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Search Results: 1 - 10 of 1309 matches for " Masaru Tomita "
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The GC Skew Index: A Measure of Genomic Compositional Asymmetry and the Degree of Replicational Selection
Kazuharu Arakawa,Masaru Tomita
Evolutionary Bioinformatics , 2007,
Abstract: Circular bacterial chromosomes have highly polarized nucleotide composition in the two replichores, and this genomic strand asymmetry can be visualized using GC skew graphs. Here we propose and discuss the GC skew index (GCSI) for the quantification of genomic compositional skew, which combines a normalized measure of fast Fourier transform to capture the shape of the skew graph and Euclidean distance between the two vertices in a cumulative skew graph to represent the degree of skew. We calculated GCSI for all available bacterial genomes, and GCSI correlated well with the visibility of GC skew. This novel index is useful for estimating confi dence levels for the prediction of replication origin and terminus by methods based on GC skew and for measuring the strength of replicational selection in a genome.
Selection Effects on the Positioning of Genes and Gene Structures from the Interplay of Replication and Transcription in Bacterial Genomes
Kazuharu Arakawa,Masaru Tomita
Evolutionary Bioinformatics , 2007,
Abstract: Bacterial chromosomes are partly shaped by the functional requirements for efficient replication, which lead to strand bias as commonly characterized by the excess of guanines over cytosines in the leading strand. Gene structures are also highly organized within bacterial genomes as a result of such functional constraints, displaying characteristic positioning and structuring along the genome. Here we analyze the gene structures in completely sequenced bacterial chromosomes to observe the positional constraints on gene orientation, length, and codon usage with regard to the positions of replication origin and terminus. Selection on these gene features is different in regions surrounding the terminus of replication from the rest of the genome, but the selection could be either positive or negative depending on the species, and these positional effects are partly attributed to the A-T enrichment near the terminus. Characteristic gene structuring relative to the position of replication origin and terminus is commonly observed among most bacterial species with circular chromosomes, and therefore we argue that the highly organized gene positioning as well as the strand bias should be considered for genomics studies of bacteria.
Quantifying periodicity in omics data
Masaru Tomita,Douglas B. Murray
Frontiers in Cell and Developmental Biology , 2014, DOI: 10.3389/fcell.2014.00040
Abstract: Oscillations play a significant role in biological systems, with many examples in the fast, ultradian, circadian, circalunar, and yearly time domains. However, determining periodicity in such data can be problematic. There are a number of computational methods to identify the periodic components in large datasets, such as signal-to-noise based Fourier decomposition, Fisher's g-test and autocorrelation. However, the available methods assume a sinusoidal model and do not attempt to quantify the waveform shape and the presence of multiple periodicities, which provide vital clues in determining the underlying dynamics. Here, we developed a Fourier based measure that generates a de-noised waveform from multiple significant frequencies. This waveform is then correlated with the raw data from the respiratory oscillation found in yeast, to provide oscillation statistics including waveform metrics and multi-periods. The method is compared and contrasted to commonly used statistics. Moreover, we show the utility of the program in the analysis of noisy datasets and other high-throughput analyses, such as metabolomics and flow cytometry, respectively.
Predicting the Kinetic Properties Associated with Redox Imbalance after Oxidative Crisis in G6PD-Deficient Erythrocytes: A Simulation Study
Hanae Shimo,Taiko Nishino,Masaru Tomita
Advances in Hematology , 2011, DOI: 10.1155/2011/398945
Abstract: It is well known that G6PD-deficient individuals are highly susceptible to oxidative stress. However, the differences in the degree of metabolic alterations among patients during an oxidative crisis have not been extensively studied. In this study, we applied mathematical modeling to assess the metabolic changes in erythrocytes of various G6PD-deficient patients during hydrogen peroxide- (H2O2-) induced perturbation and predict the kinetic properties that elicit redox imbalance after exposure to an oxidative agent. Simulation results showed a discrepancy in the ability to restore regular metabolite levels and redox homeostasis among patients. Two trends were observed in the response of redox status (GSH/GSSG) to oxidative stress, a mild decrease associated with slow recovery and a drastic decline associated with rapid recovery. The former was concluded to apply to patients with severe clinical symptoms. Low and high of G6PD were shown to be kinetic properties that enhance consequent redox imbalance. 1. Introduction Glucose-6-phosphate dehydrogenase (G6PD) deficiency, an X-chromosome linked genetic disorder, is the most prevalent mutation in humans affecting more than 400 million people worldwide [1–4]. It is characterized by the decreased activity of the G6PD enzyme, which is the central factor of the antioxidant defense system in erythrocytes (or RBCs). The enzyme is responsible for maintaining the high levels of reduced glutathione (GSH) and nicotine adenine dinucleotide phosphate (NADPH) that protect the cell from oxidative damage caused by harmful reactive oxygen species (ROS). As RBCs are unable to generate NADPH through other pathways [5, 6], G6PD-deficient RBCs lack the ability to tolerate excessive amounts of oxidative stress [7–9]. The most common clinical manifestation associated with G6PD deficiency is hemolytic anemia, which is generally triggered by the intake of oxidative drugs or foods [5, 10]. At times, the defect can result in complications such as kidney failure, severe neonatal jaundice, gallstones, and may require blood transfusion [2, 9–11]. The clinical consequences of drug-induced G6PD deficiency-related hemolysis depend on several factors including the kinetic properties of the G6PD variant. Commonly the diagnosis of patients is performed by a rapid fluorescent spot test of NADPH generation [12, 13] and a quantitative spectrophotometric assay of G6PD activity [10, 14]. Although these tests provide us with some perspective on the degree of severity of a patient’s clinical symptoms, they are based on measurements of G6PD-specific
Indeterminacy of Reverse Engineering of Gene Regulatory Networks: The Curse of Gene Elasticity
Arun Krishnan, Alessandro Giuliani, Masaru Tomita
PLOS ONE , 2007, DOI: 10.1371/journal.pone.0000562
Abstract: Background Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. A number of reverse engineering approaches have been developed to help uncover the regulatory networks giving rise to the observed gene expression profiles. However, this is an overspecified problem due to the fact that more than one genotype (network wiring) can give rise to the same phenotype. We refer to this phenomenon as “gene elasticity.” In this work, we study the effect of this particular problem on the pure, data-driven inference of gene regulatory networks. Methodology We simulated a four-gene network in order to produce “data” (protein levels) that we use in lieu of real experimental data. We then optimized the network connections between the four genes with a view to obtain the original network that gave rise to the data. We did this for two different cases: one in which only the network connections were optimized and the other in which both the network connections as well as the kinetic parameters (given as reaction probabilities in our case) were estimated. We observed that multiple genotypes gave rise to very similar protein levels. Statistical experimentation indicates that it is impossible to differentiate between the different networks on the basis of both equilibrium as well as dynamic data. Conclusions We show explicitly that reverse engineering of GRNs from pure expression data is an indeterminate problem. Our results suggest the unsuitability of an inferential, purely data-driven approach for the reverse engineering transcriptional networks in the case of gene regulatory networks displaying a certain level of complexity.
Validation of Bacterial Replication Termination Models Using Simulation of Genomic Mutations
Nobuaki Kono, Kazuharu Arakawa, Masaru Tomita
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0034526
Abstract: In bacterial circular chromosomes and most plasmids, the replication is known to be terminated when either of the following occurs: the forks progressing in opposite directions meet at the distal end of the chromosome or the replication forks become trapped by Tus proteins bound to Ter sites. Most bacterial genomes have various polarities in their genomic structures. The most notable feature is polar genomic compositional asymmetry of the bases G and C in the leading and lagging strands, called GC skew. This asymmetry is caused by replication-associated mutation bias, and this “footprint" of the replication machinery suggests that, in contrast to the two known mechanisms, replication termination occurs near the chromosome dimer resolution site dif. To understand this difference between the known replication machinery and genomic compositional bias, we undertook a simulation study of genomic mutations, and we report here how different replication termination models contribute to the generation of replication-related genomic compositional asymmetry. Contrary to naive expectations, our results show that a single finite termination site at dif or at the GC skew shift point is not sufficient to reconstruct the genomic compositional bias as observed in published sequences. The results also show that the known replication mechanisms are sufficient to explain the position of the GC skew shift point.
OryzaPG-DB: Rice Proteome Database based on Shotgun Proteogenomics
Mohamed Helmy, Masaru Tomita, Yasushi Ishihama
BMC Plant Biology , 2011, DOI: 10.1186/1471-2229-11-63
Abstract: Here, we present OryzaPG-DB, a rice proteome database based on shotgun proteogenomics, which incorporates the genomic features of experimental shotgun proteomics data. This version of the database was created from the results of 27 nanoLC-MS/MS runs on a hybrid ion trap-orbitrap mass spectrometer, which offers high accuracy for analyzing tryptic digests from undifferentiated cultured rice cells. Peptides were identified by searching the product ion spectra against the protein, cDNA, transcript and genome databases from Michigan State University, and were mapped to the rice genome. Approximately 3200 genes were covered by these peptides and 40 of them contained novel genomic features. Users can search, download or navigate the database per chromosome, gene, protein, cDNA or transcript and download the updated annotations in standard GFF3 format, with visualization in PNG format. In addition, the database scheme of OryzaPG was designed to be generic and can be reused to host similar proteogenomic information for other species. OryzaPG is the first proteogenomics-based database of the rice proteome, providing peptide-based expression profiles, together with the corresponding genomic origin, including the annotation of novelty for each peptide.The OryzaPG database was constructed and is freely available at http://oryzapg.iab.keio.ac.jp/ webcite.Among high-throughput experimental methods, genome sequencing represents a turning point in the understanding of biological systems. Nevertheless, the biological significance of the sequenced genome cannot be understood unless the protein-coding genes and their products are accurately identified. Thus, genome annotation has become major issue [1-3]. Genome annotation is the process of gene structure and function determination, and it usually takes place after genome sequencing and before data deposition in a database or databank [2,4,5].In typical genome annotation work, experimental and computational methods are integrated to an
GeNESiS: gene network evolution simulation software
Anton Kratz, Masaru Tomita, Arun Krishnan
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-541
Abstract: In this work, we present a parallel software package, GeNESiS for the modeling and simulation of the evolution of gene regulatory networks (GRNs). The software models the process of gene regulation through a combination of finite-state and stochastic models. The evolution of GRNs is then simulated by means of a genetic algorithm with the network connections represented as binary strings. The software allows users to simulate the evolution under varying selective pressures and starting conditions. We believe that the software provides a way for researchers to understand the evolutionary behavior of populations of GRNs.We believe that GeNESiS will serve as a useful tool for scientists interested in understanding the evolution of gene regulatory networks under a range of different conditions and selective pressures. Such modeling efforts can lead to a greater understanding of the network characteristics of GRNs.While a lot of interest has been focused on the modeling and simulation of Gene Regulatory Networks (GRNs) in recent years, the evolutionary mechanisms that give rise to GRNs in the first place are still largely unknown. There have been efforts at understanding particular aspects of evolution, such as the correlation between development, evolution and robustness or canalization of the network ([1,2]). Studies on the evolution of GRNs have tended to focus on certain a priori assumptions about the nature of the evolutionary force such as stabilizing selection ([3-6]) or the use of more abstract ([7]) and analytical ([8]) models. Siegal et al. [1] showed that the developmental process constrains the genetic system to produce robustness even in the absence of a selection towards optimum.In an earlier work [9], we developed a framework to analyze the effect of objective functions, input types and starting populations on the evolution of GRNs with a specific emphasis on the robustness of evolved GRNs. We observed that robustness evolves along with the networks as an e
Measure of synonymous codon usage diversity among genes in bacteria
Haruo Suzuki, Rintaro Saito, Masaru Tomita
BMC Bioinformatics , 2009, DOI: 10.1186/1471-2105-10-167
Abstract: The application of Dmean to 268 bacterial genomes shows that in bacteria with extremely biased genomic G+C compositions there is little diversity in synonymous codon usage among genes. Furthermore, our findings contradict previous reports. For example, a low level of diversity in codon usage among genes has been reported for Helicobacter pylori, but based on Dmean, the diversity level of this species is higher than those of more than half of bacteria tested here. The discrepancies between our findings and previous reports are probably due to differences in the methods used for measuring codon usage diversity.We recommend that Dmean be used to measure the diversity level of codon usage among genes. This measure can be applied to other compositional features such as amino acid usage and dinucleotide relative abundance as a genomic signature.Most amino acids can be encoded by more than one codon (i.e., a triplet of nucleotides); such codons are described as being synonymous, and usually differ by one nucleotide in the third position. In most bacteria, alternative synonymous codons are not used with equal frequencies. Grantham et al. [1] showed that genes from same species often show similar patterns of codon usage, and proposed the 'genome hypothesis' that there exists a species-specific pattern of codon usage. Then, it was shown that in many organisms there are also considerable differences in codon usage among genes within a genome [2]. Previous analyses of codon usage diversity in bacteria have mostly focused on individual genomes, with no quantitative attempt to compare the diversity levels among different genomes. For comparative genomic analysis, it is desirable to quantify the level of codon usage diversity among genes in such a way that the estimates could be compared among genomes.Different factors have been proposed to explain the preferential usage of a subset of synonymous codons, including biased mutation pressure (genome-wide mutational bias toward G/C or
Variation in the Correlation of G + C Composition with Synonymous Codon Usage Bias among Bacteria
Haruo Suzuki, Rintaro Saito, Masaru Tomita
EURASIP Journal on Bioinformatics and Systems Biology , 2007, DOI: 10.1155/2007/61374
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