During 1998 the primary focus of the Genome Sequence DataBase (GSDB; http://www.ncgr.org/gsdb ) located at the National Center for Genome Resources (NCGR) has been to improve data quality, improve data collections, and provide new methods and tools to access and analyze data. Data quality has been improved by extensive curation of certain data fields necessary for maintaining data collections and for using certain tools. Data quality has also been increased by improvements to the suite of programs that import data from the International Nucleotide Sequence Database Collaboration (IC). The Sequence Tag Alignment and Consensus Knowledgebase (STACK), a database of human expressed gene sequences developed by the South African National Bioinformatics Institute (SANBI), became available within the last year, allowing public access to this valuable resource of expressed sequences. Data access was improved by the addition of the Sequence Viewer, a platform-independent graphical viewer for GSDB sequence data. This tool has also been integrated with other searching and data retrieval tools. A BLAST homology search service was also made available, allowing researchers to search all of the data, including the unique data, that are available from GSDB. These improvements are designed to make GSDB more accessible to users, extend the rich searching capability already present in GSDB, and to facilitate the transition to an integrated system containing many different types of biological data

Booker,  M.

Farmer,  A.

Harger,  C.

Harpold,  M.

Huang,  W.

Inman,  J.

Kiphart,  D.

Kodira,  C.

Root,  S.

Schilkey,  F.

Schwertfeger,  J.

Siepel,  A.

Skupski,  M. P.

Stamper,  D.

Thayer,  N.

Thompson,  R.

Wortman,  J.

Zhuang,  J. J.

Nucleic Acids Research

PubMed

Cold Spring Harbor Laboratory Institutional Repository

 1999 Oxford University Press 35–38Nucleic Acids Research, 1999, Vol. 27, No. 1The Genome Sequence DataBase: towards anintegrated functional genomics resourceM. P. Skupski, M. Booker, A. Farmer, M. Harpold, W. Huang, J. Inman, D. Kiphart,C. Kodira, S. Root, F. Schilkey, J. Schwertfeger, A. Siepel, D. Stamper, N. Thayer,R. Thompson, J. Wortman, J. J. Zhuang and C. Harger*National Center for Genome Resources, 1800 Old Pecos Trail, Suite A, Santa Fe, NM 87505, USAReceived November 9, 1998; Revised and Accepted November 11, 1998ABSTRACTDuring 1998 the primary focus of the Genome SequenceDataBase (GSDB; http://www.ncgr.org/gsdb ) locatedat the National Center for Genome Resources (NCGR)has been to improve data quality, improve datacollections, and provide new methods and tools toaccess and analyze data. Data quality has beenimproved by extensive curation of certain data fieldsnecessary for maintaining data collections and forusing certain tools. Data quality has also been in-creased by improvements to the suite of programs thatimport data from the International Nucleotide SequenceDatabase Collaboration (IC). The Sequence Tag Align-ment and Consensus Knowledgebase (STACK), adatabase of human expressed gene sequences devel-oped by the South African National BioinformaticsInstitute (SANBI), became available within the last year,allowing public access to this valuable resource ofexpressed sequences. Data access was improved bythe addition of the Sequence Viewer, a platform-independent graphical viewer for GSDB sequencedata. This tool has also been integrated with othersearching and data retrieval tools. A BLAST homologysearch service was also made available, allowingresearchers to search all of the data, including theunique data, that are available from GSDB. Theseimprovements are designed to make GSDB moreaccessible to users, extend the rich searching capabil-ity already present in GSDB, and to facilitate thetransition to an integrated system containing manydifferent types of biological data.INTRODUCTIONThe genomic research community has embraced the idea offunctional genomics, involving the integration and analysis ofmany different kinds of biological data at the level of completegenomes. In the past two years there have already been a numberof studies examining functional genomics both by comparingcomplete genomes (1–7) and by examining the levels ofexpression of large numbers of coding regions in both yeast andhuman studies (8–15).This emphasis on functional genomics has made it clear that thecurrent paradigm of sequence databases is inadequate for the taskof storing and linking all of the data that are necessary forfunctional genomic studies. Additional data types that arenecessary include expression data, population polymorphismdata and biochemical pathway data. NCGR believes that a systemthat incorporates all of these kinds of data will be necessary forbiological discovery in the next five years, and that the mostimportant requirement for such a system is that there be accuratelinks between the different types of data, so that a researcher cannavigate from sequence data to polymorphism data to expressiondata to biochemical pathway data in any order and all combina-tions.One of the most important components of such an integratedsystem is a high-quality sequence database. To establish linksamong the different data types, the quality of the sequence andannotation must be high. The concept of a gene has undergoneradical change in the last 20 years, and the concept probably haslimited utility in the current era of genomics (16). However, geneand product names can be associated with stretches of sequencethat are known to produce a specific product, whether that stretchof sequence actually codes for an amino acid product, or has someregulatory role. NCGR believes that accurate annotation of geneand product names is essential in order to establish links with theother types of data necessary for an integrated system. Other datathat must be accurate are taxonomy, chromosome, and mapinformation, because they allow the establishment of meaningfullinks between different types of data.Some of the organism specific databases have begun tointegrate other kinds of data (17, http://genome-www.stanford.edu/Saccharomyces ; 18, http://WWW.informatics.jax.org ). Oneof the major criticisms of these specialized databases is that theyare not easily accessible to non-experts because they have beendeveloped by and for experts in the speciality they serve (16). Toavoid this problem and make an integrated system usable byresearchers at all levels, the system must have visualization andanalysis tools that are intuitive and easy to learn.The Genome Sequence DataBase (GSDB) located at theNational Center for Genome Resources (NCGR;*To whom correspondence should be addressed. Tel: +1 505 982 7840; Fax: +1 505 995 4432; Email: cah@ncgr.org at Cold Spring Harbor Laboratory on January 12, 2015http://nar.oxfordjournals.org/Downloaded from  Nucleic Acids Research, 1999, Vol. 27, No. 136http://www.ncgr.org ) is a relational database that includes all ofthe data available from the databases that belong to theInternational Nucleotide Sequence Database Collaboration (IC).GSDB also provides support for data types that are not supportedby the IC databases, including sequence analysis data, representa-tions of pairwise alignments, and discontiguous sequences, whichare groupings of individual sequences that have a known spatialrelationship (e.g., all of the exons of a gene). This allowsresearchers to store meaningful relationships among sequencesand make them available to others. NCGR has concentrated onusing the strengths of the relational database system and theunique data types to provide better data access and analysis tools,interesting data collections, and more accurate data in certainfields.In an effort to move toward an integrated system, GSDB hasconcentrated on data quality, new data collections, and access andanalysis tools during the last year.DATA QUALITY IMPROVEMENTSData curationThe GSDB staff has extensively curated the taxonomy of allorganisms to ensure that the taxonomy followed within thedatabase is consistent within each taxonomic group. The focus ontaxonomy is driven first by a recognition that taxonomy will bevery important when establishing links among different kinds ofdata that are incorporated into an integrated system. Second, newaccess and analysis tools that have been developed in the last yearrequire that taxonomy be represented accurately within thedatabase. Sequences that belong to new, unmatched species havetheir taxonomy updated within a day of entry into GSDB.Additional efforts on curation are focused on the chromosomefield for human sequences. This allows researchers working onhuman sequences to narrow the search if they know in whichchromosome their sequence resides. It can also help placesequences if they can find significant homology to a sequencewith a known location.Data acquisitionData from the IC databases are imported into GSDB each night,using a suite of special import programs to place each dataelement into its proper location. Over 99% of all data from the ICdatabases has been correctly imported into GSDB within 24–48hours of its initial release by the database of origin. Improvementshave been made to the import suite to ensure that the data fromIC flatfiles is placed into the proper fields, and reports aregenerated nightly of fields frequently in need of curation so thatthey can be reviewed and corrected by the biology staff asnecessary.Biology staff members routinely survey the Internet to findsequence data not included in any of the other sequence databases(‘data mining’), and format these data for entry into GSDB usingGIO (the GSDB Input/Output file format). Genome center websites supported by the Department of Energy and the NationalInstitutes of Health are a special focus. Appropriate credit is givento the center from which the data was mined, and links back totheir website are included. About 4.5% of the data within GSDBare unique to GSDB, providing a rich source of information toresearchers worldwide.DATA COLLECTIONSSTACKThe Sequence Tag Alignment and Consensus Knowledgebase(STACK), a public database of human expressed gene sequences,was analyzed and developed by the South African NationalBioinformatics Institute (SANBI; 19,20). These sequencesconsist of consensus sequences derived from aligned expressedsequence tags (ESTs) and clustered sequences (discontiguoussequences) that are part of a single gene. SANBI chose to depositthese data in GSDB for public access because GSDB is the onlypublic sequence database with the ability to represent bothalignment and discontiguous sequence data.STACK data are extremely valuable, because the consensussequences that were built from the analysis that SANBIperformed are longer than the consensus sequences that havebeen made by other groups and are longer than the individualESTs that were used to construct the consensi. The increase inlength makes identification of individual genes much more likely,and improves the ability of a researcher with a sequence thatmatches one of the ESTs to find a match.STACK data can be accessed and retrieved using a specialversion of Maestro, a database query tool, developed specificallyfor retrieving these collaborative data, SANBI Maestro(http://www.ncgr.org/cgi-bin/sanbi/maestro/front.pl ).Human sequence-based mapsThe human discontiguous sequences constructed using thesequence tagged sites (STS) markers from the WhiteheadInstitute for Biomedical Research and Stanford Human GenomeCenter (21) have been expanded to include genomic sequences.Genomic sequences are placed on these maps by determininghomology with sequences already in place. On average, 60genomic sequences have been placed on each chromosome, andnewly acquired data are checked regularly to locate new matchesand to place them on each chromosome.Accession numbers of these maps can be obtained from the‘What’s New’ section of the GSDB web site (http://www.ncgr.org/gsdb ), and the discontiguous sequences can be retrieved inflatfile format using Maestro (http://www.ncgr.org/gsdb/maestro/Index.html ). The flatfile format of discontiguous sequencesincludes all sequences that are part of the discontig and anyinformation about order and distance that is known among thesequences.DATA ACCESS AND ANALYSIS IMPROVEMENTSSequence Viewer Sequence Viewer is a new platform-independent graphicalviewer for sequence data, implemented in Java as an Internet-based applet that can be launched from a web browser or used asa stand-alone application with increased functionality. The appletversion of Sequence Viewer is integrated with Maestro, theweb-based search tool for GSDB, and sequences can be vieweddirectly from Maestro results. The application version ofSequence Viewer can be downloaded from the Sequence Viewerweb site (http://www.ncgr.org/gsdb/sv ).Specific advantages of the Sequence Viewer include: easyvisualization of the features of a sequence including placement offeatures, length, type and name; easy access to feature-associated at Cold Spring Harbor Laboratory on January 12, 2015http://nar.oxfordjournals.org/Downloaded from 37Nucleic Acids Research, 1994, Vol. 22, No. 1Nucleic Acids Research, 1999, Vol. 27, No. 1 37sequence due to integration with Excerpt, GSDB’s sub-sequenceretrieval script; simple identification of STS markers throughdisplay as vertical bars; simple text display of additionalinformation about features and sequences, such as reference dataor gene and product information; clear indication of the strand onwhich a feature occurs; easy color customization of feature types;clear viewing of large sequences that contain extensive annota-tion on any platform.Sequence Viewer is intended as the first module of a tool thatwill eventually allow viewing and editing of sequences, multiplealignments and discontiguous sequences.Table 1. Summary of the organization of the searchable sets into finersubsets to allow more precision in searchingData set SubsetsArchaeaEubacteriaVirus RNA virusesDNA virusesUnclassified virusesChordates Fugu (puffer fish)All other chordates (excludes mammals)Mammals RodentMouseRatOther rodentsNon-human primatesAll other mammalsHuman Individual chromosomesESTsSTSsunmapped sequencesNon-chordate animals Caenorhabditis elegansDrosophila melanogasterAll other non-chordatesPlants EudicotsArabidopsis thalianaOther dicotsMonocotsNon-flowering vascular plantsOther plantsFungi Saccharomyces cerevisiaeAll other fungiMiscellaneous eukaryotes All eukaryotes that are not in the kingdomsAnimalia, Plantae, or FungiOrganelles Human mitochondrionPlant mitochondrionChordate mitochondrionChloroplastNon-vertebrate, non-plant mitochondrionOther organellesNon-human ESTsNon-human STSsSynthetic sequencesUnidentified sequences Sequences of uncertain originComplete genomes Each microbial complete genomeSequence similarity searchingA TimeLogic DeCypher II was recently acquired to provide aserver for homology searching using several algorithms. CurrentlyBLAST is available to use in searching nucleotide sequencesfrom GSDB and protein sequences from several protein databases(http://seqsim.ncgr.org ). GSDB contains sequence data that is notavailable elsewhere. This unique data can be searched using theBLAST similarity search.To allow more flexibility in homology searching, we providesearchable subsets, primarily broken down along taxonomic linesso that researchers can choose to search only those sequences thatare relevant (Table 1). The domains of Archaea and Eubacteriaare available as separate search sets. Within eukaryotes, eachkingdom is available as a search set, with many of the kingdomssplit into smaller subsets to allow maximum flexibility inchoosing a search set. Additional search sets that are broken outinclude STS, EST and STACK data, as well as individual humanchromosomes.Users can choose a single data set, or can choose multiple datasets from the subsets provided. This allows researchers to searcha smaller set of sequences if they are trying to determine if theirsequence is already in the database for the species from which itwas obtained. An advantage to researchers working on humansis that they can search on individual chromosomes to determineif their sequence occurs in a larger contig that has been sequencedor to help place the sequence along the chromosome.To support the breakdown of the data into these search sets, theGSDB staff have been extensively reviewing and curating datafields used to identify subsets, including taxonomy and chromo-some data. Ensuring accuracy of these fields means that thesearch subsets will contain all data relevant to the researcher’sneeds.The DeCypher includes accelerated versions of Smith–Waterman,Frame Search, Symmetric Frame Independent and Profile Searchthat will become publicly available for searching data fromGSDB during the first half of 1999.Integration of toolsAnother focus during the past year has been on integration amongthe tools that are used for accessing data from GSDB. Forexample, a search done using Maestro, the web-based query toolthat searches GSDB based on certain fields, will return options toretrieve a sequence in flatfile format; using Excerpt, a script thatretrieves only a portion of a sequence; and Sequence Viewer.Also, Sequence Viewer has options that allow the retrieval of thesequence flatfile, and of a portion of the sequence using Excerpt.FUTURE DIRECTIONSDuring the next year GSDB will become a component of anintegrated biological knowledge system that is designed to houseadditional types of biological data, including expression data,biochemical pathway data, and population polymorphism data.As part of this transition, NCGR intends to offer continued publicaccess to GSDB. NCGR will continue to create new tools anddatabases that are useful to the biological research community.CONTACT INFORMATIONGSDB can be contacted at: National Center for GenomeResources, 1800 Old Pecos Trail, Suite A, Santa Fe, NM 87505, at Cold Spring Harbor Laboratory on January 12, 2015http://nar.oxfordjournals.org/Downloaded from  Nucleic Acids Research, 1999, Vol. 27, No. 138USA. Tel: +1 505 982–7840 or +1 800 450 4854; Email:ncgr@ncgr.org or gsdb@ncgr.org; URL: http://www.ncgr.orgACKNOWLEDGEMENTSThis work was funded by Cooperative Agreement DE-FC03-95ER62062 with the Office of Biological and Environ-mental Research of the Department of Energy.REFERENCES1 Koonin,E.V. and Galperin,M.Y. (1997) Curr. Opin. Genet. Dev., 7,757–763.2 Mushegian,A.R. and Koonin,E.V. (1996) Proc. Natl Acad. Sci. USA, 93,10268–10273.3 Koonin,E.V., Mushegian,A.R. and Rudd,K.E. (1996) Curr. 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Universal Academy Press Inc.Tokyo, Japan, pp. 187–196.20 Burke,J., Wang,H., Hide,W. and Davison,D. (1998) Genome Res., 8,276–290.21 Harger,C., Skupski,M., Bingham,J., Farmer,A., Hoisie,S., Hraber,P.,Kiphart,D., Krakowski,L., McLeod,M., Schwertfeger,J. et al. (1998)Nucleic Acids Res., 26, 21–26. at Cold Spring Harbor Laboratory on January 12, 2015http://nar.oxfordjournals.org/Downloaded from 

The Genome Sequence DataBase: towards an integrated functional genomics resource

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The Genome Sequence DataBase: towards an integrated functional genomics resource

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