Multiple alignments - applications

Identify conserved motifs - patterns (PROSITE)Profiles (Pfam)Phylogenetic studiesPrediction of protein secondary structureExperimental : design of probes

Example of experimental application of msa.Probes may be designed for PCR to amplify a region of DNA.

GCCCAAATTACGGGGACAACGGATCTTGGGTTATC......CGGGACGGG GCCCAAATTACGGGGTACTTACGCGGGGACTTTAT......CGGGACGGG GCCCAAATTACGGGGACGGACTTAGC...............CGGGACGGG GCCCAAATTACGGGGCGAGTCTATCTTTTACTTATCTTT..CGGGACGGG GCCCAAATTACGGGGCGGACTTTACTTATCTTTTTCTTT..CGGGACGGG GCCCAAATTACGGGGACGGACGGCGATCGAGCGATCG....CGGGACGGG GCCCAAATTACGGGGACGACGTACGTGAGCC..........CGGGACGGG GCCCAAATTACGGGGACAATTTATCTATCTTTATC......CGGGACGGG GCCCAAATTACGGGGACAACGATCGTGACTGACTG......CGGGACGGG GCCCAAATTACGGGGACAATACGGGACTTATCGGGCTTCC.CGGGACGGG GCCCAAATTACGGGGCGGAGCGGAGCGAGCGGGACGGGCG.CGGGACGGG GCCCAAATTACGGGGACGAGCGGCATCTACTTCGCGCTA..CGGGACGGG GCCCAAATTACGGGGAAAACAATTCTATCTTTATCGCAAAACGGGACGGG

Multiple sequence alignment

PILEUP

PileUp does a series of progressive, pairwise alignments between sequences and clusters of sequences to generate the final multiple alignment. A cluster consists of two or more already-aligned sequences.

PileUp begins by doing pairwise alignments that score the similarity between every possible pair of sequences. These similarity scores are used to create a clustering order that can be represented as a dendrogram. The clustering strategy represented by the dendrogram is called UPGMA that stands for unweighted pair-group method using arithmetic averages (Sneath, P.H.A. and Sokal, R.R. (1973) in Numerical Taxonomy (pp; 230-234), W.H. Freeman and Company, San Francisco, California, USA).

The dendrogram shows the order of the pairwise alignments of sequences and clusters of sequences that together generate the final alignment. For example:

PileUp aligns the two most related sequences to each other in order to produce the first cluster. It then aligns the next most related sequence to this cluster or the next two most-related sequences to each other in order to produce another cluster. A series of such pairwise alignments that includes increasingly dissimilar sequences and clusters of sequences at each iteration produces the final alignment.

In the above example, Seq1 and Seq2 are aligned first. Next, Seq3 and Seq4 are aligned. The cluster of Seq1-aligned-to-Seq2 is then aligned to the cluster of Seq3-aligned-to-Seq4. Finally, Seq5 is aligned to the cluster that now contains Seq1 through Seq4 to generate the final alignment of Seq1 through Seq5.

Each pairwise alignment in PileUp uses the method of Needleman and Wunsch (Journal of Molecular Biology 48; 443-453 (1970)), that is extended for use with clusters of aligned sequences rather than only individual sequences. For a pairwise alignment of individual sequences, the comparison score between any two sequence symbols is found in a scoring matrix. For a pairwise alignment of clusters of sequences, the comparison score between any two positions in those clusters is simply the arithmetic average of the scores for all possible symbol comparisons at those positions. When gaps are inserted into a cluster to produce an alignment, they are inserted at the same position in all of the sequences of the cluster.

CLUSTAL

Clustalw creates a multiple alignment, using methods reminiscent of those of Pileup. One difference between the programs: During the multiple alignment, terminal gaps are penalised in Clustal but not in PILEUP. This will make the PILEUP alignments better when the sequences are of very different lengths (has no effect if there are no large terminal gaps).

CLUSTALW (W = weighting , different weigths to sequences and parameters at different positions in alignments) ftp://ftp.sunet.se/pub/molbio/align/clustal

See documentation in file clustalv.doc

CLUSTAL W (1.7) Multiple Sequence Alignments

Sequence format is PearsonSequence 1: Seq1 26 aaSequence 2: Seq2 33 aaSequence 3: Seq3 30 aaSequence 4: Seq4 31 aaSequence 5: Seq5 26 aaStart of Pairwise alignmentsAligning...Sequences (1:2) Aligned. Score: 61Sequences (1:3) Aligned. Score: 50Sequences (1:4) Aligned. Score: 15Sequences (1:5) Aligned. Score: 11Sequences (2:3) Aligned. Score: 46Sequences (2:4) Aligned. Score: 29Sequences (2:5) Aligned. Score: 38Sequences (3:4) Aligned. Score: 40Sequences (3:5) Aligned. Score: 34Sequences (4:5) Aligned. Score: 61Guide tree file created: [t.dnd]Start of Multiple AlignmentThere are 4 groupsAligning...Group 1: Sequences: 2 Score:371Group 2: Sequences: 3 Score:180Group 3: Sequences: 2 Score:351Group 4: Sequences: 5 Score:136Alignment Score 209CLUSTAL-Alignment file created [t.aln]

Examples of clustal parameters:

Pairwise -gap openinggap extensionsubstitution matrix

Multiple alignment -gap openinggap extensionsubstitution matrix

Multiple alignment software

Pileup (GCG)

Clustalw / Clustalx

MSA (program that in principle finds the true optimal multiple alignment by thedynamic programming method)

T-coffee

Multiple alignment editors/viewers

SeqLab (GCG)MACAW (search for motifs, blocks)JalviewCINEMAGenedocBoxshadeMview

Clustalx

njplot

Multiple sequence alignment formatting Jalview

Multiple sequence alignment formatting Boxshade

hth01 TPRQKVAIIYDVGVSTLYKRFPhth02 IPRKQVAIIYDVAVSTLYKKFPhth03 HPRQQLAIIFGIGVSTLYRYFPhth04 GSKTKLAQAAGIRLASLYSWKGhth05 TTFKQIALESGLSTGTISSFINhth06 IPYQEFAKLIGKSTGAVRRMIDhth07 VTLQQFAELEGVSERTAYRWTThth08 FTYNQYAQMMNISRENAYGVLAhth09 LGASHISKTMNIARSTYVKVINhth10 TGATEIAHQLSIARSTVYKILEhth11 ISISAIAREFNTTRQTILRVKAhth12 GNISALADAENISRKIITRCINhth13 MVLADIAQAVEMHESTISRVTThth14 LVLHDIAEAVGMHESTISRVTThth15 LNLRIVADAIKMHESTVSRVTShth16 MTRGDIGNYLGLTVETISRLLGhth17 LSLSALSRQFGYAPTTLANALEhth18 MSLAELGRSNGLSSSTLKNALDhth19 FDIASVAQHVCLSPSRLSHLFRhth20 LRIDEVARHVCLSPSRLAHLFRhth21 VTLEALADQVAMSPFHLHRLFKhth22 VLYPDIAKKFNTTASRVERAIR

Multiple sequence alignment formatting Mview

Multiple alignments - applications

Identify conserved motifs - patterns (PROSITE)Profiles (Pfam)Phylogenetic studiesPrediction of protein secondary structureExperimental : design of probes

TPRQKVAIIY DVGVSTLYKR FP IPRKQVAIIY DVAVSTLYKK FP HPRQQLAIIF GIGVSTLYRY FP GSKTKLAQAA GIRLASLYSW KG TTFKQIALES GLSTGTISSF IN IPYQEFAKLI GKSTGAVRRM ID VTLQQFAELE GVSERTAYRW TT FTYNQYAQMM NISRENAYGV LA LGASHISKTM NIARSTYVKV IN TGATEIAHQL SIARSTVYKI LE ISISAIAREF NTTRQTILRV KA GNISALADAE NISRKIITRC IN MVLADIAQAV EMHESTISRV TT LVLHDIAEAV GMHESTISRV TT LNLRIVADAI KMHESTVSRV TS MTRGDIGNYL GLTVETISRL LG LSLSALSRQF GYAPTTLANA LE MSLAELGRSN GLSSSTLKNA LD FDIASVAQHV CLSPSRLSHL FR LRIDEVARHV CLSPSRLAHL FR VTLEALADQV AMSPFHLHRL FK VLYPDIAKKF NTTASRVERA IR

Profiles : Example with HTH (helix turn helix) motif

A B C D E F G H I K L M N P Q R S T V W X Y Z -25 -89 -44 -89 -74 -6 -79 -65 31 -63 33 31 -66 -79 -57 -66 -41 -9 28 -62 -40 -27 -74-11 -23 -62 -23 -27 -81 -29 -51 -56 -27 -59 -41 0 3 -27 -39 19 29 -37 -97 -34 -72 -27-25 -102 -52 -102 -68 -7 -103 -53 18 -38 36 14 -72 -89 -46 -24 -50 -37 3 -62 -42 -3 -68 2 -9 -67 -9 13 -82 -28 -18 -78 10 -69 -38 6 -27 26 -3 29 0 -57 -90 -25 -57 13 -7 28 -82 28 51 -85 -48 -16 -76 11 -74 -42 -8 -38 44 -10 7 -26 -55 -97 -23 -58 51-32 -116 -40 -116 -97 14 -130 -93 96 -87 72 39 -105 -101 -86 -95 -71 -32 77 -78 -49 -13 -97198 -100 -12 -100 -54 -112 17 -106 -66 -54 -66 -60 -94 -57 -54 -57 60 -3 -15 -161 -49 -112 -54-40 -3 -89 -3 22 -78 -70 -14 -60 21 -54 -28 -3 -53 31 20 -18 -33 -52 -95 -29 -52 22 6 -49 -52 -49 -12 -46 -64 -20 -24 -21 -19 -8 -39 -54 0 -27 -7 -18 -13 -76 -29 -27 -12-25 -75 -52 -75 -50 19 -88 -50 24 -56 11 17 -64 -81 -47 -68 -40 -28 24 -52 -36 8 -50

-17 -1 -65 -1 -30 -100 78 -41 -111 -36 -113 -82 40 -65 -38 -46 12 -39 -91 -97 -43 -89 -30-28 -100 -38 -100 -78 -10 -114 -82 65 -58 60 54 -81 -82 -56 -67 -50 -13 56 -71 -41 -27 -78 30 -27 -47 -27 -16 -70 -3 -7 -71 -18 -70 -45 8 -44 -15 -25 68 22 -58 -94 -27 -55 -16-14 -39 -78 -39 4 -84 -70 -45 -46 -4 -48 -29 -36 -1 -5 0 -19 -6 -25 -102 -34 -65 4 19 -10 -61 -10 6 -74 -4 -38 -83 1 -79 -44 16 -46 3 -25 93 15 -73 -102 -26 -70 6 -4 -46 -55 -46 -36 -85 -77 -56 -50 -28 -49 -41 4 -52 -31 -15 30 142 -20 -95 -33 -76 -36-17 -121 -34 -121 -94 -8 -124 -98 84 -79 84 43 -103 -96 -77 -85 -63 -28 68 -85 -48 -27 -94-10 -55 -56 -55 -26 -9 -59 6 -45 -23 -42 -30 -26 -64 -16 -34 11 -15 -38 -40 -28 45 -26-36 -49 -105 -49 3 -102 -51 14 -109 66 -83 -46 23 -65 24 110 -9 -33 -102 -110 -35 -64 3 -8 -99 -26 -99 -69 -14 -87 -73 24 -52 21 17 -86 -79 -53 -61 -48 -25 30 -35 -41 -16 -69

-38 -93 -50 -93 -79 37 -109 -72 32 -60 35 14 -76 -94 -71 -68 -44 -7 16 -50 -43 -5 -79-15 0 -79 0 4 -92 -21 -31 -84 -2 -81 -56 16 -8 -6 -4 9 2 -65 -101 -31 -75 4

Profile based on HTH motif alignment

Profilemake Makes a profile from a multiple sequence alignment.Profilesearch Compares a profile to a sequence database. Finds

the sequences that best fit the profile.Profilescan Compares a sequence to a library of profiles.

Finds the profile that best fit the sequenceProfilegap Compares a sequence and a profile, producing a

sequence-profile alignmentProfilesegments Aligns a profile of the sequences found by

profilesearch.

MEME Finds conserved motifs in a group of unaligned sequences. MEME saves these motifs as a set of profiles. You can search a database of sequences with these profiles using the MotifSearch program.

PSIBLAST

PSI-BLAST is an important tool to identify remote protein similarity. It proceeds by way of the following steps:

(1) PSI-BLAST takes as an input a single protein sequence and compares it to a protein database, using the gapped BLAST program . (2) The program constructs a multiple alignment, and then a profile, from any

significant local alignments found. The original query sequence servesas a template for the multiple alignment and profile, whose lengths are identical to that of the query.

(3) The profile is compared to the protein database, again seeking local alignments. After a few minor modifications, the BLAST algorithm can be used for this directly.

(4) PSI-BLAST estimates the statistical significance of the local alignments found. Because profile substitution scores are constructed to a fixed scale , and gap scores remain independent of position, the statistical theory and parameters for gapped BLAST alignments remain applicable to profile alignments.

(5) Finally, PSI-BLAST iterates, by returning to step (2), an arbitrary number

of times or until convergence.

Profile-alignment statistics allow PSI-BLAST to proceed as a natural extension of BLAST; the results produced in iterative search steps are comparable to those produced from the first pass.

Advantage : Unlike most profile-based search methods, PSI-BLAST runs as one program, starting with a single protein sequence, and the intermediate steps of multiple alignment and profile construction are invisible to the user.

Psiblast tutorial http://www.ncbi.nlm.nih.gov/Education/BLASTinfo/psi1.html

Evidence of Med4/Trap36 homology.PSI-Blast using human Trap36 as query sequence

Results from round 2 Score ESequences producing significant alignments: (bits) ValueSequences used in model and found again:

ref|NP_054885.1| HSPC126 protein; p36 TRAP/SMCC/PC2 subunit [Hom... 367 e-101gb|AAF37289.1|AF230381_1 (AF230381) p36 TRAP/SMCC/PC2 subunit [H... 366 e-100ref|XP_007213.1| HSPC126 protein [Homo sapiens] 354 7e-97gb|AAF50591.1| (AE003559) CG8609 gene product [Drosophila melano... 283 1e-75pir||T27901 hypothetical protein ZK546.13 - Caenorhabditis elega... 223 2e-57

Sequences not found previously or not previously below threshold:

gb|AAD45920.1|AF162224_1 (AF162224) angiopoietin-related protein... 33 2.8ref|NP_014817.1| Stoichiometric member of mediator complex; Med4... 33 2.8emb|CAB64662.1| (AJ249991) myosin heavy chain [Mytilus galloprov... 33 3.7gb|AAF62395.1| (AF183909) myosin heavy chain cardiac muscle spec... 33 4.8gb|AAF62394.1| (AF183909) myosin heavy chain cardiac muscle spec... 33 4.8gb|AAF62392.1|AF183909_2 (AF183909) myosin heavy chain catch (sm... 33 4.8gb|AAF62391.1|AF183909_1 (AF183909) myosin heavy chain striated ... 33 4.8pir||T22890 hypothetical protein F58A3.1c - Caenorhabditis elega... 33 4.8pir||T22888 hypothetical protein F58A3.1b - Caenorhabditis elega... 33 4.8gb|AAB38367.1| (U80221) F58A3.1b [Caenorhabditis elegans] 33 4.8

Gustafsson CM, Samuelsson T. Mol Microbiol. 2001 41:1-8.

An evolutionary conserved core of mediator subunits

Sequence logo

Multiple alignments - applications

Identify conserved motifs - patterns (PROSITE)Profiles (Pfam)Phylogenetic studiesPrediction of protein secondary structureExperimental : design of probes

Number of OTUs Number of rootedtrees

Number of unrootedtrees

2 1 13 3 14 15 35 105 156 954 1057 10,395 9548 135,135 10,3959 2,027,025 135,13510 34,459,425 2,027,025

(2n - 5)!N = ------------- 2n-3(n - 3)!

Distance matrix methodsUPGMA Example

(Unweighted pair group method with arithmetic mean)

 A  B  C  D  E B  2 C  4  4 D  6  6  6 E  6  6  6  4 F  8  8  8  8  8

http://www.icp.ucl.ac.be/~opperd/private/upgma.html

UPGMA Example (cont’d)

 A  B  C  D  E

 B  2

 C  4  4

 D  6  6  6

 E  6  6  6  4

 F  8  8  8  8  8

 A,B  C  D  E

 C  4

 D  6  6

 E  6  6  4

 F  8  8  8  8

kjji

iki

ji

ikij D

nnn

Dnn

nD ,,),( ?

??

?

D(A,B),C = (DAC + DBC) / 2 = 4D(A,B),D = (DAD + DBD) / 2 = 6D(A,B),E = (DAE + DBE) / 2 = 6D(A,B),F = (DAF + DBF) / 2 = 8

http://www.icp.ucl.ac.be/~opperd/private/upgma.html

UPGMA Example (cont’d)

 A,B  C  D,E

 C  4

 D,E  6  6

 F  8  8  8

 AB,C

 D,E

 D,E  6

 F  8  8

 ABC,DE

 F  8

http://www.icp.ucl.ac.be/~opperd/private/upgma.html

UPGMA and the effect of unequal rates of evolution

Maximum parsimony and Informative sites

Site 1 2 3 4 5 6 7 8 9Sequence -------------------------1 A A G A G T G C A2 A G C C G T G C G3 A G A T A T C C A4 A G A G A T C C G * * *

Examples of software in phylogenetic analysis

PHYLIP (Phylogenetic Inference Package)http://evolution.genetics.washington.edu/phylip.html Examples:

DNAPARS / PROTPARS - maximum parsimonyNEIGHBOR - neighbor or UPGMA joining

PAUP (Phylogenetic Analysis Using Parsimony)(GCG version: PaupSearch)