Biology subjects

Hasegawa, T.

Publications and source records attributed to Hasegawa, T..

29 records · Page 2Linked to original sources

bioRxiv2020

Canopy micrometeorology monitoring in diverse climates innovatively improves the evaluation heat-induced sterility of rice under climate change

This study is the first and unique of open-field studies to assess the determination process of heat-induced spikelet sterility (HISS) of rice by using the same variety and the same monitoring system, MINCER (Micrometeorological Instrument for Near Canopy Environment of Rice), covering the major-rice growing regions from Sub-Saharan Africa, South, Southeast, and East Asia, and USA. Applying the observation data from the monitoring network, MINCERnet, to the canopy heat balance model, IM2PACT, it was quantitatively corroborated in open-field conditions worldwide that the canopy and panicle transpiration and their evaporative cooling effect played a great role on the micrometeorological gap between the ambient air temperature and the panicle temperature, and that the sterility rate due to HISS in open-fields can be evaluated accurately in diverse climates by the mean panicle temperature at flowering hours in the flowering period. The heat balance structure suggested that the risk of HISS should be higher in high humidity climates rather than in dry climates also in the future, which lead to the importance of the humidity accuracy as well as of the air temperature in climate scenarios and their spatial downscaling for future prediction of rice heat stress and production. Applying the heat-tolerant variety was suggested to be able to keep the sterility due to HISS low in all climates. It is needed of the approach using the panicle temperature as indicator of HISS by intervening sub-model and/or monitoring of micrometeorology inside the canopy to reduce uncertainties in future rice yield prediction under various adaptation measures.

plant biology↗

bioRxiv2020

OsNLP4 is required for nitrate assimilation gene expressions and nitrate-dependent growth in rice

In plants, nitrate is important nutrient and signaling molecule that modulates the expression of many genes and regulates growth. In paddy grown rice, nitrogen is mostly supplied in the form of ammonium, but nitrate also shares substantial portion of available nitrogen. A number of nitrogen transporters and nitrate assimilation enzymes have been identified and functionally characterized. However, little is known about the nitrate sensor system and regulatory mechanisms of these nitrate related genes. In recent years, NIN-like proteins (NLPs) have been described as key transcription factors of nitrogen responses in Arabidopsis thaliana. But the functions of OsNLPs in rice are still elusive. Here we report the characterization of OsNLP4 to reveal its function in rice. Growths of OsNLP4 knockout mutants were reduced under the nitrate supply, but not under ammonium supply. The mRNA accumulation of genes involved in nitrate assimilation were declined significantly and nitrate uptake rate and nitrate reductase activity were also impaired in the mutants. Using rice protoplast transient expression system, OsNLP4-GFP fusion was localized to nucleus irrespective of nitrate conditions. OsNLP4 was also required for normal yield under paddy field conditions. We propose the OsNLP4 is essential for regulation of genes involved in nitrate assimilation and nitrate-dependent growth in rice. One sentence summaryThe osnlp4 mutants exhibit abnormal nitrate response and poor growth under nitrate supply and in paddy field conditions.

plant biology↗

bioRxiv2019

A multifunctional R package for identification of tumor-specific neoantigens

It is known that some mutated peptides, such as those resulting from missense mutations and frameshift insertions, can bind to the major histocompatibility complex and be presented to antitumor T-cells on the surface of a tumor cell. These peptides are termed neoantigen and it is important to understand this process for cancer immunotherapy. Here, we introduce an R package that can predict a list of potential neoantigens from a variety of mutations, which include not only somatic point mutations but insertions, deletions, and structural variants. Beyond the existing applications, this package is capable of attaching and reflecting several additional information, e.g., wild-type binding capability, allele specific RNA expression levels, single nucleotide polymorphism information, and combinations of mutations to filter out infeasible peptides as neoantigen. AvailabilityThe R package is available at http://github/hase62/Neoantimon.

bioinformatics↗

bioRxiv2019

A unified simulation model for understanding the diversity of cancer evolution

Because cancer evolution underlies the therapeutic difficulties of cancer, it is clinically important to understand the evolutionary dynamics of cancer. Thus far, a number of evolutionary processes have been proposed to be working in cancer evolution. However, there exists no simulation model that can describe the different evolutionary processes in a unified manner. In this study, we constructed a unified simulation model for describing the different evolutionary processes and performed sensitivity analysis on the model to determine the conditions in which cancer growth is driven by each of the different evolutionary processes. Our sensitivity analysis has successfully provided a series of novel insights into the evolutionary dynamics of cancer. For example, we found that, while a high neutral mutation rate shapes neutral intratumor heterogeneity (ITH) characterized by a fractal-like pattern, a stem cell hierarchy can also contribute to shaping neutral ITH by apparently increasing the mutation rate. Although It has been reported that the evolutionary principle shaping ITH shifts from selection to accumulation of neutral mutations during colorectal tumorigenesis, our simulation revealed the possibility that this evolutionary shift is triggered by drastic evolutionary events that occur in a a short time and confer a marked fitness increase on one or a few cells. This result helps us understand that each process works not separately but simultaneously and continuously as a series of phases of cancer evolution. Collectively, this study serves as a basis to understand in greater depth the diversity of cancer evolution.

cancer biology↗

bioRxiv2019

Decreased Activity of the Ghrhr and Gh Promoters Causes Dominantly Inherited GH Deficiency

Isolated growth hormone deficiency type II (IGHD2) is mainly caused by heterozygous splice-site mutations in intron 3 of the GH1 gene. A dominant negative effect of the mutant growth hormone (GH) lacking exon 3 on wild-type GH secretion has been proposed; however, the molecular mechanisms involved are elusive. To uncover the molecular systems underlying GH deficiency in IGHD2, we established IGHD2 model mice, which carry both wild-type and mutant copies of the human GH1 gene, replacing each of the endogenous mouse Gh loci. Our IGHD2 model mice exhibited growth retardation associated with intact cellular architecture and mildly activated ER stress in the pituitary gland, caused by decreases in the growth hormone releasing hormone receptor (Ghrhr) and Gh gene promoter activities. Decreases in Ghrhr and Gh promoter activities were likely caused by reduced levels of nuclear CREB3L2, which was demonstrated to stimulate the activity of the Ghrhr and Gh promoters. This is the first in vivo study revealing a novel molecular mechanism of GH deficiency in IGHD2, representing a new paradigm, differing from widely accepted models.

genetics↗

bioRxiv2019

Sensitivity analysis of agent-based simulation utilizing massively parallel computation and interactive data visualization

An essential step in the analysis of agent-based simulation is sensitivity analysis, which namely examines the dependency of parameter values on simulation results. Although a number of approaches have been proposed for sensitivity analysis, they still have limitations in exhaustivity and interpretability. In this study, we propose a novel methodology for sensitivity analysis of agent-based simulation, MASSIVE (Massively parallel Agent-based Simulations and Subsequent Interactive Visualization-based Exploration). MASSIVE takes a unique paradigm, which is completely different from those of sensitivity analysis methods developed so far, By combining massively parallel computation and interactive data visualization, MASSIVE enables us to inspect a broad parameter space intuitively. We demonstrated the utility of MASSIVE by its application to cancer evolution simulation, which successfully identified conditions that generate heterogeneous tumors. We believe that our approach would be a de facto standard for sensitivity analysis of agent-based simulation in an era of ever-growing computational technology. All the result form our MASSIVE analysis is available at https://www.hgc.jp/~niiyan/massive.

bioinformatics↗

bioRxiv2018

Comprehensive Analysis of Indels in Whole-genome Microsatellite Regions and Microsatellite Instability across 21 Cancer Types

Microsatellites are repeats of 1-6bp units and [~]10 million microsatellites have been identified across the human genome. Microsatellites are vulnerable to DNA mismatch errors, and have thus been used to detect cancers with mismatch repair deficiency. To reveal the mutational landscape of the microsatellite repeat regions at the genome level, we analyzed approximately 20.1 billion microsatellites in 2,717 whole genomes of pan-cancer samples across 21 tissue types. Firstly, we developed a new insertion and deletion caller (MIMcall) that takes into consideration the error patterns of different types of microsatellites. Among the 2,717 pan-cancer samples, our analysis identified 31 samples, including colorectal, uterus, and stomach cancers, with higher microsatellite mutation rate ([≥] 0.03), which we defined as microsatellite instability (MSI) cancers in genome-wide level. Next, we found 20 highly-mutated microsatellites that can be used to detect MSI cancers with high sensitivity. Third, we found that replication timing and DNA shape were significantly associated with mutation rates of the microsatellites. Analysis of germline variation of the microsatellites suggested that the amount of germline variations and somatic mutation rates were correlated. Lastly, analysis of mutations in mismatch repair genes showed that somatic SNVs and short indels had larger functional impact than germline mutations and structural variations. Our analysis provides a comprehensive picture of mutations in the microsatellite regions, and reveals possible causes of mutations, as well as provides a useful marker set for MSI detection.

cancer biology↗

bioRxiv2018

A protocol for an intercomparison of biodiversity and ecosystem services models using harmonized land-use and climate scenarios

Abstract.To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land use and climate change on biodiversity and ecosystem services (i.e. natures contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenarios selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem service models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modelling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modelling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.

ecology↗

bioRxiv2018

Immuno-genomic PanCancer Landscape Reveals Diverse Immune Escape Mechanisms and Immuno-Editing Histories

Immune reactions in the tumor micro-environment are one of the cancer hallmarks and emerging immune therapies have been proven effective in many types of cancer. To investigate cancer genome-immune interactions and the role of immuno-editing or immune escape mechanisms in cancer development, we analyzed 2,834 whole genomes and RNA-seq datasets across 31 distinct tumor types from the PanCancer Analysis of Whole Genomes (PCAWG) project with respect to key immuno-genomic aspects. We show that selective copy number changes in immune-related genes could contribute to immune escape. Furthermore, we developed an index of the immuno-editing history of each tumor sample based on the information of mutations in exonic regions and pseudogenes. Our immuno-genomic analyses of pan-cancer analyses have the potential to identify a subset of tumors with immunogenicity and diverse background or intrinsic pathways associated with their immune status and immuno-editing history.

genomics↗

bioRxiv2017

Systematic identification of cancer-specific MHC-binding peptides with RAVEN

Immunotherapy can revolutionize anti-cancer therapy if specific targets are available. Recurrent somatic mutations in the exome can create highly specific neo-antigens. However, especially pediatric cancers are oligo-mutated and hardly exhibit recurrent neo-antigens. Yet, immunogenic peptides encoded by cancer-specific genes (CSGs), which are virtually not expressed in normal tissues, may enable a targeted immunotherapy of such cancers. Here, we describe an algorithm and provide a user-friendly software named RAVEN (Rich Analysis of Variable gene Expressions in Numerous tissues), which automatizes the systematic and fast identification of CSG-encoded peptides highly affine to Major Histocompatibility Complexes (MHC) starting from publicly available gene expression data. We applied RAVEN to a dataset assembled from more than 2,700 simultaneously normalized gene expression microarrays comprising 50 tumor entities, with a focus on sarcomas and pediatric cancers, and 71 normal tissue types. RAVEN performed a transcriptome-wide scan in each cancer entity for gender-specific CSGs. As a proof-of-concept we identified several established CSGs, but also many novel candidates potentially suitable for targeting multiple cancer types. The specific expression of the most promising CSGs was validated by qRT-PCR in cancer cell lines and by immunohistochemistry in a comprehensive tissue-microarray comprising 412 samples. Subsequently, RAVEN identified likely immunogenic peptides encoded by these CSGs by predicting the affinity to MHCs. Putative highly affine peptides were automatically crosschecked with the UniProt protein-database to exclude sequence identity with abundantly expressed proteins. The predicted affinity of selected peptides was validated in T2-cell peptide-binding assays in which many showed similar kinetics to a very immunogenic influenza control peptide.\n\nCollectively, we provide a comprehensive, exquisitely curated and validated catalogue of cancer-specific and highly MHC-affine peptides across 50 cancer entities. In addition, we developed an intuitive and freely available software to easily apply our algorithm to any gene expression dataset (https://github.com/JSGerke/RAVENsoftware). We anticipate that our peptide libraries and software constitute a rich resource to accelerate the development of novel immunotherapies.

immunology↗

bioRxiv2017

Spatial and temporal translocation of PKCα in single endothelial cell in response to focal mechanical stimulus

We observed the kinetics of protein kinase C (PKC) and the intracellular Ca2+ wave in endothelial cells (ECs) in response to microscopic mechanical stress to investigate the effect of mechanical stress on PKC translocation. The results show that a focal mechanical stimulus induced biphasic and directional PKC translocation; PKC initially translocated toward distinct spots near or at the membrane and then accumulated at the stimulus point. The low initial translocation occurred simultaneously in parallel with the increase in Ca2+. Initial translocation was inhibited in spite of Ca2+ increase when the diacylglycerol (DAG) binding domain of PKC was inhibited, suggesting that translocation requires intracellular Ca2+ increase and DAG. On the other hand, high secondary translocation was delayed, occurring after the Ca2+ wave; however, this secondary translocation occurred even when Ca2+ release from the endoplasmic reticulum was inhibited, while it did not occur when the mechanosensitive (MS) channel was inhibited. These results indicated that at least Ca2+ influx through MS channels is required. Our results support the implication of PKC in the Ca2+ signaling pathway in response to mechanical stress in ECs.\n\nSummary statementIn response to a focal mechanical stimulus, PKC in an endothelial cell was initially translocated toward distinct spots near or at the membrane and then accumulated at the stimulus point.

cell biology↗