The advent of next-generation sequencing technologies is transforming biology by enabling individual researchers to sequence the genomes of individual organisms or cells on a massive scale. In order to realize the translational potential of this technology we will need advanced information systems to integrate and interpret this deluge of data. These systems must be capable of extracting the location and function of genes and biological features from genomic data, requiring the coordinated parallel execution of multiple bioinformatics analyses and intelligent synthesis of the results. The resulting databases must be structured to allow complex biological knowledge to be recorded in a computable way, which requires the development of logic-based knowledge structures called ontologies. To visualise and manipulate the results, new graphical interfaces and knowledge acquisition tools are required. Finally, to help understand complex disease processes, these information systems must be equipped with the capability to integrate and make inferences over multiple data sets derived from numerous sources. RESULTS: Here I describe research, design and implementation of some of the components of such a next-generation information system. I first describe the automated pipeline system used for the annotation of the Drosophila genome, and the application of this system in genomic research. This was succeeded by the development of a flexible graphoriented database system called Chado, which relies on the use of ontologies for structuring data and knowledge. I also describe research to develop, restructure and enhance a number of biological ontologies, adding a layer of logical semantics that increases the computability of these key knowledge sources. The resulting database and ontology collection can be accessed through a suite of tools. Finally I describe how the combination of genome analysis, ontology-based database representation and powerful tools can be combined in order to make inferences about genotype-phenotype relationships within and across species. CONCLUSION: The large volumes of complex data generated by high-throughput genomic and systems biology technology threatens to overwhelm us, unless we can devise better computing tools to assist us with its analysis. Ontologies are key technologies, but many existing ontologies are not interoperable or lack features that make them computable. Here I have shown how concerted ontology, tool and database development can be applied to make inferences of value to translational research.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第19034号 / 農博第2112号 / 新制||農||1031(附属図書館) / 学位論文||H27||N4916(農学部図書室) / 31985 / 京都大学大学院農学研究科応用生物科学専攻 / (主査)教授 左子 芳彦, 教授 澤山 茂樹, 准教授 吉田 天士 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

The increasing availability of high-quality genome assemblies raised interest in the characterization of genomic architecture. Major architectural elements, such as common repeats and segmental duplications (SDs), increase genome plasticity that stimulates further evolution by changing the genomic structure and inventing new genes. Optimal computation of SDs within a genome requires quadratic-time local alignment algorithms that are impractical due to the size of most genomes. Additionally, to perform evolutionary analysis, one needs to characterize SDs in multiple genomes and find relations between those SDs and unique (non-duplicated) segments in other genomes. A na ̈ıve approach consisting of multiple sequence alignment would make the optimal solution to this problem even more impractical. Thus there is a need for fast and accurate algorithms to characterize SD structure in multiple genome assemblies to better understand the evolutionary forces that shaped the genomes of today. Here we introduce a new approach, BISER, to quickly detect SDs in multiple genomes and identify elementary SDs and core duplicons that drive the formation of such SDs. BISER improves earlier tools by (i) scaling the detection of SDs with low homology (75%) to multiple genomes while introducing further 10–34× speed-ups over the existing tools, and by (ii) characterizing elementary SDs and detecting core duplicons to help trace the evolutionary history of duplications to as far as 300 million years. / Graduate

The rise in large-scale cancer genomics data collection initiatives has paved the way for extensive research aimed at understanding the biology of human cancer. While the majority of this research is motivated by clinical applications aimed at advancing targeted therapy, cancer prevention initiatives are less emphasized. Many cancers are not attributable to known heritable genetic factors, making environmental exposure a main suspect in driving cancer risk. A major aspect of cancer prevention involves the identification of chemical carcinogens, substances linked to increased cancer susceptibility. Traditional methods for chemical carcinogens testing, including epidemiological studies and rodent bioassays, are expensive to conduct, not scalable to a large number of chemicals, and not capable of detecting specific mechanisms of actions of carcinogenicity. Thus, there exists a dire need for improvement in data generation and computational method development for chemical carcinogenicity testing. Here, we coin the term "carcinogenome" to denote the complete cancer genomic landscape encompassing both its repertoire of environmental chemical exposures, as well as its germ-line and somatic mutations and epi-genetic regulators. To study the carcinogenome, we analyze both the genomic behavior of real human tumors as well as profiles of the exposome, that is, data derived from chemical exposures in human, animal or cell line models. My thesis consists of two distinct projects that, through the generation and innovative analysis of multi-omics data, aim at advancing our understanding of the molecular mechanisms of cancer initiation and progression, and of the role environmental exposure plays in these processes. First, I detail our effort at data generation and method development for characterizing environmental contributions to carcinogenesis using transcriptional profiles of chemical perturbations. Second, I present the tool iEDGE (Integration of Epi-DNA and Gene Expression) and its applications to the integrative analysis of multi-level cancer genomics data from human primary tumors of multiple cancer types. These projects collectively further our understanding of the carcinogenome and will hopefully foster both cancer prevention, through the identification of environmental chemical carcinogens, and cancer therapy, through the discovery of novel cancer gene drivers and therapeutic targets.

The complete genome sequence of bacteriophage VR7 has been determined. The genome sequence is 169,285 nt, with an overall G+C content of 40,3%, compared with 35.3 % of T4. VR7 encodes 293 putative protein-encoding open reading frames (ORFs) and tRNAMet. In total, 211 of the 293 VR7 open reading frames encode putative proteins that share 30% ‒ 97% amino acid sequence identity with those found in T4; 46 ORFs resemble genes from other T4-like phages, 9 show similarities to genes of non T4 type phages and 27 ORFs lack any database matches. Homologs to the T4 α-gt, β-gt, SegA, SegB, SegC, SegD, SegE, I-TevI, I-TevII, I-TevIII, gp42, Ac, NrdG, NrdD, Arn, IPI, IPII, IPIII, Mrh as well as the T4-specific tRNAs are all absent in VR7. The amino acid sequences of the three major structural proteins gp23, gp18 and gp19 of VR7 show 84.9%, 71.3% and 69.9% aa identity respectively with adequate proteins of T4. In total, 43 PE, 43 PM and 44 PL have been identified in VR7. Moreover, phage VR7 encodes homologues of all transcription-associated proteins of T4. The functional complementation experiments of VR7 MotA, sharing only 34% amino acid sequence identity with MotA of T4, have been performed. It has been demonstrated, that the presence of plasmid encoded VR7 MotA complements the T4motAΔ mutant for growth in E. coli, and activates middle-mode transcription during the growth of T4motA-. Bacteriophages VR5, VR7 and VR20 have been characterized. It has been demonstrated that these phages... [to full text] / Nustačius 169,285 b.p. bakteriofago VR7 genomo nukleotidų seką aptikta viena tRNRMET ir 293 hipotetiniai ASR. Du šimtai vienuolika šio fago genų koduoja baltymus, kurie yra 30% ‒ 97% homologiški atitinkamiems fago T4 baltymams. Keturiasdešimt šeši fago VR7 baltymai neturi analogų T4, bet yra homologiški įvairių kitų T4 giminingų fagų baltymams, 9 baltymai nėra artimi T4-giminingų fagų koduojamiems baltymams, o 27 bakteriofago VR7 ASR koduoja baltymus, kuriems homologų NCBI duomenų bazėje nėra. Fago VR7 genome nėra genų, koduojančių bakteriofago T4 : α ir β gliukoziltransferazes (α-gt , β-gt) , DNR endonukleazes SegA, SegB, SegC, SegD, DNR metilazę Dam, dCMP hidroksimetilazę gp42, atsparumą akriflavinui sąlygojantį baltymą Ac bei ląstelės šeimininkės σ32 fosforilinime dalyvaujančio mrh geno produkto. Nustatyta, kad GC sudaro 40,3% fago VR7 genominės DNR, kai tuo tarpu fago T4 - 35%. Taipogi nustatyta, kad VR7 gp18, gp19 ir gp23 yra tik 71.3% , 69.9% ir 84.9% homologiški atitinkamiems fago T4 baltymams. Tiriant bakteriofago VR7 transkripcijos reguliaciją buvo aptikti 43 ankstyvieji, 43 vidurinieji bei 44 vėlyvieji promotoriai. Šio fago genominėje DNR taip pat buvo identifikuoti visų fago T4 transkripcijos reguliacijoje dalyvaujančių baltymų homologai. Klonavus bakteriofago VR7 geną motA buvo atliktas funkcinės komplementacijos tyrimas fago T4motA- sistemoje in vivo. Nustatyta, kad plazmidėje koduojamas fago VR7 viduriniosios transkripcijos aktyvatorius MotA, kurio... [toliau žr. visą tekstą]

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京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第21812号 / 農博第2325号 / 新制||農||1066(附属図書館) / 学位論文||H31||N5184(農学部図書室) / 京都大学大学院農学研究科応用生物科学専攻 / (主査)教授 左子 芳彦, 教授 澤山 茂樹, 准教授 吉田 天士 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

The gram-negative bacteria Edwardsiella ictaluri causes significant economic losses in aquacultured fish. Generally considered host-specific to catfish, there are reports of E. ictaluri outbreaks from other aquacultured species, including ornamental fish raised in the southeastern U.S. Thus, a comprehensive phenotypic and genotypic characterization of E. ictaluri isolates from catfish and ornamental aquaculture was warranted. Morphological, biochemical, and protein profiles of catfish and ornamental derived isolates were mostly similar. Plasmid profiles of wild-type isolates were consistent within groups. Analysis of putative anti-microbial resistant isolates from catfish revealed the presence of multi-drug resistant plasmids. Genomic comparisons indicated marked differences among host groups, including unique T4SSs and phage elements among ornamental fish-derived E. ictaluri isolates. An optimal MLSA scheme consisting of eight reference genes was defined, revealing isolates from catfish and ornamental aquaculture form two discrete phyletic lineages. This study advances our understanding of E. ictaluri affecting two important agricultural commodities in the U.S.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第22485号 / 農博第2389号 / 新制||農||1075(附属図書館) / 学位論文||R2||N5265(農学部図書室) / 京都大学大学院農学研究科応用生物科学専攻 / (主査)教授 吉田 天士, 教授 澤山 茂樹, 教授 菅原 達也 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

Nausea and vomiting are among the most common symptoms of early pregnancy. Its most extreme form Hyperemesis gravidarum often requires hospitalization and has been linked as a risk factor of perinatal depression. The emetic reflex is to a large extent triggered in the intestinal epithelium by the enterochromaffin cells, however the interplay between gut microbiome and pregnancy nausea is yet unclear. The aim of this study is to investigate the variation in gut microbiota diversity on second-trimester pregnant women with different levels of nausea, and to ascertain potential key species involved in that variation. Using shotgun sequencing to capture bacterial diversity from 1078 fecal samples, we found a reduction on species richness on women with strong nausea. There are measurable differences in the gut microbiota community composition based on the strength of nausea although depression seemed to be even more relevant to explain those differences. Our results provide evidence for the association of nausea and perinatal depression, but further studies are needed to elucidate the mechanisms underpinning the gut-brain axis cross-talk role in nausea and perinatal depression. No evidence of variation in species evenness or differential abundance of species were found. Finally, random forests results point at Lactococcus lactis as potentially displaying a key role determining the intensity of the nausea, although better models are needed to infer clear assumptions.