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Tutorial 5. Multiple sequence alignments and motif discovery. Multiple sequence alignments and motif discovery. Multiple sequence alignment ClustalW Muscle Motif discovery MEME Jaspar. A. C. D. B. Multiple Sequence Alignment. More than two sequences DNA Protein
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Tutorial 5 Multiple sequence alignments and motif discovery
Multiple sequence alignments and motif discovery • Multiple sequence alignment • ClustalW • Muscle • Motif discovery • MEME • Jaspar
A C D B Multiple Sequence Alignment • More than two sequences • DNA • Protein • Evolutionary relation • Homology Phylogenetic tree • Detect motif GTCGTAGTCGGCTCGACGTCTAGCGAGCGTGATGCGAAGAGGCGAGCGCCGTCGCGTCGTAAC GTCGTAGTCG-GC-TCGACGTC-TAG-CGAGCGT-GATGC-GAAG-AG-GCG-AG-CGCCGTCG-CG-TCGTA-AC
A C D B Multiple Sequence Alignment • Dynamic Programming • Optimal alignment • Exponential in #Sequences • Progressive • Efficient • Heuristic GTCGTAGTCGGCTCGACGTCTAGCGAGCGTGATGCGAAGAGGCGAGCGCCGTCGCGTCGTAAC GTCGTAGTCG-GC-TCGACGTC-TAG-CGAGCGT-GATGC-GAAG-AG-GCG-AG-CGCCGTCG-CG-TCGTA-AC
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
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 - Input http://www.ebi.ac.uk/Tools/clustalw2/index.html Input sequences Scoring matrix Gap scoring Output format Email address
ClustalW - Output Match strength in decreasing order: * : .
ClustalW - Output Pairwise alignment scores Building tree Building alignment Final score
ClustalW Output Sequence names Sequence positions Match strength in decreasing order: * : .
ClustalW - Output Branch length
Muscle http://www.ebi.ac.uk/Tools/muscle/index.html
What’s the difference between Muscle and ClustalW? ClustalW Muscle
Can we find motifs using multiple sequence alignment? 1 3 5 7 9 ..YDEEGGDAEE.. ..YDEEGGDAEE.. ..YGEEGADYED.. ..YDEEGADYEE.. ..YNDEGDDYEE.. ..YHDEGAADEE.. * :** *: • Motif • A 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
Email address How many times in each sequence? MEME - Input Input file (fasta file) Range of motif lengths How many motifs? How many sites?
MEME - Output Motif score
MEME - Output Motif score Motif length Number of times
MEME - Output Low uncertainty = High information content
MEME - Output Multilevel Consensus
MEME - Output Position in sequence Strength of match Sequence names Motif within sequence
MEME - Output Sequence names Motif location in the input sequence Overall strength of motif matches
MAST http://meme.sdsc.edu/meme4_4_0/cgi-bin/mast.cgi • 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.
MEME - Input Email address Database Input file (motifs)
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.
Search profile http://jaspar.genereg.net/
logo Name of gene/protein organism score