DDBJ working on evaluation and classification of bacterial genes in INSDC.
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ABSTRACT:
SUBMITTER: Sugawara H
PROVIDER: S-EPMC1669713 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Massively parallel high throughput sequencing technologies allow us to interrogate the microbial composition of biological samples at unprecedented resolution. The typical approach is to perform high-throughout sequencing of 16S rRNA genes, which are then taxonomically classified based on similarity to known sequences in existing databases. Current technologies cause a predicament though, because although they enable deep coverage of samples, they are limited in the length of sequence they can produce. As a result, high-throughout studies of microbial communities often do not sequence the entire 16S rRNA gene. The challenge is to obtain reliable representation of bacterial communities through taxonomic classification of short 16S rRNA gene sequences. In this study we explored properties of different study designs and developed specific recommendations for effective use of short-read sequencing technologies for the purpose of interrogating bacterial communities, with a focus on classification using naïve Bayesian classifiers. To assess precision and coverage of each design, we used a collection of ∼8,500 manually curated 16S rRNA gene sequences from cultured bacteria and a set of over one million bacterial 16S rRNA gene sequences retrieved from environmental samples, respectively. We also tested different configurations of taxonomic classification approaches using short read sequencing data, and provide recommendations for optimal choice of the relevant parameters. We conclude that with a judicious selection of the sequenced region and the corresponding choice of a suitable training set for taxonomic classification, it is possible to explore bacterial communities at great depth using current technologies, with only a minimal loss of taxonomic resolution.
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Project description:The DNA Data Bank of Japan (DDBJ, http://www.ddbj.nig.ac.jp) provides a nucleotide sequence archive database and accompanying database tools for sequence submission, entry retrieval and annotation analysis. The DDBJ collected and released 3,637,446 entries/2,272,231,889 bases between July 2009 and June 2010. A highlight of the released data was archive datasets from next-generation sequencing reads of Japanese rice cultivar, Koshihikari submitted by the National Institute of Agrobiological Sciences. In this period, we started a new archive for quantitative genomics data, the DDBJ Omics aRchive (DOR). The DOR stores quantitative data both from the microarray and high-throughput new sequencing platforms. Moreover, we improved the content of the DDBJ patent sequence, released a new submission tool of the DDBJ Sequence Read Archive (DRA) which archives massive raw sequencing reads, and enhanced a cloud computing-based analytical system from sequencing reads, the DDBJ Read Annotation Pipeline. In this article, we describe these new functions of the DDBJ databases and support tools.
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Project description:The DNA data bank of Japan (DDBJ, http://www.ddbj.nig.ac.jp) maintains a primary nucleotide sequence database and provides analytical resources for biological information to researchers. This database content is exchanged with the US National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute (EBI) within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). Resources provided by the DDBJ include traditional nucleotide sequence data released in the form of 27 316 452 entries or 16 876 791 557 base pairs (as of June 2012), and raw reads of new generation sequencers in the sequence read archive (SRA). A Japanese researcher published his own genome sequence via DDBJ-SRA on 31 July 2012. To cope with the ongoing genomic data deluge, in March 2012, our computer previous system was totally replaced by a commodity cluster-based system that boasts 122.5 TFlops of CPU capacity and 5 PB of storage space. During this upgrade, it was considered crucial to replace and refactor substantial portions of the DDBJ software systems as well. As a result of the replacement process, which took more than 2 years to perform, we have achieved significant improvements in system performance.
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Project description:DDBJ (http://www.ddbj.nig.ac.jp) collected and released 1 880 115 entries or 1 134 086 245 bases in the period from July 2006 to June 2007. The released data contains the high-throughput cDNAs of cricket and high-quality draft genome of medaka among others. Our computer system has been upgraded since March 2007. Another new aspect is an efficient data retrieval tool that has recently been equipped and served at DDBJ. It is called All-round Retrieval for Sequence and Annotation, which enables the user to search for keywords also in the Feature/Qualifier of the International Nucleotide Sequence Database Collaboration (http://www.insdc.org/). We will also replace our home page with a more efficient one by the end of 2007.
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Project description:Knowledge of bacterial lipolytic enzymes is increasing at a rapid and exciting rate. To obtain an overview of this industrially very important class of enzymes and their characteristics, we have collected and classified the information available from protein and nucleotide databases. Here we propose an updated and extensive classification of bacterial esterases and lipases based mainly on a comparison of their amino acid sequences and some fundamental biological properties. These new insights result in the identification of eight different families with the largest being further divided into six subfamilies. Moreover, the classification enables us to predict (1) important structural features such as residues forming the catalytic site or the presence of disulphide bonds, (2) types of secretion mechanism and requirement for lipase-specific foldases, and (3) the potential relationship to other enzyme families. This work will therefore contribute to a faster identification and to an easier characterization of novel bacterial lipolytic enzymes.
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Project description:BackgroundDisease severity is important when considering genes for inclusion on reproductive expanded carrier screening (ECS) panels. We applied a validated and previously published algorithm that classifies diseases into four severity categories (mild, moderate, severe, and profound) to 176 genes screened by ECS. Disease traits defining severity categories in the algorithm were then mapped to four severity-related ECS panel design criteria cited by the American College of Obstetricians and Gynecologists (ACOG).MethodsEight genetic counselors (GCs) and four medical geneticists (MDs) applied the severity algorithm to subsets of 176 genes. MDs and GCs then determined by group consensus how each of these disease traits mapped to ACOG severity criteria, enabling determination of the number of ACOG severity criteria met by each gene.ResultsUpon consensus GC and MD application of the severity algorithm, 68 (39%) genes were classified as profound, 71 (40%) as severe, 36 (20%) as moderate, and one (1%) as mild. After mapping of disease traits to ACOG severity criteria, 170 out of 176 genes (96.6%) were found to meet at least one of the four criteria, 129 genes (73.3%) met at least two, 73 genes (41.5%) met at least three, and 17 genes (9.7%) met all four.ConclusionThis study classified the severity of a large set of Mendelian genes by collaborative clinical expert application of a trait-based algorithm. Further, it operationalized difficult to interpret ACOG severity criteria via mapping of disease traits, thereby promoting consistency of ACOG criteria interpretation.
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Project description:The Bioinformation and DDBJ (DNA Data Bank of Japan) Center (DDBJ Center; https://www.ddbj.nig.ac.jp) operates archival databases that collect nucleotide sequences, study and sample information, and distribute them without access restriction to progress life science research as a member of the International Nucleotide Sequence Database Collaboration (INSDC), in collaboration with the National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute. Besides the INSDC databases, the DDBJ Center also provides the Genomic Expression Archive for functional genomics data and the Japanese Genotype-phenotype Archive for human data requiring controlled access. Additionally, the DDBJ Center started a new public repository, MetaboBank, for experimental raw data and metadata from metabolomics research in October 2020. In response to the COVID-19 pandemic, the DDBJ Center openly shares SARS-CoV-2 genome sequences in collaboration with Shizuoka Prefecture and Keio University. The operation of DDBJ is based on the National Institute of Genetics (NIG) supercomputer, which is open for large-scale sequence data analysis for life science researchers. This paper reports recent updates on the archival databases and the services of DDBJ.
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Project description:DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) collected and released 2 368 110 entries or 1 415 106 598 bases in the period from July 2007 to June 2008. The releases in this period include genome scale data of Bombyx mori, Oryzas latipes, Drosophila and Lotus japonicus. In addition, from this year we collected and released trace archive data in collaboration with National Center for Biotechnology Information (NCBI). The first release contains those of O. latipes and bacterial meta genomes in human gut. To cope with the current progress of sequencing technology, we also accepted and released more than 100 million of short reads of parasitic protozoa and their hosts that were produced by using a Solexa sequencer.
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