Biology subjects

Aburatani, H.

Publications and source records attributed to Aburatani, H..

15 recordsLinked to original sources

bioRxiv2026

A cuffed CRISPR guide RNA for microRNA activity-dependent genome editing

Cells in multicellular eukaryotic systems are diverse biological units, with characteristics and functions determined by their molecular profiles. CRISPR-Cas9 genome editing has been widely used across biology to modulate gene expression and study gene function. However, there is currently no versatile and scalable method for editing a cells genome in response to endogenous cellular signals. Here, we report the engineering of a CRISPR guide RNA that efficiently confers genome editing in response to the catalytic activity of a target microRNA (miRNA) within a cell. miRNAs are short non-coding RNAs that are widely conserved across eukaryotes and can cleave their target RNA through almost perfect base pairing. In mammals, miRNAs are largely involved in development and homeostasis as well as disease progression and developmental disorders. To leverage these properties for genome editing, we developed a cuffed guide RNA (cgRNA) which is composed of a permutated order of sequence domains from the commonly used single guide RNA (sgRNA). These permutated domains were then concatenated with a miRNA target sequence, yielding a warped guide RNA that is inactive until cleaved by a complementary miRNA. We demonstrated that cgRNA enabled efficient miRNA activity-dependent genome editing in human and mouse cell lines. Biochemical and structural analyses revealed three stages of inhibition of the CRISPR genome-editing pathway for unprocessed cgRNA. Utilizing a lentiviral library of cgRNAs containing miRNA targets covering mouse genome-wide miRNAs, we identified miRNA cleavage activities and their sequence specificities in mouse embryonic stem cells and during smooth muscle cell differentiation. Furthermore, we showed that endogenous mRNA expression could be irreversibly recorded into a DNA sequence using a cgRNA targeted by a synthetic miRNA repeat. cgRNA is a simple, robust, miRNA activity-gated genome editing system that could facilitate the development of cell state-specific genome editing, the mapping of miRNA activity and gene expression landscapes, and the recording of molecularly determined cell states during the long-term progression of multicellular systems.

bioengineering↗

bioRxiv2026

A positional and combinatorial regulatory code for alternative splicing

Alternative pre-mRNA splicing generates extensive transcript diversity, yet the regulatory code that determines how splicing decisions are encoded across the transcriptome remains poorly defined. Splicing outcomes are controlled by combinatorial RNA-binding protein (RBP) interactions and positional context, but how these features are integrated at the transcriptome scale remains unclear. CLIP-based approaches have mapped RBP binding, but directly comparable endogenous maps across multiple RBPs are lacking, limiting inference of global regulatory principles. Here we introduce SCALE-CLIP, an endogenous CLIP framework that integrates CRISPR-Cas9-mediated epitope tagging with long-read-guided read attribution to generate directly comparable RBP binding maps across splicing-regulatory factors. Applied to 23 RBPs, SCALE-CLIP expanded endogenous RBP coverage and, across benchmarked shared factors, increased peak recovery by a median of 12.2-fold relative to ENCODE eCLIP while preserving specificity and reproducibility. We define a transcriptome-wide positional and combinatorial code for alternative splicing, in which binding position is a primary determinant of regulatory outcome: SRSF binding within alternative exons promotes inclusion, whereas binding on flanking exons drives exon skipping. Higher-order SRSF occupancy further tunes this code, buffering exon inclusion when centered on alternative exons but reinforcing repression when distributed across flanking exons. We also show that m6A provides an epitranscriptomic layer that locally enhances SRSF binding and is associated with increased exon inclusion. Together, these results establish a multi-layered RNA-binding logic in which binding position, combinatorial RBP architecture and RNA modification jointly shape splicing outcomes, providing a framework for rational interpretation and modulation of alternative splicing.

molecular biology↗

bioRxiv2026

Personalized reference genome-based pipeline reveals comprehensive haplotype-resolved views of cancer genomes

Cancer genome analysis relies on standard human reference genomes, but detecting somatic alterations in highly repetitive or individual-specific regions remains challenging. We developed the Personalized Reference genome-based Cancer Genome Analysis Pipeline (PRCGAP, https://github.com/yos-sk/PRCGAP), to our knowledge, the first comprehensive pipeline integrating haplotype-resolved analyses of somatic point mutations, structural variants, copy number, and DNA methylation on personalized diploid reference genomes, with each variant phased and annotated by genomic features. We applied PRCGAP to eight tumor-normal cell line pairs and three newly collected pediatric B-cell acute lymphoblastic leukemia (B-ALL) clinical samples. PRCGAP recovered most standard reference-based variants (86.7-96.4% across variant types), validated by orthogonal short-read sequencing, while additionally detecting variants that standard references missed (23.4% of SNVs and 32.6% of SVs). Notably, PRCGAP uncovered variants in centromeric and telomeric regions, and somatic single-nucleotide variants were enriched in centromere dip regions, the putative kinetochore formation sites. Using PRCGAP outputs, we identified L1 retrotransposition source sites absent from standard references and showed that a B-ALL IGH::DUX4 fusion arose from a DUX4 pseudogene within an internal D4Z4 repeat unit, rather than the canonical full-length DUX4 gene. Within a single haplotype-resolved framework, PRCGAP opens regions of the cancer genome that are inaccessible to standard references.

bioinformatics↗

bioRxiv2026

Chromatin landscape and epigenetic heterogeneity of acute myeloid leukemia

Acute myeloid leukemia (AML) is an aggressive hematologic cancer characterized by proliferation of immature myeloblasts. It shows profound molecular heterogeneity, which has been primarily studied through genetic abnormalities, providing the basis for disease classification, prognostication, and therapeutic choice. However, genetic factors alone may not fully explain AML pathogenesis and diversity, while leaving the role of abnormal epigenome, particularly chromatin state, largely unexplored in a large cohort of patients. Here we show that AML is classified into 16 subgroups with distinct chromatin accessibility profiles based on ATAC-seq in 1,563 AML cases, including novel AML subgroups not previously recognized in conventional genomic classifications. By integrating multi-omics analyses of genome, transcriptome, and major histone marks, we show that these epigenetic subgroups exhibit unique features in clinical presentation, gene mutations, differentiation states, gene expression, and super-enhancer profiles, which are validated across independent cohorts. Single-cell sequencing demonstrates the presence of subgroup-specific ATAC signatures that are shared by all leukemic cells, confirming the definitive role of the epigenome in the ATAC-based classification. Mechanistically, each subgroup is associated with a distinct gene regulatory network centered on key transcription factors, where subgroup-specific super-enhancers play a pivotal role. These ATAC subgroups also have prognostic significance independent of genomic classification, and help reveal unexpected drug sensitivities. In summary, ATAC-based chromatin profiling in this large sample set, combined with multi-omics data, provides new insights into AML pathogenesis beyond genomic profiling and also serves as an invaluable resource for AML research.

cancer biology↗

bioRxiv2025

Hox - Meis-relayed topographical genetic switch underlies cardiopharyngeal neural crest diversification, revealed by multimodal analysis

Neural crest cells (NCCs) are multipotent migratory cells essential for cardiac development, yet the lineage trajectories and gene regulatory networks (GRNs) underlying their differentiation in the cardiopharyngeal region remain unclear. Here, we integrate single-cell RNA-seq, spatial transcriptomics, and multiomic analyses to construct a comprehensive map of NCC lineages in developing mouse cardiopharyngeal tissues. We identify a transition from Hox-positive pharyngeal NCCs to Hox-negative intracardiac populations associated with the outflow tract cushion, accompanied by a shift in Meis transcription factor binding and GRN architecture. By contrast, NCCs forming the aorticopulmonary septum and great vessel smooth muscle retain distinct Hox-codes. A Meis2-Sox9-Scx GRN defines a skeletogenic progenitor-like intermediate state that gives rise to coronary artery smooth muscle and semilunar valves. Our findings suggest that the loss of Hox-dependent regional identity enables pharyngeal NCCs to acquire new fates upon entering the cardiac cushion, providing insight into the developmental origins of coronary and valvular calcification.

developmental biology↗

bioRxiv2023

Pooled CRISPR screening of high-content cellular phenotypes by ghost cytometry

Fast enrichment of cells based on morphological information remains a challenge, limiting genome-wide perturbation screening for diverse high-content phenotypes of cells. Here we show that multi-modal ghost cytometry-based cell sorting is applicable to fast pooled CRISPR screening for both fluorescence and label-free high-content phenotypes of millions of cells. By employing the high-content cell sorter in the fluorescence mode, we enabled the genome-wide CRISPR screening of genes that affect NF-{kappa}B nuclear translocation. Furthermore, by employing the multi-parametric, label-free mode, we performed the large-scale screening to identify a gene involved in macrophage polarization. Especially the label-free platform can enrich target phenotypes without invasive staining, preserving untouched cells for downstream assays and unlocking the potential to screen for the cellular phenotypes even when suitable markers are lacking. One-Sentence SummaryMachine vision-based cell sorter enabled genome-wide perturbation screens for high-content cell phenotypes even without labeling

cell biology↗

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

Repetitive DNA promotes RNAi-mediated heterochromatin formation via an anti-silencing factor in fission yeast.

In most eukaryotes, constitutive heterochromatin, defined by histone H3 lysine 9 methylation (H3K9me), is enriched on repetitive DNA, such as pericentromeric repeats and transposons. Furthermore, repetitive transgenes also induce heterochromatin formation in diverse model organisms. However, the mechanisms that promote heterochromatin formation at repetitive DNA elements are still not clear. Here, using fission yeast, we show that tandemly repeated mRNA genes promote RNA interference (RNAi)-mediated heterochromatin formation in co-operation with an anti-silencing factor, Epe1. Although the presence of tandemly repeated genes itself does not cause heterochromatin formation, once complementary small RNAs are artificially supplied in trans, the RNAi machinery assembled on the repeated genes starts producing cognate small RNAs in cis to autonomously maintain heterochromatin at these sites. The establishment of this "repeat-induced RNAi" depends on the copy number of repeated genes and also requires Epe1, which is known to remove H3K9me and derepress the transcription of genes underlying heterochromatin. Analogous to repeated genes, the DNA sequence underlying constitutive heterochromatin encodes widespread transcription start sites (TSSs), from which Epe1 activates ncRNA transcription to promote RNAi-mediated heterochromatin formation. Our results suggest that, when repetitive transcription units underlie heterochromatin, Epe1 generates sufficient transcripts for the activation of RNAi without disruption of heterochromatin.

biochemistry↗

bioRxiv2022

Cardiac neural crest lineage diversity and underlying gene regulatory networks revealed by multimodal analysis

Neural crest cells (NCCs), a multipotent stem cell population, contribute to cardiac development as a source of the outflow septum, vascular smooth muscle and semilunar valves. However, genetic programs underlying lineage diversification of cardiac NCCs remain largely unknown. Using single-cell (sc) and spatial transcriptomics, we demonstrate multiple NCC subpopulations with distinct gene expression signatures; smooth muscle(-like), non-muscle mesenchymal, and Schwann cell progenitor/melanoblast-like cells. Integrative scRNA-seq and scATAC-seq analyses predict lineage trajectories starting from immature NCCs, which bifurcate into smooth muscle(-like) and non-muscle mesenchymal lineages in association with hierarchical transcription factor networks. Combinatory analyses with Cre-mediated genetic lineage tracing characterize intermediate NCCs at the bifurcation as Sox9+/Scx+ tendon and cartilage progenitor-like cells with genetic programs, some of which are common to skeletal tissues whereas others are unique to cardiac NCCs. These findings provide a basis for understanding the roles of NCCs in cardiac development and pathogenesis particularly associated with calcification.

developmental biology↗

bioRxiv2021

Glutamine deficiency in solid tumors confers resistance to ribosomal RNA synthesis inhibitors

Ribosome biogenesis involves the processing of precursor ribosomal RNAs (pre-rRNAs) and sequential assembly with ribosomal proteins. Here we report that nutrient deprivation severely impairs pre-rRNA processing and leads to the accumulation of unprocessed rRNAs. Upon nutrient restoration, the accumulated pre-rRNAs are processed into mature rRNAs that are utilized for ribosome biogenesis. Failure to accumulate pre-rRNAs under nutrient deprivation leads to perturbed ribosome assembly during nutrient restoration and subsequent apoptosis via uL5/uL18-mediated activation of p53. Restoration of glutamine alone activates p53 by triggering uL5/uL18 translation. Induction of uL5/uL18 protein synthesis by glutamine was dependent on the translation factor eukaryotic elongation factor 2 (eEF2), which was in turn dependent on Raf/MEK/ERK signalling. Depriving cells of glutamine prevents the activation of p53 by rRNA synthesis inhibitors. Our data reveals a mechanism that cancer cells can exploit to suppress p53-mediated apoptosis during fluctuations in environmental nutrient availability.

cancer biology↗

bioRxiv2020

Artificial intelligence based computational framework for drug-target prioritization and inference of novel repositionable drugs for Alzheimer's disease

BackgroundIdentification of novel therapeutic targets is a key for successful drug development. However, the cost to experimentally identify therapeutic targets is huge and only 400 genes are targets for FDA-approved drugs. Therefore, it is inevitable to develop powerful computational tools to identify potential novel therapeutic targets. Because proteins make their functions together with their interacting partners, a protein-protein interaction network (PIN) in human could be a useful resource to build computational tools to investigate potential targets for therapeutic drugs. Network embedding methods, especially deep-learning based methods would be useful tools to extract an informative low-dimensional latent space that contains enough information required to fully represent original high-dimensional non-linear data of PINs. ResultsIn this study, we developed a deep learning based computational framework that extracts low-dimensional latent space embedded in high-dimensional data of the human PIN and uses the features in the latent space (latent features) to infer potential novel targets for therapeutic drugs. We examined the relationships between the latent features and the representative network metrics and found that the network metrics can explain a large number of the latent features, while several latent features do not correlate with all the network metrics. The results indicate that the features are likely to capture information that the representative network metrics can not capture, while the latent features also can capture information obtained from the network metrics. Our computational framework uses the latent features together with state-of-the-art machine learning techniques to infer potential drug target genes. We applied our computational framework to prioritized novel putative target genes for Alzheimers disease and successfully identified key genes for potential novel therapeutic targets (e.g., DLG4, EGFR, RAC1, SYK, PTK2B, SOCS1). Furthermore, based on these putative targets, we inferred repositionable candidate-compounds for the disease (e.g., Tamoxifen, Bosutinib, and Dasatinib) DiscussionsOur computational framework could be powerful computational tools to efficiently prioritize new therapeutic targets and drug repositioning. It is pertinent to note here that our computational platform is easily applicable to investigate novel potential targets and repositionable compounds for any diseases, especially for rare diseases.

bioinformatics↗

bioRxiv2019

Population-specific and transethnic genome-wide analyses reveal distinct and shared genetic risks of coronary artery disease

To elucidate the genetics of coronary artery disease (CAD) in the Japanese population, we conducted a large-scale genome-wide association study (GWAS) of 168,228 Japanese (25,892 cases and 142,336 controls) with genotype imputation using a newly developed reference panel of Japanese haplotypes including 1,782 CAD cases and 3,148 controls. We detected 9 novel disease-susceptibility loci and Japanese-specific rare variants contributing to disease severity and increased cardiovascular mortality. We then conducted a transethnic meta-analysis and discovered 37 additional novel loci. Using the result of the meta-analysis, we derived a polygenic risk score (PRS) for CAD, which outperformed those derived from either Japanese or European GWAS. The PRS prioritized risk factors among various clinical parameters and segregated individuals with increased risk of long-term cardiovascular mortality. Our data improves clinical characterization of CAD genetics and suggests the utility of transethnic meta-analysis for PRS derivation in non-European populations.

genetics↗

bioRxiv2019

Comprehensive epigenome characterization reveals diverse transcriptional regulation across human vascular endothelial cells

BackgroundEndothelial cells (ECs) make up the innermost layer throughout the entire vasculature. Their phenotypes and physiological functions are initially regulated by developmental signals and extracellular stimuli. The underlying molecular mechanisms responsible for the diverse phenotypes of ECs from different organs are not well understood.\n\nResultsTo characterize the transcriptomic and epigenomic landscape in the vascular system, we cataloged gene expression and active histone marks in nine types of human ECs (generating 148 genome-wide datasets) and carried out a comprehensive analysis with chromatin interaction data. We identified 3,765 EC-specific enhancers, some of which were associated with disease-associated genetic variations. We also identified various candidate marker genes for each EC type. Notably, reflecting the developmental origins of ECs and their roles in angiogenesis, vasculogenesis and wound healing.\n\nConclusionsWhile the importance of several HOX genes for early vascular development and adult angiogenesis in pathological conditions has been reported, a systematic analysis of the regulation and roles of HOX genes in mature tissue cells has been lacking. These datasets provide a valuable resource for understanding the vascular system and associated diseases.

genomics↗

bioRxiv2019

A single CRISPR base editor to induce simultaneous C-to-T and A-to-G mutations

While several Cas9-derived base editors have been developed to induce either C-to-T or A-to-G mutation at target genomic sites, the possible genome editing space when using the current base editors remains limited. Here, we present a novel base editor, Target-ACE, which integrates the abilities of both of the previously developed C-to-T and A-to-G base editors by fusing an activation-induced cytidine deaminase (AID) and an engineered tRNA adenosine deaminase (TadA) to a catalytically impaired Streptococcus pyogenes Cas9. In mammalian cells, Target-ACE enabled heterologous editing of multiple bases in a small sequence window of target sites with increased efficiency compared with a mixture of two relevant base editor enzymes, each of which may block the same target DNA molecule from the other. Furthermore, by modeling editing patterns using deep sequencing data, the editing spectra of Target-ACE and other base editors were simulated across the human genome, demonstrating the highest potency of Target-ACE to edit amino acid coding patterns. Taking these findings together, Target-ACE is a new tool that broadens the capabilities for base editing for various applications.

bioengineering↗

bioRxiv2019

Lysine demethylase 7a regulates the anterior-posterior development in mouse by modulating the transcription of Hox gene cluster

Temporal and spatial colinear expression of the Hox genes determines the specification of positional identities during vertebrate development. Post-translational modifications of histones contribute to transcriptional regulation. Lysine demethylase 7A (Kdm7a) demethylates lysine 9 di-methylation of histone H3 (H3K9me2) and participates in the transcriptional activation of developmental genes. However, the role of Kdm7a during mouse embryonic development remains to be elucidated. Here, we show that Kdm7a-/- mouse exhibits an anterior homeotic transformation of the axial skeleton, including an increased number of presacral elements. Importantly, posterior Hox genes (caudally from Hox9) are specifically downregulated in the Kdm7a-/- embryo, which correlates with increased levels of H3K9me2. These observations suggest that Kdm7a controls the transcription of posterior Hox genes, likely via its demethylating activity, and thereby regulating the murine anterior-posterior development. Such epigenetic regulatory mechanisms may be harnessed for the proper control of coordinate body patterning in vertebrates.

molecular biology↗