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Dealing with the Data Deluge – New Strategies in Prokaryotic Genome Analysis [chapter]

Leonid Zaslavsky, Stacy Ciufo, Boris Fedorov, Boris Kiryutin, Igor Tolstoy, Tatiana Tatusova
2016 Next Generation Sequencing - Advances, Applications and Challenges  
Recent technological innovations have ignited an explosion in microbial genome sequencing that has fundamentally changed our understanding of biology of microbes and profoundly impacted public health policy. This huge increase in DNA sequence data presents new challenges for the annotation, analysis, and visualization bioinformatics tools. New strategies have been designed to bring an order to this genome sequence shockwave and improve the usability of associated data. Genomes are organized in
more » ... hierarchical distance tree using single-copy ribosomal protein marker distances for distance calculation. Protein distance measures dissimilarity between markers of the same type and the subsequent genomic distance averages over the majority of marker-distances, ignoring the outliers. More than 30,000 genomes from public archives have been organized in a marker distance tree resulting in 6,438 species-level clades representing 7,597 taxonomic species. This computational infrastructure provides a foundation for prokaryotic gene and genome analysis, allowing easy access to pre-calculated genome groups at various distance levels. One of the most challenging problems in the current data deluge is the presentation of the relevant data at an appropriate resolution for each application, eliminating data redundancy but keeping biologically interesting variations.
doi:10.5772/62125 fatcat:cxwvhwsxwrc7nk7a2qqdczlaem

The National Center for Biotechnology Information's Protein Clusters Database

William Klimke, Richa Agarwala, Azat Badretdin, Slava Chetvernin, Stacy Ciufo, Boris Fedorov, Boris Kiryutin, Kathleen O'Neill, Wolfgang Resch, Sergei Resenchuk, Susan Schafer, Igor Tolstoy (+1 others)
2008 Nucleic Acids Research  
Rapid increases in DNA sequencing capabilities have led to a vast increase in the data generated from prokaryotic genomic studies, which has been a boon to scientists studying micro-organism evolution and to those who wish to understand the biological underpinnings of microbial systems. The NCBI Protein Clusters Database (ProtClustDB) has been created to efficiently maintain and keep the deluge of data up to date. ProtClustDB contains both curated and uncurated clusters of proteins grouped by
more » ... quence similarity. The May 2008 release contains a total of 285 386 clusters derived from over 1.7 million proteins encoded by 3806 nt sequences from the RefSeq collection of complete chromosomes and plasmids from four major groups: prokaryotes, bacteriophages and the mitochondrial and chloroplast organelles. There are 7180 clusters containing 376 513 proteins with curated gene and protein functional annotation. PubMed identifiers and external cross references are collected for all clusters and provide additional information resources. A suite of web tools is available to explore more detailed information, such as multiple alignments, phylogenetic trees and genomic neighborhoods. ProtClustDB provides an efficient method to aggregate gene and protein annotation for researchers and is available at sites/entrez?db=proteinclusters.
doi:10.1093/nar/gkn734 pmid:18940865 pmcid:PMC2686591 fatcat:rtrzuma6ubb33i6gsivhsi7yca

Virus variation resources at the National Center for Biotechnology Information: dengue virus

Wolfgang Resch, Leonid Zaslavsky, Boris Kiryutin, Michael Rozanov, Yiming Bao, Tatiana A Tatusova
2009 BMC Microbiology  
There is an increasing number of complete and incomplete virus genome sequences available in public databases. This large body of sequence data harbors information about epidemiology, phylogeny, and virulence. Several specialized databases, such as the NCBI Influenza Virus Resource or the Los Alamos HIV database, offer sophisticated query interfaces along with integrated exploratory data analysis tools for individual virus species to facilitate extracting this information. Thus far, there has
more » ... t been a comprehensive database for dengue virus, a significant public health threat. Results: We have created an integrated web resource for dengue virus. The technology developed for the NCBI Influenza Virus Resource has been extended to process non-segmented dengue virus genomes. In order to allow efficient processing of the dengue genome, which is large in comparison with individual influenza segments, we developed an offline pre-alignment procedure which generates a multiple sequence alignment of all dengue sequences. The pre-calculated alignment is then used to rapidly create alignments of sequence subsets in response to user queries. This improvement in technology will also facilitate the incorporation of additional virus species in the future. The set of virus-specific databases at NCBI, which will be referred to as Virus Variation Resources (VVR), allow users to build complex queries against virus-specific databases and then apply exploratory data analysis tools to the results. The metadata is automatically collected where possible, and extended with data extracted from the literature. Conclusion: The NCBI Dengue Virus Resource integrates dengue sequence information with relevant metadata (sample collection time and location, disease severity, serotype, sequenced genome region) and facilitates retrieval and preliminary analysis of dengue sequences using integrated web analysis and visualization tools.
doi:10.1186/1471-2180-9-65 pmid:19341451 pmcid:PMC2675532 fatcat:wcq2tghshzgzrfna5tcnfnwdju

Virus Variation Resource—recent updates and future directions

J. Rodney Brister, Yiming Bao, Sergey A. Zhdanov, Yuri Ostapchuck, Vyacheslav Chetvernin, Boris Kiryutin, Leonid Zaslavsky, Michael Kimelman, Tatiana A. Tatusova
2013 Nucleic Acids Research  
Virus Variation ( omes/VirusVariation/) is a comprehensive, webbased resource designed to support the retrieval and display of large virus sequence datasets. The resource includes a value added database, a specialized search interface and a suite of sequence data displays. Virus-specific sequence annotation and database loading pipelines produce consistent protein and gene annotation and capture sequence descriptors from sequence records then map these metadata to
more » ... a controlled vocabulary. The database supports a metadata driven, web-based search interface where sequences can be selected using a variety of biological and clinical criteria. Retrieved sequences can then be downloaded in a variety of formats or analyzed using a suite of tools and displays. Over the past 2 years, the pre-existing influenza and Dengue virus resources have been combined into a single construct and West Nile virus added to the resultant resource. A number of improvements were incorporated into the sequence annotation and database loading pipelines, and the virus-specific search interfaces were updated to support more advanced functions. Several new features have also been added to the sequence download options, and a new multiple sequence alignment viewer has been incorporated into the resource tool set. Together these enhancements should support enhanced usability and the inclusion of new viruses in the future.
doi:10.1093/nar/gkt1268 pmid:24304891 pmcid:PMC3965055 fatcat:uyjd4rsizzdtbe7nd4vektt3p4

The COG database: an updated version includes eukaryotes

Roman L Tatusov, Natalie D Fedorova, John D Jackson, Aviva R Jacobs, Boris Kiryutin, Eugene V Koonin, Dmitri M Krylov, Raja Mazumder, Sergei L Mekhedov, Anastasia N Nikolskaya, B Sridhar Rao, Sergei Smirnov (+5 others)
2003 BMC Bioinformatics  
The availability of multiple, essentially complete genome sequences of prokaryotes and eukaryotes spurred both the demand and the opportunity for the construction of an evolutionary classification of genes from these genomes. Such a classification system based on orthologous relationships between genes appears to be a natural framework for comparative genomics and should facilitate both functional annotation of genomes and large-scale evolutionary studies. We describe here a major update of the
more » ... previously developed system for delineation of Clusters of Orthologous Groups of proteins (COGs) from the sequenced genomes of prokaryotes and unicellular eukaryotes and the construction of clusters of predicted orthologs for 7 eukaryotic genomes, which we named KOGs after eukaryotic orthologous groups. The COG collection currently consists of 138,458 proteins, which form 4873 COGs and comprise 75% of the 185,505 (predicted) proteins encoded in 66 genomes of unicellular organisms. The eukaryotic orthologous groups (KOGs) include proteins from 7 eukaryotic genomes: three animals (the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster and Homo sapiens), one plant, Arabidopsis thaliana, two fungi (Saccharomyces cerevisiae and Schizosaccharomyces pombe), and the intracellular microsporidian parasite Encephalitozoon cuniculi. The current KOG set consists of 4852 clusters of orthologs, which include 59,838 proteins, or approximately 54% of the analyzed eukaryotic 110,655 gene products. Compared to the coverage of the prokaryotic genomes with COGs, a considerably smaller fraction of eukaryotic genes could be included into the KOGs; addition of new eukaryotic genomes is expected to result in substantial increase in the coverage of eukaryotic genomes with KOGs. Examination of the phyletic patterns of KOGs reveals a conserved core represented in all analyzed species and consisting of approximately 20% of the KOG set. This conserved portion of the KOG set is much greater than the ubiquitous portion of the COG set (approximately 1% of the COGs). In part, this difference is probably due to the small number of included eukaryotic genomes, but it could also reflect the relative compactness of eukaryotes as a clade and the greater evolutionary stability of eukaryotic genomes. The updated collection of orthologous protein sets for prokaryotes and eukaryotes is expected to be a useful platform for functional annotation of newly sequenced genomes, including those of complex eukaryotes, and genome-wide evolutionary studies.
doi:10.1186/1471-2105-4-41 pmid:12969510 pmcid:PMC222959 fatcat:xuukptdqqnf3bfyb6zpg2gsdfi

The genome of the model beetle and pest Tribolium castaneum

Stephen Richards, Richard A. Gibbs, George M. Weinstock, Susan J. Brown, Robin Denell, Richard W. Beeman, Richard Gibbs, Richard W. Beeman, Susan J. Brown, Gregor Bucher, Markus Friedrich, Cornelis J. P. Grimmelikhuijzen (+226 others)
2008 Nature  
Tribolium castaneum is a member of the most species-rich eukaryotic order, a powerful model organism for the study of generalized insect development, and an important pest of stored agricultural products. We describe its genome sequence here. This omnivorous beetle has evolved the ability to interact with a diverse chemical environment, as shown by large expansions in odorant and gustatory receptors, as well as P450 and other detoxification enzymes. Development in Tribolium is more
more » ... e of other insects than is Drosophila, a fact reflected in gene content and function. For example, Tribolium has retained more ancestral genes involved in cell-cell communication than Drosophila, some being expressed in the growth zone crucial for axial elongation in short-germ development. Systemic RNA interference in T. castaneum functions differently from that in Caenorhabditis elegans, but nevertheless offers similar power for the elucidation of gene function and identification of targets for selective insect control.
doi:10.1038/nature06784 pmid:18362917 fatcat:wvac7enik5ahrabxhyjdsmtfbu

Plant Genome Resources at the National Center for Biotechnology Information

D. L. Wheeler
2005 Plant Physiology  
ACKNOWLEDGMENTS The authors would like to thank Pavel Bolotov, Andrei Kochergin, Igor Tolstoy, and Boris Kiryutin for their expertise and diligence in the maintenance of many of the databases highlighted  ... 
doi:10.1104/pp.104.058842 pmid:16010002 pmcid:PMC1176401 fatcat:ahddqdwaynd4lpflww7sw3zkli

National Center for Biotechnology Information Viral Genomes Project

Y. Bao, S. Federhen, D. Leipe, V. Pham, S. Resenchuk, M. Rozanov, R. Tatusov, T. Tatusova
2004 Journal of Virology  
ACKNOWLEDGMENTS We acknowledge Pavel Bolotov for technical database support, Boris Kiryutin for cluster analysis, Andrei Kochergin for programming help, and Alexandre Souvorov for graphical alignment displays  ... 
doi:10.1128/jvi.78.14.7291-7298.2004 pmid:15220402 pmcid:PMC434121 fatcat:tmzwbehdqzc33koywo63666gl4