1 / 41

Sequence Alignment techniques

Sequence Alignment techniques. Definition. A sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationship between the sequences. Sequence Alignments ?.

kathyross
Télécharger la présentation

Sequence Alignment techniques

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Sequence Alignment techniques

  2. Definition • A sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationship between the sequences.

  3. Sequence Alignments ? 1. I have just sequenced something. What is known about the thing I sequenced? 2. I have a unique sequence. Is there similarity to another gene that has a known function? 3. I found a new protein in a lower organism. Is it similar to a protein from another species? 4. I have decided to work on a new gene. The people in the field will not give me the plasmid. I need the complete cDNA sequence to perform RT-PCR. 5. I wish to perform molecular modeling of the proteins sequence which has significant similarity to sequence of a protein for which the 3D structure is available.

  4. Sequence alignments • Pair wise • Multiple

  5. Pairwise protein sequence alignment • definition: compare pairs of sequences and search for series of characters that are in the same order • sequences in rows with identical (or similar) characters in same columns and non-identical (non-similar) characters either in same column (mismatch) or opposite a gap ----TFGK------ ||| ----TFGR------ HCKLTFGKWFTSEW | ||| | KCGPTFGRIACGEM Local - most similar sub-regions of sequences aligned (islands of similarity) Global - entire sequences aligned up to both ends

  6. Methods of pairwise sequence alignment… • dot matrix - all possible matches between sequence residues are found; used to compare two sequences to look for regions where they may align; very useful for finding indels and repeats in sequences; can be used as a first pass to see if there is any similarity between sequences • dynamic programming - mathematically guaranteed to find optimal alignment (global or local) between pairs of sequences; very computationally expensive - # of steps increases exponentially with sequence length

  7. Dot matrix method 1 - one sequence listed along top of page and second sequence listed along the side 2 - move across row and put dot in any column where the character is the same 3 - continue for each row until all possible character matches between the sequences are represented by dots 4 - diagonal rows of dots reveal sequence similarity (can also find repeats and inverted repeats off the main diagonal) 5 - isolated dots represent random similarity unrelated to the alignment H C G E T F G R W F T P E W K C • G • P • T • • F • • G • R • I A C • G • • E • • M

  8. Protein sequence Alignments… • Dot matrix method not a convenient method • Manual alignment of sequences ? • For sequence of length N, about 22N/√2N alignments are possible (for n=300, 10179 alignments!) • Mathematical solution: Dynamic programming (nothing to do with computer!)

  9. Protein sequence Alignments… • In naturally occurring conserved proteins certain amino acids are favorably replaced in the process of natural selection. • Based on these observations and mutations substitution matrices have been generated. • For example: • BLOSUM (Block Substitution Matrices) matrices: BLOSUM40, BLOSUM60 etc. • PAM (Point Accepted Mutation) matrices: PAM80, PAM120, PAM250 • These matrices are used by various protein sequence alignment algorithms.

  10. Dynamic programming • a dot matrix shows regions of similarity but not path that connects disjointed regions i.e. the optimal alignment which is the ultimate goal of pairwise sequence comparison • dynamic programming was applied to sequence alignment by Needleman & Wunsch to achieve this end • dynamic programming is a general class of optimization solutions that finds best solutions by breaking down large intractable problems into smaller pieces and then solving • ultimately a sequence or ‘path’ of subproblem scores that yields the highest overall score is chosen as the optimal solution for the entire problem

  11. Dynamic programming & sequence alignment • overall problem is broken down into subproblems of aligning each residue of one sequence to each residue of the other • choose the best solution to the problem among the three options of (1) - aligning residues (2) - introducing gap in sequence 1 or (3) - introducing gap in sequence 2 • each high scoring choice rules out two low scoring choices - this is critical in reducing the overall space of alignments needed to be evaluated (essence of time saving) • the algorithm use a matrix similar to the dot matrix with sequences on the top and left axes • at each position in the matrix the algorithm computes the best score and stores a pointer from the previous position from where the highest score was derived • finally a ‘trace back’ step is performed where the highest scoring path along the pointers is traced - this represents the optimal alignment

  12. Dynamic programming & sequence alignment: Steps… • Two sequences are arranged in a matrix table. • Initial GAP penalties (d) are listed in the first row or column. • First values of substitutions scores (Si,j) are filled in the table using substitution matrices • The simple matrix table is converted to dynamic programming table using the following mathematical equation. • Hi,j = max { (Hi-1,j-1 + Si,j), (Hi-1,j – d), (Hi,j-1 –d) }

  13. H G S A Q V K T E A E M • Hi,j = max { (Hi-1,j-1 + Si,j), (Hi-1,j – d), (Hi,j-1 –d) }

  14. sequence 1 M - N A L S D R T sequence 2 M G S D R T T E T score 6 -12 1 0 -3 1 0 -1 3 = -5 sequence 1 M N A - L S D R T sequence 2 M G S D R T T E T score 6 0 1-12 -3 1 0 -1 3 = -5

  15. Which matrix to use? • PAM120 for general use • PAM60 for close relations • PAM250 for distant relations • BLOSUM62 for general use • BLOSUM80 for close relations • BLOSUM45 for distant relations • When comparing closely related proteins one should use lower PAM or higher BLOSUM matrices, for distantly related proteins higher PAM or lower BLOSUM matrices.

  16. Global alignment algorithms : Needleman and Wunsch • Local Alignment algorithms: Smith-Waterman local alignment http://www.ebi.ac.uk/Tools/emboss/align/

  17. Needleman S.B. and Wunsch C.D. 1970. J. Mol. Biol. 48: 443-453 Smith T.F. and Waterman M.S. 1981. J. Mol. Biol. 147: 195-197 Eddy, S.R. 2004. Nature Biotechnology 22: 909 - 910  

  18. Multiple Sequence Alignment

  19. Multiple Sequence Alignment

  20. Clustal • Most widely used algorithm for MSA • Available in different forms ClustalW, ClustalX • Different Output formats • Apart from standalone it is also available in: • BIOEDIT, GCG, EMBOSS, Macvector etc.

  21. ClustalW • Formats: NBRF/PIR, EMBL/SwissProt, Pearson (Fasta), GDE, Clustal, GCG/MSF, RSF. • Output formats: same as above + Phylip

  22. Web server: http://www.ebi.ac.uk/clustalw/index.html Align few sequences by default parameters. Change parameters like GAP penalties and note the changes in alignment outputs. Exercise: Make a dynamic programming matrix for a protein sequence of length 7. Use BLOSUM40 matrix to generate a dynamic programming matrix using the mathematical equation given in the presentation. Trace back the path of maximum scores and obtain optical alignment(s)

  23. Exercise to be submitted by Thursday • Go to http://expasy.org/tools/randseq.html • Generate a random protein sequence of length 25 amino acids of average amino acid composition • Draw a dot plot. Identify regions of similarities, repeats, inverted repeats. • Submit the record to me.

More Related