Basic terms:

1
Basic terms

• Similarity - measurable quantity.
• Similarity- applied to proteins using concept of
  conservative substitutions
• Identity
• percentage
• Homology-specific term indicating relationship by
  evolution

2
Basic terms

• Orthologs homologous sequences found in two or
  more species, that have the same function (i.e.
  alpha- hemoglobin).

3
Basic terms

• Orthologs homologous sequences found it two or
  more species, that have the same function (i.e.
  alpha- hemoglobin).
• Paralogs homologous sequences found in the same
  species that arose by gene duplication. ( alpha
  and beta hemoglobin).

4
Pairwise comparison

• Dotplot
• All against all comparison.
• Every position is compared with every other
  position.

5
Pairwise comparison

• Dotplot
• All against all comparison.
• Every position is compared with every other
  position.
• Nucleic acids and proteins have polarity.

6
Pairwise comparison

• Dotplot
• All against all comparison.
• Every position is compared with every other
  position.
• Nucleic acids and proteins have polarity.
• Typically only one direction makes biological
  sense.

7
Pairwise comparison

• Dotplot
• All against all comparison.
• Every position is compared with every other
  position.
• Nucleic acids and proteins have polarity.
• Typically only one direction makes biological
  sense.
• 5 to 3 or amino terminus to carboxyl terminus.

8
Simple plot

• Window size of sequence block used for
  comparison. In previous example
• window 1
• Stringency Number of matches required to score
  positive. In previous example
• stringency 1 (required exact match)

9
DotPlot
WINDOW 4 STRINGENCY 2
GATCGTACCATGGAATCGTCCAGATCA
GATC
(4/4)
GATC
- (0/4)
GATC
- (0/4)
GATC
(2/4)
10
Dot Plot

• Compare two sequences in every register.
• Vary size of window and stringency depending upon
  sequences being compared.
• For nucleotide sequences typically start with
  window 21 stringency 14
• Protein - start with smaller window 3,
  stringency 1 or 2.
• Important to test different stringencies.

11
Intergenic comparison

• Nucleotide sequence contains three domains.
• 50 - 350 - Strong conservation
• Indel places comparison out of register
• 450 - 1300 - Slightly weaker conservation
• 1300 - 2400 - Strong conservation

12
Scoring Alignments

• Quality Score
• Score x for match, -y for mismatch

13
Scoring Alignments

• Quality Score
• Score x for match, -y for mismatch
• Penalty for
• Creating Gap
• Extending a gap

14
Scoring Alignments

• Quality Score
• Quality 10(match)

15
Scoring Alignments

• Quality Score
• Quality 10(match) -1(mismatch)

16
Scoring Alignments

• Quality Score
• Quality 10(match) -1(mismatch) -
• (Gap Creation Penalty)(of Gaps)

17
Scoring Alignments

• Quality Score
• Quality 10(match) -1(mismatch) -
• (Gap Creation Penalty)(of Gaps) (Gap Ext.
  Pen.)(Total length of Gaps)
• Scoring scheme incorporates an evolutionary
  model--

18
Scoring Alignments

• Quality Score
• Quality 10(match) -1(mismatch) -
• (Gap Creation Penalty)(of Gaps) (Gap Ext.
  Pen.)(Total length of Gaps)
• Scoring scheme incorporates an evolutionary
  model--
• Matches are conserved

19
Scoring Alignments

• Quality Score
• Quality 10(match) -1(mismatch) -
• (Gap Creation Penalty)(of Gaps) (Gap Ext.
  Pen.)(Total length of Gaps)
• Scoring scheme incorporates an evolutionary
  model--
• Matches are conserved
• Mismatches are divergences

20
Scoring Alignments

• Quality Score
• Quality 10(match) -1(mismatch) -
• (Gap Creation Penalty)(of Gaps) (Gap Ext.
  Pen.)(Total length of Gaps)
• Scoring scheme incorporates an evolutionary
  model--
• Matches are conserved
• Mismatches are divergences
• Gaps are more likely to disrupt function, hence
  greater penalty than mismatch.

21
Scoring Alignments

• Quality Score
• Quality 10(match) -1(mismatch) -
• (Gap Creation Penalty)(of Gaps) (Gap Ext.
  Pen.)(Total length of Gaps)
• Scoring scheme incorporates an evolutionary
  model--
• Matches are conserved
• Mismatches are divergences
• Gaps are more likely to disrupt function, hence
  greater penalty than mismatch.
• Introduction of a gap (indel) penalized more than
  extension of a gap.

22
Z Score (standardized score)

• Z (Scorealignment - Average Scorerandom)

Standard Deviationrandom
23

• Quality ScoreRandomization
• Program takes sequence and randomizes it X times
  (user select).
• Determines average quality score and standard
  deviation with randomized sequences
• Compare randomized scores with Quality score to
  help determine if alignment is potentially
  significant.

24
Randomization

• It has become clear that
• Sequences appear to evolve in a word like
  fashion.
• 26 letters of the alphabet--combined to make
  words.
• Words actually communicate information.
• Randomization should actually occur at the level
  of strings of nucleotides (2-4).

25
Global Alignment

• Global - Compares all possible alignments of two
  sequences and presents the one with the greatest
  number of matches and the fewest gaps.

26
Global Alignment

• Global - Compares all possible alignments of two
  sequences and presents the one with the greatest
  number of matches and the fewest gaps.
• Alignment will run from one end of the longest
  sequence, to the other end.

27
Global Alignment

• Global - Compares all possible alignments of two
  sequences and presents the one with the greatest
  number of matches and the fewest gaps.
• Alignment will run from one end of the longest
  sequence, to the other end.
• Best for closely related sequences.

28
Global Alignment

• Global - Compares all possible alignments of two
  sequences and presents the one with the greatest
  number of matches and the fewest gaps.
• Alignment will run from one end of the longest
  sequence, to the other end.
• Best for closely related sequences.
• Can miss short regions of strongly conserved
  sequence.

29
Local Alignment

• Identifies segments of alignment with the highest
  possible score.

30
Local Alignment

• Identifies segments of alignment with the highest
  possible score.
• Align sequences, extends aligned regions in both
  directions until score falls to zero.

31
Local Alignment

• Identifies segments of alignment with the highest
  possible score.
• Align sequences, extends aligned regions in both
  directions until score falls to zero.
• Best for comparing sequences whose relationship
  is unknown.

32
Global Alignment
Local Alignment
33
Blast 2
Basic Local Alignment Search Tool E (expect)
value number of hits expected by random chance
in a database of same size. Larger numerical
value lower significance HIV sequence
34

• Both Global and Local alignment programs will
  (almost) always give a match.

35

• Both Global and Local alignment programs will
  (almost) always give a match.
• It is important to determine if the match is
  biologically relevant.

36

• Both Global and Local alignment programs will
  (almost) always give a match.
• It is important to determine if the match is
  biologically relevant.
• Not necessarily relevant Low complexity regions.
• Sequence repeats (glutamine runs)

37

• Both Global and Local alignment programs will
  (almost) always give a match.
• It is important to determine if the match is
  biologically relevant.
• Not necessarily relevant Low complexity regions.
• Sequence repeats (glutamine runs)
• Transmembrane regions (high in hydrophobes)

38

• Both Global and Local alignment programs will
  (almost) always give a match.
• It is important to determine if the match is
  biologically relevant.
• Not necessarily relevant Low complexity regions.
• Sequence repeats (glutamine runs)
• Transmembrane regions (high in hydrophobes)
• If working with coding regions, you are typically
  better off comparing protein sequences. Greater
  information content.