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Part I : SEQUENCE COMPARISON
PAIRWISE ALIGNMENT
Manisha Brahmachary
designed by Manisha, NUS
OUTLINE
What is sequence Comparison
Ways to do Sequence Comparison
Dot Plot
BLAST
FASTA
designed by Manisha, NUS
What is sequence alignment
or sequence comparison?
Given two sequences of letters and a scoring scheme
for evaluating matching letters , find best pairing from
one sequence to letters of the other sequence.
 THIS IS A RATHER LONGER SENTENCE THAN THE NEXT.
 THIS IS A SHORT SENTENCE
 Align:
 THIS IS A RATHER LONGER SENTENCE THAN THE NEXT.
 THIS IS A#######SHORT###SENTENCE############## (path 1)
 or
 THIS IS A SHORT#########SENTENCE############## (path 2)
designed by Manisha, NUS
Aligning biological sequences
 DNA (4 letter alphabet)
TTGACAC
TTTACAC
 Proteins (20 letter alphabet)
RKVA--GMAKPNM
RKIAVAAASKPAV
designed by Manisha, NUS
Why do Sequence Alignment?
 Finding novel genes in
silico
 Phylogenetic/Evolutionary
 Structure-template for
modelling
 Functional prediction
designed by Manisha, NUS
Types of Sequence
Comparison
Pairwise Alignment
Comparison of two sequences
Multiple Alignment
Comparison of more than two sequences
designed by Manisha, NUS
CONCEPTS IN SEQUENCE
COMPARISON
 IDENTITY
Percentage identity between sequences means
that they have a certain number of residues
(nucleotide /amino- acids ) that are identical at
that particular position after aligning both
sequences.
designed by Manisha, NUS
Query:
RCI CTRGFCRCLCRR
Subject:
RCLCRRGVCRCICT R
• Exact match (shown by | ) : 10 identical residues
• Above example :
•Percentage identity: 10 identical matches /15 residues in the
aligned sequence *100 = 66% identity
designed by Manisha, NUS
Query:
RCI CTRGFCRCLCRR
Subject:
RCLCRRGVCRCICT R
MISMATCH(s) HERE
designed by Manisha, NUS
Query:
RCICT-RGFCRCLC---RR
Subject:
RCLCRRGVCRCICTAR
• Mismatch when different characters , therefore insertion
of gaps.
• Gaps have penalties:
• Insertion of first gap( GAP OPENING) : high penalty
(For eg. –2, subtracting 2 )
• Insertion of consecutive gaps ( GAP EXTENSION): less
penalty
(For eg. -1 (subtracting 1 for each consecutive gap)
•More no. of gaps lesser the score of the alignment
designed by Manisha, NUS
RCICT-RGFCRCLC---RR
RCLCRRGVCRCICTAR-
Substitution:
Less score than identical match
For eg: +1 per substitution
designed by Manisha, NUS
Substitution - Replace a residue with
another of similar physiochemical
property.
Category
Amino Acid
Acids and Amides
Asp (D) Glu(E) Asn (N) Gln (Q)
Basic
His (H) Lys (K) Arg (R)
Aromatic
Phe (F) Tyr (Y) Trp (W)
Hydrophilic
Ala (A) Cys (C) Gly (G) Pro (P) Ser (S) Thr (T)
Hydrophobic
Ile (I) Leu (L) Met (M) Val (V)
designed by Manisha, NUS
Similarity
RCICT-RGFCRCLC---RR
RCLCRRGVCRCICTAR
Similarity = Identical matches +
Substitutions
Eg. (10 identical matches +
 2 substitution) / 15 aligned residues *
100 = 80% similarity
designed by Manisha, NUS
For DNA:
Identity and gap are applicable
ACTCGGCCCCGCG CTCACTG C
ACTCGGAC - - GCG CTCAGTGC
designed by Manisha, NUS
Similarity Vs. Homology
 Homology: When two similar proteins come from a
common ancestor.
Homology is inferred from Similarity
If two sequences are similar, then they are known
as homologous sequences.
Usually, at least 30% identity over 400 bp for DNA
sequences and over 125 amino acids for proteins.
designed by Manisha, NUS
Scoring Matrices used in
sequence comparison
What is a scoring Matrix:
Scoring matrices are used when we compare
sequences with one another
Gives us a measure of which residue can be
substituted by which residue.
designed by Manisha, NUS
Scoring Matrices

For Amino acids,
Each amino acid is compared to
every other and a score is given
to this pair
High score if they are the same
residue
(e.g. Cysteine compared to cysteine)
 Low, if they are very different
(e.g. Tryptophan compared to cysteine)
designed by Manisha, NUS
Scoring Matrices
for DNA:
A
C
G
T
A
1
0
0
0
C
0
1
0
0
G
0
0
1
0
T
0
0
0
1
DNA sequence: 4
characters only (A,T,G,C)
Unitary matrix used for
scoring:
A scoring system in
which only identical
characters receive a
positive score.
designed by Manisha, NUS
SCORING SCHEMES FOR PROTEIN
SEQUENCE ALIGNMENTS
Scoring matrices used are: PAM(Point Accepted
Mutation) and BLOSUM(BLOcks SUbstitution Matrix
 BLOSUM45---->BLOSUM 90 means MORE
DIVERSE TO LESS DIVERSE
PAM30---PAM250 means
LESS DIVERSE TO MORE DIVERSE

NOTE: Many different matrices are in use, each gives different values to pairs of
amino acids
Depending on how distantly related your sequences are, you might want to
choose different matrices for your comparisons
designed by Manisha, NUS
Scoring Matrices
Notes:
BLOSUM 45
PAM250
BLOSUM62
BLOSUM90
PAM160
PAM 100
MORE DIVERGENT
LESS DIVERGENT
designed by Manisha, NUS
Ways to do Pairwise Alignment
Dot Plot (simplest method)
Statistical computation based
Local alignment e.g. BLAST, FASTA
Global alignment e.g. CLUSTAL
designed by Manisha, NUS
What are Dot Plots
Program to do sequence comparison to
find out:
–Are the two sequences similar ?
– Are there Repeat regions in your
sequence?
designed by Manisha, NUS
STEPS IN DOT PLOT
•Take two sequences to be compared
•Sequence A:MEHRKPGTGQ
•Sequence B:MEHRKPGTGQ
•Place sequence A in x-axis (Row). Place sequence B in yaxis (Column)
M E H R K P G T G Q
X-axis
Y-axis
designed by Manisha, NUS
•Plot a dot everytime there is a match between
an element of row sequence and an element of
column sequence
•Do you see any diagonal line extending?
•If yes, then there is a match !
designed by Manisha, NUS
Patterns in Dot Plot
GGTCCTTGGCTGAAAGACCCCA
When two sequences
are “identical”
Sequence :
GGTCCTTGGCTGAAAG
ACCCCA
designed by Manisha, NUS
Application of Dot Plot
Using self comparison : Finding Repeats
Sequence used:
CATCTCAAAAACAACAACAAAAAAAAAAAAAAAAGAAAAAAAA
Human ALU sequence
CATCTCAAAAACAACAA
CAAAAAAAAAAAAAAAA
GAAAAAAAA
•Omit main diagonal
•Clusters of diagonal
lines show repeats
in the sequence.
designed by Manisha, NUS
Notes:What are repeats?
 Repeats:are stretches of repeated regions of residues in
a sequence.
 Importance of repeats:
 In protein:
Regulatory regions
Binding sites
In DNA:
Present in Transposons, chromosomal mutational
hotspots, many genetic diseases related with
repeats.eg.Huntington.
designed by Manisha, NUS
Patterns in Dot Plot
When two
sequences
are similar :
Broken
diagonal,the
interrupted region
shows regions of
mismatch
designed by Manisha, NUS
Patterns in Dot Plot
Two different, but related
sequences
GREGYPADSKGCKITCFLTAAGYCNTECTLKKGSSGYCAWPA
Broken diagonal clusters
of dots parallel to the
central diagonal.
Distance between
the lines show
no. of insertions
done to get the alignment.
designed by Manisha, NUS
Two models of alignment:
Local and Global alignments
Global alignment:
 Looks for similarity across full extent of
sequences
Site:http://www2.igh.cnrs.fr/bin/align-guess.cgi
designed by Manisha, NUS
GLOBAL Alignment
The two sequences
are matched across
their whole sequence
length.
designed by Manisha, NUS
Local alignment
Looks for regions of similarity in parts of
the sequences only
Softwares : BLAST, FASTA
designed by Manisha, NUS
Local Alignment
Example of local
alignment between
two sequences using
lalign program.
(http://www.ch.embnet.org/software/LALIG
N_form.html)
Notice that the
alignment is shown
only of those regions
that have strong
identity or strong
similarity
designed by Manisha, NUS
Why two different models?
 Global alignment
High degree of Homology
Good for modelling
Local Alignment
Localised Similarity ( conserved regions
with structural , functional importance,
Repeats, Domains)
designed by Manisha, NUS
FASTA
Fast Alignment (expanded form of FASTA)by
Pearson and Lipmann.
Is a method based on dynamic programming.
Websites available:
http://www.ebi.ac.uk/fasta33/
http://www.dna.affrc.go.jp/htdocs/Blast/fasta
designed by Manisha, NUS
.html
What is BLAST?
Basic Local Alignment Search Tool (BLAST)
Method for Pairwise Alignment.
Is used to search for homologous sequences
from a database (of nucleotide/protein
sequence) for a given query sequence.
Modified version of FASTA
Faster in generating output.
Sites for doing BLAST:
http://www.ncbi.nlm.nih.gov
designed by Manisha, NUS
How to go about doing
BLAST
SARS virus gene:
SGFRKMAFPSGKVEGCMVQVTCGTTTLNGLWLDDTVYCPRHVICTAEDMLNPNYE
DLLIRKSNHSFLVQAGNVQLRVIGHSMQNCLLRLKVDTSNPKTPKYKFVRIQPGQTF
SVLACYNGSPSGVYQCAMRPNHTIKGSFLNGSCGSVGFNIDYDCVSFCYMHHMEL
PTGVHAGTDLEGKFYGPFVDRQTAQAAGTDTTITLNVLAWLYAAVINGDRWFLNRF
TTTLNDFNLVAMKYNYEPLTQDHVDILGPLSAQTGIAVLDMCAALKELLQNGMNGR
T ILGSTILEDEFTPFDVVRQCSGVTFQ
designed by Manisha, NUS
designed by Manisha, NUS
BLAST output for a protein query sequence
from a SARS virus
Score (bits)
is the score given
letter by letter
during alignment
based on the
Subtitution
matrices.
High score = less
E value.
designed by Manisha, NUS
•E value: No. of chance
alignments that one will
get as hits.
•Lower the E value
lesser no. of chance hits
•E value of zero or less
than zero indicates very
good hit (highly
homologous sequence)
•E value is also known as
P(N) in some BLAST
programs
designed by Manisha, NUS
BLAST OUTPUT
Gives the identity
Gives the similarity
designed by Manisha, NUS
BLAST
BLAST query schemes:
Amino acid seq: against db?
Blastp (protein sequence db)
Tblastn (translated nucleotide
sequence db)
DNA seq: against db?
Blastn (nucleotide db)
Blastx ( protein sequence db)
Tblastx (translated nucleotide
sequence db)
designed by Manisha, NUS
Gene(CDNA), Unknown
CTAACATGCTTAGGATAATGGCCTCTCTTGTTCTTGCTCGCAAACATAACACTT
GCTGTAACTTATCACA
BLAST
NMLRIMASLVLARKHNTC
CNLSHRFYRLANECAQVL
SEMVMCGGSLYVKPGGT
SSGDATTAYANSVFNIC
DNA Sequencing
Translate into 6 frames,
Amino acid seq.choose
appropriate frame.
BLAST RESULTS
Choose the best hit using the lowest
E value, highest %identity
If , High % identity and low e-value
Function, family of
gene found
CLUSTAL
Use multiple sequences
Find conserved regions,
Domains,
Phylogenetic relations:which family of
designed by Manisha,
NUS
gene closest
to your target gene/protein
SUMMARY
TODAY WE LOOKED AT:
Methods to compare two sequences:
 Dot plots (simplest, graphical view)
 Different patterns of Dot plots
 Local alignment
 Global alignment
 Difference between these two models
FASTA
 BLAST
 other types of BLAST
designed by Manisha, NUS