EECS 730 Introduction to Bioinformatics Sequence Alignment. Luke Huan Electrical Engineering and Computer Science

Transcription

1 EECS 730 Introduction to Bioinformatics Sequence Alignment Luke Huan Electrical Engineering and Computer Science

2 Database What is database An organized set of data Can web pages, books, journal articles, tables, text files, and spreadsheet files be considered as databases? Molecular Biology Databases To disseminate biological data and information To provide biological data in computer-readable form To allow analysis of biological data 2012/9/11 EECS 730 2

3 Biological Information Nucleic acids: DNA sequence, genes, gene products (proteins), mutation, gene coding, distribution patterns, motifs Genomics: genome, gene structure and expression, genetic map, genetic disorder RNA sequence, secondary structure, 3D structure, interactions Proteins: Protein sequence, corresponding gene, secondary structure, 3D structure, function, motifs, homology, interactions Proteomics: expression profile, proteins in disease processes etc. Ligands and drugs (inhibitors, activators, substrates, metabolites) 2012/9/11 EECS 730 3

4 Biological Information Function: Binding sites, interactions, molecular action (binding, chemical reaction, etc.) Biological effect (signaling, transport, feedback, regulation, modification, etc.) Functional relationship, protein families, motifs, and homologs Pathways: Molecular networks, biological chain events, regulation, feedback, kinetic data 2012/9/11 EECS 730 4

5 Overview of molecular biology databases Sequence DNA Genbank ( EMBL (European Molecular Biology Laboratory, DDBJ (DNA Data Bank of Japan) Protein Swissprot ( NCBI Protein classification databases Prosite ( Pfam ( InterPro ( Gene ontology ( 2012/9/11 EECS 730 5

6 Overview of molecular biology databases Structure PDB (Protein Data Bank, X-ray crystallography, NMR, modeling KLOTHO (small molecules, Genome Mouse genome database ( Yeast genome ( Bacterial genomes ( Human genome browsers NCBI UCSC genome.ucsc.edu EBI Celera /9/11 EECS 730 6

7 Overview of molecular biology databases Genetic disorders OMIM (Online Mendelian Inheritance in Man, Taxonomy ( Literature PubMed ( 2012/9/11 EECS 730 7

8 Data about Databases 2012/9/11 EECS 730 8

9 Molecular biology databases Nucleic acids sequence Genome data Protein sequence Protein classification Protein structure 2012/9/11 EECS 730 9

10 Nucleic Acids databases What info are in these databases: DNA sequence, genes, gene products (proteins), mutation, gene coding, distribution patterns, motifs Genomics: genome, gene structure and expression, genetic map, genetic disorder RNA sequence, secondary structure, 3D structure, interactions 2012/9/11 EECS

11 Nucleic Acids databases DNA databases GenBank, EMBL, DDBJ 1. General purpose databases focusing on DNA sequences and their properties 2. GenBank, EMBL-bank and DDBJ exchange data to ensure comprehensive worldwide coverage and accession numbers are managed consistently between the three centers. 2012/9/11 EECS

12 Three major public DNA databases EMBL GenBank DDBJ 2012/9/11 EECS

13 International Nucleotide Sequence Database Collaboration 2012/9/11 EECS

14 EMBL nucleotide sequence database EMBL ( Contains nucleotide sequences collected from all public sources. Accessible through Sequence Retrieval System (SRS) which allows keyword searching Sequence similarity search tools: Blitz, Fasta, and BLAST (studied later) 2012/9/11 EECS

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16 EMBL Entry header ID entryname dataclass; molecule; division; sequence length (BP). 2012/9/11 EECS

17 EMBL Entry feature table Coding sequence 2012/9/11 EECS

18 EMBL Entry sequence 2012/9/11 EECS

19 EMBL format ID: IDentification AC: Accession numbers The primary means of identifying sequences providing a stable way of identifying entries from release to release. DE: description KW: Key Word information which can be used to generate cross-reference indexes of the sequence entries based on functional, structural, or other categories deemed important. OS: Organism Species OC: Organism Classification the taxonomic classification Of the source organism The OG (OrGanelle) linetype indicates the sub-cellular location of non-nuclear sequences. SQ: SeQuence header marks the beginning of the sequence data and Gives a summary of its content. The sequence data line has a line code consisting of two blanks. 2012/9/11 EECS

20 What is an accession number? An accession number is label that used to identify a sequence. It is a string of letters and/or numbers that corresponds to a molecular sequence. Examples (all for retinol-binding protein, RBP4): X02775 NT_ Rs GenBank genomic DNA sequence Genomic contig dbsnp (single nucleotide polymorphism) DNA N An expressed sequence tag (1 of 170) NM_ RefSeq DNA sequence (from a transcript) RNA NP_ RefSeq protein AAC02945 GenBank protein Q28369 SwissProt protein 1KT7 Protein Data Bank structure record protein 2012/9/11 EECS

21 GenBank database GenBank ( Contains publicly available DNA sequences from more than 100,000 organisms. Also contains derived protein sequences, and annotations describing biological, structural, and other relevant features. Accessible through Entrez, NCBI s integrated retrieval system Sequence similarity search tools: BLAST (studied later) 2012/9/11 EECS

22 Number of base pairs in Genbank, present Base Pairs (billions) Base Pairs 1.E+11 1.E+10 1.E+09 1.E+08 Semilogarithmic plot 1.E+07 2-fold / 18 mo 10-fold / 5 yr 1.E Year Year These graphs provide one example of the rapidly accumulating data in biology, leading to entire new fields of study. 2012/9/11 EECS

23 >100,000 species are represented in GenBank all species 128,941 viruses 6,137 bacteria 31,262 archaea 2,100 eukaryota 87, /9/11 EECS

24 The most sequenced organisms in GeneBank Homo sapiens 10.7 billion bases Mus musculus 6.5b Rattus norvegicus 5.6b Danio rerio 1.7b Zea mays 1.4b Oryza sativa 0.8b Drosophila melanogaster 0.7b Gallus gallus 0.5b Arabidopsis thaliana 0.5b Updated GenBank release /9/11 EECS

25 A GenBank entry HEADER /9/11 EECS

26 GenBank entry - FEATURES 2012/9/11 EECS

27 GenBank entry - SEQUENCE 2012/9/11 EECS

28 Common sequence formats EMBL release format Genbank release format FASTA format : >X12345 Y098TR gene CGTATCTTACGAGCTACTACGA GGTCTTATCGGACGAGCGACT /9/11 EECS

29 FASTA format Fig Page /9/11 EECS

30 cdna cdna: DNA that is synthesized to be complementary to a mrna molecule. A cdna represents a portion of the DNA that specifies a protein (coding sequence of a gene). If the sequence of the cdna is known, the sequence of the DNA is known. Non-translated introns are not found in the cdna. (They are removed after the DNA is transcribed into mrna) DNA RNA protein complementary DNA (cdna) 2012/9/11 EECS

31 EST (Expressed Sequence Tag) Expressed Sequence Tags (ESTs) correspond to partial mrna sequences of expressed genes. They are sequences of cdna which have been reversetranscribed from mrna Short sequences (~ bases), each is result of single sequencing experiment -> high frequency of errors They represent a snapshot of what is expressed in a given tissue, and developmental stage. 2012/9/11 EECS

32 dbest (Expressed Sequence Tags database) dbest is a division of GenBank that contains sequence data and other information on cdna sequences, or ESTs, from a number of organisms. 2012/9/11 EECS

33 EST (Expressed Sequence Tag) Applications: Discovery of new genes Mapping of various genomes Identification of coding regions in genomic sequences. EST libraries are used to answer questions like: What genes in specific cell or tissue are expressed? 2012/9/11 EECS

34 One gene have multiple EST sequences! 2012/9/11 EECS

35 UniGene: Unique Genes UniGene partitions GenBank sequences into a nonredundant set of gene-oriented clusters. Each UniGene cluster contains sequences that represent a unique gene, as well as related information such as the tissue types in which the gene has been expressed and map location. A majority of sequences are ESTs. 2012/9/11 EECS

36 Cluster sizes in UniGene This is a gene with 1 EST associated; the cluster size is 1 This is a gene with 10 ESTs associated; the cluster size is /9/11 EECS

37 Cluster sizes in UniGene (human) Cluster size Number of clusters 1 8, , , , , , , , ,000-30, /9/11 EECS UniGene build 172, 8/04

38 UniGene: unique genes via ESTs Conclusion: UniGene is a useful tool to look up information about expressed genes. UniGene displays information about the abundance of a transcript (expressed gene), as well as its regional distribution of expression (e.g. brain vs. liver). We will discuss UniGene further on in the section of gene expression. 2012/9/11 EECS Page 31

39 Using a database How to get information out of a database: Browsing: no targeted information to retrieve Search: looking for particular information Searching a database: Must have a key that identifies the element(s) of the database that are of interest. Access number Name of gene Sequence of gene Keyword (any word that occurs somewhere in the database records) Other information 2012/9/11 EECS

40 NCBI and Entrez One of the most useful and comprehensive sources of databases is the NCBI, part of the National Library of Medicine. NCBI provides interesting summaries, browsers for genome data, and search tools Entrez is their database search interface Can search on gene names, sequences, chromosomal location, diseases, keywords /9/11 EECS

41 National Center for Biotechnology Information (NCBI) /9/11 EECS

42 Entrez integrates the scientific literature; DNA and protein sequence databases; 3D protein structure data; population study data sets; assemblies of complete genomes 2012/9/11 EECS

43 Entrez is a search and retrieval system that integrates NCBI databases 2012/9/11 EECS

44 2012/9/11 EECS

45 Example of how to access sequence data: HIV-1 pol There are many possible approaches. Begin at the main page of NCBI, and type an Entrez query: hiv-1 pol 2012/9/11 EECS

46 2012/9/11 EECS

47 Searching for HIV-1 pol: Following the genome link yields a manageable three results 2012/9/11 EECS Page 34

48 Example of how to access sequence data: HIV-1 pol For the Entrez query: hiv-1 pol there are about 40,000 nucleotide or protein records (and >100,000 records for a search for hiv-1 ), but these can easily be reduced in two easy steps: --specify the organism, e.g. hiv-1[organism] --limit the output to RefSeq! 2012/9/11 EECS

49 over 100,000 nucleotide entries for HIV-1 only 1 RefSeq 2012/9/11 EECS

50 NCBI s important RefSeq project: best representative sequences The RefSeq collection aims to provide a comprehensive, integrated, non-redundant set of sequences, including genomic DNA, transcript (RNA), and protein products, for major research organisms. It provides an expertly curated accession number that corresponds to the most stable, agreed-upon reference version of a sequence. RefSeq identifiers include the following formats: Complete genome NC_###### Complete chromosome NC_###### Genomic contig NT_###### mrna (DNA format) NM_###### e.g. NM_ Protein NP_###### e.g. NP_ /9/11 EECS

51 Strategy for assessment of alternative multiple sequence alignment algorithms 1. Create or obtain a database of protein sequences for which the 3D structure is known. Thus we can define true homologs using structural criteria. BaliBase: a reference alignment resource with over 1,000 sequences in 142 alignments Try making multiple sequence alignments with many different sets of proteins (very related, very distant, few gaps, many gaps, insertions, outliers). 3. Compare the answers. 2012/9/11 EECS

52 Acknowledge Many of the images and slides in this PowerPoint presentation are from Bioinformatics and Functional Genomics by Jonathan Pevsner (ISBN ). Copyright 2003 by John Wiley & Sons, Inc. 2012/9/11 EECS