Sequence formats and databases in bioinformatics

Transcription

1 Sequence formats and databases in bioinformatics Definitions/Basics Sequence formats Databases in Biology Dinesh Gupta Structural and Computational Biology Group ICGEB

2 What is Bioinformatics? Bioinformatics is the use of computers to solve biological and biomedical problems. Bioinformatics is the application of information technology to mine, visualize, analyze, integrate, and manage biological and genetic information, which can then be applied in, among other things, accelerating drug discovery and development. Application of tools of computation and analysis to the capture and interpretation of biological data. Biological Data management and analysis. NIH definition of Bioinformatics ( Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data.

3 Use of Bioinformatics DNA analysis Genome sequencing Sequence assembly Sequence/gene annotations Genefinding/Sequence translation tools Sequence Similarity searching (eg. BLAST, ClustalW) Comparison between genomes Evolution of sequences (Phylogenetic analysis) Gene expression

4 Use of Bioinformatics (..contd.) Protein analysis Structure X-ray crystallography Homology based models Drug designing Sequence Sequence similarity Protein family assignments Conserved motifs Proteomics data analysis Protein Evolution

5 Uses of Bioinformatics (..contd.) Other uses: Drug designing Vaccine development Dairy technology Forensics Crop improvement Designing enzymes for detergents Genetic counseling

6 Bioinformatics: Integration of several fields Physics Computer Science Biological Science Bioinformatics Mathematics Statistics Chemistry

7 Recent events making bioinformatics more important Exponential expansion of biological information Expansion of multiple types of information Cheaper high throughput technologies Improvement in computation power Lack of standards/quality Need for micro and macro analysis Need for better algorithms

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9 Vast Growth in (Structural) Data... but number of Fundementally New (Fold) Parts Not Increasing that Fast Total in Databank New Submissions New Folds

10 Bioinformatics Analysis? It is like any other lab analysis! You need to know your data/input sources You need to understand your methods and their assumptions You need a plan to get from point A to point B You need to understand your equipment You need to be critical and understand potential sources of error You need to interpret your results Your results need to be reproducible Your results should be testable

11 References, but not limited to: Baxevanis & Ouellette Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins 2 nd Edition. John Wiley Publishing. Gibas & Jambeck Developing Bioinformatics Computer Skills. O Reilly. Bioinformatics: Genome Sequence Analysis Mount 2001 Bioinformatics For Dummies Claverie & Notredame 2003 Introduction to Bioinformatics Lesk 2002

12 Sequence formats: Basics Why different formats? Type of information Software requirements Database requirements

13 Main file formats used in Bioinformatics ASN.1 EMBL, Swiss Prot FASTA GCG GenBank/GenPept PHYLIP PIR

14 ASN 1: Abstract Syntax Notation 1 used by NCBI Seq-entry ::= set { class phy-set, descr { pub { pub { article { title { name "Cross-species infection of blood parasites between resident and migratory songbirds in Africa" }, authors { names std { { name name { last "Waldenstroem", first "Jonas", initials "J." } }, { name name { last "Bensch", first "Staffan", initials "S." } }, { name name { last "Kiboi", first "Sam", initials "S." } }, { name name { last "Hasselquist", first "Dennis", initials "D." } }, { name name {

15 The first line of each sequence entry is the ID definition line which contains entry name, dataclass, molecule, division and sequence length. XX line contains no data, just a separator The AC line lists the accession number. DE line gives description about the sequence FT precise annotation for the sequence Sequence information SQ in the first two spaces. The sequence information begins on the fifth line of the sequence entry. The last line of each sequence entry in the file is a terminator line which has the two characters // in the first two spaces. EMBL/Swiss Prot ( ID AA03518 standard; DNA; FUN; 237 BP. XX AC U03518; XX AC U03518; XX DE Aspergillus awamori internal transcribed spacer 1 (ITS1) and 18S DE rrna and 5.8S rrna genes, partial sequence. DE rrna and 5.8S rrna genes, partial sequence. RX MEDLINE; RX PUBMED; XX FT rrna <1..20 FT /product="18s ribosomal RNA" FT misc_rna FT /standard_name="internal transcribed spacer 1 (ITS1)" FT rrna 206..>237 FT /product="5.8s ribosomal RNA" SQ Sequence 237 BP; 41 A; 77 C; 67 G; 52 T; 0 other; aacctgcgga aggatcatta ccgagtgcgg gtcctttggg cccaacctcc catccgtgtc 60 tattgtaccc tgttgcttcg gcgggcccgc cgcttgtcgg ccgccggggg ggcgcctctg 120 ccccccgggc ccgtgcccgc cggagacccc aacacgaaca ctgtctgaaa gcgtgcagtc 180 tgagttgatt gaatgcaatc agttaaaact ttcaacaatg gatctcttgg ttccggc 237 //

16 FASTA A sequence in Fasta format begins with a single-line description, followed by lines of sequence data. The description line is distinguished from the sequence data by a greaterthan (">") symbol in the first column. It is recommended that all lines of text be shorter than 80 characters in length. >U03518 Aspergillus awamori internal transcribed spacer 1 (ITS1) AACCTGCGGAAGGATCATTACCGAGTGCGGGTCCTTTGGGCCCAACCTCCCATCCGTGTCTATTGTACCC TGTTGCTTCGGCGGGCCCGCCGCTTGTCGGCCGCCGGGGGGGCGCCTCTGCCCCCCGGGCCCGTGCCCGC CGGAGACCCCAACACGAACACTGTCTGAAAGCGTGCAGTCTGAGTTGATTGAATGCAATCAGTTAAAACT TTCAACAATGGATCTCTTGGTTCCGGC

17 GCG Exactly one sequence Begins with annotation lines Start of the sequence is marked by a line ending with ".. This line also contains the sequence identifier, the sequence length and a checksum ID AA03518 standard; DNA; FUN; 237 BP. XX AC U03518; XX DE Aspergillus awamori internal transcribed spacer 1 (ITS1) and 18S DE rrna and 5.8S rrna genes, partial sequence. XX SQ Sequence 237 BP; 41 A; 77 C; 67 G; 52 T; 0 other; AA03518 Length: 237 Check: aacctgcgga aggatcatta ccgagtgcgg gtcctttggg cccaacctcc catccgtgtc 61 tattgtaccc tgttgcttcg gcgggcccgc cgcttgtcgg ccgccggggg ggcgcctctg 121 ccccccgggc ccgtgcccgc cggagacccc aacacgaaca ctgtctgaaa gcgtgcagtc 181 tgagttgatt gaatgcaatc agttaaaact ttcaacaatg gatctcttgg ttccggc

18 GenBank/GenPept The nucleotide (GenBank) and protein (Gen Pept) database entries are available from Entrez in this format Can contain several sequences One sequence starts with: LOCUS The sequence starts with: "ORIGIN The sequence ends with: "// LOCUS AAU bp DNA PLN 04-FEB-1995 DEFINITION Aspergillus awamori internal transcribed spacer 1 (ITS1) and 18S rrna and 5.8S rrna genes, partial sequence. ACCESSION U03518 BASE COUNT 41 a 77 c 67 g 52 t ORIGIN 1 aacctgcgga aggatcatta ccgagtgcgg gtcctttggg cccaacctcc catccgtgtc 61 tattgtaccc tgttgcttcg gcgggcccgc cgcttgtcgg ccgccggggg ggcgcctctg 121 ccccccgggc ccgtgcccgc cggagacccc aacacgaaca ctgtctgaaa gcgtgcagtc 181 tgagttgatt gaatgcaatc agttaaaact ttcaacaatg gatctcttgg ttccggc //

19 Phylip format G019uabh ATACATCATA ACACTACTTC CTACCCATAA GCTCCTTTTA ACTTGTTAAA G028uaah CATAAGCTCC TTTTAACTTG TTAAAGTCTT GCTTGAATTA AAGACTTGTT GTCTTGCTTG AATTAAAGAC TTGTTTAAAC ACAAAAATTT AGAGTTTTAC TAAACACAAA ATTTAGACTT TTACTCAACA AAAGTGATTG ATTGATTGAT TCAACAAAAG TGATTGATTG ATTGATTGAT TGATTGATGG TTTACAGTAG TGATTGATTG ATGGTTTACA GTAGGACTTC ATTCTAGTCA TTATAGCTGC The first line of the input file contains the number of sequences and their length (all should have the same length) separated by blanks. The next line contains a sequence name, next lines are the sequence itself in blocks of 10 characters. Then follow rest of sequences.

20 Other formats MEGA #mega Title: infile.fasta #G019uabh ATACATCATAACACTACTTCCTACCCATAAGCTCCTTTTAACTTGTTAAAGTCTTGCTTG AATTAAAGACTTGTTTAAACACAAAAATTTAGAGTTTTACTCAACAAAAGTGATTGATTG ATTGATTGATTGATTGATGGTTTACAGTAGGACTTCATTCTAGTCATTATAGCTGCTGGC AGTATAACTGGCCAGCCTTTAATACATTGCTGCTTAGAGTCAAAGCATGTACTTAGAGTT GGTATGATTTATCTTTTTGGTCTTCTATAGCCTCCTTCCCCATCCCCATCAGTCTTAATC AGTCTTGTTACGTTATGACTAATCTTTGGGGATTGTGCAGAATGTTATTTTAGATAAGCA AAACGAGCAAAATGGGGAGTTACTTATATTTCTTTAAAGC #G028uaah CATAAGCTCCTTTTAACTTGTTAAAGTCTTGCTTGAATTAAAGACTTGTTTAAACACAAA ATTTAGACTTTTACTCAACAAAAGTGATTGATTGATTGATTGATTGATTGATGGTTTACA GTAGGACTTCATTCTAGTCATTATAGCTGCTGGCAGTATAACTGGCCAGCCTTTAATACA TTGCTGCTTAGAGTCAAAGCATGTACTTAGAGTTGGTATGATTTATCTTTTTGGTCTTCT ATAGCCTCCTTCCCCATCCCATCAGTCT

21 ReadSeq Don Gilbert May 2001 Indiana University, Bloomington, Indiana WWW Seqret A program in EMBOSS suite

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27 The Readseq package can read most common formats: examples of all these formats are included in the readseq directory. The formats include: IG/Stanford, used by Intelligenetics and others GenBank/GB, genbank flatfile format NBRF format (SAM modifications cause this to break when sequences do not have a terminating asterix) EMBL, EMBL flatfile format GCG, single sequence format of GCG software DNAStrider, for common Mac program Fitch format, limited use Pearson/Fasta, a common format used by Fasta programs and others Zuker format, limited use. Input only. Olsen, format printed by Olsen VMS sequence editor. Input only. Phylip3.2, sequential format for Phylip programs Plain/Raw, sequence data only (no name, document, numbering) MSF multi sequence format used by GCG software PAUP's multiple sequence (NEXUS) format PIR/CODATA format used by PIR

28 Databases in Biology

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30 Need for databases in Biology? Need for storing and communicating large datasets has grown. Need to disseminate biological information. Provide Organized data for analysis friendly retrieval. Need to make biological data available in computerreadable form.

31 Different classifications of databases Type of data nucleotide sequences protein sequences proteins sequence patterns or motifs macromolecular 3D structure gene expression data metabolic pathways proteomics data

32 Different classifications of databases. Primary or derived databases Primary databases: experimental results directly into database Secondary databases: results of analysis of primary databases Aggregate of many databases Links to other data items Combination of data Consolidation of data

33 Different classifications of databases. Technical design Flat-files Relational database (SQL) Exchange/publication technologies (HTML, CORBA, XML,...) Each one of the above are inter convertible

34 Different classifications of databases. Availability Publicly available, no restrictions Available, but with copyright Accessible, but not downloadable Academic, but not freely available Proprietary, commercial; possibly free for academics

35 Different classifications of databases. Content Protein/DNA/RNA/miRNA etc. Family: kinases Common physical properties: membrane bound, mitochondrial proteins Common chemical properties: Proteases, reductases etc. Sequences of a particular genome/species: e.g. Influenza sequences, plasmodium sequences etc. Motifs/domains

36 Where to look for databases? Search Engines Journals related to Bioinformatics Websites like: Several others websites

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38 NAR DB issue new dbs since last year! Total >1230! ( e/a/ Complete list Searchable m1037/dc1/1 (html format), also as downloadable word file)

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40 Database searching tips Look for links to Help or Examples Always check update dates Level of curation Try Boolean searches Be careful with UK/US spelling differences leukaemia vs leukemia haemoglobin vs hemoglobin colour vs color

41 Exercise Retrieve sequences from sequence databases Convert sequence formats Study different formats and flow of information