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An introduction to biological databases

An introduction to biological databases. August 2001. Database or databank ?. At the beginning, subtle distinctions were done between databases and databanks (in UK, but not in the USA), such as: « Database management programs for the gestion of databanks »

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An introduction to biological databases

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  1. An introduction to biologicaldatabases August 2001

  2. Database or databank ? • At the beginning, subtle distinctions were done between databases and databanks (in UK, but not in the USA), such as: « Database management programs for the gestion of databanks » • From now on, the term « database » (db) is usually preferred

  3. What is a database ? • A collection of • structured • searchable (index) -> table of contents • updated periodically (release) -> new edition • cross-referenced (hyperlinks) -> links with other db data • Includes also associated tools (software) necessary for db access, db updating, db information insertion, db information deletion…. • Data storage managment: flat files, relational databases…

  4. Databases: a « flat file » example « Introduction To Database »Teacher Database (flat file, 3 entries) Accession number: 1 First Name: Amos Last Name: Bairoch Course: DEA=oct-nov-dec 2000 http://www.expasy.org/people/amos.html // Accession number: 2 First Name: Laurent Last name: Falquet Course: EMBnet=sept 2000, sept 2001;DEA=oct-nov-dec 2000; // Accession number 3: First Name: Marie-Claude Last name: Blatter Garin Course: EMBnet=sept 2000; sept 2001; DEA=oct-nov-dec 2000; http://www.expasy.org/people/Marie-Claude.Blatter-Garin.html // • Easy to manage: all the entries are visible at the same time !

  5. Databases: a « relational » example (cont.) Relational database (« table file »): Easier to manage; choice of the output

  6. Why biological databases ? • Explosive growth in biological data • Data (sequences, 3D structures, 2D gel analysis, MS analysis….) are no longer published in a conventional manner, but directly submitted to databases • Essential tools for biological research, as classical publications used to be !

  7. Some statistics • More than 1000 different databases • Generally accessible through the web ( • Google: http://www.google.ch/ • Biohunt: http://www.expasy.org/BioHunt/ • Amos’ links: www.expasy.ch/alinks.html • Variable size: <100Kb to >10Gb • DNA: > 10 Gb • Protein: 1 Gb • 3D structure: 5 Gb • Other: smaller • Update frequency: daily to annually

  8. Biological databases • Some databases in the field of molecular biology… • AATDB, AceDb, ACUTS, ADB, AFDB, AGIS, AMSdb, • ARR, AsDb, BBDB, BCGD, Beanref, Biolmage, • BioMagResBank, BIOMDB, BLOCKS, BovGBASE, • BOVMAP, BSORF, BTKbase, CANSITE, CarbBank, • CARBHYD, CATH, CAZY, CCDC, CD4OLbase, CGAP, • ChickGBASE, Colibri, COPE, CottonDB, CSNDB, CUTG, • CyanoBase, dbCFC, dbEST, dbSTS, DDBJ, DGP, DictyDb, • Picty_cDB, DIP, DOGS, DOMO, DPD, DPlnteract, ECDC, • ECGC, EC02DBASE, EcoCyc, EcoGene, EMBL, EMD db, • ENZYME, EPD, EpoDB, ESTHER, FlyBase, FlyView, • GCRDB, GDB, GENATLAS, Genbank, GeneCards, • Genline, GenLink, GENOTK, GenProtEC, GIFTS, • GPCRDB, GRAP, GRBase, gRNAsdb, GRR, GSDB, • HAEMB, HAMSTERS, HEART-2DPAGE, HEXAdb, HGMD, • HIDB, HIDC, HlVdb, HotMolecBase, HOVERGEN, HPDB, • HSC-2DPAGE, ICN, ICTVDB, IL2RGbase, IMGT, Kabat, • KDNA, KEGG, Klotho, LGIC, MAD, MaizeDb, MDB, • Medline, Mendel, MEROPS, MGDB, MGI, MHCPEP5 • Micado, MitoDat, MITOMAP, MJDB, MmtDB, Mol-R-Us, • MPDB, MRR, MutBase, MycDB, NDB, NRSub, 0-lycBase, • OMIA, OMIM, OPD, ORDB, OWL, PAHdb, PatBase, PDB, • PDD, Pfam, PhosphoBase, PigBASE, PIR, PKR, PMD, • PPDB, PRESAGE, PRINTS, ProDom, Prolysis, PROSITE, • PROTOMAP, RatMAP, RDP, REBASE, RGP, SBASE, • SCOP, SeqAnaiRef, SGD, SGP, SheepMap, Soybase, • SPAD, SRNA db, SRPDB, STACK, StyGene,Sub2D, • SubtiList, SWISS-2DPAGE, SWISS-3DIMAGE, SWISS- • MODEL Repository, SWISS-PROT, TelDB, TGN, tmRDB, • TOPS, TRANSFAC, TRR, UniGene, URNADB, V BASE, • VDRR, VectorDB, WDCM, WIT, WormPep, YEPD, YPD, • YPM, etc .................. !!!!

  9. Distribution of sequence databases • Books, articles 1968 -> 1985 • Computer tapes 1982 ->1992 • Floppy disks 1984 -> 1990 • CD-ROM 1989 -> ? • FTP 1989 -> ? • On-line services 1982 -> 1994 • WWW 1993 -> ? • DVD 2001 -> ?

  10. Categories of databases for Life Sciences • Sequences (DNA, protein) -> Primary db • Genomics • Protein domain/family -> Secondary db • Mutation/polymorphism • Proteomics (2D gel, MS) • 3D structure -> Structure db • Metabolism • Bibliography • Others

  11. Sequence Databases: some « technical » definitions • Data storage management: • flat file: text file • relational (e.g., Oracle) • object oriented (rare in biological field) • Flat file format: • fasta • GCG • NBRF/PIR • MSF…. • standardized format ?

  12. Ideal minimal content of a « sequence » db • Sequences !! • Accession number (AC) • References • Taxonomic data • ANNOTATION/CURATION • Keywords • Cross-references • Documentation

  13. Sequence database: example SWISS-PROT Flat file ID EPO_HUMAN STANDARD; PRT; 193 AA. AC P01588; Q9UHA0; Q9UEZ5; Q9UDZ0; DT 21-JUL-1986 (Rel. 01, Created) DT 21-JUL-1986 (Rel. 01, Last sequence update) DT 20-AUG-2001 (Rel. 40, Last annotation update) DE Erythropoietin precursor. GN EPO. OS Homo sapiens (Human). OC Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; OC Mammalia; Eutheria; Primates; Catarrhini; Hominidae; Homo. OX NCBI_TaxID=9606; RN [1] RP SEQUENCE FROM N.A. RX MEDLINE=85137899; PubMed=3838366; RA Jacobs K., Shoemaker C., Rudersdorf R., Neill S.D., Kaufman R.J., RA Mufson A., Seehra J., Jones S.S., Hewick R., Fritsch E.F., RA Kawakita M., Shimizu T., Miyake T.; RT "Isolation and characterization of genomic and cDNA clones of human RT erythropoietin."; RL Nature 313:806-810(1985). …. CC -!- FUNCTION: ERYTHROPOIETIN IS THE PRINCIPAL HORMONE INVOLVED IN THE CC REGULATION OF ERYTHROCYTE DIFFERENTIATION AND THE MAINTENANCE OF A CC PHYSIOLOGICAL LEVEL OF CIRCULATING ERYTHROCYTE MASS. CC -!- SUBCELLULAR LOCATION: SECRETED. CC -!- TISSUE SPECIFICITY: PRODUCED BY KIDNEY OR LIVER OF ADULT MAMMALS CC AND BY LIVER OF FETAL OR NEONATAL MAMMALS. CC -!- PHARMACEUTICAL: Available under the names Epogen (Amgen) and CC Procrit (Ortho Biotech). … DR EMBL; X02158; CAA26095.1; -. DR EMBL; X02157; CAA26094.1; -. DR EMBL; M11319; AAA52400.1; -. DR EMBL; AF053356; AAC78791.1; -. DR EMBL; AF202308; AAF23132.1; -. DR EMBL; AF202306; AAF23132.1; JOINED. …. KW Erythrocyte maturation; Glycoprotein; Hormone; Signal; Pharmaceutical. taxonomy reference annotations Cross-references Keywords

  14. Sequence database: example (cont.) FT SIGNAL 1 27 FT CHAIN 28 193 ERYTHROPOIETIN. FT PROPEP 190 193 MAY BE REMOVED IN PROCESSED PROTEIN. FT DISULFID 34 188 FT DISULFID 56 60 FT CARBOHYD 51 51 N-LINKED (GLCNAC...). FT CARBOHYD 65 65 N-LINKED (GLCNAC...). FT CARBOHYD 110 110 N-LINKED (GLCNAC...). FT CARBOHYD 153 153 O-LINKED (GALNAC...). FT VARIANT 131 132 SL -> NF (IN AN HEPATOCELLULAR FT CARCINOMA). FT /FTId=VAR_009870. FT VARIANT 149 149 P -> Q (IN AN HEPATOCELLULAR CARCINOMA). FT /FTId=VAR_009871. FT CONFLICT 40 40 E -> Q (IN REF. 1; CAA26095). FT CONFLICT 85 85 Q -> QQ (IN REF. 5). FT CONFLICT 140 140 G -> R (IN REF. 1; CAA26095). ** ** ################# INTERNAL SECTION ################## **CL 7q22; SQ SEQUENCE 193 AA; 21306 MW; C91F0E4C26A52033 CRC64; MGVHECPAWL WLLLSLLSLP LGLPVLGAPP RLICDSRVLE RYLLEAKEAE NITTGCAEHC SLNENITVPD TKVNFYAWKR MEVGQQAVEV WQGLALLSEA VLRGQALLVN SSQPWEPLQL HVDKAVSGLR SLTTLLRALG AQKEAISPPD AASAAPLRTI TADTFRKLFR VYSNFLRGKL KLYTGEACRT GDR // annotation sequence

  15. Sequence database: example …a SWISS-PROT entry, in fasta format: >sp|P01588|EPO_HUMAN ERYTHROPOIETIN PRECURSOR - Homo sapiens (Human). MGVHECPAWLWLLLSLLSLPLGLPVLGAPPRLICDSRVLERYLLEAKEAE NITTGCAEHCSLNENITVPDTKVNFYAWKRMEVGQQAVEVWQGLALLSEA VLRGQALLVNSSQPWEPLQLHVDKAVSGLRSLTTLLRALGAQKEAISPPD AASAAPLRTITADTFRKLFRVYSNFLRGKLKLYTGEACRTGDR

  16. Database 1: nucleotide sequence Laurent Falquet

  17. Databases 2: genomics • Contain information on genes, gene location (mapping), gene nomenclature and links to sequence databases; has usually no sequence; • Exist for most organisms important for life science research; • Examples: MIM, GDB (human), MGD (mouse), FlyBase (Drosophila), SGD (yeast), MaizeDB (maize), SubtiList (B.subtilis), etc.; • Format: generally relational (Oracle, SyBase or AceDb).

  18. MIM • OMIM™: Online Mendelian Inheritance in Man • a catalog of human genes and genetic disorders • contains a summary of literature, pictures, and reference information. It also contains numerous links to articles and sequence information.

  19. MIM: example *133170 ERYTHROPOIETIN; EPO Alternative titles; symbols EP TABLE OF CONTENTS TEXT REFERENCES SEE ALSO CONTRIBUTORS CREATION DATE EDIT HISTORY Database Links Gene Map Locus: 7q21 Note: pressing the symbol will find the citations in MEDLINE whose text most closely matches the text of the preceding OMIM paragraph, using the Entrez MEDLINE neighboring function. TEXT Human erythropoietin is an acidic glycoprotein hormone with molecular weight 34,000. As the prime regulator of red cell production, its major functions are to promote erythroid differentiation and to initiate hemoglobin synthesis. Sherwood and Shouval (1986) described a human renal carcinoma cell line that continuously produces erythropoietin. Eschbach et al. (1987) demonstrated the effectiveness of recombinant human erythropoietin in treating the anemia of end-stage renal disease. Lee-Huang (1984) cloned human erythropoietin cDNA in E. coli. McDonald et al. (1986) and Shoemaker and Mitsock (1986) cloned the mouse gene and the latter workers showed that coding DNA and amino acid sequence are about 80% conserved between man and mouse. This is a much higher order of conservation than for various interferons, interleukin-2, and GM-CSF. ……

  20. For information:Sequence and genomic database projects- Ensembl- TIGR

  21. Ensembl: automatic annotation of eukaryotic genomes • Contains all the human genome DNA sequences currently available in the public domain. • Automated annotation: by using different software tools, features are identified in the DNA sequences: • Genes (known or predicted) • Single nucleotide polymorphisms (SNPs) • Repeats • Homologies • Created and maintained by the EBI and the Sanger Center (UK)

  22. Ensembl: www.ensembl.org With Ensembl you can ... - Search the DNA from the human genome - Browse chromosomes - Find genes, SNPs and mouse genome matches - Look for proteins and protein families Ensemble provides: - Identification of 90% of known human genes in the genome sequence - Prediction of 10,000 additional genes, all with supporting evidence

  23. Ensembl: Browse chromosomes

  24. The Institute for Genomic Research (TIGR) The TIGR Databases are a collection of curated databases containing: DNA and proteinsequence, gene expression, cellular role, protein family, taxonomic data Almost for microbes, plants but also humans. TIGR is engaged insequencing BACs from human chromosome 16 as well as a large-scale BAC end sequencing project.

  25. Database 3: protein sequence • SWISS-PROT: created in 1986 (A.Bairoch) http://www.expasy.org/sprot/ • TrEMBL: created in 1996; complement to SWISS-PROT; derived from automated EMBL CDS translations (« proteomic » version of EMBL) • PIR-PSD: Protein Information Resources http://pir.georgetown.edu/

  26. Database 3: protein sequence • PRF: Protein Research Foundation (Japan): Peptide/Protein Sequence Database (PRF/SEQDB) http://www.prf.or.jp/en/index.html • GenPept: produced by parsing the corresponding GenBank release for translated coding regions. • Many specialized protein databases for specific families or groups of proteins. • Examples: YPD (yeast proteins), AMSDb (antibacterial peptides), GPCRDB (7 TM receptors), IMGT (immune system) etc.

  27. SWISS-PROT • Collaboration between the SIB (CH) and EMBL/EBI (UK) • Fully-annotated (manually), non-redundant, cross-referenced, documented protein sequence database. • ~100 ’000 sequences from more than 6’800 different species; 70 ’000 references (publications); 550 ’000 cross-references (databases); ~200 Mb of annotations. • Weekly releases; available from about 50 servers across the world, the main source being ExPASy

  28. SWISS-PROT: example Never changed

  29. SWISS-PROT (cont.)

  30. SWISS-PROT (cont.)

  31. TrEMBL (TRanslation of EMBL) • We cannot cope with the speed with which new data is coming out AND we do not want to dilute the quality of SWISS-PROT -> TrEMBL, created in 1996. • TrEMBL is automatically generated (from annotated EMBL coding sequences (CDS)) and annotated using software tools. • Contains all what is not yet in SWISS-PROT. SWISS-PROT + TrEMBL = all known protein sequences. • Well-structured SWISS-PROT-like resource.

  32. The simplified story of a SWISS-PROT entry cDNAs, genomes, …. • « Automatic » • Redundancy check (merge) • Family attribution (InterPro) • Annotation (computer) EMBLnew EMBL CDS TrEMBLnew TrEMBL • «Manual» • Redundancy (merge, conflicts) • Annotation (manual) • SWISS-PROT tools (macros…) • SWISS-PROT documentation • Medline • Databases (MIM, MGD….) • Brain storming SWISS-PROT Once in SWISS-PROT, the entry is no more in TrEMBL, but still in EMBL (archive) CDS: proposed and submitted at EMBL by authors or by genome projects (can be experimentally proved or derived from gene prediction programs). TrEMBL does not translate DNA sequences, nor use gene prediction programs: only take CDS already annotated in the EMBL entry.

  33. The two defined classes of entries are: • STANDARD • Data which are complete to the standards laid down by • the SWISS-PROT database. • PRELIMINARY • Sequence entries which have not yet been annotated by • the SWISS-PROT staff up to the standards laid down by • SWISS-PROT. These entries are exclusively found in • TrEMBL. • Remark 1: • Some PRELIMINARY entries are manually CURATED • (there is no flag yet for utilisators, but soon…) Remark 2: • TrEMBL= SPTrEMBL + REMTrEMBL: SPTrEMBL contains TrEMBL entries which are going to be integrated into SWISS-PROT. • SPTR (SWall) = SWISS-PROT + TrEMBL + TrEMBLnew

  34. TrEMBL: a platform for the improvement of automatic annotation tools • After a lot of testing, many new annotation tools are going to be applied systematically (SignalP, TMMPred, REP, InterPro domain assignement). • EVIDENCE TAGS are added to any part of a TrEMBL entry not derived from the original EMBL entry (not visible for external users). • -> follow up of all added informations

  35. TrEMBL: example « Old » TrEMBL which does not exist anymore, because it has been integrated into the SWISS-PROT EPO_HUMAN entry: low redundancy

  36. Redundancy • SWISS-PROT and TrEMBL introduces some degree of • redundancy • Only 100 % identical sequences are automatically merged • between SWISS-PROT and TrEMBL; • Complete sequences or fragments with 1-3 conflicts will be • automatically merged soon (first genome projects; • check for chromosomal location and gene names)

  37. SWISS-PROT / TrEMBL: a minimal of redundancy Human EPO: Blastp results

  38. SWISS-PROT and TrEMBL introduce a new arithmetical concept ! How many sequences in SWISS-PROT + TrEMBL ? 100’000 + 540’000 = about 400’000 (august 2001) • SWISS-PROT and TrEMBL (SPTR) a minimum of redundancy

  39. SWISS-PROT and TrEMBL introduce a new arithmetical concept ! In the case of human data, the redundancy is very high: 7’300 + 33’000 = about 20’000

  40. Database 3: Protein sequence Something else ?

  41. Database 3: protein sequence • PIR-PSD: Protein Information Resources http://pir.georgetown.edu/ • PRF: Protein Research Foundation (Japan): Peptide/Protein Sequence Database (PRF/SEQDB) http://www.prf.or.jp/en/index.html • GenPept: produced by parsing the corresponding GenBank release for translated coding regions. • Many specialized protein databases for specific families or groups of proteins. • Examples: YPD (yeast proteins), AMSDb (antibacterial peptides), GPCRDB (7 TM receptors), IMGT (immune system) etc.

  42. PIR-International Protein Sequence Database (PIR-PSD) • Protein Information Resource, created in 1984 • Maintained by MIPS (Germany) and JIPID (Japan) • Successor of the National Biochemical Research Foundation (NBRF) protein sequence database developed in 1965 by M. O. Dayhoff « Atlas of Protein Sequence and Structure » • Also produce a computer generated supplemental database of GenBank/EMBL translations (PATCHX) • « Well » annotated • Automatically classified into protein families (ProClass). • In august 2001: 239’764 entries.

  43. PIR-PSD: example « well annotated »

  44. Database 4: protein domain/family • Contains biologically significant « pattern / profiles/ HMM » formulated in such a way that, with appropriate computional tools, it can rapidly and reliably determine to which known family of proteins (if any) a new sequence belongs to • -> tools to identify what is the function of uncharacterized proteins translated from genomic or cDNA sequences (« functional diagnostic »)

  45. Protein domain/family • Most proteins have « modular » structure • Estimation: ~ 3 domains / protein • Domains (conserved sequences or structures) are identified by multi sequence alignments • Domains can be defined by different methods: • Pattern (regular expression); used for very conserved domains • Profiles (weighted matrices): two-dimensional tables of position specific match-, gap-, and insertion-scores, derived from aligned sequence families; used for less conserved domains • Hidden Markov Model (HMM); probabilistic models; an other method to generate profiles.

  46. Some statistics • 15 most common protein domains for H. sapiens(Incomplete) Immunoglobulin and major histocompatibility complex domain Zinc finger, C2H2 type Eukaryotic protein kinase Rhodopsin-like GPCR superfamily Pleckstrin homology (PH) domain RING finger Src homology 3 (SH3) domain RNA-binding region RNP-1 (RNA recognition motif) EF-hand family Homeobox domain Krab box PDZ domain (also known as DHR or GLGF) Fibronectin type III domain EGF-like domain Cadherin domain http://www.ebi.ac.uk/proteome/HUMAN/interpro/top15d.html

  47. Protein domain/family db • Secondary databases are the fruit of analyses of the sequences found in the primary sequence db • Either manually curated (i.e. PROSITE, Pfam, etc.) or automatically generated (i.e. ProDom, DOMO) • Some depend on the method used to detect if a protein belongs to a particular domain/family (patterns, profiles, HMM)

  48. Protein domain/family db PROSITE Patterns /Profiles ProDom Aligned motifs PRINTS Aligned motifs Pfam HMM (Hidden Markov Models) SMART HMM BLOCKS Aligned motifs InterPro

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