Authorship：Corresponding author   Publishing type：Research paper (scientific journal)   Publisher：Public Library of Science (PLoS)  

Among mutations that occur in SARS-CoV-2, efficient identification of mutations advantageous for viral replication and transmission is important to characterize and defeat this rampant virus. Mutations rapidly expanding frequency in a viral population are candidates for advantageous mutations, but neutral mutations hitchhiking with advantageous mutations are also likely to be included. To distinguish these, we focus on mutations that appear to occur independently in different lineages and expand in frequency in a convergent evolutionary manner. Batch-learning SOM (BLSOM) can separate SARS-CoV-2 genome sequences according by lineage from only providing the oligonucleotide composition. Focusing on remarkably expanding 20-mers, each of which is only represented by one copy in the viral genome, allows us to correlate the expanding 20-mers to mutations. Using visualization functions in BLSOM, we can efficiently identify mutations that have expanded remarkably both in the Omicron lineage, which is phylogenetically distinct from other lineages, and in other lineages. Most of these mutations involved changes in amino acids, but there were a few that did not, such as an intergenic mutation.

DOI： 10.1371/journal.pone.0273860

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Language：English   Publishing type：Research paper (scientific journal)  

BACKGROUND: Unsupervised AI (artificial intelligence) can obtain novel knowledge from big data without particular models or prior knowledge and is highly desirable for unveiling hidden features in big data. SARS-CoV-2 poses a serious threat to public health and one important issue in characterizing this fast-evolving virus is to elucidate various aspects of their genome sequence changes. We previously established unsupervised AI, a BLSOM (batch-learning SOM), which can analyze five million genomic sequences simultaneously. The present study applied the BLSOM to the oligonucleotide compositions of forty thousand SARS-CoV-2 genomes. RESULTS: While only the oligonucleotide composition was given, the obtained clusters of genomes corresponded primarily to known main clades and internal divisions in the main clades. Since the BLSOM is explainable AI, it reveals which features of the oligonucleotide composition are responsible for clade clustering. Additionally, BLSOM also provided information concerning the special genomic region possibly undergoing RNA modifications. CONCLUSIONS: The BLSOM has powerful image display capabilities and enables efficient knowledge discovery about viral evolutionary processes, and it can complement phylogenetic methods based on sequence alignment.

DOI： 10.1186/s12866-022-02484-3

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Language：English   Publishing type：Research paper (scientific journal)  

We aimed to analyze the situation of the first two epidemic waves in Myanmar using the publicly available daily situation of COVID-19 and whole-genome sequencing data of SARS-CoV-2. From March 23 to December 31, 2020, there were 33,917 confirmed cases and 741 deaths in Myanmar (case fatality rate of 2.18%). The first wave in Myanmar from March to July was linked to overseas travel, and then a second wave started from Rakhine State, a western border state, leading to the second wave spreading countrywide in Myanmar from August to December 2020. The estimated effective reproductive number (Rt) nationwide reached 6-8 at the beginning of each wave and gradually decreased as the epidemic spread to the community. The whole-genome analysis of 10 Myanmar SARS-CoV-2 strains together with 31 previously registered strains showed that the first wave was caused by GISAID clade O or PANGOLIN lineage B.6 and the second wave was changed to clade GH or lineage B.1.36.16 with a close genetic relationship with other South Asian strains. Constant monitoring of epidemiological situations combined with SARS-CoV-2 genome analysis is important for adjusting public health measures to mitigate the community transmissions of COVID-19.

DOI： 10.3390/v14020259

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Authorship：Corresponding author   Language：English   Publishing type：Research paper (scientific journal)  

In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: an unsupervised AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4-6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers that appeared after the epidemic started could be connected to mutations, and the BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explain BLSOMs for various topics, such as the tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explain BLSOMs for various eukaryotes, including fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found enrichments in transcription factor-binding sequences in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) could be separated according to their corresponding amino acid.

DOI： 10.1266/ggs.21-00025

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Authorship：Lead author,　Corresponding author   Publishing type：Research paper (scientific journal)   Publisher：Ubiquity Press, Ltd.  

DOI： 10.5334/dsj-2021-029

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Language：English   Publishing type：Research paper (scientific journal)  

BACKGROUND: When a virus that has grown in a nonhuman host starts an epidemic in the human population, human cells may not provide growth conditions ideal for the virus. Therefore, the invasion of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which is usually prevalent in the bat population, into the human population is thought to have necessitated changes in the viral genome for efficient growth in the new environment. In the present study, to understand host-dependent changes in coronavirus genomes, we focused on the mono- and oligonucleotide compositions of SARS-CoV-2 genomes and investigated how these compositions changed time-dependently in the human cellular environment. We also compared the oligonucleotide compositions of SARS-CoV-2 and other coronaviruses prevalent in humans or bats to investigate the causes of changes in the host environment. RESULTS: Time-series analyses of changes in the nucleotide compositions of SARS-CoV-2 genomes revealed a group of mono- and oligonucleotides whose compositions changed in a common direction for all clades, even though viruses belonging to different clades should evolve independently. Interestingly, the compositions of these oligonucleotides changed towards those of coronaviruses that have been prevalent in humans for a long period and away from those of bat coronaviruses. CONCLUSIONS: Clade-independent, time-dependent changes are thought to have biological significance and should relate to viral adaptation to a new host environment, providing important clues for understanding viral host adaptation mechanisms.

DOI： 10.1186/s12866-021-02158-6

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Language：English   Publishing type：Research paper (scientific journal)  

Tick-borne flaviviruses (TBFVs) infect mammalian hosts through tick bites and can cause various serious illnesses, such as encephalitis and hemorrhagic fevers, both in humans and animals. Despite their importance to public health, there is limited epidemiological information on TBFV infection in Africa. Herein, we report that a novel flavivirus, Mpulungu flavivirus (MPFV), was discovered in a Rhipicephalus muhsamae tick in Zambia. MPFV was found to be genetically related to Ngoye virus detected in ticks in Senegal, and these viruses formed a unique lineage in the genus Flavivirus. Analyses of dinucleotide contents of flaviviruses indicated that MPFV was similar to those of other TBFVs with a typical vertebrate genome signature, suggesting that MPFV may infect vertebrate hosts. Bioinformatic analyses of the secondary structures in the 3'-untranslated regions (UTRs) revealed that MPFV exhibited unique exoribonuclease-resistant RNA (xrRNA) structures. Utilizing biochemical approaches, we clarified that two xrRNA structures of MPFV in the 3'-UTR could prevent exoribonuclease activity. In summary, our findings provide new information regarding the geographical distribution of TBFV and xrRNA structures in the 3'-UTR of flaviviruses.

DOI： 10.1038/s41598-021-84365-9

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The coronavirus disease 2019 (COVID-19) has caused a serious disease burden and poses a tremendous public health challenge worldwide. Here, we report a comprehensive epidemiological and genomic analysis of SARS-CoV-2 from 63 patients in Niigata City, a medium-sized Japanese city, during the early phase of the pandemic, between February and May 2020. Among the 63 patients, 32 (51%) were female, with a mean (±standard deviation) age of 47.9 ± 22.3 years. Fever (65%, 41/63), malaise (51%, 32/63), and cough (35%, 22/63) were the most common clinical symptoms. The median C t value after the onset of symptoms lowered within 9 days at 20.9 cycles (interquartile range, 17-26 cycles), but after 10 days, the median C t value exceeded 30 cycles (p < 0.001). Of the 63 cases, 27 were distributed in the first epidemic wave and 33 in the second, and between the two waves, three cases from abroad were identified. The first wave was epidemiologically characterized by a single cluster related to indoor sports activity spread in closed settings, which included mixing indoors with families, relatives, and colleagues. The second wave showed more epidemiologically diversified events, with most index cases not related to each other. Almost all secondary cases were infected by droplets or aerosols from closed indoor settings, but at least two cases in the first wave were suspected to be contact infections. Results of the genomic analysis identified two possible clusters in Niigata City, the first of which was attributed to clade S (19B by Nexstrain clade) with a monophyletic group derived from the Wuhan prototype strain but that of the second wave was polyphyletic suggesting multiple introductions, and the clade was changed to GR (20B), which mainly spread in Europe in early 2020. These findings depict characteristics of SARS-CoV-2 transmission in the early stages in local community settings during February to May 2020 in Japan, and this integrated approach of epidemiological and genomic analysis may provide valuable information for public health policy decision-making for successful containment of chains of infection.

DOI： 10.3389/fmicb.2021.749149

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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Frontiers Media SA  

Horizontal gene transfer (HGT) has been widely suggested to play a critical role in the environmental adaptation of microbes; however, the number and origin of the genes in microbial genomes obtained through HGT remain unknown as the frequency of detected HGT events is generally underestimated, particularly in the absence of information on donor sequences. As an alternative to phylogeny-based methods that rely on sequence alignments, we have developed an alignment-free clustering method on the basis of an unsupervised neural network "Batch-Learning Self-Organizing Map (BLSOM)" in which sequence fragments are clustered based solely on oligonucleotide similarity without taxonomical information, to detect HGT candidates and their origin in entire genomes. By mapping the microbial genomic sequences on large-scale BLSOMs constructed with nearly all prokaryotic genomes, HGT candidates can be identified, and their origin assigned comprehensively, even for microbial genomes that exhibit high novelty. By focusing on two types of Alphaproteobacteria, specifically psychrotolerant Sphingomonas strains from an Antarctic lake, we detected HGT candidates using BLSOM and found higher proportions of HGT candidates from organisms belonging to Betaproteobacteria in the genomes of these two Antarctic strains compared with those of continental strains. Further, an origin difference was noted in the HGT candidates found in the two Antarctic strains. Although their origins were highly diversified, gene functions related to the cell wall or membrane biogenesis were shared among the HGT candidates. Moreover, analyses of amino acid frequency suggested that housekeeping genes and some HGT candidates of the Antarctic strains exhibited different characteristics to other continental strains. Lys, Ser, Thr, and Val were the amino acids found to be increased in the Antarctic strains, whereas Ala, Arg, Glu, and Leu were decreased. Our findings strongly suggest a low-temperature adaptation process for microbes that may have arisen convergently as an independent evolutionary strategy in each Antarctic strain. Hence, BLSOM analysis could serve as a powerful tool in not only detecting HGT candidates and their origins in entire genomes, but also in providing novel perspectives into the environmental adaptations of microbes.

DOI： 10.3389/fmicb.2020.01486

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Conspecific male animals fight for resources such as food and mating opportunities but typically stop fighting after assessing their relative fighting abilities to avoid serious injuries. Physiologically, how the fighting behavior is controlled remains unknown. Using the fighting fish Betta splendens, we studied behavioral and brain-transcriptomic changes during the fight between the two opponents. At the behavioral level, surface-breathing, and biting/striking occurred only during intervals between mouth-locking. Eventually, the behaviors of the two opponents became synchronized, with each pair showing a unique behavioral pattern. At the physiological level, we examined the expression patterns of 23,306 brain transcripts using RNA-sequencing data from brains of fighting pairs after a 20-min (D20) and a 60-min (D60) fight. The two opponents in each D60 fighting pair showed a strong gene expression correlation, whereas those in D20 fighting pairs showed a weak correlation. Moreover, each fighting pair in the D60 group showed pair-specific gene expression patterns in a grade of membership analysis (GoM) and were grouped as a pair in the heatmap clustering. The observed pair-specific individualization in brain-transcriptomic synchronization (PIBS) suggested that this synchronization provides a physiological basis for the behavioral synchronization. An analysis using the synchronized genes in fighting pairs of the D60 group found genes enriched for ion transport, synaptic function, and learning and memory. Brain-transcriptomic synchronization could be a general phenomenon and may provide a new cornerstone with which to investigate coordinating and sustaining social interactions between two interacting partners of vertebrates.

DOI： 10.1371/journal.pgen.1008831

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As a result of the extensive decoding of a massive amount of genomic and metagenomic sequence data, a large number of genes whose functions cannot be predicted by sequence similarity searches are accumulating, and such genes are of little use to science or industry. Current genome and metagenome sequencing largely depend on high-throughput and low-cost methods. In the case of genome sequencing for a single species, high-density sequencing can reduce sequencing errors. For metagenome sequences, however, high-density sequencing does not necessarily increase the sequence quality because multiple and unknown genomes, including those of closely related species, are likely to exist in the sample. Therefore, a function prediction method that is robust against sequence errors becomes an increased need. Here, we present a method for predicting protein gene function that does not depend on sequence similarity searches. Using an unsupervised machine learning method called BLSOM (batch-learning self-organizing map) for short oligopeptide frequencies, we previously developed a sequence alignment-free method for clustering bacterial protein genes according to clusters of orthologous groups of proteins (COGs), without using information from COGs during machine learning. This allows function-unknown proteins to cluster with function-known proteins, based solely on similarity with respect to oligopeptide frequency, although the method required high-performance supercomputers (HPCs). Based on a wide range of knowledge obtained with HPCs, we have now developed a strategy to correlate function-unknown proteins with COG categories, using only oligopeptide frequency distances (OPDs), which can be conducted with PC-level computers. The OPD strategy is suitable for predicting the functions of proteins with low sequence similarity and is applied here to predict the functions of a large number of gene candidates discovered using metagenome sequencing.

DOI： 10.1266/ggs.19-00041

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Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.ygeno.2018.09.002

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Ticks transmit a wide range of viral, bacterial, and protozoal pathogens, which are often zoonotic. Several novel tick-borne viral pathogens have been reported during the past few years. The aim of this study was to investigate a diversity of tick viral populations, which may contain as-yet unidentified viruses, using a combination of high throughput pyrosequencing and Batch Learning Self-Organizing Map (BLSOM) program, which enables phylogenetic estimation based on the similarity of oligonucleotide frequencies. DNA/cDNA prepared from virus-enriched fractions obtained from Ixodes persulcatus ticks was pyrosequenced. After de novo assembly, contigs were cataloged by the BLSOM program. In total 41 different viral families and order including those previously associated with human and animal diseases such as Bunyavirales, Flaviviridae, and Reoviridae, were detected. Therefore, our strategy is applicable for viral population analysis of other arthropods of medical and veterinary importance, such as mosquitos and lice. The results lead to the contribution to the prediction of emerging tick-borne viral diseases. A sufficient understanding of tick viral populations will also empower to analyze and understand tick biology including vector competency and interactions with other pathogens.

DOI： 10.1292/jvms.18-0483

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Language：English   Publishing type：Research paper (scientific journal)  

We investigated the circulation patterns of human influenza A and B viruses in Myanmar between 2010 and 2015 by analyzing full HA genes. Upper respiratory tract specimens were collected from patients with symptoms of influenza-like illness. A total of 2,860 respiratory samples were screened by influenza rapid diagnostic test, of which 1,577 (55.1%) and 810 (28.3%) were positive for influenza A and B, respectively. Of the 1,010 specimens that were positive for virus isolation, 370 (36.6%) were A(H1N1)pdm09, 327 (32.4%) were A(H3N2), 130 (12.9%) B(Victoria), and 183 (18.1%) were B(Yamagata) viruses. Our data showed that influenza epidemics mainly occurred during the rainy season in Myanmar. Our three study sites, Yangon, Pyinmana, and Pyin Oo Lwin had similar seasonality and circulating type and subtype of influenza in a given year. Moreover, viruses circulating in Myanmar during the study period were closely related genetically to those detected in Thailand, India, and China. Phylogeographic analysis showed that A(H1N1)pdm09 viruses in Myanmar originated from Europe and migrated to other countries via Japan. Similarly, A(H3N2) viruses in Myanmar originated from Europe, and disseminated to the various countries via Australia. In addition, Myanmar plays a key role in reseeding of influenza B viruses to Southeast Asia and East Asia as well as Europe and Africa. Thus, we concluded that influenza virus in Myanmar has a strong link to neighboring Asian countries, Europe and Oceania.

DOI： 10.1371/journal.pone.0210550

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1128/MRA.01028-18

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Language：English   Publishing type：Research paper (scientific journal)  

Mosquito-borne alphaviruses are disseminated globally and cause febrile illness in humans and animals. Since the prevalence and diversity of alphaviruses has not been previously investigated in Zambia, reverse transcription PCR was employed as a broad-spectrum approach for the detection of alphaviruses in mosquitoes. From 552 mosquito pools, a novel alphavirus, tentatively named Mwinilunga alphavirus (MWAV), was discovered from a single Culex quinquefasciatus mosquito pool. The full genome of MWAV was subsequently determined, and pairwise comparisons demonstrated that MWAV represented a new alphavirus species. Phylogenetic analyses and a linear discriminant analysis based on the dinucleotide ratios in various virus sequences indicated that MWAV is related to a mosquito-specific alphavirus distinct from other known mosquito-borne alphaviruses due to its inability to replicate in vertebrate cell lines. Further analyses of these novel alphaviruses will help to facilitate a greater understanding of the molecular determinants of host range restriction and the evolutionary relationships of alphaviruses.

DOI： 10.1016/j.virusres.2018.04.005

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Language：English   Publishing type：Research paper (scientific journal)  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：BIOMED CENTRAL LTD  

Background: Breeding programs often rely on marker-assisted tests or variant calling of next generation sequence (NGS) data to identify regions of genomic introgression arising from the hybridization of two plant species. In this paper we present IntroMap, a bioinformatics pipeline for the screening of candidate plants through the application of signal processing techniques to NGS data, using alignment to a reference genome sequence (annotation is not required) that shares homology with the recurrent parental cultivar, and without the need for de novo assembly of the read data or variant calling.
Results: We show the accurate identification of introgressed genomic regions using both in silico simulated genomes, and a hybridized cultivar data set using our pipeline. Additionally we show, through targeted marker-based assays, validation of the IntroMap predicted regions for the hybrid cultivar.
Conclusions: This approach can be used to automate the screening of large populations, reducing the time and labor required, and can improve the accuracy of the detection of introgressed regions in comparison to a marker-based approach. In contrast to other approaches that generally rely upon a variant calling step, our method achieves accurate identification of introgressed regions without variant calling, relying solely upon alignment.

DOI： 10.1186/s12863-017-0568-5

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：NATURE PUBLISHING GROUP  

Anaerobic digesters are man-made habitats for fermentative and methanogenic microbes, and are characterized by extremely high concentrations of organics. However, little is known about how microbes adapt to such habitats. In the present study, we report phylogenetic, metagenomic, and metatranscriptomic analyses of microbiomes in thermophilic packed-bed digesters fed acetate as the major substrate, and we have shown that acetoclastic and hydrogenotrophic methanogens that utilize acetate as a carbon source dominate there. Deep sequencing and precise binning of the metagenomes reconstructed complete genomes for two dominant methanogens affiliated with the genera Methanosarcina and Methanothermobacter, along with 37 draft genomes. The reconstructed Methanosarcina genome was almost identical to that of a thermophilic acetoclastic methanogen Methanosarcina thermophila TM-1, indicating its cosmopolitan distribution in thermophilic digesters. The reconstructed Methanothermobacter (designated as Met2) was closely related to Methanothermobacter tenebrarum, a non-autotrophic hydrogenotrophic methanogen that grows in the presence of acetate. Met2 lacks the Cdh complex required for CO2 fixation, suggesting that it requires organic molecules, such as acetate, as carbon sources. Although the metagenomic analysis also detected autotrophic methanogens, they were less than 1% in abundance of Met2. These results suggested that non-autotrophic methanogens preferentially grow in anaerobic digesters containing high concentrations of organics.

DOI： 10.1038/s41598-017-01752-x

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Genetics Society of Japan  

Unsupervised data mining capable of extracting a wide range of knowledge from big data without prior knowledge or particular models is a timely application in the era of big sequence data accumulation in genome research. By handling oligonucleotide compositions as high-dimensional data, we have previously modified the conventional self-organizing map (SOM) for genome informatics and established BLSOM, which can analyze more than ten million sequences simultaneously. Here, we develop BLSOM specialized for tRNA genes (tDNAs) that can cluster (self-organize) more than one million microbial tDNAs according to their cognate amino acid solely depending on tetra- and pentanucleotide compositions. This unsupervised clustering can reveal combinatorial oligonucleotide motifs that are responsible for the amino acid-dependent clustering, as well as other functionally and structurally important consensus motifs, which have been evolutionarily conserved. BLSOM is also useful for identifying tDNAs as phylogenetic markers for special phylotypes. When we constructed BLSOM with ‘species-unknown’ tDNAs from metagenomic sequences plus ‘species-known’ microbial tDNAs, a large portion of metagenomic tDNAs self-organized with species-known tDNAs, yielding information on microbial communities in environmental samples. BLSOM can also enhance accuracy in the tDNA database obtained from big sequence data. This unsupervised data mining should become important for studying numerous functionally unclear RNAs obtained from a wide range of organisms.

DOI： 10.1266/ggs.16-00068

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：NATURE PUBLISHING GROUP  

Methylotrophs are organisms that are able to grow on C1 compounds as carbon and energy sources. They play important roles in the global carbon cycle and contribute largely to industrial wastewater treatment. To identify and characterize methylotrophs that are involved in methanol degradation in wastewater-treatment plants, methanol-fed activated-sludge (MAS) microbiomes were subjected to phylogenetic and metagenomic analyses, and genomic features of dominant methylotrophs in MAS were compared with those preferentially grown in laboratory enrichment cultures (LECs). These analyses consistently indicate that Hyphomicrobium plays important roles in MAS, while Methylophilus occurred predominantly in LECs. Comparative analyses of bin genomes reconstructed for the Hyphomicrobium and Methylophilus methylotrophs suggest that they have different C1-assimilation pathways. In addition, function-module analyses suggest that their cell-surface structures are different. Comparison of the MAS bin genome with genomes of closely related Hyphomicrobium isolates suggests that genes unnecessary in MAS (for instance, genes for anaerobic respiration) have been lost from the genome of the dominant methylotroph. We suggest that genomic features and coded functions in the MAS bin genome provide us with insights into how this methylotroph adapts to activated-sludge ecosystems.

DOI： 10.1038/srep26650

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Language：English   Publishing type：Part of collection (book)   Publisher：Pan Stanford Publishing Pte. Ltd.  

Genetic and environmental factors influence the elaborate feedback mechanism that enables the human adaptive form to make internal adjustments in response to environmental stimuli. Human survival may ultimately depend on research elucidating the complex dynamics of the human genome, as well as an understanding of how environmental pressures affect the genome and influence human traits. This chapter reviews our present knowledge of the mechanisms by which haplotypes comprising multiple single-nucleotide polymorphisms (SNPs) can contribute to differences between human population groups. Herein, we describe current approaches to detecting natural selection in pigmentation candidate genes on the basis of haplotypes revealed by SNP analyses. This chapter also discusses methods for elucidating the selective genetic mechanisms that have operated to alter human skin pigmentation, which may be induced by ultraviolet radiation (UVR) in the birthplaces of human populations. Finally, we present our recommendation of spatial statistical methods for clarifying gene-environment interactions, as applicable to interactions with UVR levels. Spatial statistical approaches that apply environmental association rules can be used to extend our knowledge of human adaptation to the environment.

DOI： 10.4032/9789814669641

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：HINDAWI LTD  

Tsetse flies (Glossina spp.) are the primary vectors of trypanosomes, which can cause human and animal African trypanosomiasis in Sub-Saharan African countries. The objective of this study was to explore the genome of Glossina morsitans morsitans for evidence of horizontal gene transfer (HGT) from microorganisms. We employed an alignment-free clustering method, that is, batch learning self-organising map (BLSOM), in which sequence fragments are clustered based on the similarity of oligonucleotide frequencies independently of sequence homology. After an initial scan of HGT events using BLSOM, we identified 3.8% of the tsetse fly genome as HGT candidates. The predicted donors of these HGT candidates included known symbionts, such as Wolbachia, as well as bacteria that have not previously been associated with the tsetse fly. We detected HGT candidates from diverse bacteria such as Bacillus and Flavobacteria, suggesting a past association between these taxa. Functional annotation revealed that the HGT candidates encoded loci in various functional pathways, such as metabolic and antibiotic biosynthesis pathways. These findings provide a basis for understanding the coevolutionary history of the tsetse fly and its microbes and establish the effectiveness of BLSOM for the detection of HGT events.

DOI： 10.1155/2016/3164624

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Genetics Society of Japan  

Unsupervised data mining capable of extracting a wide range of information from big sequence data without prior knowledge or particular models is highly desirable in an era of big data accumulation for research on genes, genomes and genetic systems. By handling oligonucleotide compositions in genomic sequences as high-dimensional data, we have previously modified the conventional SOM (self-organizing map) for genome informatics and established BLSOM for oligonucleotide composition, which can analyze more than ten million sequences simultaneously and is thus suitable for big data analyses. Oligonucleotides often represent motif sequences responsible for sequence-specific binding of proteins such as transcription factors. The distribution of such functionally important oligonucleotides is probably biased in genomic sequences, and may differ among genomic regions. When constructing BLSOMs to analyze pentanucleotide composition in 50-kb sequences derived from the human genome in this study, we found that BLSOMs did not classify human sequences according to chromosome but revealed several specific zones, which are enriched for a class of CG-containing pentanucleotides
these zones are composed primarily of sequences derived from pericentric regions. The biological significance of enrichment of these pentanucleotides in pericentric regions is discussed in connection with cell type- and stage-dependent formation of the condensed heterochromatin in the chromocenter, which is formed through association of pericentric regions of multiple chromosomes.

DOI： 10.1266/ggs.90.43

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：PUBLIC LIBRARY SCIENCE  

Kampo formulations comprise a number of crude natural drugs/herbs as constituents. The crude drugs/herbs have been traditionally classified by their traditional classifications or efficacies in Kampo medicines; however, it has been difficult to establish the scientific link between experimental evidence and traditional classifications in Kampo medicine. To clarify such traditional conceptions, we tested 112 crude drugs/herbs that are major components of Kampo formulations, in the multi-pathway analysis of 10 well-studied transcriptional activities including CREB, ERSF, HIF-1 alpha, IRFs, MYC, NF-kappa B, p53, SMAD, SOX2, and TCF/LEF in A549 human lung cancer cells. By clustering the results of multi-pathway analysis with the Spearman rank-correlation coefficient and Ward linkage, three distinct traditional categories were significantly enriched in the major groupings, which are heat-clearing and dampness-drying herbs, acrid and warm exterior-resolving herbs, and acrid and cool exterior-resolving herbs. These results indicate that these crude drugs/herbs have similar effects on intracellular signaling and further imply that the traditional classifications of those enriched crude drugs/herbs can be supported by such experimental evidence. Collectively, our new in vitro multi-pathway analysis may be useful to clarify the mechanism of action of crude drugs/herbs and Kampo formulations.

DOI： 10.1371/journal.pone.0128872

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：PUBLIC LIBRARY SCIENCE  

Several pieces of evidence suggest that small RNA degradation products together with tRNase Z(L) appear to form another layer of the whole gene regulatory network. The degraded RNAsuch as a 5'-half-tRNA and an rRNA fragment function as small guide RNA (sgRNA) to guide the enzyme to target RNA. We were curious whether there exist RNAs in plasma that can function as sgRNAs for tRNase Z(L), whether these RNAs are working as signaling molecules between cells to fulfill physiological roles, and whether there are any differences in plasma sgRNA species and levels between normal and pathological conditions. Here, we analyzed small plasma RNAs from three healthy persons and three multiple myeloma patients for potential sgRNAs by deep sequencing. We also examined small RNAs from peripheral blood mononuclear cells (PBMC) of three healthy persons and three myeloma patients and from various cultured human cell lines for sgRNAs. We found that read-number distribution patterns of plasma and PBMC RNAs differ between persons in the range of 5-40 nt and that there are many RNA species that exist significantly more or less abundantly in the plasma or PBMC of the myeloma patients than those of the healthy persons. Furthermore, we found that there are many potential sgRNAs in the 5-40-nt RNAs and that, among them, a 31-nt RNA fragment derived from 94-nt Y4-RNA, which can function as a 50-half-tRNA-type sgRNA, is overwhelmingly abundant in the plasma of 2/3 of the examinees. These observations suggest that the gene regulatory network via tRNase Z(L) and sgRNA may be extended intercellularly.

DOI： 10.1371/journal.pone.0118631

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：HINDAWI PUBLISHING CORPORATION  

With the remarkable increase in genomic sequence data from various organisms, novel tools are needed for comprehensive analyses of available big sequence data. We previously developed a Batch-Learning Self-Organizing Map (BLSOM), which can cluster genomic fragment sequences according to phylotype solely dependent on oligonucleotide composition and applied to genome and metagenomic studies. BLSOM is suitable for high-performance parallel-computing and can analyze big data simultaneously, but a large-scale BLSOM needs a large computational resource. We have developed Self-Compressing BLSOM (SC-BLSOM) for reduction of computation time, which allows us to carry out comprehensive analysis of big sequence data without the use of high-performance supercomputers. The strategy of SC-BLSOM is to hierarchically construct BLSOMs according to data class, such as phylotype. The first-layer BLSOM was constructed with each of the divided input data pieces that represents the data subclass, such as phylotype division, resulting in compression of the number of data pieces. The second BLSOM was constructed with a total of weight vectors obtained in the first-layer BLSOMs. We compared SC-BLSOM with the conventional BLSOM by analyzing bacterial genome sequences. SC-BLSOM could be constructed faster than BLSOM and cluster the sequences according to phylotype with high accuracy, showing the method's suitability for efficient knowledge discovery from big sequence data.

DOI： 10.1155/2015/506052

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Language：English   Publisher：GENETICS SOC JAPAN  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

With a remarkable increase in genomic sequence data of a wide range of species, novel tools are needed for comprehensive analyses of the big sequence data. Self-organizingmap (SOM) is a powerful tool for clustering high-dimensional data on one plane. For oligonucleotide composition shandled as high-dimensional data, we have previously modified the conventional SOM for genome informatics: BLSOM. In the present study, we constructed BLSOMs for oligonucleotide compositions in fragment sequences (e.g. 100 kb) from a wide range of vertebrates, including coelacanth, and found that the sequences were clustered primarily according to species without species information. As one of the nearest living relatives of tetrapod ancestors, coelacanth is believed to provide access to the phenotypic and genomic transitions leading to the emergence of tetrapods. The characteristic oligonucleotide composition found for coelacanth was connected with the lowest dinucleotide CG occurrence (i.e. the highest CG suppression) among fishes, which was rather equivalent to that of tetrapods. This evident CG suppression in coelacanth should reflect molecular evolutionary processes of epigenetic systems including DNA methylation during vertebrate evolution. Sequence of a de novo DNA methylase (Dntm3a) of coelacanth was found to be more closely related to that of tetrapods than that of other fishes.

DOI： 10.1093/dnares/dsu012

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Methanol is widely used in industrial processes, and as such, is discharged in large quantities in wastewater. Microbial fuel cells (MFCs) have the potential to recover electric energy from organic pollutants in wastewater; however, the use of MFCs to generate electricity from methanol has not been reported. In the present study, we developed single-chamber MFCs that generated electricity from methanol at the maximum power density of 220 mW m(-2) (based on the projected area of the anode). In order to reveal how microbes generate electricity from methanol, pyrosequencing of 16S rRNA-gene amplicons and Illumina shotgun sequencing of metagenome were conducted. The pyrosequencing detected in abundance Dysgonomonas, Sporomusa, and Desulfovibrio in the electrolyte and anode and cathode biofilms, while Geobacter was detected only in the anode biofilm. Based on known physiological properties of these bacteria, it is considered that Sporomusa converts methanol into acetate, which is then utilized by Geobacter to generate electricity. This speculation is supported by results of shotgun metagenomics of the anode-biofilm microbes, which reconstructed relevant catabolic pathways in these bacteria. These results suggest that methanol is anaerobically catabolized by syntrophic bacterial consortia with electrodes as electron acceptors.

DOI： 10.1371/journal.pone.0098425

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Frontiers Research Foundation  

The tRNA gene data base curated by experts "tRNADB-CE" (http://trna.ie.niigata-u.ac.jp) was constructed by analyzing 1,966 complete and 5,272 draft genomes of prokaryotes, 171 viruses', 121 chloroplasts', and 12 eukaryotes' genomes plus fragment sequences obtained by metagenome studies of environmental samples. 595,115 tRNA genes in total, and thus two times of genes compiled previously, have been registered, for which sequence, clover-leaf structure, and results of sequence-similarity and oligonucleotide-pattern searches can be browsed. To provide collective knowledge with help from experts in tRNA researches, we added a column for enregistering comments to each tRNA. By grouping bacterial tRNAs with an identical sequence, we have found high phylogenetic preservation of tRNA sequences, especially at the phylum level. Since many species-unknown tRNAs from metagenomic sequences have sequences identical to those found in species-known prokaryotes, the identical sequence group (ISG) can provide phylogenetic markers to investigate the microbial community in an environmental ecosystem. This strategy can be applied to a huge amount of short sequences obtained from next-generation sequencers, as showing that tRNADB-CE is a well-timed database in the era of big sequence data. It is also discussed that batch-learning self-organizing-map with oligonucleotide composition is useful for efficient knowledge discovery from big sequence data. © 2014 Abe, Inokuchi, Yamada, Muto, Iwasaki and Ikemura.

DOI： 10.3389/fgene.2014.00114

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：HINDAWI PUBLISHING CORPORATION  

A strategy of evolutionary studies that can compare vast numbers of genome sequences is becoming increasingly important with the remarkable progress of high-throughput DNA sequencing methods. We previously established a sequence alignment-free clustering method "BLSOM" for di-, tri-, and tetranucleotide compositions in genome sequences, which can characterize sequence characteristics (genome signatures) of a wide range of species. In the present study, we generated BLSOMs for tetra- and pentanucleotide compositions in approximately one million sequence fragments derived from 101 eukaryotes, for which almost complete genome sequences were available. BLSOM recognized phylotype-specific characteristics (e.g., key combinations of oligonucleotide frequencies) in the genome sequences, permitting phylotype-specific clustering of the sequences without any information regarding the species. In our detailed examination of 12 Drosophila species, the correlation between their phylogenetic classification and the classification on the BLSOMs was observed to visualize oligonucleotides diagnostic for species-specific clustering.

DOI： 10.1155/2014/985706

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DOI： 10.3390/microorganisms1010137

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：PUBLIC LIBRARY SCIENCE  

In sediment-type microbial fuel cells (sMFCs) operating in rice paddy fields, rice-root exudates are converted to electricity by anode-associated rhizosphere microbes. Previous studies have shown that members of the family Geobacteraceae are enriched on the anodes of rhizosphere sMFCs. To deepen our understanding of rhizosphere microbes involved in electricity generation in sMFCs, here, we conducted comparative analyses of anode-associated microbiomes in three MFC systems: a rice paddy-field sMFC, and acetate-and glucose-fed MFCs in which pieces of graphite felt that had functioned as anodes in rice paddy-field sMFC were used as rhizosphere microbe-bearing anodes. After electric outputs became stable, microbiomes associated with the anodes of these MFC systems were analyzed by pyrotag sequencing of 16S rRNA gene amplicons and Illumina shotgun metagenomics. Pyrotag sequencing showed that Geobacteraceae bacteria were associated with the anodes of all three systems, but the dominant Geobacter species in each MFC were different. Specifically, species closely related to G. metallireducens comprised 90% of the anode Geobacteraceae in the acetate-fed MFC, but were only relatively minor components of the rhizosphere sMFC and glucose-fed MFC, whereas species closely related to G. psychrophilus were abundantly detected. This trend was confirmed by the phylogenetic assignments of predicted genes in shotgun metagenome sequences of the anode microbiomes. Our findings suggest that G. psychrophilus and its related species preferentially grow on the anodes of rhizosphere sMFCs and generate electricity through syntrophic interactions with organisms that excrete electron donors.

DOI： 10.1371/journal.pone.0077443

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：BIOMED CENTRAL LTD  

Background: With the remarkable increase of microbial and viral sequence data obtained from high-throughput DNA sequencers, novel tools are needed for comprehensive analysis of the big sequence data. We have developed "Batch-Learning Self-Organizing Map (BLSOM)" which can characterize very many, even millions of, genomic sequences on one plane. Influenza virus is one of zoonotic viruses and shows clear host tropism. Important issues for bioinformatics studies of influenza viruses are prediction of genomic sequence changes in the near future and surveillance of potentially hazardous strains.
Methods: To characterize sequence changes in influenza virus genomes after invasion into humans from other animal hosts, we applied BLSOMs to analyses of mono-, di-, tri-, and tetranucleotide compositions in all genome sequences of influenza A and B viruses and found clear host-dependent clustering (self-organization) of the sequences.
Results: Viruses isolated from humans and birds differed in mononucleotide composition from each other. In addition, host-dependent oligonucleotide compositions that could not be explained with the host-dependent mononucleotide composition were revealed by oligonucleotide BLSOMs. Retrospective time-dependent directional changes of mono-and oligonucleotide compositions, which were visualized for human strains on BLSOMs, could provide predictive information about sequence changes in newly invaded viruses from other animal hosts (e. g. the swine-derived pandemic H1N1/09).
Conclusions: Basing on the host-dependent oligonucleotide composition, we proposed a strategy for prediction of directional changes of virus sequences and for surveillance of potentially hazardous strains when introduced into human populations from non-human sources. Millions of genomic sequences from infectious microbes and viruses have become available because of their medical and social importance, and BLSOM can characterize the big data and support efficient knowledge discovery.

DOI： 10.1186/1471-2334-13-386

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

Biology is increasingly becoming a data-intensive science with the recent progress of the omics fields, e.g. genomics, transcriptomics, proteomics and metabolomics. The species-metabolite relationship database, KNApSAcK Core, has been widely utilized and cited in metabolomics research, and chronological analysis of that research work has helped to reveal recent trends in metabolomics research. To meet the needs of these trends, the KNApSAcK database has been extended by incorporating a secondary metabolic pathway database called Motorcycle DB. We examined the enzyme sequence diversity related to secondary metabolism by means of batch-learning self-organizing maps (BL-SOMs). Initially, we constructed a map by using a big data matrix consisting of the frequencies of all possible dipeptides in the protein sequence segments of plants and bacteria. The enzyme sequence diversity of the secondary metabolic pathways was examined by identifying clusters of segments associated with certain enzyme groups in the resulting map. The extent of diversity of 15 secondary metabolic enzyme groups is discussed. Data-intensive approaches such as BL-SOM applied to big data matrices are needed for systematizing protein sequences. Handling big data has become an inevitable part of biology.

DOI： 10.1093/pcp/pct041

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The Rice Annotation Project Database (RAP-DB, http://rapdb.dna.affrc.go.jp/ ) has been providing a comprehensive set of gene annotations for the genome sequence of rice, Oryza sativa (japonica group) cv. Nipponbare. Since the first release in 2005, RAP-DB has been updated several times along with the genome assembly updates. Here, we present our newest RAP-DB based on the latest genome assembly, Os-Nipponbare-Reference-IRGSP-1.0 (IRGSP-1.0), which was released in 2011. We detected 37,869 loci by mapping transcript and protein sequences of 150 monocot species. To provide plant researchers with highly reliable and up to date rice gene annotations, we have been incorporating literature-based manually curated data, and 1,626 loci currently incorporate literature-based annotation data, including commonly used gene names or gene symbols. Transcriptional activities are shown at the nucleotide level by mapping RNA-Seq reads derived from 27 samples. We also mapped the Illumina reads of a Japanese leading japonica cultivar, Koshihikari, and a Chinese indica cultivar, Guangluai-4, to the genome and show alignments together with the single nucleotide polymorphisms (SNPs) and gene functional annotations through a newly developed browser, Short-Read Assembly Browser (S-RAB). We have developed two satellite databases, Plant Gene Family Database (PGFD) and Integrative Database of Cereal Gene Phylogeny (IDCGP), which display gene family and homologous gene relationships among diverse plant species. RAP-DB and the satellite databases offer simple and user-friendly web interfaces, enabling plant and genome researchers to access the data easily and facilitating a broad range of plant research topics. © 2013 The Author 2013. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved.

DOI： 10.1093/pcp/pcs183

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：AMER SOC MICROBIOLOGY  

We sequenced the genome of Theileria orientalis, a tick-borne apicomplexan protozoan parasite of cattle. The focus of this study was a comparative genome analysis of T. orientalis relative to other highly pathogenic Theileria species, T. parva and T. annulata. T. parva and T. annulata induce transformation of infected cells of lymphocyte or macrophage/monocyte lineages; in contrast, T. orientalis does not induce uncontrolled proliferation of infected leukocytes and multiplies predominantly within infected erythrocytes. While synteny across homologous chromosomes of the three Theileria species was found to be well conserved overall, subtelomeric structures were found to differ substantially, as T. orientalis lacks the large tandemly arrayed subtelomere-encoded variable secreted protein-encoding gene family. Moreover, expansion of particular gene families by gene duplication was found in the genomes of the two transforming Theileria species, most notably, the TashAT/TpHN and Tar/Tpr gene families. Gene families that are present only in T. parva and T. annulata and not in T. orientalis, Babesia bovis, or Plasmodium were also identified. Identification of differences between the genome sequences of Theileria species with different abilities to transform and immortalize bovine leukocytes will provide insight into proteins and mechanisms that have evolved to induce and regulate this process. The T. orientalis genome database is available at http://totdb.czc.hokudai.ac.jp/.
IMPORTANCE Cancer-like growth of leukocytes infected with malignant Theileria parasites is a unique cellular event, as it involves the transformation and immortalization of one eukaryotic cell by another. In this study, we sequenced the whole genome of a nontransforming Theileria species, Theileria orientalis, and compared it to the published sequences representative of two malignant, transforming species, T. parva and T. annulata. The genome-wide comparison of these parasite species highlights significant genetic diversity that may be associated with evolution of the mechanism(s) deployed by an intracellular eukaryotic parasite to transform its host cell.

DOI： 10.1128/mBio.00204-12

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Physiological Anthropology  

Detecting natural selection would provide valuable insight into the molecular mechanisms of pathogenesis and advanced knowledge about the history of human adaptations to local environments. This study tried to detect natural selection in pigmentation candidate genes from haplotype structure as revealed by SNP analyses. We estimated the frequencies of diplotypes (combinations of the haplotypes) expected from Hardy-Weinberg equilibrium to evaluate natural selection. We also tested for correlations between the haplotypes with a high frequency and melanin content. The results indicated the possible difference of the melanin contents among the haplotypes. We suggest the possibility of natural selection to a mutation linking to the SNPs in the haplotypes. This paper also discusses future approaches to detecting natural selection in pigmentation candidate genes from haplotype structure as revealed by SNP analyses.

DOI： 10.20718/jjpa.16.2_99

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

Influenza virus poses a significant threat to public health, as exemplified by the recent introduction of the new pandemic strain H1N1/09 into human populations. Pandemics have been initiated by the occurrence of novel changes in animal sources that eventually adapt to human. One important issue in studies of viral genomes, particularly those of influenza virus, is to predict possible changes in genomic sequence that will become hazardous. We previously established a clustering method termed 'BLSOM' (batch-learning self-organizing map) that does not depend on sequence alignment and can characterize and compare even 1 million genomic sequences in one run. Strategies for comparing a vast number of genomic sequences simultaneously become increasingly important in genome studies because of remarkable progresses in nucleotide sequencing. In this study, we have constructed BLSOMs based on the oligonucleotide and codon composition of all influenza A viral strains available. Without prior information with regard to their hosts, sequences derived from strains isolated from avian or human sources were successfully clustered according to the hosts. Notably, the pandemic H1N1/09 strains have oligonucleotide and codon compositions that are clearly different from those of human seasonal influenza A strains. This enables us to infer future directional changes in the influenza A viral genome.

DOI： 10.1093/dnares/dsr005

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

We updated the tRNADB-CE by analyzing 939 complete and 1301 draft genomes of prokaryotes and eukaryotes, 171 complete virus genomes, 121 complete chloroplast genomes and approximately 230 million sequences obtained by metagenome analyses of 210 environmental samples. The 287 102 tRNA genes in total, and thus two times of the tRNA genes compiled previously, are compiled, in which sequence information, clover-leaf structure and results of sequence similarity and oligonucleotide-pattern search can be browsed. In order to pool collective knowledge with help from any experts in the tRNA research field, we included a column to which comments can be added on each tRNA gene. By compiling tRNAs of known prokaryotes with identical sequences, we found high phylogenetic preservation of tRNA sequences, especially at a phylum level. Furthermore, a large number of tRNAs obtained by metagenome analyses of environmental samples had sequences identical to those found in known prokaryotes. The identical sequence group, therefore, can be used as phylogenetic markers to clarify the microbial community structure of an ecosystem. The updated tRNADB-CE provided functions, with which users can obtain the phylotype-specific markers (e.g. genus-specific markers) by themselves and clarify microbial community structures of ecosystems in detail. tRNADB-CE can be accessed freely at http://trna.nagahama-i-bio.ac.jp.

DOI： 10.1093/nar/gkq1007

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPRINGER-VERLAG BERLIN  

Influenza A viruses cause a significant threat to public health as highlighted by the recent introduction of the swine-derived H1N1 virus (pandemic H1N1/09) into human populations. Pandemics were primarily initiated by introduction from animal sources and successive adaptation among humans through human-to-human transmission. We established a sequence alignment-free clustering method "BLSOM", which can analyze and compare all influenza A virus genome sequences on one map. Separation according to host animal, subtype and epidemic year could be efficiently visualized. Notably, H1N1/09 strains have oligonucleotide and codon compositions clearly distinct from those of seasonal human flu strains. This enabled us to make inferences about directional changes of H1N1/09 sequences in the near future and to list codons and oligonucleotides with the potential of reduction in H1N1/09 sequences. The strong visualization power of BLSOM also provides surveillance strategies for efficiently detecting potential precursors to pandemic viruses.

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Although remarkable progress in metagenomic sequencing of various environmental samples has been made, large numbers of fragment sequences have been registered in the international DNA databanks, primarily without information on gene function and phylotype, and thus with limited usefulness. Industrial useful biological activity is often carried out by a set of genes, such as those constituting an operon. In this connection, metagenomic approaches have a weakness because sets of the genes are usually split up, since the sequences obtained by metagenome analyses are fragmented into 1-kb or much shorter segments. Therefore, even when a set of genes responsible for an industrially useful function is found in one metagenome library, it is usually difficult to know whether a single genome harbors the entire gene set or whether different genomes have individual genes. By modifying Self-Organizing Map (SOM), we previously developed BLSOM for oligonucleotide composition, which allowed classification (self-organization) of sequence fragments according to genomes. Because BLSOM could reassociate genomic fragments according to genomes, BLSOM may ameliorate the abovementioned weakness of metagenome analyses. Here, we have developed a strategy for clustering of metagenomic sequences according to phylotypes and genomes, by testing a gene set contributing to environment preservation.

DOI： 10.1266/ggs.86.53

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：TAYLOR & FRANCIS AS  

Genetic and environmental factors are both part of an elaborate feedback mechanism whereby the human adaptive form reacts to environmental stimuli via internal adjustments. Human survival may ultimately depend on understanding two important components of future environmental adaptation. First, we must elucidate the dynamics of the human genome underpinning the complex human phenotype. Second, we must understand how the environment pressures and affects the genome, helping to determine human traits. This article reviews current approaches to detecting the natural selection of skin color variation in human populations. We include statistical methods for clarifying gene environment interactions applicable to the interactions with UV radiation levels. We recommend spatial data mining as an efficient approach that applies environmental association rules, extending our knowledge of adaptation to the environment.

DOI： 10.1586/ERM.10.90

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Language：English   Publishing type：Part of collection (book)   Publisher：John Wiley and Sons  

DOI： 10.1002/9780470669716.ch10

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

As a result of remarkable progresses of DNA sequencing technology, vast quantities of genomic sequences have been decoded. Homology search for amino acid sequences, such as BLAST, has become a basic tool for assigning functions of genes/proteins when genomic sequences are decoded. Although the homology search has clearly been a powerful and irreplaceable method, the functions of only 50% or fewer of genes can be predicted when a novel genome is decoded. A prediction method independent of the homology search is urgently needed. By analyzing oligonucleotide compositions in genomic sequences, we previously developed a modified Self-organizing Map &apos;BLSOM&apos; that clustered genomic fragments according to phylotype with no advance knowledge of phylotype. Using BLSOM for di-, trii- and tetrapeptide compositions, we developed a system to enable separation (self-organization) of proteins by function. Analyzing oligopeptide frequencies in proteins previously classified into COGs (clusters of orthologous groups of proteins), BLSOMs could faithfully reproduce the COG classifications. This indicated that proteins, whose functions are unknown because of lack of significant sequence similarity with function-known proteins, can be related to function-known proteins based on similarity in oligopeptide composition. BLSOM was applied to predict functions of vast quantities of proteins derived from mixed genomes in environmental samples.

DOI： 10.1093/dnares/dsp018

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：TAYLOR & FRANCIS LTD  

Six Bifidobacterium adolescentis strains, JCM1275, JCM1251, JCM7044, JCM7045, JCM7046, and 9-124, were analyzed using a tiling array designed according to the full genome sequence of ATCC15703. The results demonstrated deletion clusters along with single-gene mutations and deletions. Most deletions concerned genes involved in polysaccharide and cell-surface biogenesis. A dendrogram illustrating the deletions and mutations is presented and the evolution of B. adolescentis is discussed.

DOI： 10.1271/bbb.80843

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

The human genome is composed of large-scale compartmentalized structures, including long G+C% (GC%) mosaic structures and replication-timing zones, which are related to chromosome band zones. Previously, we measured replication timing along the entire lengths of human chromosomes 11q and 21q at the sequence level, and it was suggested that the transition regions of replication timing from early to late S-phase coincided with "unstable" regions of the genome associated with increased DNA damage. In the present study, we measured replication timing of 15 known oncogenes and tumor suppressor genes on human chromosomes 11q and 21q using two human cell lines (THP-1 and Jurkat). We found unusual relationships between replication timing and the GC content of the genomic regions in which these cancer-related genes were located. Many of these genes showed similar replication timing between the two cell lines, and the majority replicated intermediately between early and late in both cell lines. On the other hand, more than half of these genes were located at very GC-rich (50-55 GC%) regions. In addition, we analyzed the exact relationships between early/late-switch regions of replication timing where cancer-related genes were located, and GC% transitions in and around five R/G-chromosomal band boundaries (each ca. 4 Mb) by using newly designed PCR primer sets. We found that the majority of cancer-related genes including oncogenes were located in GC-rich isochores close to GC% transitions within early/late-switch regions of replication timing. many of which replicated intermediately between the early and late S-phase. Unusual relationships between replication timing and GC content of the genomic regions in which cancer-related genes were located may be related to the molecular mechanisms of genomic instability associated with increased DNA damage. (C) 2008 Elsevier B.V. All rights reserved.

DOI： 10.1016/j.gene.2008.12.004

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

We constructed a new large-scale database of tRNA genes by analyzing 534 complete genomes of prokaryotes and 394 draft genomes in WGS (Whole Genome Shotgun) division in DDBJ/EMBL/GenBank and approximately 6.2 million DNA fragment sequences obtained from metagenomic analyses. This exhaustive search for tRNA genes was performed by running three computer programs to enhance completeness and accuracy of the prediction. Discordances of assignment among three programs were found for similar to 4% of the total of tRNA gene candidates obtained from these prokaryote genomes analyzed. The discordant cases were manually checked by experts in the tRNA experimental field. In total, 144 061 tRNA genes were registered in the database &apos;tRNADB-CE&apos;, and the number of the genes was more than four times of that of the genes previously reported by the database from analyses of complete genomes with tRNAscan-SE program. The tRNADB-CE allows for browsing sequence information, cloverleaf structures and results of similarity searches among all tRNA genes. For each of the complete genomes, the number of tRNA genes for individual anticodons and the codon usage frequency in all protein genes and the positioning of individual tRNA genes in each genome can be browsed. tRNADB-CE can be accessed freely at http://trna.nagahamaibio.ac.jp.

DOI： 10.1093/nar/gkn692

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：JAPANESE SOC PLANT CELL & MOLECULAR BIOL  

Novel tools are needed for comprehensive comparisons of the inter-and intraspecies characteristics of a large amounts of available genome sequences. An unsupervised neural network algorithm, Kohonen&apos;s Self-Organizing Map (SOM), is an effective tool for clustering and visualizing high-dimensional complex data on a single map. We modified the conventional SOM for genome informatics on the basis of Batch Learning SOM (BLSOM), making the resulting map independent of the order of data input. We generated BLSOMs for oligonucleotide frequencies in fragment sequences (e. g. 10-kb) from 13 plant genomes for which almost complete genome sequences are available. BLSOM recognized species-specific characteristics (key combinations of oligonucleotide frequencies) in most of the fragment sequences, permitting classification (self-organization) of sequences according to species without any information regarding the species during computation. To disclose sequence characteristics of a single genome independently of other genomes, we constructed BLSOMs for sequence fragments from one genome plus computer-generated random sequences. Genomic sequences were clearly separated from random sequences, revealing the oligonucleotides with characteristic occurrence levels in the genomic sequences. We discussed these oligonucleotides diagnostic for genomic sequences, in connection with genetic signal sequences. Because the classification and visualization power is very high, BLSOM is thought to be an efficient and powerful tool for extracting a wide range of genomic information.

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPRINGER-VERLAG BERLIN  

As the result of the decoding of large numbers of genome sequences, numerous proteins whose functions cannot be identified by the homology search of amino acid sequences have accumulated and remain of no use to science and industry. Establishment of novel prediction methods for protein function is urgently needed. We previously developed Batch-Learning SOM (BL-SOM) for genome informatics; here, we developed BL-SOM to predict functions of proteins on the basis of similarity in oligopeptide composition of proteins. Oligopeptides are component parts of a protein and involved in formation of its functional motifs and structural parts. Concerning oligopeptide frequencies in 110,000 proteins classified into 2853 function-known COGS (clusters of orthologous groups), BL-SOM could faithfully reproduce the COG classifications, and therefore, proteins whose functions have been unidentified with homology searches could be related to function-known proteins. BL-SOM was applied to predict protein functions of large numbers of proteins obtained from metagenome analyses.

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPRINGER-VERLAG BERLIN  

Self-Organizing Map (SOM) developed by Kohonen's group is an effective tool for clustering and visualizing high-dimensional complex data on a two-dimensional map. We previously modified the conventional SOM to genome informatics, making the learning process and resulting map independent of the order of data input. This BLSOM developed on the basis of batch-learning SOM became Suitable for actualizing high-performance parallel-computing using high-performance supercomputers. This BLSOM revealed phylotype-specific characteristics of oligonucleotide frequencies occurred in their genome sequences and thus permitted clustering (self-organization) of genome fragments (e.g., 10 kb) according to phylotype without phylogenetic information during the BLSOM learning. Using a high-performance supercomputer "the Earth Simulator", almost all prokaryotic, eukaryotic and viral sequences currently available could be classified according to phylotypes on a single map. Using this large-scale BLSOM, phylotypes of a large lumber of genomic fragments obtained by metagenome analyses of environmental samples could be predicted.

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Language：English   Publisher：GENETICS SOC JAPAN  

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The anaerobic biodegradation of organic matter is accomplished by sequential syntrophic catabolism by microbes in different niches. Pelotomaculum thermopropionicum is a representative syntrophic bacterium that catalyzes the intermediate bottleneck step in the anaerobic-biodegradation process, whereby volatile fatty acids (VFAs) and alcohols produced by upstream fermenting bacteria are converted to acetate, hydrogen, and carbon dioxide (substrates for downstream methanogenic archaea). To reveal genomic features that contribute to our understanding of the ecological niche and evolution of P. thermopropionicum, we sequenced its 3,025,375-bp genome and performed comparative analyses with genomes of other community members available in the databases. In the genome, 2920 coding sequences (CDSs) were identified. These CDSs showed a distinct distribution pattern in the functional categories of the Clusters of Orthologous Groups database, which is considered to reflect the niche of this organism. P. thermopropionicum has simple catabolic pathways, in which the propionate-oxidizing methylmalonyl-CoA pathway constitutes the backbone and is linked to several peripheral pathways. Genes for most of the important catabolic enzymes are physically linked to those for PAS-domain-containing regulators, suggesting that the catabolic pathways are regulated in response to environmental conditions and/or global cellular situations rather than specific substrates. Comparative analyses of codon usages revealed close evolutionary relationships between P. thermopropionicum and other niche members, while it was distant from phylogenetically related sugar-fermenting bacteria. These analyses suggest that P. thermopropionicum has evolved as a syntrophy specialist by interacting with niche-associated microbes.

DOI： 10.1101/gr.7136508

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：IVYSPRING INT PUBL  

This study aimed to identify single nucleotide polymorphism (SNP) alleles at multiple loci associated with racial differences in skin color using SNP genotyping. A total of 122 Caucasians in Toledo, Ohio and 100 Mongoloids in Japan were genotyped for 20 SNPs in 7 candidate genes, encoding the Agouti signaling protein (ASIP), tyrosinase-related protein 1 (TYRP1), tyrosinase (TYR), melanocortin 1 receptor (MC1R), oculocutaneous albinism II (OCA2), microphthalmia-associated transcription factor (MITF), and myosin VA (MYO5A). Data were used to analyze associations between the 20 SNP alleles using linkage disequilibrium (LD). Combinations of SNP alleles were jointly tested under LD for associations with racial groups by performing chi(2) test for independence. Results showed that SNP alleles at multiple loci can be considered the haplotype that contributes to significant differences between the two population groups and suggest a high probability of LD. Confirmation of these findings requires further study with other ethnic groups to analyze the associations between SNP alleles at multiple loci and skin color variation among races.

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Language：English   Publisher：GENETICS SOC JAPAN  

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Physiological Anthropology  

Our study aims to clarify molecular basis of human skin color diversity and investigate environmental adaptability to ultraviolet irradiation in order to predict human health risk influenced by severe environments in the future. One hundred and twenty-two Caucasians living in Toledo, Ohio participated in this study. Their back and cheek were measured for melanin value for skin pigmentation index as a quantitative trait. Their buccal cells as samples were collected and used for DNA extraction. DNA was used for SNP genotyping with the technology of Masscode system that involves the two-step PCR amplification and comprises a platform chemistry of cleavable mass spectrometry tags. Our results of statistical analysis show that SNP allele in multiple loci are related and suggest high possibility of linkage disequilibrium. Our study plans to collect data on other ethic groups in order to analyze correlation between SNP allele in multiple loci and identify loci associated with human skin color diversity.

DOI： 10.20718/jjpa.12.1_1

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

Genome Information Broker for Viruses (GIB-V) is a comprehensive virus genome/segment database. We extracted 18 418 complete virus genomes/segments from the International Nucleotide Sequence Database Collaboration (INSDC, http://www.insdc.org/) by DNA Data Bank of Japan (DDBJ), EMBL and GenBank and stored them in our system. The list of registered viruses is arranged hierarchically according to taxonomy. Keyword searches can be performed for genome/segment data or biological features of any virus stored in GIB-V. GIB-V is equipped with a BLAST search function, and search results are displayed graphically or in list form. Moreover, the BLAST results can be used online with the ClustalW feature of the DDBJ. All available virus genome/segment data can be collected by the GIB-V download function. GIB-V can be accessed at no charge at http://gib-v.genes.nig.ac.jp/.

DOI： 10.1093/nar/gkl1004

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) newly collected and released 12 927 184 entries or 13 787 688 598 bases in the period from July 2005 to June 2006. The released data contain honeybee expressed sequence tags (ESTs), re-examined and re-annotated complete genome data of Escherichia coli K-12 W3110, medaka WGS and human MGA. We also systematically evaluated and classified the genes in the complete bacterial genomes submitted to the International Nucleotide Sequence Database Collaboration (INSDC, http://insdc.org) that is composed of DDBJ, EMBL Bank and GenBank. The examination and classification selected 557 000 genes as reliable ones among all the bacterial genes predicted by us.

DOI： 10.1093/nar/gkl908

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：LIBERTAS ACAD  

This study was undertaken to clarify the molecular basis for human skin color variation and the environmental adaptability to ultraviolet irradiation, with the ultimate goal of predicting the impact of changes in future environments on human health risk. One hundred twenty-two Caucasians living in Toledo, Ohio participated. Back and cheek skin were assayed for melanin as a quantitative trait marker. Buccal cell samples were collected and used for DNA extraction. DNA was used for SNP genotyping using the Masscode (TM) system, which entails two-step PCR amplification and a platform chemistry which allows cleavable mass spectrometry tags. The results show gene-gene interaction between SNP alleles at multiple loci (not necessarily on the same chromosome) contributes to inter-individual skin color variation while suggesting a high probability of linkage disequilibrium. Confirmation of these findings requires further study with other ethic groups to analyze the associations between SNP alleles at multiple loci and human skin color variation. Our overarching goal is to use remote sensing data to clarify the interaction between atmospheric environments and SNP allelic frequency and investigate human adaptability to ultraviolet irradiation. Such information should greatly assist in the prediction of the health effects of future environmental changes such as ozone depletion and increased ultraviolet exposure. If such health effects are to some extent predictable, it might be possible to prepare for such changes in advance and thus reduce the extent of their impact.

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Language：English   Publisher：GENETICS SOC JAPAN  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

A large number of complete microorganism genomes has been sequenced and submitted to the public database and then incorporated into our complete genome database, Genome Information Broker (GIB, http://gib.genes.nig.ae.jp/). However, when comparative genomics is carried out, researchers must be aware that there are protein-coding genes not confirmed by homology or motif search and that reliable protein-coding genes are missing. Therefore, we developed a protocol (Gene Trek in Prokaryote Space, GTPS) for finding possible protein-coding genes in bacterial genomes. GTPS assigns a degree of reliability to predicted protein-coding genes. We first systematically applied the protocol to the complete genomes of all 123 bacterial species and strains that were publicly available as of July 2003, and then to those of 183 species and strains available as of September 2004. We found a number of incorrect genes and several new ones in the genome data in question. We also found a way to estimate the total number of orthologous genes in the bacterial world.

DOI： 10.1093/dnares/dsl014

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：BIOMED CENTRAL LTD  

Background: Genome databases contain diverse kinds of information, including gene annotations and nucleotide and amino acid sequences. It is not easy to integrate such information for genomic study. There are few tools for integrated analyses of genomic data, therefore, we developed software that enables users to handle, manipulate, and analyze genome data with a variety of sequence analysis programs.
Results: The G-InforBIO system is a novel tool for genome data management and sequence analysis. The system can import genome data encoded as eXtensible Markup Language documents as formatted text documents, including annotations and sequences, from DNA Data Bank of Japan and GenBank encoded as flat files. The genome database is constructed automatically after importing, and the database can be exported as documents formatted with eXtensible Markup Language or tab-deliminated text. Users can retrieve data from the database by keyword searches, edit annotation data of genes, and process data with G-InforBIO. In addition, information in the G-InforBIO database can be analyzed seamlessly with nine different software programs, including programs for clustering and homology analyses.
Conclusion: The G-InforBIO system simplifies genome analyses by integrating several available software programs to allow efficient handling and manipulation of genome data. G-InforBIO is freely available from the download site.

DOI： 10.1186/1471-2105-7-368

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

Novel tools are needed for comprehensive comparisons of interspecies characteristics of massive amounts of genomic sequences currently available. An unsupervised neural network algorithm, Self-Organizing Map (SOM), is an effective tool for clustering and visualizing high-dimensional complex data on a single map. We modified the conventional SOM, oil the basis of batch-learning SOM, for genome informatics making the learning process and resulting map independent of the order of data input. We generated the SOMs for tri- and tetranucleotide frequencies in 10- and 100-kb sequence fragments from 38 eukaryotes for which almost complete genome sequences are available. SOM recognized species-specific characteristics (key combinations of oligonucleotide frequencies) in the genomic sequences, permitting species-specific classification of the sequences without any information regarding the species. We also generated the SOM for tetranucleotide frequencies in 1-kb sequence fragments from the human genome and found sequences for four functional categories (5' and 3' UTRs, CDSs and introns) were classified primarily according to the categories. Because the classification and visualization power is very high, SOM is an efficient and powerful tool for extracting a wide range of genome information. (C) 2005 Elsevier B.V. All rights reserved.

DOI： 10.1016/j.gene.2005.09.040

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：KARGER  

Imprinted genes in mammals show monoallelic expression dependent on parental origin and are often associated with differentially methylated regions (DMRs). There are two classes of DMR: primary DMRs acquire gamete-specific methylation in either spermatogenesis or oogenesis and maintain the allelic methylation differences throughout development; secondary DMRs establish differential methylation patterns after fertilization. Targeted disruption of some primary DMRs showed that they dictate the allelic expression of nearby imprinted genes and the establishment of the allelic methylation of secondary DMRs. However, how primary DMRs are recognized by the imprinting machinery is unknown. As a step toward elucidating the sequence features of the primary DMRs, we have determined the extents and boundaries of 15 primary mouse DMRs (including 12 maternally methylated and three paternally methylated DMRs) in 12.5-dpc embryos by bisulfite sequencing. We found that the average size of the DMRs was 3.2 kb and that their average G+C content was 54%. Dinucleotide content analysis of the DMR sequences revealed that, although they are generally CpG rich, the paternally methylated DMRs contain less CpGs than the maternally methylated DMRs. Our findings provide a basis for the further characterization of DMRs. Copyright (c) 2006 S. Karger AG, Basel.

DOI： 10.1159/000090824

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

The goal of this group project has been to coordinate and bring up-to-date information on all genes of Escherichia coli K-12. Annotation of the genome of an organism entails identification of genes, the boundaries of genes in terms of precise start and end sites, and description of the gene products. Known and predicted functions were assigned to each gene product on the basis of experimental evidence or sequence analysis. Since both kinds of evidence are constantly expanding, no annotation is complete at any moment in time. This is a snapshot analysis based on the most recent genome sequences of two E.coli K-12 bacteria. An accurate and up-to-date description of E.coli K-12 genes is of particular importance to the scientific community because experimentally determined properties of its gene products provide fundamental information for annotation of innumerable genes of other organisms. Availability of the complete genome sequence of two K-12 strains allows comparison of their genotypes and mutant status of alleles.

DOI： 10.1093/nar/gkj405

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：TRANSWORLD RESEARCH NETWORK  

Novel tools are needed for comprehensive comparisons of the inter- and intraspecies characteristics of massive amounts of available genomic sequences. An unsupervised neural network algorithm, Kohonen's Self-Organizing Map (SOM), is an effective tool for clustering and visualizing high-dimensional complex data on a single map. We modified the conventional SOM for genome informatics, making the learning process and resulting map independent of the order of data input. We generated SOMs for tri-, tetra-, and pentanucleotide frequencies in 300,000 10-kb sequences derived from 13 eukaryote genomes for which almost complete sequences are available (a total of 3 Gb), using a high-performance supercomputer, the Earth Simulator. SOM recognized species-specific characteristics (key combinations of oligonucleotide frequencies) in most 10-kb sequences, permitting species-specific classification (self-organization) of sequences without any information regarding the species. Because the classification power is very high, SOM is thought to be an efficient andpowerful tool for extracting a wide range of genomic information. SOM was then constructed with oligonucleotide frequencies in 10-kb sequences from 2.8 Gb of human genome sequences, and the SOM identified oligonucleotides with ftequencies characteristically biased from random occurrence level. Furthermore, 1-kb sequences rich in the biased oligonucleotides were self-organized on the map. Because these oligonucleotides often corresponded to functional signal sequences (e.g. binding sites for transcription factors) or their constituent elements, we could categorize occurrence patterns and frequencies of such pentanucleotides in the human genome that are thought to regulate transcription.

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：CANADIAN SCIENCE PUBLISHING, NRC RESEARCH PRESS  

The aim of this study was to identify a novel 1,4-beta-xylanase gene from the mixed genome DNA of human fecal bacteria without bacterial cultivation. Total DNA was isolated from a population of bacteria extracted from fecal microbiota. Using PCR, the gene fragments encoding 5 different family 10 xylanases (xyn10A, xyn10B, xyn10C, xyn10D, and xyn10E) were found. Amino acid sequences deduced from these genes were highly homologous with those of xylanases from anaerobic intestinal bacteria such as Bacteroides spp. and Prevotella spp. Self-organizing map (SOM) analysis revealed that xynA10 was classified into Bacteroidetes. To confirm that one of these genes encodes an active enzyme, a full-length xyn10A gene was obtained using nested primers specific to the internal fragments and random primers. The xyn10A gene encoding the xylanase Xyn10A consists of 1146 bp and encodes a protein of 382 amino acids and a molecular weight of 43 552. Xyn10A was a single module novel xylanase. Xyn10A was purified from a recombinant Escherichia coli strain and characterized. This enzyme was optimally active at 40 degrees C and stable up to 50 degrees C at pH 6.5 and over the pH range 4.0-11.0 at 25 degrees C. In addition, 2 ORFs (ORF1 and ORF2) were identified upstream of xyn10A. These results suggested that many unidentified xylanolytic bacteria exist in the human gut and may contribute to the breakdown of xylan which contains dietary fiber.

DOI： 10.1139/W04-136

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：NATURE PUBLISHING GROUP  

Recent awareness that most microorganisms in the environment are resistant to cultivation has prompted scientists to directly clone useful genes from environmental metagenomes(1). Two screening methods are currently available for the metagenome approach, namely, nucleotide sequence-based screening(2) and enzyme activity-based screening(3). Here we have introduced and optimized a third option for the isolation of novel catabolic operons, that is, substrate-induced gene expression screening (SIGEX). This method is based on the knowledge that catabolic-gene expression is generally induced by relevant substrates and, in many cases, controlled by regulatory elements situated proximate to catabolic genes. For SIGEX to be high throughput, we constructed an operon-trap gfp-expression vector available for shotgun cloning that allows for the selection of positive clones in liquid cultures by fluorescence-activated cell sorting. The utility of SIGEX was demonstrated by the cloning of aromatic hydrocarbon-induced genes from a groundwater metagenome library and subsequent genome-informatics analysis.

DOI： 10.1038/nbt1048

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Language：English   Publishing type：Research paper (scientific journal)  

A self-organizing map (SOM) was developed as a novel bioinformatics strategy for phylogenetic classification of sequence fragments obtained from pooled genome samples of uncultured microbes in environmental and clinical samples. This phylogenetic classification was possible without either orthologous sequence sets or sequence alignments. We first constructed SOMs for tetranucleotide frequencies in 210 000 5 kb sequence fragments obtained from 1502 prokaryotes for which at least 10 kb of genomic sequence has been deposited in public DNA databases. The sequences could be classified primarily according to phylogenetic groups without information regarding the species. We used the SOM method to classify sequence fragments derived from environmental samples of the Sargasso Sea and of an acidophilic biofilm growing in acid mine drainage. Phylogenetic diversity of the environmental sequences was effectively visualized on a single map. Sequences that were derived from a single genome but cloned independently could be reassociated in silico. G + C% has been used for a long period as a fundamental parameter for phylogenetic classification of microbes, but the G + C% is apparently too simple a parameter to differentiate a wide variety of known species. Oligonucleotide frequency can be used to distinguish the species because oligonucleotide frequencies vary significantly among their genomes. © The Author 2006. Kazusa DNA Research Institute.

DOI： 10.1093/dnares/dsi015

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Japanese Society for Bioinformatics  

In one scenario of gene evolution, exon shuffling plays a fundamental role in increasing gene diversity. This paper is an appraisal of the biological relevance of categorising proteins by their splicing profiles (exon-intron structures). The central question is whether protein function is more correlated with splicing profiles than sequence similarity, or not. To approach this question, a splicing profile similarity (SPS) index, which measures relative exon length discrepancy, was devised. Arbitrary human proteins were compared, in terms of SPS and amino acid sequence similarity, to their 1) mouse orthologues and 2) human paralogues, which epitomise functional equivalence and non-equivalence, respectively, to methodically elucidate the global relationship between a) biological function, b) splicing profile similarity, and c) sequence similarity. Protein function is more correlated with splicing profile similarity than sequence similarity as demonstrated by the fact that human-mouse orthologues (HMOs) display significantly higher splicing profile similarity than do human-human paralogues (HHPs), despite the mutual sequence similarity between these two categories. This finding indicates that splicing profile-based protein categorisation is biologically meaningful.

DOI： 10.11234/gi1990.15.2_13

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Language：English   Publishing type：Research paper (international conference proceedings)  

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：INT INST INFORMATICS & SYSTEMICS  

Expression profile data for all the genes in a genome can be obtained by transcriptome experiments such as GeneChip and cDNA array systems. Classification of genes in high resolution based on expression profiles may become a key to understand the integrated system in a cell. To attain this purpose, we conduct butch-learning self-organizing map (BL-SOM) for classifying genes based on expression profiles. In the present study, we consider two-types of SOMs based on configuration of units. One of them has planar representation space called "Plain SOM" and the other has spherical space called "Spherical SOM". In general, the profile vectors of gene expression are normalized to unity in length in order to focus not on the absolute quantity of expression but the similarity of the direction. In the present study, we propose a measure for the suitability of SOM to a given data set and confirm that the Spherical SOM is actually suitable for the data on gene expression. Then, we examine biological meanings of gene classification of Bacillus subtilis.

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：INT INST INFORMATICS & SYSTEMICS  

Novel bioinformatic tools are needed for comprehensive analyses of massive amounts of available genome DNA sequences. An unsupervised neural network algorithm, self-organizing map (SOM), is an effective tool for clustering and visualizing high-dimensional complex data on a single map. We generated SOMs for tri-, tetra-, and pentanucleotide frequencies in 300,000 10-kb sequences from 13 eukaryotes for which almost complete genomic sequences are available (a total of 3 Gb). SOM recognized in most 10-kb sequences species-specific characteristics (key combinations of oligonucleotide frequencies), permitting species-specific classification of sequences without any information regarding the species. Because the classification power is very high, SOM is an efficient and powerful tool for extracting a wide range of genomic information. SOM constructed with oligonucleotide frequencies in 10-kb sequences from 2.8 Gb of human sequences identified oligonucleotides occurring with frequencies characteristically biased from random occurrence predicted from the mononucleotide composition; 10-kb sequences rich in these oligonucleotides were self-organized on a map. Because these oligonucleotides often corresponded to genetic signals or their constituent elements, we propose an in silico method that should be useful for identification of genetic signal sequences in genomes for which large amounts of sequence data are available but additional experimental data are lacking.

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD  

Dinucleosome formation is the first step in the organization of the higher order chromatin structure. With the ultimate aim of elucidating the dinucleosome structure, we constructed a library of human dinucleosome DNA. The library consists of PCR-amplifiable DNA fragments obtained by treatment of nuclei of erythroid K562 cells with micrococcal nuclease followed by extraction of DNA and adaptor ligation to the blunt-ended DNA fragments. The library was then cloned using a plasmid vector and the sequences of the clones were determined. The dominating clones containing the Alu elements were removed. A total of 1002 clones, which comprised a dinucleosome database, contained 84 and 918 clones from the clones before and after removing Alu elements, respectively. Approximately 70% of the clones were between 300 and 400 bp in size and they were distributed to various locations of all chromosomes except the Y chromosome. The clones containing A(2)N(8)A(2)N(8)A(2) or T2N8T2N8T2 sequences were classified into three types, Type I (N shape), Type II (V shape) and Type III (M shape) according to DNA curvature plots. The locations of experimentally determined curved DNA segments matched well with the calculated ones though the clones of Types I and Ill showed additional curved DNA segments as revealed by the curvature plots. The distributions of complementary dinucleotides in the nucleosome DNA, at the ends of the dinucleosome DNA clones, allowed us to predict the positions of the nucleosome dyad axis, and estimate the size of the nucleosome core DNA, 125 nt. The distributions of AA and TT dinucleotides, as well as other RR and YY dinucleotides, showed a periodicity with an average period of 10.4 bases, close to the values observed before. Mapping of nucleosome positions in the dinucleosome database based on the observed periodicity revealed that the nucleosomes were separated by a linker of 7.5+ similar to 10 X n nt. This indicates that the nucleosome-nucleosome orientations are, typically, halfway between parallel and antiparallel. Also an important finding is that the distributions of AA/TT and other RR/YY dinucleotides, apparently, reflect both DNA curvature and DNA bendability cooperatively contributing to the nucleosome formation. (C) 2003 Elsevier Ltd. All rights reserved.

DOI： 10.1016/S0022-2836(03)00838-6

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT  

With the increasing amount of available genome sequences, novel tools are needed for comprehensive analysis of species-specific sequence characteristics for a wide variety of genomes. We used an unsupervised neural network algorithm, a self-organizing map (SOM), to analyze di-, tri-, and tetranucleotide frequencies in a wide variety of prokaryotic and eukaryotic genomes. The SOM, which can cluster complex data efficiently, was shown to be an excellent tool for analyzing global characteristics of genome sequences and for revealing key combinations of oligonucleotides representing individual genomes. From analysis of 1- and 10-kb genomic sequences derived from 65 bacteria (a total of 170 Mb) and from 6 eukaryotes (460 Mb), clear species-specific separations of major portions of the sequences were obtained with the di-, tri-, and tetranucleotide SOMs. The unsupervised algorithm could recognize, in most 10-kb sequences, the species-specific characteristics (key combinations of oligonucleotide frequencies) that are signature features of each genome. We were able to classify DNA sequences within one and between many species into subgroups that corresponded generally to biological categories. Because the classification power is very high, the SOM is an efficient and fundamental bioinformatic strategy for extracting a wide range of genomic information from a vast amount of sequences.

DOI： 10.1101/gr.634603

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Japanese Society for Bioinformatics  

With the increasing amount of available genome sequences, novel tools are needed for comprehensive analysis of species-specific sequence characteristics for a wide variety of genomes. We used an unsupervised neural network algorithm, Kohonen's self-organizing map (SOM), to analyze diand trinucleotide frequencies in 9 eukaryotic genomes of known sequences (a total of 1.2 Gb); <I>S. cerevisiae, S. pombe, C. elegans, A. thaliana, D. melanogaster, Fugu</I>, and rice, as well as <I>P. falciparum</I> chromosomes 2 and 3, and human chromosomes 14, 20, 21, and 22, that have been almost completely sequenced. Each genomic sequence with different window sizes was encoded as a 16-and 64-dimensional vector giving relative frequencies of di- and trinucleotides, respectively. From analysis of a total of 120, 000 nonoverlapping 10-kb sequences and overlapping 100-kb sequences with a moving step size of 10 kb, derived from a total of the 1.2 Gb genomic sequences, clear species-specific separations of most sequences were obtained with the SOMs. The unsupervised algorithm could recognize, in most of the 120, 000 10-kb sequences, the species-specific characteristics (key combinations of oligonucleotide frequencies) that are signature representations of each genome. Because the classification power is very high, the SOMs can provide fundamental bioinformatic strategies for extracting a wide range of genomic information that could not otherwise be obtained.

DOI： 10.11234/gi1990.13.12

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

With increases in the amounts of available DNA sequence data, it has become increasingly important to develop tools for comprehensive systematic analysis and comparison of species-specific characteristics of protein-coding sequences for a wide variety of genomes. In the present study, we used a novel neural-network algorithm, a self-organizing map (SOM), to efficiently and comprehensively analyze codon usage in approximately 60,000 genes from 29 bacterial species simultaneously. This SOM makes it possible to cluster and visualize genes of individual species separately at a much higher resolution than can be obtained with principal component analysis. The organization of the SOM can be explained by the genome G + C% and tRNA compositions of the individual species. We used SOM to examine codon usage heterogeneity in the E. coli O157 genome, which contains 'O157-unique segments' (O-islands), and showed that SOM is a powerful tool for characterization of horizontally transferred genes. (C) 2001 Elsevier Science B.V. All rights reserved.

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Japanese Society for Bioinformatics  

DOI： 10.11234/gi1990.10.314

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Japanese Society for Bioinformatics  

DOI： 10.11234/gi1990.9.369

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DOI： 10.1038/ismej.2014.83

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Language：Japanese   Publisher：Japan Society of Physiological Anthropology  

To gain a better understanding of the adaptive evolution of human skin pigmentation, we combined genetic engineering, remote sensing, and geographic information systems in a new approach for detecting gene-environment interactions. Previously, we detected natural selection on haplotypes of the OCA2 gene that had been revealed by SNP analyses. In this study, we analyzed ultraviolet radiation data obtained from satellite records. These results were subjected to a spatial statistical analysis technique for analyzing gene-environment interactions. The results suggested that skin color variations may be affected by mutations induced by ultraviolet radiation. These findings are consistent with the hypothesis that global variations in skin pigmentation may have resulted from localized adaptations to different ultraviolet radiation conditions via natural selection.

DOI： 10.20718/jjpa.19.1_13

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (other)   Publisher：生物工学会  

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Other Link： http://id.nii.ac.jp/1001/00066226/

Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)   Publisher：エヌ・ティー・エス  

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (other)   Publisher：日本化学会情報化学部会  

DOI： 10.11546/cicsj.26.40

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (other)   Publisher：日本化学会情報化学部会  

DOI： 10.11546/cicsj.26.11

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DOI： 10.11546/cicsj.26.20

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DOI： 10.11546/cicsj.26.31

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Language：Japanese   Publisher：Division of Chemical Information and Computer Sciences The Chemical Society of Japan  

Metagenome analyses of mixed genomes of uncultured microorganisms derived from various environmental samples have been progressively developed, and four million or more of gene candidates are registered in the international DNA databanks without information of their gene functions. As a bioinformatics exercise in Nagahama Institute of Bio-Science and Technology, a database for genes that may contribute achievement of the environmentally sustainable world in a broad sense are constructed. Students independently set and search for, on their own motivation, such genes that may contribute environmental cleanup and detoxification from a huge number of gene candidates obtained by metagenome analyses but left of no use because of lack of annotation concerning their functions. Genes newly annotated by students have been registered in the "Database for Genes Contributing Sustainable World" constructed by our group and publicized with students names. Many gene candidates that are thought to have the potentiality in the heavy metal removal, the degradation of agrichemicals, PCB, or environmental hormones, and the bio-fuel production have been found. The exercise text is available by requests.

DOI： 10.11545/ciqs.2007.0.j13.0

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J-GLOBAL

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Language：Japanese  

J-GLOBAL

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (other)   Publisher：Japanese Society of Soil Microbiology  

DOI： 10.18946/jssm.58.2_57

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CiNii Books

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Other Link： http://agriknowledge.affrc.go.jp/RN/2010701558

Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：統計数理研究所  

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CiNii Books

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Language：Japanese   Presentation type：Oral presentation (invited, special)  

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Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

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Language：Japanese   Presentation type：Oral presentation (invited, special)  

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Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

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Language：Japanese   Presentation type：Oral presentation (invited, special)  

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Language：Japanese   Presentation type：Oral presentation (invited, special)  

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Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

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Language：English   Presentation type：Oral presentation (invited, special)  

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Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

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Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

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Language：Japanese   Presentation type：Oral presentation (invited, special)  

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Audience： General

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Audience： Graduate students,　Researchesrs

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Audience： High school students

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