Roadmap

1
Roadmap

• The topics
• basic concepts of molecular biology
• more on Perl
• overview of the field
• biological databases and database searching
• sequence alignments
• phylogenetics
• structure prediction
• microarray data analysis

2
Sequence alignments

• Introduction
• What is an alignment?
• Why do alignments?
• A bit of history
• Dot matrix comparison
• Scoring alignments
• Alignment methods
• Significance of alignments

3
What is Sequence alignment

• Sequence alignment is an arrangement of two or
  more sequences, highlighting their similarity.

4
Why do alignments?

• Sequence Alignment is useful for discovering
  structural, functional and evolutional
  information in biological sequences.

5
Over time, genes accumulate mutations

• Environmental factors
• Radiation
• Oxidation
• Mistakes in replication/repair
• Deletions, Duplications
• Insertions
• Inversions
• Point mutations

6
Comparing two sequences

• Point mutations, easyACGTCTGATACGCCGTATAGTCTATCT
  ACGTCTGATTCGCCCTATCGTCTATCT
• Insertions/deletions, must alignACGTCTGATACGCCGT
  ATAGTCTATCTCTGATTCGCATCGTCTATCT

ACGTCTGATACGCCGTATAGTCTATCT----CTGATTCGC---ATCGTC
TATCT
7
Sequence Alignment

• Doolittle RF, Hunkapiller MW, Hood LE,
• Devare SG, Robbins KC, Aaronson SA,
• Antoniades HN. Science 221275-277, 1983.
• A sequence for platelet derived
• growth factor (PDGF) from mammalian cells was
  virtually identical to the sequence for the
  retrovirus encoded oncogene known as v-sis (gene
  causing cancer in animals).
• Retrovirus had acquired the gene from the host
  cell as some kind of genetic exchange event and
  then had produced a mutant that could alter the
  function of the normal protein when it infected
  another animal.

8
Dot Matrix Comparison

• A T C A G A G G T C T G
• B T C A G A G C T G

C
T
G
T
G
G
A
G
A
C
T
X
X
X
T
X
X
C
X
X
A
X
X
X
X
G
X
X
A
X
X
X
X
G
X
X
C
X
X
X
T
X
X
X
X
G
9
Interpretation of dot matrix

• Regions of similarity appear as diagonal runs of
  dots
• Reverse diagonals (perpendicular to diagonal)
  indicate inversions
• Can link or "join" separate diagonals to form
  alignment with "gaps"

10
More on Dot Matrix

• Improving detection of matching regions by
  filtering
• using sliding window to compare the two
  sequences. For example, print a dot at a matrix
  position only if
• 7 out of the next 11 positions in the sequence
  are identical
• Similarity score of the next 11 positions in the
  sequence is greater than 5.

11
Sequence repeats

• Many sequences contains repetitive regions.

a retrovirus vector sequence against itself using
a window size of 9 and mismatch limit of
2 (http//arbl.cvmbs.colostate.edu/molkit/dnadot/b
kg.html)
12
More on Dot Matrix

• Dot matrix graphically presents regions of
  identity or similarity between two sequences
• The use of windows and thresholds can reduce
  noise in dot matrix
• Inversions and duplications have unique
  signatures in dot matrix

13
Software

• Dotlet (java applet)
• www.ch.embnet.org
• Dnadot
• arbl.cvmbs.colostate.edu/molkit/dnadot/
• Dotter
• www.cgr.ki.se/cgr/groups/sonnhammer/Dotter.html
• Dottup
• www.emboss.org

14
How to measure the similarity

• Basically three kinds of changes can occur at any
  given position within a sequence
• Mutation
• Insertion
• Deletion
• Insertion and deletion have been found to occur
  in nature at a significantly lower frequency than
  mutations.

15
Scoring Matrices for Aligning DNA Sequences

• Transition --- substitutions in which a purine
  (A/G) is replaced by another purine (A/G) or a
  pyrimadine (C/T) is replaced by another
  pyrimadine (C/T).
• Transversions ---
• (A/G) ? (C/T)

16
Scoring a sequence alignment

• Match score 1
• Mismatch score 0
• Gap penalty 1
• ACGTCTGATACGCCGTATAGTCTATCT
  ----CTGATTCGC---ATCGTCTATCT
• Matches 18 (1)
• Mismatches 2 0
• Gaps 7 ( 1)

Score 11
17
Gap opening and extension penalties

• We want to find alignments that are
  evolutionarily likely.
• Which of the following alignments seems more
  likely to you?
• ACGTCTGATACGCCGTATAGTCTATCTACGTCTGAT-------ATAGT
  CTATCTACGTCTGATACGCCGTATAGTCTATCTAC-T-TGA--CG-C
  GT-TA-TCTATCT
• We can achieve this by penalizing more for a new
  gap, than for extending an existing gap

?
?
18
Scoring a sequence alignment

• Match/mismatch score 1/0
• Open/extension penalty 2/1ACGTCTGATACGCCGTATAG
  TCTATCT ----CTGATTCGC-
  --ATCGTCTATCT
• Matches 18 (1)
• Mismatches 2 0
• Open 2 (2)
• Extension 5 (1)

Score 9
19
Amino Acid Substitution Matrices

• PAM - point accepted mutation based on global
  alignment evolutionary model
• BLOSUM - block substitutions based on local
  alignments similarity among conserved sequences

20
Part of PAM 250 Matrix
C S T P A G
C 12
S 0 2
T -2 1 3
P -3 1 0 6
A -2 1 1 1 2
G -3 1 0 -1 1 5
21
PAM matrices

• PAM 1 Matrix reflects an amount of evolution
  producing on average one mutation per hundred
  amino acids (1 unit evolution).
• PAM 250 --- 250 unit evolution

22
Limitations of PAM Matrices

• Constructed based on the phylogenetic
  relationships prior to scoring mutations
• Difficulty of determining ancestral relationships
  among sequences
• Based on a small set of closely related proteins

23
BLOSUM Matrices

• Based on the observed amino acid substitutions in
  a large set of 2000 conserved amino acid
  patterns (blocks). The blocks are found in a
  database of protein sequences representing more
  than 500 families of related proteins and act as
  signatures of these protein families.
• The matrices are measured on the multiple
  alignment of the blocks.
• The entries of the matrices are computed based on
  the same principle used in PAM -- log(odds
  ratio).

24
Part of BLOSUM 62 Matrix

• BLOSUM62 was measured on pairs of sequences with
  an average of 62 identical amino acids.

C S T P A G
C 9
S -1 4
T -1 1 5
P -3 -1 -1 7
A 0 1 0 -1 4
G -3 0 -2 -2 0 6
25
PAM vs. BLOSUM

• PAM
• Based on mutational model of evolution (Markov
  process)
• PAM1 is based on sequences of 85 similarity
• Designed to track the evolutionary origins
• BLOSUM
• Based on the multiple alignment of blocks
• Good to be used to compare distant sequences
• Designed to find proteins conserved domains

26
Gap Penalty

• Optimal penalties vary from sequence to sequence,
  and finding the most adequate value is a matter
  of empirical trial and error.
• When compare distantly related sequences, a high
  gap-opening penalty and a very low gap-extension
  penalty often give better results
• When compare closely related sequences, gaps
  should be penalized on both a gap-opening and
  gap-extension