution from Japanese and Chinese lineages. Most hybrids were inferred to be F2 or backcross individuals, while F1 hybrids were rare. Mitochondrial analysis indicated that all hybrids possessed Japanese-type mitochondrial genome, suggesting male-mediated introgression from Chinese salamanders. Differential expression analysis revealed enhanced stress-response pathways in hybrids and stronger antiviral responses in Japanese individuals. Using the axolotl genome as a reference, we constructed a virtual chromosomal map, identifying large haplotype blocks and supporting recent hybridization with limited recombination. This study provides a genome-wide framework for understanding hybridization dynamics and supports future conservation and evolutionary studies.

ecology↗

bioRxiv2026

Identification of a microRNA with a mutation in the loop structure in the silkworm Bombyx mori

MicroRNAs (miRNAs) play essential roles in the posttranscriptional regulation of gene expression in organisms. In the process of synthesizing mature miRNAs from miRNA precursors, the miRNA precursors are cleaved via Dicer at their loop structure, after which the miRNA precursors become mature and regulate transcription. However, the consequences of altering the loop sequence are not fully understood. The silkworm Bombyx mori is a lepidopteran insect with many genetic strains. We identified a mutant of the miRNA miR-3260 whose the part of the loop structure was lacking in a silkworm strain with translucent larval skin. Here, we aimed to analyze the role of wild-type miR-3260 and the influence of the mutation of the loop structure in B. mori. First, we identified the genomic region responsible for the translucent larval skin phenotype and determined that the mutated miR-3260 nucleotide sequences. Then, we predicted the binding partners of wild-type miR-3260 using the RNA hybrid tool and found two juvenile hormone (JH)-related genes as targets of wild-type miR-3260. Next, we assessed the relationships between miR-3260 and JH and found that miR-3260 was highly expressed in the Corpora allata and its expression responded to JH treatment. Meanwhile, miR-3260 mimic and inhibitor did not induce the typical phenotypes associated with JH in B. mori. Then, we compared the dicing products from wild-type and mutant miR-3260 precursors and observed that neither form underwent Dicer-mediated cleavage when the loop structure was altered. These results suggest that loop mutations in the miR-3260 precursor may not influence dicing activity, consistent with the lack of observable phenotypic effects.

molecular biology↗

bioRxiv2026

Genome-wide Identification of Transcriptional Start Sites and Candidate Enhancers Regulating Worker Metamorphosis in Apis mellifera

Eusociality in bees represents a major evolutionary transition and understanding its molecular basis is fundamental for sociogenomic studies. Comparative genomics has revealed correlations between transcription factor binding site (TFBS) abundance and social complexity; however, when and where these TFBSs function in a eusocial context remains largely unclear. In this study, we performed cap analysis of gene expression (CAGE) during worker metamorphosis in the honeybee Apis mellifera to identify TFBSs within active enhancers and decipher the regulatory relationships between these enhancers and their target genes. We identified 17,349 transcription start sites (TSSs) and 842 candidate enhancers. Using CAGE, we identified five clusters based on expression patterns. Notably, genes associated with the canonical metamorphic regulators, Broad complex (Br-c) and E93, were found within specific clusters. By integrating the correlations between enhancer and TSS activities with motif enrichment analysis, we identified 15 transcription factor-enhancer-TSS regulatory relationships. Among these, tramtrack (ttk)-binding sites were identified in five enhancers associated with four target genes, including Br-c. The number of target genes regulated by ttk was the highest in our dataset. To examine whether this regulatory relationship is conserved across bee species with varying levels of sociality, we analyzed the sequence conservation of ttk-binding sites in Br-c enhancers and found that perfect sequence conservation of ttk-binding site was restricted to the Apis genus. The ttk-binding sites of other target genes exhibited the same Apis-specific conservation pattern. Our findings suggest that gene regulatory relationships during worker metamorphosis occur in a lineage-specific manner in the Apis genus. SignificanceHoneybees produce distinct castes--queens and workers--from genetically identical larvae via differences in gene regulation. Although enhancers have been computationally predicted, their actual activity during bee development has rarely been measured directly, and the CAGE technology has never been applied for this purpose. We identified active enhancers during worker metamorphosis and discovered that the transcription factor ttk may regulate Br-c, a key developmental gene. This study provides the first direct evidence of active enhancers and their regulatory roles in honeybee worker metamorphosis.

genomics↗

bioRxiv2026

Supporting Metadata Curation from Public Life Science Databases Using Open-Weight Large Language Models

Although the Gene Expression Omnibus and other public repositories are expanding rapidly, curation across these databases has not kept pace. Data reuse is often hindered by unstandardized metadata comprising unstructured text. To address this, we developed a workflow that combines retrieval via application programming interfaces with semantic filtering using large language models (LLMs) to support metadata screening as an initial step in broader curation workflows. As a focused pilot evaluation, we benchmarked multiple LLMs using metadata from 150 candidate Arabidopsis RNA-seq projects to classify projects containing exogenous ABA-treated samples and matched untreated controls. Simple keyword searches yielded many false positives (F1=0.59); classification using LLMs significantly improved performance. Several open-weight models achieved near-perfect classification performance in this defined task (F1>0.98), comparable to that of closed models. We also found that, for some high-performing models, self-reported confidence scores may help identify high-confidence cases that can be prioritized for automated processing. These results suggest that open-weight LLMs can support scalable metadata screening in local environments as an initial step in broader curation workflows, providing a foundation for accelerating public dataset reuse.

bioinformatics↗

bioRxiv2026

Functional Annotation Workflow for Fungal Transcriptomes

Although RNA sequencing (RNA-seq) enables rapid transcriptome profiling, functional annotation of fungal transcriptomes remains challenging. Existing tools prioritize broad taxonomic coverage, and reference genomes are scarce for non-model species. This study aimed to develop a fungal-specific functional annotation workflow to support rapid and accurate functional analyses downstream of RNA-seq, independent of reference genome availability. To evaluate the workflow, RNA-seq data from 57 samples of Lentinula edodes strain H600 (shiitake mushroom) were retrieved, along with full-length transcript sequencing (Iso-Seq) data and corresponding RNA-seq data from 20 samples of Phakopsora pachyrhizi (Asian soybean rust) from public databases. The workflow successfully annotated over 96% of protein-coding transcripts and demonstrated applicability to Iso-Seq data. Functional enrichment analyses revealed higher-resolution functional detection than existing annotation tools. Furthermore, integrating homology searches against fungal-specific databases with expression pattern-based annotations highlighted the workflows utility for target identification in genome editing and other applications. Overall, the results of this study highlight the potential of the developed workflow in facilitating the discovery of functionally important transcripts and their translation into biotechnological applications.

microbiology↗

bioRxiv2025

Genome editing of the flavanone 3-hydroxylase gene produces a green Perilla line with elevated luteolin accumulation

Perilla frutescens var. crispa is widely cultivated in East Asia and produces a diverse range of secondary metabolites with nutritional and medicinal value. Based on anthocyanin content, perilla is classified into red and green chemotypes. The anthocyanin biosynthetic pathway is highly conserved among plants, and the flavanone 3-hydroxylase gene (F3H) in red perilla is considered essential for this pathway. Here, we used CRISPR-Cas9 genome editing to generate novel Perilla lines with altered metabolite profiles. In four edited T plants, multiple biallelic indels, including a -3 bp in-frame deletion, were introduced at the target site. In the T generation, these mutations and the transgene segregated in a Mendelian manner, resulting in recovery of null-segregant plants. Metabolite analysis revealed strong suppression of anthocyanin biosynthesis and a significant increase in luteolin accumulation in edited lines compared with the wild type. Transcriptome analysis further confirmed the loss of F3H function, demonstrating a metabolic shift of the flavonoid pathway toward luteolin production. This study provides the first functional validation of F3H in perilla and highlights its potential application in breeding cultivars with controlled bioactive compound contents. Our findings also demonstrate practical strategies for implementing genome editing in non-model crops and developing high-value functional cultivars. Practitioner PointsO_LIEditing a single flavonoid biosynthetic gene (F3H) effectively alters pigment composition in perilla leaves. C_LIO_LIIncreased accumulation of luteolin-related compounds suggests potential for enhancing functional metabolites without complex pathway engineering. C_LIO_LIGenome editing offers a feasible tool for perilla improvement in breeding and functional food development. C_LI

plant biology↗

bioRxiv2025

High-quality genome assembly and functional annotation of Hiroshima-derived Pacific oyster Magallana gigas

The Pacific oyster (Magallana gigas) is a widely distributed marine bivalve of major importance in aquaculture and is abundant along the Asian coasts. The Hiroshima Prefecture is the principal region for oyster production in Japan. The currently available reference genomes are derived from oysters of UK origin and do not fully capture the genetic characteristics of the Hiroshima populations. Here, we present a high-quality genome assembly and functional annotation of M. gigas from Hiroshima, Japan. The genome was assembled using PacBio HiFi long reads. After assembly, the contaminant contigs were removed, yielding a final assembly with a total length of 707 Mb, contig N50 of 7.9 Mb, and BUSCO completeness of 99.9 %. Of the 44,639 predicted protein-coding genes identified using GALBA, 43,806 were successfully annotated using a functional annotation workflow (Fanflow). Overall, the high-quality assembly and annotation provide a valuable genomic resource for exploring the genetic diversity and environmental adaptations of Hiroshima oyster populations. The data will facilitate future studies in breeding, functional genomics, and genome editing.

genomics↗

bioRxiv2025

Functional Annotation of Novel Heat Stress-responsive Genes in Rice Utilizing Public Transcriptomes and Structurome

MotivationLife science databases include large collections of public transcriptome and large-scale structural data. The reuse and integration of these datasets may facilitate the identification of understudied genes and enable functional annotation across distantly related species, including plants and humans. ResultsIn this study, we used heat stress-responsive genes in rice as a model to functionally annotate previously understudied genes by integrating publicly available transcriptome data with structural information from the AlphaFold Protein Structure Database. Initially, we conducted a meta-analysis of public heat stress-related transcriptome datasets, identified gene groups, and verified stress-related terms through enrichment analysis. Subsequently, we performed structural alignment and sequence alignment between rice and human proteins, focusing on candidates exhibiting low sequence similarity but high structural similarity (LS-HS conditions). We further incorporated supplemental data from public databases, including shared domain information between rice and human. This approach yielded a unique set of LS-HS candidates, notably those associated with metal homeostasis, such as iron and copper metabolism. Overall, our integrative method provided insights into these genes by leveraging diverse, publicly available datasets. Availability and implementationThe "plant2human workflow" for this analysis is available at https://doi.org/10.48546/WORKFLOWHUB.WORKFLOW.1206.8.

bioinformatics↗

bioRxiv2025

Meta-Analysis of Wild Relatives and Domesticated Species of Rice, Tomato, and Soybean Using Publicly Available Transcriptome Data

The domesticated species currently available in the market have been developed through the breeding of wild relatives. Breeding strategies using wild relatives with high genetic diversity are attracting attention as an important approach for ad-dressing climate change and ensuring sustainable food supply. However, studies examining gene expression variation in multiple wild and domesticated species are few. Therefore, we aimed to investigate the changes in gene expression associated with domestication. We performed a meta-analysis of public gene expression data of domesticated species of rice, tomato, and soybean and their presumed ancestral species. In wild relatives, the expression of genes involved in osmotic, drought, and wound stress tolerance was upregulated. In domesticated species, upregulated expression was observed in genes related to auxin and those involved in the efflux of heavy metals and harmful substances. These findings provide insights into how domestication influences changes in crop traits. Thus, our findings may contribute to rapid breeding and development of new varieties capable of growing in harsh natural environments. Hence, a new cultivation method called "de novo domestication" has been proposed, which combines the genetic diversity of currently unused wild relatives and wild relatives with genome editing technologies that enable rapid breeding.

plant biology↗

bioRxiv2025

Genome assembly and annotation of the naked mole rat Heterocephalus glaber reared in Japan

The naked mole rat (NMR, Heterocephalus glaber) is a eusocial rodent that is native to northeastern Africa. NMRs exhibit extraordinary traits such as longevity, resistance to age-related decline, and remarkable hypoxia tolerance. Although the reference genome of this species has been determined because of its unique characteristics, the significance or role of intraspecific genomic variations remains unknown. In this study, we used PacBio long-read sequencing to generate a genome assembly of NMR reared in Japan. The assembled genome is 2.56 Gb. Benchmarking Universal Single-Copy Orthologs (BUSCO) revealed high completeness (95.2%). BRAKER3 estimated 26,714 protein-coding genes, and we successfully added functional annotations for 26,232 protein-coding genes using the functional annotation workflow. We identified 417 gene models that were previously undetectable in the reference genome of this species. We also identified structural and amino acid sequence variations between our assembly and the reference genome, suggesting the presence of intraspecific genomic variations. This new genomic resource could help uncover the molecular mechanisms underlying the behavioral and physiological traits of NMR.

genomics↗

bioRxiv2025

The metabolic ability of swallowtails results in the production of bioactive substances from plant components

Host plant selection may depend on the metabolic system in herbivorous insects. Although oligophagous insects take up specific host plant components, how host plant components and their biological activities are altered through their metabolic systems remains unknown. Here, by examining gene expression of metabolic enzymes and components in the larval frass, we investigated the metabolic ability of Papilio memnon larvae fed with Citrus x paradisi (grapefruit) against host plant components. The gene expression levels of some metabolic enzymes were fluctuated between the larval midgut and the larval fat bodies. Furthermore, the chloroform extract from the larval frass, but not that from grapefruit leaves, inhibited cell viability of human pancreatic cancer cell line, MIA PaCa2. Finally, we identified two chlorophyll catabolites, pheophorbide-a and pyropheophorbide-a, in the larval frass extract. Pyropheophorbide-a reduces cell viability of and induces morphological changes in cells of MIA PaCa2; in addition, pheophorbide-a and pyropheophorbide-a inhibit the aggregation of amyloid {beta}-protein (human, 1-42). Therefore, the chemical structure and biological activity of host plant components are affected by the P. memnon metabolic system. Our findings may contribute to the development of a bioprocess for the production of pheophorbide-a and pyrophephorbide-a from chlorophyll via the metabolic functions of P. memnon larvae.

biochemistry↗

bioRxiv2025

Extraction of biological terms using large language models enhances the usability of metadata in the BioSample database

BioSample is a comprehensive repository of experimental sample metadata, playing a crucial role in providing a comprehensive archive and enabling experiment searches regardless of type. However, the difficulty in comprehensively defining the rules for describing metadata and limited user awareness of best practices for metadata have resulted in substantial variability depending on the submitter. This inconsistency poses significant challenges to the findability and reusability of the data. Given the vast scale of BioSample, which hosts over 40 million records, manual curation is impractical. Rule-based automatic ontology mapping methods have been proposed to address this issue, but their effectiveness is limited by the heterogeneity of BioSample metadata. Recently, large language models (LLMs) have gained attention in natural language processing and have been expected as promising tools for automating metadata curation. In this study, we evaluated the performance of LLMs in extracting cell line names from BioSample descriptions using a gold-standard dataset derived from ChIP-Atlas, a secondary database of epigenomics experiment data, which manually curates samples. Our results demonstrated that LLM-assisted methods outperformed traditional approaches, achieving higher accuracy and coverage. We further extended this approach to extraction of information about experimentally manipulated genes from metadata where manual curation had not yet been applied in ChIP-Atlas. This also yielded successful results for the usage of the database, which facilitates more precise filtering of data and prevents misinterpretation caused by inclusion of unintended data. These findings underscore the potential of LLMs to improve the findability and reusability of experimental data in general, significantly reducing user workload and enabling more effective scientific data management.

bioinformatics↗

bioRxiv2025

Risk Prediction of RNA Off-Targets of CRISPR Base Editors in Tissue-Specific Transcriptomes Using Language Models

Base-editing technologies, particularly cytosine base editors (CBEs), allow precise gene modification without introducing double-strand breaks; however, unintended RNA off-target effects remain a critical concern and are under-studied. To address this gap, we developed PiCTURE, a standardized computational pipeline for detecting and quantifying transcriptome-wide CBE-induced RNA off-target events. PiCTURE identifies both canonical ACW (W = A or T/U) motif-dependent and non-canonical RNA off-targets, revealing a broader WCW motif that underlies many unanticipated edits. Additionally, we developed two machine learning models based on the DNABERT-2 language model, termed STL and SNL, which outperformed motif-only approaches in terms of accuracy, precision, recall, and F1 score. To demonstrate the practical application of our predictive model for CBE-induced RNA off-target risk, we integrated PiCTURE outputs with the PROTECTiO pipeline and estimated RNA off-target risk for each transcript showing tissue-specific expression. The analysis revealed differences among tissues: while the brain and ovaries exhibited relatively low off-target burden, the colon and lungs displayed relatively high risks. Our study provides a comprehensive frame-work for RNA off-target profiling, emphasizing the importance of advanced machine learning-based classifiers in CBE safety evaluations and offering valuable insights for the development of safer genome-editing therapies.

genomics↗

bioRxiv2025

Data-driven workflow for comprehensive gene expression analysis in complex microbiomes

Complex microbiomes, characterized by highly diverse microbial species, are ubiquitous in the environment. However, the genomes of many constituent microbes remain uncharacterized, complicating the use of publicly available genome sequences as reference data for gene expression analysis based on next-generation sequencing (NGS) data. Consequently, selecting suitable reference sequences is critical for accurate gene expression analysis in complex microbiomes. Additionally, such analyses require precise quantitative evaluation of the genes within each microorganism. In this study, we identified appropriate reference sequences and developed a data-driven analytical workflow for gene expression analysis in complex microbiomes. Utilizing metagenomic and metatranscriptomic NGS reads from these microbiomes, the workflow evaluates gene abundance and transcriptional levels, addressing key analytical challenges. The findings demonstrate that metagenomic contigs are more suitable than conventional reference sequences for mapping both metagenomic and metatranscriptomic data. Moreover, this workflow facilitates not only the assessment of transcriptional activity but also the evaluation of gene expression potential.

microbiology↗

bioRxiv2024

Comprehensive expression data for two honey bee species, Apis mellifera and Apis cerana japonica

Comprehensive expression datasets were constructed for Apis mellifera and Apis cerana japonica. Post-oviposition day 6 to day 58 samples of A. mellifera workers (larva to adult); day 9, 10, 12, and 13 samples of A. mellifera queen (larva to pupa); and day 9 to day 18 samples of A. cerana japonica workers (larva to adult) were prepared, and RNA-Seq data were obtained. For A. cerana japonica, reference transcript sequence data, predicted amino acid sequence data, and functional annotation data were generated based on the genome sequence and RNA-Seq data. Using the transcript sequence and RNA-Seq data, comprehensive expression data for all transcripts of A. mellifera and A. cerana japonica were prepared. Hierarchical clustering analyses and the used sample preparation method ensured that both sets of expression data were reliable for use as comprehensive reference expression datasets. Therefore, these data are applicable for honey bee research or for comparative or evolutionary studies on insect species or social insect species at the genetic and molecular levels.

genetics↗

bioRxiv2024

Pipeline to explore information on genome editing using large language models and genome editing meta-database

Genome editing (GE) is widely recognized as an effective and valuable technology in life sciences research. However, certain genes are difficult to edit depending on some factors such as the type of species, sequences, and GE tools. Therefore, confirming the presence or absence of GE practices in previous publications is crucial for the effectively design and establishment of research using GE. Although the Genome Editing Meta-database (GEM: https://bonohu.hiroshima-u.ac.jp/gem/) aims to provide as comprehensive GE information as possible, it does not indicate how each registered gene is involved in GE. In this study, we developed a systematic method for extracting essential GE information using large language models from the information based on GEM and GE-related articles. This approach allows for a systematic and efficient investigation of GE information that cannot be achieved using the current GEM alone. In addition, by converting the extracted GE information into metrics, we propose a potential application of this method to prioritize genes for future research. The extracted GE information and novel GE-related scores are expected to facilitate the efficient selection of target genes for GE and support the design of research using GE. Database Tool URLs: https://github.com/szktkyk/extract_geinfo, https://github.com/szktkyk/visualize_geinfo

bioinformatics↗