Lecture 2 Introduction to Data Formats
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1 Introduction to Bioinformatics for Medical Research Gideon Greenspan Lecture 2 Introduction to Data Formats
2 Introduction to Data Formats Real world, data and formats Sequences and alignments Trees and Pedigrees Motifs and Profiles Annotations and 3D structure Expression and pathways GenBank, SWISS-PROT, GeneCards 2
3 Data Formats Data: representation of real world Never a perfect copy Data format: computer s representation Computers require formal definitions Almost always represented as text Tools are data translators Input one type of data, output another 3
4 Nucleotide Sequences GAATCG TACTGT CCATTG CTCAGA ATCGTA CTGTCA T (for DNA) and U (for RNA) interchangeable 4
5 Reverse Complementation 5 GAATCGTACTGTCCATTGCTCA 3 3 ACTCGTTACCTGTCATGCTAAG 5 5 GAATCGTACTGTCCATTGCTCA 3 5 TGAGCAATGGACAGTACGATTC 3 5
6 Protein Sequences KGSQEFWPGTSHLEIGVKMDVYFS 6
7 Amino Acid Codes A Alanine G Gycine P Proline R Arganine H Histadine S Serine N Asparagine I Isoleucine T Threonine D Aspartic acid L Leucine W Tryptophan C Cysteine K Lysine Y Tyrosine Q Glutamine M Methionine V Valine E Glutamic acid F Phenylalanine 7
8 Multiple Sequences Many ways to encode in a file FASTA format is most common >HSBGPG Human gene for gla protein (BGP) GGCAGATTCCCCCTAGACCCGCCCGCACCATGGTCAGGCAT GCCCCTCCTCATCGCTGGGCACAGCCCAGAGGGTATAAACA GTGCTGGAGGCTGGCGGGGCAGGCCAGC >HSGLTH1 Human theta 1-globin gene CCACTGCACTCACCGCACCCGGCCAATTTTTGTGTTTTTAG TAGAGACTAAATACCATATAGTGAACACCTAAGACGGGGGG CCTTGGATCCAGGGCGA 8
9 Alignments Comparison between two sequences Add gaps to make equal in length Seek the best possible alignment Global or local alignment GAATCGTAC CGACTTCG -GAATCGTAC- CGACT--G-CG 9
10 Multiple Alignment Comparison between many sequences Many encoding formats ALN is popular Human DSHUCZ M-ATKAVCVLKGDGPVQGII Bovine DSBOCZ --ATKAVCVLKGDGPVQGTI Swordfish SODL V-L-KAVCVLRGAGETTGTV Drosophila DSF V-V-KAVCVING-D-AKGTV Maize SDMZ M-V-KAVAVLAGTD-VKGTI Yeast DSBYC V---QAVAVLKGDAGVSGVV 10
11 Taxonomy Trees 11
12 Phylogenetic Trees (raccoon: , ((sea_lion: , seal: ): , ((monkey: , cat: ): , weasel: ): ): , dog: ); 12
13 Pedigrees Pe In M F Ch MS FS Se Pr Markers
14 Motifs Common short sequence Simple motifs use IUPAC symbols R A or G K G or T B C or G or T Y C or T M A or C D A or G or T S G or C N Any base H A or C or T W A or T V A or C or G Example: CHGW matches CCGA, CTGT, CAGC 14
15 Motif Profiles Statistical model for a motif Position A C G T GTCTA: = TTGCT: =
16 Genomic Annotations Physical structure Centromere, telomeres Genes Introns, exons, alternative splice sites Binding sites Transcription factors Variable sites SNPs, repeats 16
17 Protein Annotations Domains Hydrogen bonds between peptides a-helices, b-sheets Pred: CCCEEEEEEEEEEHHHHHHHHHHEEEEEEEEEECCC AA: PPPILFGLSLSLEVTTFDNLVLARFSVRSVSLDVDT 17
18 Protein 3D structure x y z
19 Expression Levels normal hot cold uch gut fip msh vma meu git sec7b apn wos sec spf slp shm
20 Pathways 20
21 Data Formats: Summary Real world, data and data formats Nucleotide, protein sequences Sequence comparisons Alignments, motifs, profiles Relationships between entities Phylogenetic trees, pedigrees, pathways Annotations Tools are data translators 21
22 GenBank DNA/RNA sequence database USA National Institute of Health Synchronized daily with Europe, Japan Founded in 1982 Contains > 20 million sequences Total size > 20 billion base pairs >200 full species genomes Public submission 22
23 A GenBank Entry (1) Unique IDs Accession is permanent for an entry GenBank Identifier specifies one version Verbal description Organism, gene/source GenBank division, keywords Date, version Submitter, references 23
24 GenBank Divisions PRI Primate PHG Bacteriophage ROD Rodent SYN Synthetic MAM Other mammal UNA Unannotated VRT Vertebrate EST Expressed seq. tag INV Invertebrate PAT Patented PLN Plant, fungus, algae STS Sequence tag site BCT Bacterial GSS Genome survey VRL Viral HTG High-throughput 24
25 A GenBank Entry (2) The sequence itself Summary of base pair frequencies Features (at point within sequence) Genes, exons, introns, translation Promoters, binding sites Repeats, stem and loop Variation: RFLPs and SNPs Known sequence tag locations 25
26 Searching GenBank Structureless and structured All information fields are searchable Limits Only recent sequences Specific database only Exclude drafts, patented, etc Searching by sequence? Using BLAST tools 26
27 SWISS-PROT Protein sequence database Geneva University and Europe s EBI Some curation to minimize redundancy Founded in 1986 Contains > 120,000 entries Total size > 46 million amino acids TrEMBL translated nucleotide database For all coding sequences in GenBank 27
28 A SWISS-PROT Entry Core data References Biological source Annotations Function and associated diseases Post-translational modifications Domains and binding sites Secondary, quaternary structure 28
29 Searching SWISS-PROT Using SRS (sequence retrieval system) European equivalent to Entrez Other search types Retrieve accession or ID Unstructured ( full text ) Structured ( advanced ) Taxonomy browser BLAST to search by sequence 29
30 GeneCards Human gene database Weizmann Institute in Israel Founded in 1997 Describes > 14,000 known genes > 21,000 predicted genes Also: pseudogenes, gene clusters, etc Data mining approach Data sourced from 36 other databases 30
31 A GeneCards Entry (1) Aliases and descriptions HUGO standard nomenclature Chromosomal location Links to genome browsers Expression levels Different tissues 31
32 A GeneCards Entry (2) Available sequences Homologues in other organisms Proteins Protein families Mutations and other variation Related diseases Publications News articles 32
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