Vorlesung
Grundlagen der Bioinformatik
http://gobics.de/lectures/ss07/grundlagen
Sequence alignment in molecular data analysis:
Information
from a Single
Sequence
Alone
Sequence alignment in molecular data analysis:
Information
from a Single
Sequence
Alone
Multi-Organism
High Quality
Sequences
(M. Brudno)
Tools for multiple sequence alignment
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Tools for multiple sequence alignment
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Tools for multiple sequence alignment
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Tools for multiple sequence alignment
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Tools for multiple sequence alignment
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Tools for multiple sequence alignment
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 Functionally important regions more conserved than
non-functional regions
Tools for multiple sequence alignment
seq1
seq2
seq3
seq4
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 Functionally important regions more conserved than
non-functional regions
 Local sequence conservation indicates functionality!
Tools for multiple sequence alignment
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seq4
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Astronomical Number of possible alignments!
Tools for multiple sequence alignment
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Astronomical Number of possible alignments!
Tools for multiple sequence alignment
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Which one is the best ???
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Tools for multiple sequence alignment
Questions in development of alignment programs:
(1) What is a good alignment?
→ objective function (`score’)
(2) How to find a good alignment?
→ optimization algorithm
First question far more important !
Tools for multiple sequence alignment
Most important scoring scheme for multiple alignment:
Sum-of-pairs score for global alignment.
Divide-and-Conquer Alignment (DCA)
J. Stoye, A. Dress (Bielefeld)
Approximate optimal global multiple alignment



Divide sequences into small sub-sequences
Use MSA to calculate optimal alignment for subsequences
Concatenate sub-alignments
Divide-and-Conquer Alignment (DCA)
Divide-and-Conquer Alignment (DCA)
Tools for multiple sequence alignment
Problems with traditional approach:
 Results depend on gap penalty
 Heuristic guide tree determines alignment;
alignment used for phylogeny reconstruction
 Algorithm produces global alignments.
First step in sequence comparison: alignment

global alignment (Needleman and Wunsch, 1970;
Clustal W)
atctaatagttaatactcgtccaagtat
atctgtattactaaacaactggtgctacta
First step in sequence comparison: alignment

global alignment (Needleman and Wunsch, 1970;
Clustal W)
atc--taatagttaat--actcgtccaagtat
||| || || | ||
||| || | | ||
atctgtattact-aaacaactggtgctacta-
First step in sequence comparison: alignment

global alignment (Needleman and Wunsch, 1970;
Clustal W)
atc--taatagttaat--actcgtccaagtat
||| || || | ||
||| || | | ||
atctgtattact-aaacaactggtgctacta-

local alignment (Smith and Waterman, 1983)
atctaatagttaatactcgtccaagtat
gcgtgtattactaaacggttcaatctaacat
First step in sequence comparison: alignment

global alignment (Needleman and Wunsch, 1970;
Clustal W)
atc--taatagttaat--actcgtccaagtat
||| || || | ||
||| || | | ||
atctgtattact-aaacaactggtgctacta-

local alignment (Smith and Waterman, 1983)
atctaatagttaatactcgtccaagtat
gcgtgtattactaaacggttcaatctaacat
First step in sequence comparison: alignment

global alignment (Needleman and Wunsch, 1970;
Clustal W)
atc--taatagttaat--actcgtccaagtat
||| || || | ||
||| || | | ||
atctgtattact-aaacaactggtgctacta-

local alignment (Smith and Waterman, 1983)
atc--taatagttaatactcgtccaagtat
|| || | ||
gcgtgtattact-aaacggttcaatctaacat
New question:
sequence families with multiple local similarities
Neither local nor global methods appliccable
New question:
sequence families with multiple local similarities
Alignment possible if order conserved
The DIALIGN approach
Morgenstern, Dress, Werner (1996),
PNAS 93, 12098-12103

Combination of global and local methods

Assemble multiple alignment from
gap-free local pair-wise alignments
(,,fragments“)
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atc------taatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atc------taatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaa--gagtatcacccctgaattgaataa
The DIALIGN approach
atc------taatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaa--gagtatcacc----------cctgaattgaataa
The DIALIGN approach
atc------taatagttaaactcccccgtgc-ttag
cagtgcgtgtattactaac----------gg-ttcaatcgcg
caaa--gagtatcacc----------cctgaattgaataa
The DIALIGN approach
Consistency!
atc------taatagttaaactcccccgtgc-ttag
cagtgcgtgtattactaac----------gg-ttcaatcgcg
caaa--gagtatcacc----------cctgaattgaataa
The DIALIGN approach
atc------TAATAGTTAaactccccCGTGC-TTag
cagtgcGTGTATTACTAAc----------GG-TTCAATcgcg
caaa--GAGTATCAcc----------CCTGaaTTGAATaa
The DIALIGN approach
Score of an alignment:
 Define score of fragment f:
l(f) = length of f
s(f) = sum of matches (similarity values)
P(f) = probability to find a fragment with length l(f)
and at least s(f) matches in random sequences that
have the same length as the input sequences.
Score w(f) = -ln P(f)
The DIALIGN approach
Score of an alignment:
 Define score of fragment f:
 Define score of alignment as
sum of scores of involved fragments
No gap penalty!
The DIALIGN approach
Score of an alignment:
Goal in fragment-based alignment approach: find
Consistent collection of fragments with
maximum sum of weight scores
The DIALIGN approach
atctaatagttaaaccccctcgtgcttagagatccaaac
cagtgcgtgtattactaacggttcaatcgcgcacatccgc
Pair-wise alignment:
The DIALIGN approach
atctaatagttaaaccccctcgtgcttagagatccaaac
cagtgcgtgtattactaacggttcaatcgcgcacatccgc
Pair-wise alignment:
 recursive algorithm finds optimal chain of
fragments.
The DIALIGN approach
------atctaatagttaaaccccctcgtgcttag-------agatccaaac
cagtgcgtgtattactaac----------ggttcaatcgcgcacatccgc--
Pair-wise alignment:
 recursive algorithm finds optimal chain of
fragments.
The DIALIGN approach
------atctaatagttaaaccccctcgtgcttag-------agatccaaac
cagtgcgtgtattactaac----------ggttcaatcgcgcacatccgc--
Optimal pairwise alignment: chain of fragments with
maximum sum of weights found by dynamic
programming:
Standard fragment-chaining algorithm
Space-efficient algorithm
The DIALIGN approach
Multiple alignment:
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
Multiple alignment:
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaccctgaattgaagagtatcacataa
(1) Calculate all optimal pair-wise alignments
The DIALIGN approach
Multiple alignment:
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
(1) Calculate all optimal pair-wise alignments
The DIALIGN approach
Multiple alignment:
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
(1) Calculate all optimal pair-wise alignments
The DIALIGN approach
Fragments from optimal pair-wise alignments
might be inconsistent
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaa--gagtatcacccctgaattgaataa
The DIALIGN approach
atc------taatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaa--gagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
Fragments from optimal pair-wise alignments
might be inconsistent
1.
Sort fragments according to scores
2.
Include them one-by-one into growing multiple
alignment – as long as they are consistent
(greedy algorithm, comparable to rucksack
problem)
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
Consistency problem
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
Consistency problem
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
Upper and lower bounds for alignable positions
The DIALIGN approach
atc------taatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaa--gagtatcacccctgaattgaataa
Upper and lower bounds for alignable positions
The DIALIGN approach
atc------taatagt
taaactcccccgtgcttag
Cagtgcgtgtattact
aacggttcaatcgcg
caaa--gagtatcacccctgaattgaataa
Upper and lower bounds for alignable positions
The DIALIGN approach
atc------taata-----gttaaactcccccgtgcttag
Cagtgcgtgtatta-----ctaacggttcaatcgcg
caaa--gagtatcacccctgaattgaataa
Upper and lower bounds for alignable positions
The DIALIGN approach
site x = [i,p] (sequence i, position p)
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
Upper and lower bounds for alignable positions
The DIALIGN approach
Calculate upper bound bl(x,i) and lower
bound bu(x,i) for each x and sequence i
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
Upper and lower bounds for alignable positions
The DIALIGN approach
bl(x,i) and bu(x,i) updated for each
new fragment in alignment
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
Upper and lower bounds for alignable positions
The DIALIGN approach
Consistency bounds are to be updated for each
new fragment that is included in to the growing
Alignment
Efficient algorithm
(Abdeddaim and Morgenstern, 2002)
The DIALIGN approach
Advantages of segment-based approach:
 Program can produce global and local alignments!
 Sequence families alignable that cannot be aligned
with standard methods
Program input
Program usage:
> dialign2-2 [options] <input_file>
<input_file> = multi-sequence file in FASTA-format
Program output
DIALIGN 2.2.1
*************
Program code written by Burkhard Morgenstern and Said Abdeddaim
e-mail contact: [email protected]
Published research assisted by DIALIGN 2 should cite:
Burkhard Morgenstern (1999).
DIALIGN 2: improvement of the segment-to-segment
approach to multiple sequence alignment.
Bioinformatics 15, 211 - 218.
For more information, please visit the DIALIGN home page at
http://bibiserv.techfak.uni-bielefeld.de/dialign/
program call:
./dialign2-2 -nt -anc s
Aligned sequences:
==================
length:
=======
1) dog_il4
2) bla
3) blu
300
200
200
Average seq. length:
233.3
Please note that only upper-case letters are considered to be aligned.
Program output
Alignment (DIALIGN format):
===========================
dog_il4
bla
blu
1
1
1
cagg------ ----GTTTGA atctgataca ttgc------ ---------ctga------ ---------- ---------- --------GC CAAGTGGGAA
ttttgatatg agaaGTGTGA aacaagctat cctatattGC TAAGTGGCAG
0000000000 0000000000 0000000000 0000000011 1111111111
dog_il4
bla
blu
25
17
51
---------- --ATGGCACT GGGGTGAATG AGGCAGGCAG CAGAATGATC
ggtgtgaata catgggtttc cagtaccttc tgaggtccag agtacc---ccctggcttt ctATGTGCAC AGAATGGGAG GAAAGTGCCT GCTAGTGAGC
0000000000 0000000000 0000000000 0000000000 0000000000
dog_il4
bla
blu
63
63
101
GTACTGCAGC CCTGAGCTTC CACTGGCCCA TGTTGGTATC CTTGTATTTT
---------- ---------- ---TTTCCCA TGTGCTCCAT GGTGGAATGG
CAGGGACTCA GAGAGAATGG AGTATAGGGG TCAGGGCat- ---------0000000000 0000000000 0009999999 9999999888 8888888888
dog_il4
bla
blu
113
90
140
TCCGCCCCTT CCCAGCACca gcattatcct ---GGGATTG GAGAAGGGGG
ACCACTCCTT CTCAGCACaa caaagcccaa gaaGGTGTTG CGTTCTAGAC
---------- ---------- ---------- ---GGGGTGG CCTTAGGCTC
8888888888 8888888800 0000000000 0007777777 7777777777
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atc------taatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
The DIALIGN approach
atc------taatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaa--gagtatcacccctgaattgaataa
The DIALIGN approach
atc------taatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaa--gagtatcacc----------cctgaattgaataa
The DIALIGN approach
atc------taatagttaaactcccccgtgcttag
cagtgcgtgtattactaac----------ggttcaatcgcg
caaa--gagtatcacc----------cctgaattgaataa
The DIALIGN approach
atc------taatagttaaactcccccgtgc-ttag
cagtgcgtgtattactaac----------gg-ttcaatcgcg
caaa--gagtatcacc----------cctgaattgaataa
The DIALIGN approach
atc------TAATAGTTAaactccccCGTGC-TTag-----cagtgcGTGTATTACTAAc----------GG-TTCAATcgcg
caaa--GAGTATCAcc----------CCTGaaTTGAATaa--
The DIALIGN approach
atc------taatagttaaactcccccgtgc-ttag
cagtgcgtgtattactaac----------gg-ttcaatcgcg
caaa--gagtatcacc----------cctgaattgaataa
Alignment of large genomic sequences
Fragment-based alignment approach useful for
alignment of genomic sequences.
Possible applications:
 Detection of regulatory elements
 Identification of pathogenic microorganisms
 Gene prediction
DIALIGN alignment of human and murine
genomic sequences
DIALIGN alignment of tomato and Thaliana
genomic sequences
Alignment of large genomic sequences
Gene-regulatory sites identified by mulitple sequence
alignment (phylogenetic footprinting)
Alignment of large genomic sequences
Performance of long-range alignment programs
for exon discovery (human - mouse comparison)
Performance of long-range alignment programs
for exon discovery (thaliana - tomato comparison)