Lecture 4
- 1. Sequence Alignment Lecture – 4 Nafis Neehal, Lecturer, Department of CSE, DIU
- 2. CONTENTS 1. Sequence Alignment 2. Sequence Alignment Methods - Pairwise Alignment - Multiple Sequence Alignment 3. Pairwise Sequence Alignment Methods -Global Alignment (Needleman-Wunsch) - Local Alignment (Smith-Waterman) 4. Multiple Sequence Alignment - Progressive Method - Iterative Method - MSA Challenges
- 3. 1. Sequence Alignment Why and how align sequences
- 4. Sequence Alignment 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 relationships between the sequences CTGTCG-CTGCACG -TGC-CG-TG----
- 5. 2. Sequence Alignment Methods Pairwise and Multiple
- 6. Pairwise Sequence Alignment ▹A pair of sequences as input ▹Align them in such a way that, for that particular alignment the assumed region of similarity produces higher score than all the other alignments ▹Methods - Global Alignment (Needleman-Wunsch) - Local Alignment (Smith-Waterman) CTGTCGCTGCACG-- -------TGC-CGTG
- 7. Multiple Sequence Alignment • Three or more than three sequences as input • Align all the sequences altogether in such a manner that the alignment produces highest score
- 8. 3. Pairwise Sequence Alignment Global and Local methods
- 9. Global Alignment (Needleman-Wunsch) 3 Major Steps -Create 2D Matrix -Trace back -Final Alignment Create 2D Matrix - Row x Col 2D matrix draw (Row , Col size of seq1 and seq2 respectively) - Place 2 seqs as Row and Column Header - Cell (0,0) = 0 - Cell (0,1) to Cell (0,Column) and Cell (1,0) to Cell (Row,0) value = delete gap value from previous cell value - For other cell values, follow equation in (1) Trace back - Start from Cell (Row, Col) - Go back up to Cell (0,0) Final Alignment - Start from Cell (Row, Col) - If then, place character in both seq - If or then character in start seq & gap in end seq
- 10. Global Alignment (Needleman-Wunsch) - Example Input - seq1 = AAAC - seq2 = AGC Scoring Scheme δ(x, x) = 1 (Match) δ(x,-) = -2 (Gap) δ(x, y) = -1 (Mis match) Eq. 1: Cell Value A G C A A A C 0 -2 -4 -6 -2 1 -1 -3 -4 -6 -8 -1 -3 -5 0 -2 -4 -2 -1 -1 Final Alignment -AGC AAAC
- 11. Local Alignment (Smith-Waterman) 3 Major Steps -Create 2D Matrix -Trace back -Final Alignment Create 2D Matrix - Row x Col 2D matrix draw (Row , Col size of seq1 and seq2 respectively) - Place 2 seqs as Row and Column Header - First Row, First Column all value = 0 - For other cell values, follow equation in (2) Trace back - Start from each Cell which has the maximum value in the entire matrix - Go back up to the Cell where first time 0 occurs Final Alignment - Start from each Cell with max value - If then, place character in both seq - If or then character in start seq & gap in end seq
- 12. Local Alignment (Smith-Waterman) - Example Input - seq1 = AAAC - seq2 = AAG Scoring Scheme δ(x, x) = 1 (Match) δ(x,-) = -2 (Gap) δ(x, y) = -1 (Mis match) Eq. 2: Cell Value A A G A A A C 0 0 0 0 0 1 1 0 0 0 0 1 1 0 2 2 0 0 1 1 Final Alignment -AAG AAAC
- 13. 4. Multiple Sequence Alignment Progressive, Iterative
- 14. Progressive Method ▹ Two major steps – Guide Tree build up and Multiple Pairwise Alignment ▹ Steps - Take each pair, align - Generate consensus of that alignment - Align new sequence with the consensus of the previous one - Go back, Until all sequences are finished ▹ Example - Clustal ω - MAFFT - KALIGN - T-COFFEE
- 15. Iterative Method ▹ Works similarly to progressive methods ▹ Repeatedly realign the initial sequences as well as add new sequences to the growing MSA ▹ Example - DIALIGN - MUSCLE - POA
- 16. MSA Challanges ▹ Computationally Expensive ▹ Difficult to score. Multiple comparison necessary in each column of the MSA for a cumulative score ▹ Placement of gaps and scoring of substitution is more difficult ▹ Difficulty increases with diversity ▹ Relatively easy for a set of closely related sequences. Identifying the correct ancestry relationships for a set of distantly related sequences is more challenging ▹ Even difficult if some members are more alike compared to others
- 17. 95% Of Human DNA is identical to Chimpanzees 510 DNA Codes Lost throughout human evolution 2 gm DNA Can contain digital information of whole world 1.8 Meter Long DNA is squeezed into a space of 0.09 µm
- 18. Shocked?
- 19. Youtube Links ▹Global Alignment Part 1 - https://www.youtube.com/watch?v=vqxc2EfPWdk ▹Global Alignment Part 2 - https://www.youtube.com/watch?v=zwA-6_1bLgE ▹Local Alignment - https://www.youtube.com/watch?v=IatoWOsJ35Q