Biology subjects

Kijima, Y.

Publications and source records attributed to Kijima, Y..

8 recordsLinked to original sources

bioRxiv2026

Epigenetic regulators partition the genome by evolutionary and developmental constraint

Many epigenetic regulators play essential roles in animal development, but precisely how they function across different cell types without clear sequence preferences remains a foundational challenge. Here, we employed single-cell RNA sequencing to survey the mutant phenotypes of 30 essential regulatory pathways across over 450 gastrulation stage mouse embryo replicates, including essential factors associated with repressive chromatin states, RNA surveillance/processing, and other genomic roles. We then use this integrated manifold to partition mutant responses into a developmentally-resolved interaction network, revealing a hierarchy of heterochromatin-associated interactions that act orthogonally to Polycomb Repressive Complex-mediated control of embryo patterning. Compared to the embryo proper, we find that the developing placenta and yolk sac can accommodate broad swings in repetitive element expression, a resilience in keeping with the relative evolutionary recency and phenotypic plasticity of these tissues. Dense temporal sampling of Human Silencing Hub (HUSH) mutant embryogenesis further supports the notion that the gastrulating embryo is particularly constrained and depends on multiple layers of insulation, including the need to suppress evolutionarily young genetic elements to stably license highly conserved, phylotypic programs. In combination, our work highlights the power of single cell-resolved developmental genetics to contextualize the roles of epigenetic regulators, which restrict genomic action to support robust cellular identities and embryological forms.

developmental biology↗

bioRxiv2026

Folate deficiency disrupts key metabolic transitions within the developing neural ectoderm

Despite long-standing epidemiological associations, the mechanism linking folate availability to gestational neural tube defects remains unclear, partly because measuring and interpreting metabolic activity in dynamic biological systems remains challenging. Here, we apply a deep-learning-based graph-guided variational autoencoder (MeRN; Metabolic Representation Network) to infer single-cell metabolic activity and states from scRNA-seq data of mouse embryogenesis. By analyzing folate-deficient embryogenesis from E7.0 to E9.0, we identify a transient state within the nascent neural lineage that is acutely sensitive to folate availability, leading to an interconnected disruption between key bioenergetic pathways and de novo purine biosynthesis. Moreover, metabolically induced growth defects lead to permanent morphological disruptions along the dorsal-ventral axis, which we confirm by generating whole-embryo fate maps using a prime-editing-based lineage recorder (PEtracer). Collectively, our results establish a highly scalable framework for interpreting dynamic changes in embryonic metabolism and elucidating the mechanistic bases underlying environmentally linked congenital disorders.

genomics↗

bioRxiv2023

Highly efficient transgenic mouse production using piggyBac and its application to rapid phenotyping at the founder generation

Pronuclear microinjection is the most popular method for producing transgenic (Tg) animals. Because the production efficiency is typically less than 20%, phenotypic characterization of Tg animals is generally performed on the next generation (F1) onwards. However, apart from in rodents, in many animal species with long generation times, it is desirable to perform phenotyping in the founder (F0) generation. In this study, we attempted to optimize a method of Tg mouse production to achieve higher Tg production efficiency using piggyBac transposon systems and established optimal conditions under which almost all individuals in the F0 generation were Tg. We also succeeded in generating bacterial artificial chromosome Tg mice with efficiency of approximately 70%. By combining this method with genome editing technology, we established a new strategy to perform phenotyping of mice with tissue-specific knockout using the F0 generation. Taking the obtained findings together, by using this method, experimental research using Tg animals can be carried out more efficiently.

bioengineering↗

bioRxiv2023

A multi-kingdom genetic barcoding system for precise target clone isolation

Clonal heterogeneity underlies diverse biological processes, including cancer progression, cell differentiation, and microbial evolution. Cell tagging strategies with DNA barcodes have recently enabled analysis of clone size dynamics and clone-restricted transcriptomic landscapes of heterogeneous populations. However, isolating a target clone that displays a specific phenotype from a complex population remains challenging. Here, we present a new multi-kingdom genetic barcoding system, CloneSelect, in which a target cell clone can be triggered to express a reporter gene for isolation through barcode-specific CRISPR base editing. In CloneSelect, cells are first barcoded and propagated so their subpopulation can be subjected to a given experiment. A clone that shows a phenotype or genotype of interest at a given time can then be isolated from the initial or subsequent cell pools stored throughout the experimental timecourse. This novel CRISPR-barcode genetics platform provides many new ways of analyzing and manipulating mammalian, yeast, and bacterial systems. TeaserA multi-kingdom CRISPR-activatable barcoding system enables the precise isolation of target barcode-labeled clones from a complex cell population.

synthetic biology↗

bioRxiv2022

A universal sequencing read interpreter

Massively parallel DNA sequencing has led to the rapid growth of highly multiplexed experiments in biology. Such experiments produce unique sequencing results that require specific analysis pipelines to decode highly structured reads. However, no versatile framework that interprets sequencing reads for downstream biological analysis has been developed. Here we report INTERSTELLAR (interpretation, scalable transformation, and emulation of large-scale sequencing reads) that extracts data values encoded in theoretically any type of sequencing read and translates them into sequencing reads of any structure of choice. INTERSTELLAR first identifies sequence segments encoded in reads according to the users definition. Followed by error correction, values are extracted and compressed into an optimal space, which can be efficiently translated into sequencing reads of another structure. We demonstrated that INTERSTELLAR successfully extracted information from a range of sequencing reads and translated those of single-cell (sc)RNA-seq, scATAC-seq, and spatial transcriptomics to be analyzed by different software tools that have been developed for conceptually the same types of experiments. INTERSTELLAR will greatly facilitate the development of new sequencing-based experiments and sharing of data analysis pipelines.

bioinformatics↗

bioRxiv2022

The DNA-based global positioning system--a theoretical framework for large-scale spatial genomics

We present GPS-seq, a theoretical framework that enables massively scalable, optics-free spatial transcriptomics. GPS-seq combines data from high-throughput sequencing with manifold learning to obtain the spatial transcriptomic landscape of a given tissue section without optical microscopy. In this framework, similar to technologies like Slide-seq and 10X Visium, tissue samples are stamped on a surface of randomly-distributed DNA-barcoded spots (or beads). The transcriptomic sequences of proximal cells are fused to DNA barcodes, enabling the recovery of a transcriptomic pixel image by high-throughput sequencing. The barcode spots serve as "anchors" which also capture spatially diffused "satellite" barcodes, and therefore allow computational reconstruction of spot positions without optical sequencing or depositing barcodes to pre-specified positions. In theory, it could generate 100 mm x 100 mm spatial transcriptomic images with 10-20 m resolution by localizing 108 DNA-barcoded pixels with a single Illumina NovaSeq run. The general framework of GPS-seq is also compatible with standard single-cell (or single-nucleus) capture methods, and any modality of single-cell genomics, such as sci-ATAC-seq, could be transformed into spatial genomics in this strategy. We envision that GPS-seq will lead to breakthrough discoveries in diverse areas of biology by enabling organ-scale imaging of multiple genomic statuses at single-cell resolution for the first time.

bioinformatics↗

bioRxiv2021

Zebrafish Danio rerio trunk muscle structure and growth from a spatial transcriptomics perspective

Compared to mammals, some fish exhibit indeterminate growth characteristics, meaning they can continue growing throughout their lives. Zebrafish trunk skeletal muscle can in general be classified into slow, intermediate, and fast based on morphological and physiological characteristics. After hatching, hyperplasia can be observed in the muscles of juvenile zebrafish, and with growth, hyperplasia in the fast muscles gradually decreases until it stagnates, after which fast muscle development relies on hypertrophy. In slow muscle, hyperplasia continues throughout life. Teleost muscle structure and growth has been described mainly by morphological and physiological features based on the expression of a limited number of proteins, transcripts, and metabolites. The details of mechanism remain unclear. Visium Spatial Gene Expression solution was used in this study. On the adult slide, 10 clusters were obtained based on whole gene expression similarities. The spatial expression of myosin heave chains, myosin light chains and myosin-binding proteins was investigated. GO enrichment analysis was also performed on different muscle regions of aged zebrafish. Dorsal and ventral slow muscles share the same processes such as myofibril assembly and muscle tissue development. On the larvae slide, 3 clusters were obtained, GO enrichment analysis suggest active muscle formation in zebrafish larvae.

genomics↗

bioRxiv2018

Age-associated different transcriptome profiling in zebrafish and rat: insight into diversity of vertebrate aging

BackgroundAging and death are inevitable for most species and are of intense interest for human beings. Most mammals, including humans, show obvious aging phenotypes, for example, loss of tissue plasticity and sarcopenia. In this regard, fish provide attractive models because of their unique aging characteristics. First, the lifespan of fish is highly varied and some long-lived fish can live for over 200 years. Second, some fish show anti-aging features and indeterminate growth throughout their life. Because these characteristics are not found in mammalian model organisms, exploring mechanisms of senescence in fish is expected to provide new insights into vertebrate aging. Therefore, we conducted transcriptome analysis for brain, gill, heart, liver and muscle from 2-month-, 7-month-, 16month- and 39-month-old zebrafish. In addition, we downloaded RNA-seq data for sequential age related gene expression in brain, heart, liver and muscle of rat (1). These RNA-seq data from two species were compared, and common and species-specific features of senescence were analyzed.\n\nResultsScreening of differentially expressed genes (DEGs) in all zebrafish tissues examined revealed up-regulation of circadian genes and down-regulation of hmgb3a. Comparative analysis of DEG profiles associated with aging between zebrafish and rat showed both conserved and clearly different aging phenomena. Furthermore, up-regulation of circadian genes with aging and down-regulation of collagen genes were observed in both species. On the other hand, in zebrafish, up-regulation of autophagy related genes in muscle and atf3 in various tissues suggested fish-specific anti- aging characteristics. Consistent with our knowledge of mammalian aging, a tissue deterioration-related DEG profile was observed in rat. We also detected aging-associated down-regulation of muscle development and ATP metabolism-related genes in zebrafish gill. Correspondingly, hypoxia-related genes were systemically up-regulated in aged zebrafish, suggesting age-related hypoxia as a senescence modulator in fish.\n\nConclusionsOur results indicate both common and different aging profiles between fish and mammals. Gene expression profiles specific to fish will provide new insight for future translational research.

bioinformatics↗