Pairwise Sequence Alignment. Zhongming Zhao, PhD
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1 Pairwise Sequence Alignment Zhongming Zhao, PhD
2 Sequence Similarity match mismatch A T T A C G C G T A C C A T A T T A T G C G A T A C C G gap
3 Why make sequence alignments? 1. The sequences may share a common origin - a common ancestor sequence. 2. The sequences may have the same or related structure and function. 3. The difference in the alignments may be linked to the functional changes/diseases.
4 Approaches in Pairwise Sequence Alignment 1. Dot Matrix 2. Global Alignment 3. Local Alignment
5 Visualization: Dot matrix G A T T C G C A G T A T T C C G T A C G
6 Dot matrix II
7 Dot matrix III
8 Dot matrix -- Staphylococcus epidermidis RP62A and ATCC12228
9 Alignment -- Staphylococcus epidermidis RP62A and ATCC12228
10 A high-quality alignment? For DNA sequences Long runs of identity Few gaps in the aligned regions An overall high degree of identity (>80%) For protein sequences Includes most of each sequence A significant proportion of identities throughout the alignment Multiple examples of conservative substitutions Relatively few gaps 50% is very good
11 Needleman and Wunsch Original paper (1970) The number contained in each cell of the array is the largest number of identical pairs that can be found if that cell is the origin for a pathway which proceeds with increases in running indices. Identical pairs of amino acids were given the value of one. Blank cells which represent non-identical pairs have the value, zero. The operation of successive summations was begun at the last row of the array and proceeded row-by-row towards the first row. The operation has been partially completed in the R row. The enclosed cell in this row is the site of the cell operation which consists of a search along the subrow and subcolumn indicated by borders for the largest value, 4 in subrow C. This value is added to the cell from which the search began. Needleman and Wunsch, J. Mol. Biol. (1970) 48:
12 Needleman and Wunsch Original paper (1970) The alternative pathways that could form the maximum match are illustrated. The maximum match terminates at the largest number in the first row or first column, 8 in this case.
13 Local Alignment: Smith-Waterman Algorithm (1981) Match: 1.0 Mismatch: -1/3 Gap w k = /3 * k Smith and Waterman, J. Mol. Biol. 1981, 147:
14 Smith-Waterman Algorithm vs Needleman-Wunsch Algorithm David Mount Bioinformatics 2 nd edition 2004 (Figure 3.11)
15 Searching sequence from database A sequence by itself is not information. Comparison can help find the important biological information, e.g. function of unknown genes, structure of query sequences, duplicated genes. Sequence databases, e.g. NCBI.
16 Basic Local Alignment Search Tool (BLAST) Basic Local Alignment Search Tool (BLAST) was developed as a new way to perform sequence similarity search. It is a string pattern search.
17 BLAST s Short Cut: Word Hits Query: GTACTGGACATGGACCCTACAGGAA Make a lookup table of words Word Size = 11 GTACTGGACAT TACTGGACATG ACTGGACATGG CTGGACATGGA TGGACATGGAC GGACATGGACC GACATGGACCC ACATGGACCCT Minimum word size = 7 blastn default = 11 From NCBI training tutorial
18 How to search a query sequence in the reference sequence database? From
19 What BLAST Tells You BLAST reports surprising alignments Different than chance Assumptions Random sequences Constant composition Conclusions Surprising similarities imply evolutionary homology
20 Basic Local Alignment Search Tool (BLAST) Widely used similarity search tool Heuristic approach based on Smith-Waterman algorithm Finds best local alignments Provides statistical significance All combinations (DNA/Protein) query and database. DNA vs DNA (BLASTN) DNA translation vs Protein (BLASTX) Protein vs Protein (BLASTP) Protein vs DNA translation (TBLASTN) DNA translation vs DNA translation (TBLASTX) www, standalone, and network clients
21 Online BLAST Search
22 Exercise Perform BLAST search of the following sequence. In which gene? In the coding region? GGCCGTGCCT GGGGATCCAA GTTCCCCTCT CTCCACCTGT GCTCACCTCT CCTCCGTCCC CAACCCTGCA CAGGCAAGAT CGTGGACGCC GTGATTCAGG AGCACCAGCC CTCCGTGCTG CTGGAGCTGG GGGCCTACTG TGGCTACTCA GCTGTGCGCA TGGCCCGCCT GCTGTCACCA GGGGCGAGGC TCATCACCAT CGAGATCAAC CCCGACTGTG CCGCCATCAC CCAGCGGATG GTGGATTTCG CTGGC
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