Biology subjects

Okada, A.

Publications and source records attributed to Okada, A..

12 recordsLinked to original sources

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↗

bioRxiv2025

Rare k-mers reveal centromere haplogroups underlying human diversity and cancer translocations

Centromeres are among the most diverse and dynamically evolving regions of the human genome and are commonly affected in various human cancers. However, organized into highly repetitive -satellite higher-order repeats (HORs), human centromere sequences have long resisted detailed genomic analysis. Although the development of long-read sequencing platforms has enabled the analysis of complete centromere sequences, their application to a large set of samples is still largely limited, preventing our understanding of centromere variation and haplotype structures across large human populations and the structural basis of centromere-involving translocations in cancer. Here we show that rare k-mers present in centromeric regions can serve as effective markers for dissecting the complexity of centromere structure, particularly that of active -satellite HOR arrays (aHOR arrays), across human populations and for understanding centromere-involving abnormalities in cancer. Based on rare k-mer-based clustering, centromere aHOR arrays are clustered into discrete haplogroups (aHOR-HGs) with distinct structural features. These k-mers were also used to develop a framework that enables the inference of haplogroups in a given sample based on short-read whole genome sequencing (WGS) data (ascairn). By applying ascairn to large-scale human population datasets (n > 3,300), we revealed the diversity of aHOR-HGs and their geographic histories across populations. The rare k-mer-based approach was also applied to investigate the structure of 1p/19q co-deletion, a highly recurrent centromere-involving translocation in IDH-mutated oligodendrogliomas. Analyzing short-read WGS data from 142 cases with 1p/19q co-deletion using rare k-mers, we showed that breakpoints of 1p/19q co-deletion were mapped to aHOR arrays in chromosomes 1 (D1Z7) and 19 (D19Z3), which was validated by long-read sequencing of two 1p/19q co-deletion-positive cases. Notably, the translocation preferentially involved haplogroups composed of haplotypes containing larger regions susceptible to rearrangement. These results highlight the role of rare k-mers in dissecting the complexity of centromere sequences and their evolutionary history as well as understanding centromere-involving abnormalities associated with human diseases.

genomics↗

bioRxiv2024

Improvement of Antibody Affinity and Using PURE Ribosome Display and Microbial Secretion System

A method has been developed for efficiently enriching and analyzing high-affinity antibody variants by combining the PURE ribosome display (ribosome display using purified cell-free protein synthesis components) with next-generation sequencing (NGS) and the Brevibacillus choshinensis secretion system, using the NZ-1 antibody, which targets the PA tag peptide (GVAMPGAEDDVV), as a model antibody. An artificial DNA encoding the single-chain fragment of binding (scFab) of the NZ-1 antibody was synthesized and actively expressed by cell-free protein synthesis system (CFPS). Region-specific saturation mutations were introduced into the scFab gene based on its structural information. The resulting scFab library was selected against the PA tag through two rounds of PURE ribosome display, followed by Illumina sequencing to identify potential scFab variants with higher affinity. The candidates were expressed as Fab fragments using the B. choshinensis secretion system. These Fab fragments were then purified from the culture supernatant using two-step column chromatography. The binding affinity of the purified Fab was evaluated using a biolayer interferometry assay, revealing a variant Fab with higher affinity than the wild-type Fab. These results demonstrate that integrating PURE ribosome display with NGS analysis and the B. choshinensis secretion expression system enables the rapid identification and analysis of high-affinity antibody variants.

synthetic biology↗

bioRxiv2024

Comparative analysis of trans-chromosomic rodent models reveals improved somatic hypermutation and class-switch recombination in rats

Humanized rodent models, especially humanization of genetic/genomic components involved in immunity have significantly advanced our understanding of human immune system. Here, we utilized trans-chromosomic (Tc) technology to generate a TC-mAb rat model that stably harbors a mouse artificial chromosome carrying full-length human immunoglobulin (Ig) heavy and kappa light chain genes (IGHK-NAC) in a rat Ig knockout background. In contrast with TC-mAb mice, serum human IgG concentration was found higher than IgM. Number of lymphocytes was recovered, and B cell population in the spleen was normal. Remarkably, repertoire analysis revealed similarities between the model and human PBMCs; somatic hypermutation and class-switch recombination also more closely resembled humans. Furthermore, immunization resulted in generation of antigen-specific human antibodies. Collectively, our strategy to generate both rat and mouse models through introduction of the identical IGHK-NAC offers unprecedented opportunities to comprehensively evaluate genomic regulation and its outcomes associated with genomic sequences and host-derived protein factors.

bioengineering↗

bioRxiv2024

The genetic basis of the black pupae phenotype in tephritid fruit flies

The remarkable diversity of insect pigmentation offers a captivating avenue for exploring evolution and genetics. In tephritid fruit flies, decoding the molecular pathways underlying pigmentation traits also plays a central role in applied entomology. Mutant phenotypes like the black pupae (bp) have long been used as a component of genetic sexing strains, allowing male-only release in tephritid sterile insect technique applications. However, the genetic basis of bp remains largely unknown. Here, we present independent evidence from classical and modern genetics showing that the bp phenotype in the GUA10 strain of the Mexican fruit fly, Anastrepha ludens, is caused by a large deletion at the ebony locus resulting in the removal of the entire protein-coding region of the gene. Targeted knockout of ebony induced analogous bp phenotypes across six tephritid species spanning over 50 million years of divergent evolution. This functionally validated our findings and allowed for a deeper investigation into the role of Ebony in pigmentation and development in these species. Our study offers fundamental knowledge for developing new sexing strains based on the bp marker and for future evolutionary developmental biology studies in tephritid fruit flies.

genomics↗

bioRxiv2024

Systematically developing a registry of splice-site creating variants utilizing massive publicly available transcriptome sequence data

Genomic variants causing abnormal splicing play an important role in genetic disorders and cancer development. Among them, variants that cause formations of novel splice-sites (splice-site creating variants, SSCVs) are particularly difficult to identify and often overlooked in genomic studies. Additionally, these SSCVs, especially those found in deep intronic regions, are frequently considered promising candidates for treatment with splice-switching antisense oligonucleotides (ASOs), offering therapeutic potential for rare disease patients. To leverage massive transcriptome sequence data such as those available from the Sequence Read Archive, we developed a novel framework to screen for SSCVs solely using transcriptome data. We have applied it to 322,072 publicly available transcriptomes and identified 30,130 SSCVs. Utilizing this extensive collection of SSCVs, we have revealed the characteristics of Alu exonization via SSCVs, especially the hotspots of SSCVs within Alu sequences and their evolutionary relationships. Many of the SSCVs affecting disease-causing variants were predicted to generate premature termination codons and are degraded by nonsense-mediated decay. On the other hand, several genes, such as CREBBP and TP53, showed characteristic SSCV profiles indicative of heterogeneous mutational functions beyond simple loss-of-function. Finally, we discovered novel gain-of-function SSCVs in the deep intronic region of the NOTCH1 gene and demonstrated that their activation can be suppressed using splice-switching ASOs. Collectively, we provide a systematic approach for automatically acquiring a registry of SSCVs, which can be used for elucidating novel biological mechanisms for splicing and genetic variation, and become a valuable resource for pinpointing critical targets in drug discovery. Catalogs of SSCVs identified in this study are accessible on SSCV DB (https://sscvdb.io/).

bioinformatics↗

bioRxiv2022

Quantitative analysis of calcium oxalate monohydrate and dihydrate for elucidating the formation mechanism of calcium oxalate kidney stones

We aimed to identify and quantitatively analyze calcium oxalate (CaOx) kidney stones on the order of micrometers, with a focus on the quantitative identification of calcium oxalate monohydrate (COM) and dihydrate (COD). Fourier Transform Infrared (FTIR) spectroscopy, powder X-ray diffraction (PXRD), and microfocus X-ray CT measurements (micro-CT) were performed, and the results were compared. The extended analysis method of the FTIR spectrum, focusing on the 780 cm-1 peak, made it possible to achieve a reliable analysis of the COM/COD ratio. We succeeded in the quantitative analysis of COM/COD in the region of 50 x 50 m by microscopic FTIR for thin sections of kidney stones, and by the micro-CT for bulk samples. The extended analysis method of the FTIR spectrum focusing on the 780 cm-1 peak was introduced to analyze the COM/COD ratio. The analysis results based on PXRD measurement with micro sampling, microscopic FTIR analysis of a thin section, and micro-CT observation of a bulk sample of a kidney stone showed roughly consistent results, indicating that all methods can be used complementarily. This quantitative analysis method evaluates the detailed CaOx composition on the preserved stone surface and provides information on the stone formation processes and interactions with organic molecules.

biophysics↗

bioRxiv2021

Systematic identification of intron retention associated variants from massive publicly available transcriptome sequencing data

Many disease-associated genomic variants disrupt gene function through abnormal splicing. With the advancement of genomic medicine, identifying disease-associated splicing associated variants has become more important than ever. Most bioinformatics approaches to detect splicing associated variants require both genome and transcriptomic data. However, there are not many datasets where both of them are available. In this study, we developed a methodology to detect genomic variants that cause splicing changes (more specifically, intron retention), using transcriptome sequencing data alone. After demonstrating its high sensitivity and precision, we have applied it to 230,988 transcriptome sequencing data from the publicly available repository and identified 27,937 intron retention associated variants (IRAVs). In addition, by exploring positional relationships with variants registered in existing disease databases, we extracted 3,077 putative disease-associated IRAVs, which range from cancer drivers to variants linked with autosomal recessive disorders. The new in-silico screening framework proposed here provides a foundation for a platform that can automatically acquire medical knowledge making the most of massively accumulated publicly available sequencing data. Collections of IRAVs identified in this study are available through IRAVDB (https://iravdb.io/).

bioinformatics↗

bioRxiv2020

Precise characterization of somatic structural variations and mobile element insertions from paired long-read sequencing data with nanomonsv

We present our novel software, nanomonsv, for detecting somatic structural variations (SVs) using tumor and matched control long-read sequencing data with a single-base resolution. The current version of nanomonsv includes two detection modules, Canonical SV module, and Single breakend SV module. Using paired long-read sequencing data from three cancer and their matched lymphoblastoid lines, we demonstrate that Canonical SV module can identify somatic SVs that can be captured by short-read technologies with higher precision and recall than existing methods. In addition, we have developed a workflow to classify mobile element insertions while elucidating their in-depth properties, such as 5 truncations, internal inversions, as well as source sites for 3 transductions. Furthermore, Single breakend SV module enables the detection of complex SVs that can only be identified by long-reads, such as SVs involving highly-repetitive centromeric sequences, and LINE1- and virus-mediated rearrangements. In summary, our approaches applied to cancer long-read sequencing data can reveal various features of somatic SVs and will lead to a better understanding of mutational processes and functional consequences of somatic SVs.

bioinformatics↗

bioRxiv2019

SF3B1ness score: screening SF3B1 mutation status from over 60,000 transcriptomes based on a machine learning approach

In precision oncology, genomic evidence is used to determine the optimal treatment for each patient. However, identification of somatic mutations from genome sequencing data is often technically difficult and functional significance of somatic mutations is inconclusive in many cases. In this paper, to seek for an alternative approach, we tackle the problem of predicting functional mutations from transcriptome sequencing data. Focusing on SF3B1, a key splicing factor gene, we develop SF3B1ness score for classifying functional mutation status using a combination of Naive Bayes classifier and zero-inflated beta-binomial modeling (R package is available at (https://github.com/friend1WS/SF3B1ness). Using 8,992 TCGA exome and RNA sequencing data for evaluation, we show that the classifier based on SF3B1ness score is able to (1) attain very high precision (>93%) and sensitivity (>95%), (2) rescue several somatic mutations not identified by exome sequence analysis especially due to low variant allele frequencies, and (3) successfully measure functional importance for somatic mutation whose significance has been unknown. Furthermore, to demonstrate that the SF3B1ness score is highly robust and can be extensible to the cohorts outside training data, we performed a functional SF3B1 mutation screening on 51,577 additional transcriptome sequencing data. We have detected 135 samples with putative SF3B1 functional mutations including those that are rarely registered in the somatic mutation database (e.g., G664C, L747W, and R775G). Moreover, we could identify two cases with SF3B1 mutations from normal tissues, implying that SF3B1ness score can be used for detecting clonal hematopoiesis.

bioinformatics↗

bioRxiv2017

A framework for generating interactive reports for cancer genome analysis

SummaryWe introduce paplot, the software for generating dynamic reports that are frequently necessary in the post analytical phases of cancer genome studies. The \"interactive\" nature of the paplot-generated reports enables users to extract much richer information than that obtained from static graphs via most conventional visualization tools.\n\nAvailability and implementationThe python implementation for paplot (MIT license) is available at https://github.com/Genomon-Project/paplot. The documentation is at http://paplot-doc.readthedocs.io/en/latest/.\n\nContactyshira@hgc.jp

bioinformatics↗

bioRxiv2017

A comprehensive characterization of cis-acting splicing-associated variants in human cancer

Although many driver mutations are thought to promote carcinogenesis via abnormal splicing, the landscape of these splicing-associated variants (SAVs) remains unknown due to the complexity of splicing abnormalities. Here we developed a statistical framework to identify SAVs disrupting or newly creating splice site motifs and applied it to sequencing data from 8,976 samples across 31 cancer types. We constructed a catalog of 14,438 SAVs, approximately 50% of which consist of SAVs disrupting non-canonical splice sites (including the 3rd and 5th intronic bases of donor sites) or newly creating splice sites. Smoking-related signature substantially contributes to SAV generation. As many as 14.7% of samples harbor at least one SAVs in cancer-related genes, particularly in tumor suppressors. Importantly, in addition to previously reported intron retention, exon skipping or alternative splice site usage more frequently affected these genes. Our findings delineate a comprehensive portrait of SAVs, providing a basis for cancer precision medicine.

genomics↗