Multiple sequence alignmentsand motif discovery

Tutorial 5

• Multiple sequence alignment

– ClustalW

– Muscle

• Motif discovery

– MEME

– Jaspar

Multiple sequence alignments and motif discovery

• More than two sequences

– DNA

– Protein

• Evolutionary relation

– Homology Phylogenetic tree

– Detect motif

Multiple Sequence Alignment

GTCGTAGTCG-GC-TCGACGTC-TAG-CGAGCGT-GATGC-GAAG-AG-GCG-AG-CGCCGTCG-CG-TCGTA-AC

A

D B

CGTCGTAGTCGGCTCGACGTCTAGCGAGCGTGATGCGAAGAGGCGAGCGCCGTCGCGTCGTAAC

• Dynamic Programming

– Optimal alignment

– Exponential in #Sequences

• Progressive

– Efficient

– Heuristic

Multiple Sequence Alignment

GTCGTAGTCG-GC-TCGAC

GTC-TAG-CGAGCGT-GAT

GC-GAAG-AG-GCG-AG-C

GCCGTCG-CG-TCGTA-AC

A

D B

CGTCGTAGTCGGCTCGAC

GTCTAGCGAGCGTGAT

GCGAAGAGGCGAGC

GCCGTCGCGTCGTAAC

ClustalW

“CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice”, J D Thompson et al

Pairwise alignment – calculate

distance matrix

Guided tree

Progressive alignment using the guide tree

ClustalW

• Progressive

– At each step align two existing alignments or sequences

– Gaps present in older alignments remain fixed

-TGTTAAC

-TGT-AAC

-TGT--AC

ATGT---C

ATGT-GGC

ClustalW - Inputhttp://www.ebi.ac.uk/Tools/clustalw2/index.html

Input sequences

Gap scoring

Scoring matrix

Email address

Output format

ClustalW - Output

Match strength in decreasing order: * : .

ClustalW - Output

ClustalW - Output

ClustalW - Output

ClustalW - Output

Pairwise alignment scores

Building alignment

Final score

Building tree

ClustalW - Output

ClustalW Output

Sequence names Sequence positions

Match strength in decreasing order: * : .

ClustalW - Output

ClustalW - Output

Branch length

ClustalW - Output

ClustalW - Output

http://www.ebi.ac.uk/Tools/muscle/index.html

Muscle

Muscle - output

What’s the difference between Muscle and ClustalW?

ClustalW Muscle

http://www.megasoftware.net/index.html

Can we find motifs using multiple sequence alignment?

1 2 3 4 5 6 7 8 9 10

A 0 0 0 0 0 0.5 1/6 1/3 0 0

D 0 0.5 1/3 0 0 1/6 5/6 1/6 0 1/6

E 0 0 2/3 1 0 0 0 0 1 5/6

G 0 1/6 0 0 1 1/3 0 0 0 0

H 0 1/6 0 0 0 0 0 0 0 0

N 0 1/6 0 0 0 0 0 0 0 0

Y 1 0 0 0 0 0 0.5 0.5 0 0

1 3 5 7 9

..YDEEGGDAEE..

..YDEEGGDAEE..

..YGEEGADYED..

..YDEEGADYEE..

..YNDEGDDYEE..

..YHDEGAADEE..

* :** *:

MotifA widespread pattern with a biological significance

Can we find motifs using multiple sequence alignment?

YES! NO

MEME – Multiple EM* for Motif finding

• http://meme.sdsc.edu/

• Motif discovery from unaligned sequences

– Genomic or protein sequences

• Flexible model of motif presence (Motif can be absent in some sequences or appear several times in one sequence)

*Expectation-maximization

MEME - InputEmail address

Input file (fasta file)

How many times in each

sequence?

How many motifs?

How many sites?

Range of motif

lengths

MEME - Output

Motif score

MEME - Output

Motif length

Number of times

Motif score

MEME - Output

Low uncertainty

=

High information content

MEME - Output

Multilevel Consensus

Sequence names

Position in sequence

Strength of match

Motif within sequence

MEME - Output

Overall strength of motif matches

Motif location in the input sequence

MEME - OutputSequence names

MAST

• Searches for motifs (one or more) in sequence databases:

– Like BLAST but motifs for input

– Similar to iterations of PSI-BLAST

• Profile defines strength of match

– Multiple motif matches per sequence

– Combined E value for all motifs

• MEME uses MAST to summarize results:

– Each MEME result is accompanied by the MAST result for searching the discovered motifs on the given sequences.

http://meme.sdsc.edu/meme4_4_0/cgi-bin/mast.cgi

MEME - Input

Email address

Input file (motifs)

Database

JASPAR

• Profiles

– Transcription factor binding sites

– Multicellular eukaryotes

– Derived from published collections of experiments

• Open data accesss

JASPAR

• profiles

– Modeled as matrices.

– can be converted into PSSM for scanning genomic sequences.

1 2 3 4 5 6 7 8 9 10

A 0 0 0 0 0 0.5 1/6 1/3 0 0

D 0 0.5 1/3 0 0 1/6 5/6 1/6 0 1/6

E 0 0 2/3 1 0 0 0 0 1 5/6

G 0 1/6 0 0 1 1/3 0 0 0 0

H 0 1/6 0 0 0 0 0 0 0 0

N 0 1/6 0 0 0 0 0 0 0 0

Y 1 0 0 0 0 0 0.5 0.5 0 0

Search profile

http://jaspar.genereg.net/

scoreorganismlogoName of

gene/protein