Bioinformatics. Biomolecular databases

Transcription

1 Bioinformatics Biomolecular databases Jacques van HeldenFORMER ADDRESS ( ) Université Libre de Bruxelles, Belgique Bioinformatique des Génomes et des Réseaux (BiGRe lab) B!GRe Bioinformatique des Génomes et Réseaux NEW ADDRESS (since Nov 1 st, 2011) Jacques.van-Helden@univ-amu.fr Université d Aix-Marseille, France Lab. Technological Advances for Genomics and Clinics (TAGC, INSERM Unit U1090) U1090!"#$%&'&()#*'+*,-*%#".+/&0+("%&1)#.+*%,+#')%)#.

2 Contents Examples of biological databases Nucleic sequences: Genbank, EMBL, and DDBJ Protein sequences: UniProt The Gene Ontology (GO) project Issues and perspectives for biological databases

3 Biomolecular Databases Examples of biomolecular databases Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

4 Examples of biomolecular databases Sequence and structure databases Protein sequences (UniProt) DNA sequences (EMBL, Genbank, DDBJ) 3D structures (PDB) Structural motifs (CATH) Sequence motifs (PROSITE, PRODOM) Genome sequences and annotations Genome-specific databases (SGD, FlyBase, AceDB, PlasmoDB, ) Multiple genomes (Integr8, NCBI, KEGG, TIGR, ) Molecular functions Transcriptional regulation (TRANSFAC, RegulonDB, InteractDB) Enzymatic catalysis (Expasy, LIGAND/KEGG, BRENDA) Transport (YTPdb) Biological processes Metabolic pathways (EcoCyc, LIGAND/KEGG, Biocatalysis/biodegradation) Signal transduction pathways (CSNdb, Transpath) Protein-protein interactions (DIP, BIND, MINT) Gene networks (GeneNet, FlyNets)

5 Databases of databases There are hundreds of databases related to molecular biology and biochemistry. New databases are created every year. Every year, the first issue of Nucleic Acids Research is dedicated to biological databases Issue: The same journal maintains a database of databases: the Molecular Biology Database Collection Some bioinformatics centres maintain multiple database, with cross-links between them. The SRS server at EBI holds an impressive collection of databases.

6 Biomolecular Databases Nucleic sequence databases: GenBank, EMBL, and DDBJ Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

7 Nucleic sequence databases To publish an article dealing with a sequence, scientific journals impose to have previously deposited this sequence in a reference database. There are 3 main repositories for nucleic acid sequences. Sequences deposited in any of these 3 databases are automatically synchronized in the 2 other ones. Okubo et al. (2006) NAR 34: D6-D9

8 The sequencing pace Nucleic sequences Genbank (April 2011) 126,551,501,141 bases in 135,440,924 sequence records in the traditional GenBank divisions 191,401,393,188 bases in 62,715,288 sequence records in the Whole Genome Ssequencing Entire genomes GOLD Release V.2 (Oct 2011) contains ~2000 completely sequenced genomes. Protein sequences Essentially obtained by translation of putative genes in nucleic sequences (almost no direct protein sequencing). UniProtKB/TrEMBL (2011) contains 17 millions of protein sequences. Adapted from Didier Gonze

9 Size of the nucleotide database EMBL Nucleotide Sequence Database: Release Notes - Release 113 September Class entries nucleotides! ! CON:Constructed 7,236, ,112,791,043! EST:Expressed Sequence Tag 73,715,376 40,997,082,803! GSS:Genome Sequence Scan 34,528,104 21,985,922,905! HTC:High Throughput CDNA sequencing 491, ,229,662! HTG:High Throughput Genome sequencing 152,599 25,159,746,658! PAT:Patents 24,364,832 12,117,896,594! STD:Standard 13,920,617 37,665,112,606! STS:Sequence Tagged Site 1,322, ,037,867! TSA:Transcriptome Shotgun Assembly 8,085,693 5,663,938,279! WGS:Whole Genome Shotgun 88,288, ,661,696,545! ! Total 252,106, ,481,663,919!! Division entries nucleotides! ! ENV:Environmental Samples 30,908,230 14,420,391,278! FUN:Fungi 6,522,586 11,614,472,226! HUM:Human 32,094,500 38,072,362,804! INV:Invertebrates 31,907,138 52,527,673,643! MAM:Other Mammals 40,012, ,678,620,711! MUS:Mus musculus 11,745,671 19,701,637,499! PHG:Bacteriophage 8,511 85,549,111! PLN:Plants 52,428,994 55,570,452,118! PRO:Prokaryotes 2,808,489 28,807,572,238! ROD:Rodents 6,554,012 33,326,106,733! SYN:Synthetic 4,045, ,174,055! TGN:Transgenic 285, ,743,891! UNC:Unclassified 8,617,225 4,957,442,673! VRL:Viruses 1,358,528 1,518,575,082! VRT:Other Vertebrates 22,809,428 42,568,889,857! ! Total 252,106, ,481,663,919!

10 Genbank (NCBI - USA)

11 The EMBL Nucleotide Sequence Database (EBI - UK)

12 DDBJ - DNA Data Bank of Japan

13 Size of the nucleic sequence databases Summary of database contents for the 3 main databases of nucleic sequences. Source: NAR database issue January Bases (without shotgun) bases (including shotgun) Organisms URL Sequences DDBJ 2.0E E+09 EMBL 1.0E E+05 GenBank 4.6E E E E+05

14 Biomolecular Databases UniProt : protein sequences and functional annotations Jacques.van.Helden@ulb.ac.be Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

15 UniProt - the Universal Protein Resource Database content (Sept 2012) UniProtKB: 24,532,088 entries Translation of EMBL coding sequences (non-redundant with Swiss-Prot) UniProtKB/Swiss-Prot section (reviewed): 537,505 entries annotation by experts high information content many references to the literature good reliability of the information The rest (90% of the entries) Automatic annotation by sequence similarity. Features The most comprehensive protein database in the world. A huge team: >100 annotators + developers. Annotation by experts: annotators are specialized for different types of proteins or organisms. World-wide recognized as an essential resource. References Bairoch et al. The SWISS-PROT protein sequence data bank. Nucleic Acids Res (1991) vol. 19 Suppl pp The UniProt Consortium. The Universal Protein Resource (UniProt) Nucleic Acids Res (2008). Database Issue. Taxonomic distribution of the sequences Number of entries (polypeptides) in Swiss-Prot Within Eukaryotes

16 UniProt example - Human Pax-6 protein Header : name and synonyms

17 UniProt example - Human Pax-6 protein Human-based annotation by specialists

18 UniProt example - Human Pax-6 protein Structured annotation : keywords and Gene Ontology terms

19 UniProt example - Human Pax-6 protein Protein interactions; Alternative products

20 UniProt example - Human Pax-6 protein Detailed description of regions, variations, and secondary structure

21 UniProt example - Human Pax-6 protein Peptidic sequence

22 UniProt example - Human Pax-6 protein References to original publications

23 UniProt example - Human Pax-6 protein Cross-references to many databases (fragment shown)

24 3D Structure of macromolecules Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

25 PDB - The Protein Data Bank

26 Genome browsers Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

27 EnsEMBL Genome Browser (Sanger Institute + EBI)

28 UCSC Genome Browser (University California Santa Cruz - USA) Human gene Pax6 aligned with Vertebrate genomes

29 UCSC Genome Browser (University California Santa Cruz - USA) Drosophila gene eyeless (homolog to Pax6) aligned with Insect genomes

30 UCSC Genome Browser (University California Santa Cruz - USA) Drosophila 120kb chromosomal region covering the Achaete-Scute Complex

31 ECR Browser

32 EnsEMBL - Example: Drosophila gene Pax6

33 Comparative genomics Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

34 Integr8 - access to complete genomes and proteomes

35 Integr8 - genome summaries

36 Integr8 - clusters of orthologous genes (COGs)

37 Integr8 - clusters of paralogous genes

38 Databases of protein domains Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

39 Prosite - protein domains, families and functional sites

40 Prosite - aligned sequences and logo Some of the sequences that were used to built the Prosite profile for the Zn(2)-C6 fungal-type DNAbinding domain (ZN2_CY6_FUNGAL_2, PS50048). The Sequence Logo (below) indicates the level of conservation of each residue in each column of the alignment. Note the 6 cysteines, characteristic of this domain.

41 Prosite - Example of profile matrix

42 Prosite - Example of sequence logo

43 Prosite - Example of domain signature The domain signature is a string-based pattern representing the residues that are characteristic of a domain.

44 PFAM (Sanger Institute - UK) Protein families represented by multiple sequence alignments and hidden Markov models (HMMs)

45 CATH - Protein Structure Classification CATH is a hierarchical classification of protein domain structures, which clusters proteins at four major levels: Class (C), Architecture (A), Topology (T) Homologous superfamily (H). The boundaries and assignments for each protein domain are determined using a combination of automated and manual procedures which include computational techniques, empirical and statistical evidence, literature review and expert analysis. References Orengo et al. The CATH Database provides insights into protein structure/ function relationships. Nucleic Acids Res (1999) vol. 27 (1) pp Cuff et al. The CATH classification revisited--architectures reviewed and new ways to characterize structural divergence in superfamilies. Nucleic Acids Res (2008) pp.

46 CATH - Protein Structure Classification

47 InterPro (EBI - UK)

48 InterPro (EBI - UK) Antennapedia-like Homeobox (entry IPR001827)

49 Biomolecular Databases The Gene Ontology (GO) database Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

50 Ontology definition Ontologie: partie de la métaphysique qui s'intéresse à l'être en tant qu'être, indépendamment de ses déterminations particulières Ontology: part of the metaphysics that focusses on the being as a beging, independently of its particular determinations Le Petit Robert - dictionnaire alphabétique et analogique de la langue française. 1993

51 The "bio-ontologies" Answer to the problem of inconsistencies in the annotations Controlled vocabulary Hierarchical classification between the terms of the controlled vocabulary E.g.: The Gene Ontology molecular function ontology process ontology cellular component ontology

52 Gene ontology: processes

53 Gene ontology: molecular functions

54 Gene ontology: cellular components

55 Gene Ontology Database

56 Gene Ontology Database ( Example: methionine biosynthetic process

57 Status of GO annotations (NAR DB issue 2006) Term definitions Biological process terms 9,805 Molecular function terms 7,076 Cellular component terms 1,574 Sequence Ontology terms 963 Genomes with annotation 30 Excludes annotations from UniProt, which represent 261 annotated proteomes. Annotated gene products Total 1,618,739 Electronic only 1,460,632 Manually curated 158,107

58 QuickGO ( Web site A user-friendly Web interface to the Gene Ontology. Graphical display of the hierarchical relationships between terms. Convenient browsing between classes.

59 Remarks on "bio-ontologies" Improvement compared to free text controlled vocabulary (choice among synonyms) hierarchical relationships between the concepts Nothing to do with the philosophical concept of ontology A "bio-ontologies" is usually nothing more than a taxonomical classification of the terms of a controlled vocabulary Multiple possibilities of classification criteria e.g. compartment subtypes (plasma membrane is a membrane) e.g. compartment locations (nucleus is inside cytoplasm is inside plasma membrane) To be useful, should remain purpose-based each biologist might wish to define his/her own classification based on his/her needs and scope of interest impossible to define a unifying standard for all biologists No representation of molecular interactions relationships between objects are only hierarchical, not horizontal or cyclic e.g. does not describe which genes are the target of a given transcription factor

60 What is biological function? A general definition Fonction: action, rôle caractéristique dun élément, dun organe, dans un ensemble (souvent opposé à structure). Source: Le Petit Robert - dictionnaire alphabetique et analogique de la langue francaise Function: characteristic action (role) of an element (organ) within an set (often opposed to structure) Function and gene ontology Understanding the function requires to establish the link between molecular activity and the context in which it takes place (process). Multifunctionality Same activity can play different roles in different processes. Example: scute gene in Drosophila melanogaster: a transcription factor (activity) involved in sex determination, determination of neural precursors and malpighian tubules (3 processes). Multiple activities of a same protein in a given process Example: aspatokinase PutA in Escherichia coli, contains 2 enzymatic domains (enzymatic activities) + a DNA-binding domain (DNA binding transcription factor) -> 3 molecular activities in the same process (proline utilization).

61 Biomolecular Databases Small compounds, reactions and metabolic pathways Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

62 LIGAND - Small compounds and metabolic reactions

63 KEGG - Kyoto Encycplopaedia of Genes and Genomes

64 Ecocyc, BioCyc and Metacyc - Metabolic pathways

65 Biomolecular Databases Protein interaction networks and transduction pathways Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

66 Biomolecular Databases Microarray databases Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

67 Human genome resources Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

68 HapMap The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Associations between genetic variations (SNPs,...) and diseases + response to pharmaceuticals.

69 Biomolecular Databases Issues for biomolecular databases Université Libre de Bruxelles, Belgique Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe)

70 Issues for biological databases Dealing with biological complexity Data content Coverage Information content Data quality Data structure Consistency Query capabilities Interfaces User interfaces Programmatic interfaces Annotation Funding

71 Towards biological complexity The main databases currently available are focussed on one type of molecular entity : nucleic sequences, proteins, compounds, This type of organization is very convenient as far as the information to be represented is simple (e.g. DNA sequences, structures of small molecules and macromolecules). It becomes more difficult if we want to represent the interactions between biological objects, the integration of various elements in a biological process (metabolic pathways, protein interaction networks, regulatory networks, ) complex concepts such as biological function

72 Data content Scope of the database types of biological objects represented Number of entries coverage of the current knowledge Information content Level of detail in the description of the biological objects References to the source of information

73 Data quality Data Consistency always use the same name to indicate the same object (this seems trivial, but its is unfortunately still not always the case) event better: define an ID for each objects, and allow to retrieve it by any of its synonyms spelling mistakes Data Structuration distinct fields for distinct attributes of the biological objects Reliability Evidences? Level of confidence? Assignation of function by similarity recursive process propagation of errors

74 Query capabilities Browsing (click and read) Simple search select records with some constraints More elaborate search select specific fields of some records with constraints on some fields (~SQL SELECT) Complex querying ability to return an answer that results from a "live" computation, and was not part of any record of the dabatase

75 Interfaces User interfaces user-friendly convenient browsing intuitive query forms visualization (graphical output) Programmatic interfaces communication with external programs: other databases (concept of distributed database) analysis tools

76 Annotation Problem The flow of available data is increasing exponentially Strategies internal curators selected external experts public submission computer-based extraction of information from biological texts

77 Funding Public funding Problem: easier to obtain public funds for creating a new database than for maintaining or expanding existing resources Private funding Industrial companies are ready to invest in good data and good query capabilities interested by academic expertise Solutions All users pay (per query for example) Note: academic users are anyway funded by public funds Hybrid solution access is free for academic users, not for companies companies can buy the whole database an install it in-house (+ add their own private data) academia-industry interface is often ensured by a spinoff company