Biology subjects

Kudo, H.

Publications and source records attributed to Kudo, H..

4 recordsLinked to original sources

bioRxiv2020

Cryptic promoter activation occurs by at least two different mechanisms in the Arabidopsis genome

In gene-trap screening of plant genomes, promoterless reporter constructs are often expressed without trapping of annotated gene promoters. The molecular basis of this phenomenon, which has been interpreted as the trapping of cryptic promoters, is poorly understood. In this study, using Arabidopsis gene-trap lines in which a firefly luciferase (LUC) open reading frame (ORF) was expressed from intergenic regions, we found that cryptic promoter activation occurs by at least two different mechanisms: one is the capturing of pre-existing promoter-like chromatin marked by H3K4me3 and H2A.Z, and the other is the entirely new formation of promoter chromatin near the 5 end of the inserted LUC ORF. To discriminate between these, we denoted the former mechanism as "cryptic promoter capturing", and the latter one as "promoter de novo origination". The latter finding raises a question as to how inserted LUC ORF sequence is involved in this phenomenon. To examine this, we performed a model experiment with chimeric LUC genes in transgenic plants. Using Arabidopsis psaH1 promoter-LUC constructs, we found that the functional core promoter region, where transcription start sites (TSS) occur, cannot simply be determined by the upstream nor core promoter sequences; rather, its positioning proximal to the inserted LUC ORF sequence was more critical. This result suggests that the insertion of the LUC ORF sequence alters the local distribution of the TSS in the plant genome. The possible impact of the two types of cryptic promoter activation mechanisms on plant genome evolution and endosymbiotic gene transfer is discussed.

evolutionary biology↗

bioRxiv2020

Japonica Array NEO with increased genome-wide coverage and abundant disease risk SNPs

BackgroundIncreasing the power of genome-wide association studies in diverse populations is important for understanding the genetic determinants of disease risks, and large-scale genotype data are collected by genome cohort and biobank projects all over the world. In particular, ethnic-specific SNP arrays are becoming more important because the use of universal SNP arrays has some limitations in terms of cost-effectiveness and throughput. As part of the Tohoku Medical Megabank Project, which integrates prospective genome cohorts into a biobank, we have been developing a series of Japonica Arrays for genotyping participants based on reference panels constructed from whole-genome sequence data of the Japanese population. ResultsWe designed a novel version of the SNP Array for the Japanese population, called Japonica Array NEO, comprising a total of 666,883 SNPs, including tag SNPs of autosomes and X chromosome with pseudoautosomal regions, SNPs of Y chromosome and mitochondria, and known disease risk SNPs. Among them, 654,246 tag SNPs were selected from an expanded reference panel of 3,552 Japanese using pairwise r2 of linkage disequilibrium measures. Moreover, 28,298 SNPs were included for the evaluation of previously identified disease risk SNPs from the literature and databases, and those present in the Japanese population were extracted using the reference panel. The imputation performance of Japonica Array NEO was assessed by genotyping 286 Japanese samples. We found that the imputation quality r2 and INFO score in the minor allele frequency bin >2.5%-5% were >0.9 and >0.8, respectively, and >12 million markers were imputed with an INFO score >0.8. After verification, Japonica Arrays were used to efficiently genotype cohort participants from the sample selection to perform a quality assessment of the raw data; approximately 130,000 genotyping data of >150,000 participants has already been obtained. ConclusionsJaponica Array NEO is a promising tool for genotyping the Japanese population with genome-wide coverage, contributing to the development of genetic risk scores for this population and further identifying disease risk alleles among individuals of East Asian ancestry.

genomics↗

bioRxiv2019

Stat2 loss disrupts damage signalling and is protective in acute pancreatitis

Severity of sterile inflammation, as seen in acute pancreatitis, is determined by damage-sensing receptors, signalling cascades and cytokine production. Stat2 is a type I interferon signalling mediator that also has interferon-independent roles in murine lipopolysaccharide-induced NF-{kappa}B-mediated sepsis. However its role in sterile inflammation is unknown. We hypothesised that Stat2 determines severity of non-infective inflammation in the pancreas.\n\nWild type (WT) and Stat2-/- mice were injected intraperitoneally with cerulein or L-arginine. Specific cytokine-blocking antibodies were used in some experiments. Pancreata and blood were harvested 1h and 24h after the final dose of cerulein and up to 96h post L-arginine. Whole-tissue phosphoproteomic changes were assessed using label-free mass spectrometry. Tissue-specific Stat2 effects were studied in WT/Stat2-/- bone-marrow chimera and using Cre-lox recombination to delete Stat2 in pancreatic and duodenal homeobox 1(Pdx1)-expressing cells.\n\nStat2-/- mice were protected from cerulein- and L-arginine-induced pancreatitis. Protection was independent of type I interferon signalling. Stat2-/- mice had lower cytokine levels including TNF and IL-10 and reduced NF-kB nuclear localisation in pancreatic tissue compared to WT. Inhibition of TNF improved (inhibition of IL-10 worsened) cerulein-induced pancreatitis in WT but not Stat2-/- mice. Phosphoproteomics showed down-regulation of mitogen-activated protein kinase (MAPK) mediators but accumulation of Ser412-phosphorylated Tak1. Stat2 deletion in Pdx1-expressing acinar cells (Stat2flox/Pdx1-cre) reduced pancreatic TNF expression, but not histological injury or serum amylase. WT/Stat2-/- bone-marrow chimera were protected from pancreatitis irrespective of host or recipient genotype.\n\nStat2 loss results in disrupted signalling in pancreatitis, upstream of NF-{kappa}B in non-acinar and/or bone marrow derived cells.

immunology↗

bioRxiv2017

Network analysis of mass spectrometry imaging data from colorectal cancer identifies key metabolites common to metastatic development.

A deeper understanding of inter-tumor and intra-tumor heterogeneity is a critical factor for the advancement of next generation strategies against cancer. The heterogeneous morphology exhibited by solid tumors is mirrored by their metabolic heterogeneity. Defining the basic biological mechanisms that underlie tumor cell variability will be fundamental to the development of personalized cancer treatments. Variability in the molecular signatures found in local regions of cancer tissues can be captured through an untargeted analysis of their metabolic constituents. Here we demonstrate that DESI mass spectrometry imaging (MSI) combined with network analysis can provide detailed insight into the metabolic heterogeneity of colorectal cancer (CRC). We show that network modules capture signatures which differentiate tumor metabolism in the core and in the surrounding region. Moreover, module preservation analysis of network modules between patients with and without metastatic recurrence explains the inter-subject metabolic differences associated with diverse clinical outcomes such as metastatic recurrence.\n\nSignificanceNetwork analysis of DESI-MSI data from CRC human tissue reveals clinically relevant co-expression ion patterns associated with metastatic susceptibility. This delineates a more complex picture of tumor heterogeneity than conventional hard segmentation algorithms. Using tissue sections from central regions and at a distance from the tumor center, ion co-expression patterns reveal common features among patients who developed metastases (up of > 5 years) not preserved in patients who did not develop metastases. This offers insight into the nature of the complex molecular interactions associated with cancer recurrence. Presently, predicting CRC relapse is challenging, and histopathologically like-for-like cancers frequently manifest widely varying metastatic tendencies. Thus, the methodology introduced here more robustly defines the risk of metastases based on tumor biochemical heterogeneity.\n\nAuthor contributionsP.I., Z.T., R.C.G.: designed the study, developed the workflow, analyzed the data, interpreted the results, wrote the paper; N.S. collected the MS, performed the H...E staining, wrote the paper; L.D.: interpreted the results, wrote the paper; A.M.: collected the MS; A.S.: histological assessment; L.P.: collected the tissue specimens and clinical metadata; A.D.: collected the MS; H.K.: performed the H...E staining; R.M.: collected the tissue specimens and clinical metadata. R.G.: histological assessment; J.K.N: designed the study, edited the paper.

cancer biology↗