Post on 28-Mar-2015
Vorlesung
Grundlagen der Bioinformatik
http://gobics.de/lectures/ss07/grundlagen
Information from a SingleSequenceAlone
Sequence alignment in molecular data analysis:
Information from a SingleSequenceAlone
Multi-OrganismHigh QualitySequences
Sequence alignment in molecular data analysis:
(M. Brudno)
Tools for multiple sequence alignment
seq1 T Y I M R E A Q Y E
seq2 T C I V M R E A Y E
seq3 Y I M Q E V Q Q E
seq4 Y I A M R E Q Y E
Tools for multiple sequence alignment
seq1 T Y I - M R E A Q Y E
seq2 T C I V M R E A - Y E
seq3 Y - I - M Q E V Q Q E
seq4 Y – I A M R E - Q Y E
Tools for multiple sequence alignment
seq1 T Y I - M R E A Q Y E
seq2 T C I V M R E A - Y E
seq3 Y - I - M Q E V Q Q E
seq4 Y – I A M R E - Q Y E
Tools for multiple sequence alignment
seq1 T Y I - M R E A Q Y E
seq2 T C I V M R E A - Y E
seq3 Y - I - M Q E V Q Q E
seq4 Y – I A M R E - Q Y E
Tools for multiple sequence alignment
seq1 T Y I - M R E A Q Y E
seq2 T C I V M R E A - Y E
seq3 Y - I - M Q E V Q Q E
seq4 Y – I A M R E - Q Y E
Tools for multiple sequence alignment
seq1 T Y I - M R E A Q Y E
seq2 T C I V M R E A - Y E
seq3 Y - I - M Q E V Q Q E
seq4 Y – I A M R E - Q Y E
Functionally important regions more conserved than non-functional regions
Tools for multiple sequence alignment
seq1 T Y I - M R E A Q Y E
seq2 T C I V M R E A - Y E
seq3 Y - I - M Q E V Q Q E
seq4 Y – I A M R E - Q Y E
Functionally important regions more conserved than non-functional regions
Local sequence conservation indicates functionality!
Tools for multiple sequence alignment
seq1 T Y I - M R E A Q Y E
seq2 T C I V M R E A - Y E
seq3 - Y I - M Q E V Q Q E
seq4 Y – I A M R E - Q Y E
Astronomical Number of possible alignments!
Tools for multiple sequence alignment
seq1 T Y I - M R E A Q Y E
seq2 T C I V - M R E A Y E
seq3 - Y I - M Q E V Q Q E
seq4 Y – I A M R E - Q Y E
Astronomical Number of possible alignments!
Tools for multiple sequence alignment
seq1 T Y I - M R E A Q Y E
seq2 T C I V M R E A - Y E
seq3 - Y I - M Q E V Q Q E
seq4 Y – I A M R E - Q Y E
Which one is the best ???
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 sub-
sequences 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
atc------taatagttaaactcccccgtgc-ttag
cagtgcgtgtattactaac----------gg-ttcaatcgcg
caaa--gagtatcacc----------cctgaattgaataa
Consistency!
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 fs(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
atctaatagttaaaccccctcgtgcttagagatccaaaccagtgcgtgtattactaacggttcaatcgcgcacatccgc
Pair-wise alignment:
The DIALIGN approach
atctaatagttaaaccccctcgtgcttagagatccaaaccagtgcgtgtattactaacggttcaatcgcgcacatccgc
Pair-wise alignment:
recursive algorithm finds optimal chain of
fragments.
The DIALIGN approach
------atctaatagttaaaccccctcgtgcttag-------agatccaaaccagtgcgtgtattactaac----------ggttcaatcgcgcacatccgc--
Pair-wise alignment:
recursive algorithm finds optimal chain of
fragments.
The DIALIGN approach
------atctaatagttaaaccccctcgtgcttag-------agatccaaaccagtgcgtgtattactaac----------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
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
Upper and lower bounds for alignable positions
site x = [i,p] (sequence i, position p)
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
Upper and lower bounds for alignable positions
Calculate upper bound bl(x,i) and lower bound bu(x,i) for each x and sequence i
The DIALIGN approach
atctaatagttaaactcccccgtgcttag
cagtgcgtgtattactaacggttcaatcgcg
caaagagtatcacccctgaattgaataa
Upper and lower bounds for alignable positions
bl(x,i) and bu(x,i) updated for each new fragment in alignment
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: bmorgen@gwdg.de 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 300 2) bla 200 3) blu 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 1 cagg------ ----GTTTGA atctgataca ttgc------ ---------- bla 1 ctga------ ---------- ---------- --------GC CAAGTGGGAA blu 1 ttttgatatg agaaGTGTGA aacaagctat cctatattGC TAAGTGGCAG 0000000000 0000000000 0000000000 0000000011 1111111111 dog_il4 25 ---------- --ATGGCACT GGGGTGAATG AGGCAGGCAG CAGAATGATC bla 17 ggtgtgaata catgggtttc cagtaccttc tgaggtccag agtacc---- blu 51 ccctggcttt ctATGTGCAC AGAATGGGAG GAAAGTGCCT GCTAGTGAGC 0000000000 0000000000 0000000000 0000000000 0000000000 dog_il4 63 GTACTGCAGC CCTGAGCTTC CACTGGCCCA TGTTGGTATC CTTGTATTTT bla 63 ---------- ---------- ---TTTCCCA TGTGCTCCAT GGTGGAATGG blu 101 CAGGGACTCA GAGAGAATGG AGTATAGGGG TCAGGGCat- ---------- 0000000000 0000000000 0009999999 9999999888 8888888888 dog_il4 113 TCCGCCCCTT CCCAGCACca gcattatcct ---GGGATTG GAGAAGGGGG bla 90 ACCACTCCTT CTCAGCACaa caaagcccaa gaaGGTGTTG CGTTCTAGAC blu 140 ---------- ---------- ---------- ---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)