1. Welcome to Introduction to Bioinformatics
I. Scenario 4: Sequence alignment
Bring up course web site
Go to Scenario 4
Open the first sequence alignment notes

2. Scenario 3: Our Story You: Our first defense at CDC Outbreak:
. . . Anthrax?
Samples:
Confirm agent
Identify strain

3. Toxin gene-specific primers
Scenario 3: Our Story
Toxin gene-specific primers

4. Scenario 3: Our Story If DNA from bacterium with toxin gene
If DNA NOT from bacterium with toxin gene?
PCR

5. Scenario 3: Our Story If DNA from bacterium with toxin gene
If DNA NOT from bacterium with toxin gene?
PCR
(no product)

6. AATATTGACGCTTTACTACATCAGTCCATCGGAAGTACGTTGTATAATAAAATATATCTGTATG
Scenario 3: Our Story
DG47
AATATTGACGCTTTACTACATCAGTCCATCGGAAGTACGTTGTATAATAAAATATATCTGTATG
>gi| |emb|AJ |BAN Bacillus anthracis partial lef gene, isolate Microsoft-6259
Length = 2417 Score = 155 bits (78), Expect = 2e-35 Identities = 138/158 (87%) Strand = Plus / Plus
Query: 1 aatattgacgctttactacatcagtccatcggaagtacgttgtataataaaatatatctg 60
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Sbjct: 1267 aatattgacgctttactacatcagtccatcggaagtacgttgtataataaaatatatctg 1326
Query: 61 tatgaaaacatgaatataaataacttaacagcaacgttaggtgccgatttagtagattcc 120
Sbjct: 1327 tatgaaaacatgaatataaataacctaacagcaacgttaggtgccgatttagtagattcc 1386
Query: 121 acagataatacaaaaattaatcgaggtatattcaatga 158
||||||||||||||||||||||||||||||||||||||
Sbjct: 1387 acagataatacaaaaattaatcgaggtatattcaatga 1424

7. Scenario 3: Our Story
PCR
Toxin gene present

8. AATATTGACGCTTTACTACATCAGTCCATCGGAAGTACGTTGTATAATAAAATATATCTGTATG
Scenario 3: Our Story
DG47
AATATTGACGCTTTACTACATCAGTCCATCGGAAGTACGTTGTATAATAAAATATATCTGTATG
Do it!

9. Maybe it’s not from the toxin gene??
Scenario 3: Our Story
Maybe it’s not from the toxin gene??

10. AATATTGACGCTTTACTACATCAGTCCATCGGAAGTACGTTGTATAATAAAATATATCTGTATG
Scenario 3: Our Story
DG47
AATATTGACGCTTTACTACATCAGTCCATCGGAAGTACGTTGTATAATAAAATATATCTGTATG
NIDALLHQSIGSTLYNKIYLYENMNINNLTATLGADLVDSTDNTKINRGIFNEFKKNFKYSIS
Translate
Do it!

11. DG47 nucleotide sequence: Matches nothing in GenBank
DG47 amino acid sequence: 100% match to toxin gene

12. Compare nucleotide sequences by hand
Scenario 3: Our Story
Compare nucleotide sequences by hand
DG47 vs lef
Do it!

13. Compare nucleotide sequences by hand
Scenario 3: Our Story
Compare nucleotide sequences by hand
DG47      1  AATATTGACGCTTTACTACATCAGTCCATCGGAAGTACGTTGTATAATAAAATATATCTG              |||||||| |||||| ||||||| ||||| |||||||| ||||| |||||||| ||| || lef gene 1831  AATATTGATGCTTTATTACATCAATCCATTGGAAGTACCTTGTACAATAAAATTTATTTG
  DG47       61  TATGAAAACATGAATATAAATAACTTAACAGCAACGTTAGGTGCCGATTTAGTAGATTCC                |||||||| |||||||| |||||| | ||||||||  ||||||| |||||||| |||||| lef gene 1891  TATGAAAATATGAATATCAATAACCTTACAGCAACCCTAGGTGCGGATTTAGTTGATTCC
  DG47      121  ACAGATAATACAAAAATTAATCGAGGTATATTCAATGAGTTCAAAAAAAATTTCAAATAC                || |||||||| ||||||||| ||||||| |||||||| ||||||||||||||||||||| lef gene 1951  ACTGATAATACTAAAATTAATAGAGGTATTTTCAATGAATTCAAAAAAAATTTCAAATAT
  DG47      181  AGTATTTCTA                |||||||||| lef gene 2011  AGTATTTCTA
89% identical!

14. Compare nucleotide sequences by hand
Scenario 3: Our Story
Compare nucleotide sequences by hand
DG47
AATATTGACGCTTTACTACATCAGTCCATCGGAAGTACGTTGTATAATAAAATATATCTGTATG
+ lef gene
Sequence 1lcl|PCR Product DG Length190
Sequence 2lcl|M29081: Bacillus anthracis lethal factor (lef) gene, Length190
No significant similarity was found

15. Why can’t Blast figure out what you can plainly see?
Scenario 3: Our Story
DG47      1  AATATTGACGCTTTACTACATCAGTCCATCGGAAGTACGTTGTATAATAAAATATATCTG              |||||||| |||||| ||||||| ||||| |||||||| ||||| |||||||| ||| || lef gene 1831  AATATTGATGCTTTATTACATCAATCCATTGGAAGTACCTTGTACAATAAAATTTATTTG
  89% identical!
Why can’t Blast figure out what you can plainly see?
Sequence 1lcl|PCR Product DG Length190
Sequence 2lcl|M29081: Bacillus anthracis lethal factor (lef) gene, Length190
No significant similarity was found

16. Scenario 3: How does Blast work?
Clearly we need to understand more about how
sequence alignment really works!
Theory behind nucleotide vs nucleotide Blast
Working BlastN program
Theory behind protein-protein Blast
How to get Blast to do what you want

17. “Flavours” of sequence alignment
Global Alignment - Needleman-Wunsch algorithm
- Compares two sequences across their whole length
- Mostly only useful when you already know sequences might be similar
- Not useful for comparing a short query to an entire genome.
- Not discussed further in this class.
Local Alignment
- Allows alignment of subsequences of the target and the query
Usually what we want ; the query can be searched against entire genomes or large databases.

18. Crude Local Alignment Methods
The “Dot Matrix” method (Gibbs and McIntyre, 1970)
Represents the query and target sequences as a matrix ( a two-dimensional array) using a sliding window of similarity
The human eye can powerfully distinguish the identity line from the noise

19. The “Dot Matrix” method (Gibbs and McIntyre, 1970)
Normally a “window size” and “stringency” are specified
i.e. if the window size is 8 and stringency is 6, a dot is only placed if at least 6 of the current 8 positions in the query match the target

20. The “Dot Matrix” method (Gibbs and McIntyre, 1970)
window = 2
stringency = 2 G T A A T A

21. Problems with the Dot Matrix method
Requires human supervision!
A memory and processor time pig (a complete m*n matrix is calculated each time)
No explicit handling of gaps
No good quantitative score of alignment quality

22. The Smith-Waterman Algorithm (no gaps version)1 1
Match Extension = +1
NoMatch Penalty = -2 G 1 2 T 3 1 A 4 1 2
Negative values are reset to zero!! C 2 T 1 3
Download SmithWaterman1.py A 2 1 4

23. Smith Waterman – Dynamic Programming
An optimal alignment can be found starting from the highest scoring box and working backwards.
Dynamic Programming is a method for recording the solutions to subproblems, then working backwards to find an overall solution. If we incorporate gaps, we must start keeping track of this “traceback” pathway.

24. Download SmithWaterman2.py
The Smith-Waterman Algorithm (with gaps) G G T A A T A
Match Extension = +1
NoMatch Penalty = -2
Gap Penalty = -3 G 1 1 G 1 2 T 3
Take the Max of:
0; adding Query Gap;
adding Target Gap;
Match/No match; A 4 1 -2 2 C 1 -2 T
Download SmithWaterman2.py A

25. (a complete m*n matrix is still calculated each time!!)
Problems with Smith-Waterman
Still a pig! Memory and processor time requirements are huge when the query and/or the database gets large…..
(a complete m*n matrix is still calculated each time!!)
Do we really need to calculate the whole matrix?

26. BlastN – “word” based heuristics
Notice that in a typical S-W matrix, most of the boxes are empty!!!
What if we find exact matches of some seed words, then just work in the area surrounding these seeds trying to extend the alignment?
This is exactly the heuristic that blast employs to
avoid calculating the whole matrix!
(see figure on page 6 of Alignment notes)

27. BlastN Procedure Identify the subsequences of size word in the query
Filter the query sequence for repetitive “low complexity” sequences
Identify the subsequences of size word in the query
Find the exact matches in the target of the all the words
Use a modified S-W to extend the hits around the seed words
Score and report on the best matches
More on scoring on next class!!!