Introduction to Bioinformatics - Shandong University · Introduction to Bioinformatics English Courses for Graduate Students English Courses for Graduate Students Introduction to

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Introduction to Bioinformatics

Dr. rer. nat. Gong Jing

Cancer Research Center

Medicine School of Shandong University

2012.11.07

Introduction to Introduction to BioinformaticsBioinformatics

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Chapter 3

Alignment


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In the game of Mahjong Titans, you want to find the same symbol from a collection of symbols for a certain one. What you can do is to compare the symbol with every one, with your eyes.


Similarity Searches on Sequence Databases

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For a protein or DNA sequence, similarity search means finding a similar one from a collection of sequences for a query sequence.

…… > 100,000

BLAST


Similarity Searches on Sequence Databases

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Similar sequences often derive from a common ancestral sequence. They probably share similar structure and biological function. You can infer something you know about a particular DNA or protein sequence to all similar DNA or protein sequences.

Similar sequences

Similar structures Similar functions


The Importance of Similarity

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Similar sequences often derive from a common ancestral sequence. They probably share similar structure and biological function. You can infer something you know about a particular DNA or protein sequence to all similar DNA or protein sequences.

Similar structure? Similar function? Brothers?


The Importance of Similarity

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Residue: a letter; an amino acid in a protein; a base in a nucleotide.

Identity: If two sequences (protein or DNA) have the same length, the identity between them is defined as the percent of identical residues relative to their length.

Similarity: If two sequences (protein or DNA) have the same length, the similarity between them is defined as the percent of identical andsimilar residues relative to their length.

Similar or not: defined by a matrix, such as BLOSUM.

My name is Lampy.


Identity and Similarity

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seq 1 : CLHKseq 2 : CIHL

Identity = 2/4 = 50%

Similarity = 3/4 = 75%



seq 1 : C L H Kseq 2 : C I H L

seq 1 : C L H Kseq 2 : C I H L

Identical

similar



Similarity: If two sequences (protein or DNA) have the same length, the similarity between them is defined as the percent of identical andsimilar residues relative to their length.

Similar or not: defined by a matrix, such as BLOSUM.

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Similarity: If two sequences (protein or DNA) have the same length, the similarity between them is defined as the percent of similar residues relative to their length. Who and who are similar, who and who not? They are defined by a matrix, such as BLOSUM.

What happens when two sequences have different lengths?

Identity? Similarity?

seq 1 : CLHKAseq 2 : CIHL



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Homologous: In general, if two protein sequences have an identity > 25%, or two DNA sequences have an identity > 70%, they can be regarded as homologous.

Nothing is sure about the meaning of observed similarity. Some protein sequences are less than 15% identical, but they have the same 3D structure, while some are 25% identical, but they have different structures.

Homology or non-homology is never granted. The 25% cutoff is mostly a common-sense indicator. In most cases, to make sure whether two sequences are true homologous, you need to consider many other things.

Homology is a binary relationship: yes or no; similarity or identity is a quantifiable property: 0%-100%.



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BLAST (Basic Local Alignment Search Tool) – A sequence comparison algorithm optimized for speed used to search sequence databases for optimal local alignments to a query.

Different kinds of BLAST (according to the query):

BLASTn: Search a nucleotide database using a nucleotide query.

BLASTp: Search protein database using a protein query.

BLASTx: Search protein database using a translated nucleotide query.

tBLASTn: Search translated nucleotide database using a protein query.

tBLASTx: Search translated nucleotide database using a translated nucleotide query.


The Most Popular Search Tool: BLAST

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BLAST (Basic Local Alignment Search Tool) – A sequence comparison algorithm optimized for speed used to search sequence databases for optimal local alignments to a query.

Different kinds of BLAST (according to the algorithm):

standard BLAST

psi-BLAST

phi-BLAST



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The NCBI BLAST server http://www.ncbi.nlm.nih.gov/



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The NCBI BLAST server: BLASTp http://blast.ncbi.nlm.nih.gov



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blast.fasta




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http://www.crc.sdu.edu.cn/bioinfo/2012

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query only a part of your sequence

give a name to your job

blast.fasta

BLAST another sequence at the same time




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select against which database you want to search




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limit the search range to a certain species , e.g. human

select algorithm




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Part 1 : a brief summary




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sequence length and classification of the input protein.

Part 2 : graphic summary

an overview of similar sequences

……



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Part 3 : descriptions

……

go to the alignment between your query sequence and the matching sequence




go to the corresponding database entry

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Part 4 : Alignment



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Sometimes the standard BLAST is not enough. For instance, you want to catch all the members of a very large protein family, starting with one sequence that you have. When running BLAST, you catch only the most closely related sequences. The other distant members would not be found. In other words, you find your direct friends, but the friends of your friends are missing.

PSI (Position-Specific Iterated)-BLAST first looks for sequences that are closely related to yours; and then, gradually, it extends the circle of friends to include sequences that are distantly related.

- How does PSI-BLAST extend the circle of friends?

- A Position-Specific Weight Matrix and Iterations.

Introduction to BioinformaticsEnglish Courses for Graduate Students


Upgraded BLAST: PSI-BLAST

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Seq1: A B C DSeq2: B B C DSeq3: A C C DSeq4: A B D D

1 2 3 4A 75% 0 0 0B 25% 75% 0 0C 0 25% 75% 0D 0 0 25% 100%

A Position-Specific Weight Matrix describes the letter distribution of each position (column) for a family of sequences. The distributions can be presented as probabilities or other statistic values.



Position-Specific Weight Matrix

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For the query sequence ABCD, the first round of search (first iteration) of PSI-BLAST is just like BLAST. All closely related sequences BBCD, ACCD and ABDD that have one different letter are found, but BCCD that has two different residues is missing.

Then, a Position-Specific Weight Matrix is made for ABCD, BBCD, ACCD and ABDD. This matrix is used in the second round of search (second iteration). Since BCCD matches the matrix, now it is found. And then, a second matrix is made for ABCD, BBCD, ACCD, ABDD and BCCD. And then new sequences will be found. …… Iterations ……

PSI-BLAST can detect distant evolutionary relationships, especially when the proteins returned by the first round of search are all hypothetical proteins, unknown proteins or predicted proteins.

BACD ……BBCD BBAD ……

BBCA BCADBCCD BCBD

ABCD ACCD ACBD BCDDACCB ……CBDD ……

ABDD ACDD ……ABDC ……


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Upgraded BLAST: PSI-BLAST

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Upgraded BLAST: PSI-BLASTThe NCBI BLAST server: PSI-BLAST http://blast.ncbi.nlm.nih.gov

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PHI (Pattern-Hit Initiated)-BLAST: in every round of BLAST (iteration), you are required to give a sequence pattern to filter the results. Only the BLAST results that match the pattern are regarded as results.

Sequence pattern:

[LIVMF]-G-E-x-[GAS]-[LIVM]-x(3,7)

Yes: VGEAAMPRI

No: VGEAAYPRI

PHI-BLAST can find very exact “friends”.





Upgraded BLAST: PHI-BLAST

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Upgraded BLAST: PHI-BLASTThe NCBI BLAST server: PHI-BLAST http://blast.ncbi.nlm.nih.gov

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BLAST

PSI-BLAST

PHI-BLAST

Query





Upgraded BLAST: PHI-BLAST

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http://blast.ddbj.nig.ac.jpDDBJJapanhttp://www.ebi.ac.uk/Tools/sssEBIEurope

http://www.ncbi.nlm.nih.gov/BLASTNCBIUSAhttp://web.expasy.org/blastExPASyEurope

URLServerLocationBLAST Servers around the World

WU-BLAST - WU stands for Washington University. More sensitive and more gifted at inserting gaps than NCBI-BLAST.Smith and Waterman (SSEARCH): It’s slower, but more accurate than BLAST.FASTA: It’s a bit slower than BLAST but more accurate when making DNA comparisons.BLAT: Use this for locating cDNA rapidly in a genome or finding close (mammalian vs. mammalian) proteins in a genome.





Similarity Searches for Free over the Internet

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can help you to …Convince yourself that two sequences are in fact homologous;Find out that your sequences share a domain;Identify the exact location of common features, such as disulfide bridgesor catalytic active sites.

Domain: a structural and functional unit in a protein.

single-domain protein multiple-domain protein





Comparing Two Sequences

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Methods: dot plot, global/local alignment

Dot plot is the simplest means of comparing two sequences. In fact, dot plot is the only type you can do with pencil and paper, without computer. Advantages: no biological hypothesis required; results can be analyzed with your eyes.

Seq1: THEFASTCAT

Seq2: THEFATCAT

T H E F A S T C A TT x x xH xE xF xA x xT x x xC xA x xT x x x

length(seq1) = 10length(seq2) = 910 x 9 = 90 comparisons





Seq2

Seq 1

Comparing Two Sequences: Dot plot

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Seq1: THEFASTCAT

Seq2: THEFATCAT

T H E F A S T C A TT x x xH xE xF xA x xT x x xC xA x xT x x x

The diagonals indicate the segments of similarity between the two sequences.

1. THEFA2. TCAT3. AT Seq 1

Seq2






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You can also do dot plot for one sequence to discover repeated subsequences hidden in it.

Seq1: THEFASTHE

T H E F A S T H ET x xH x xE x xF xA xS xT x xH x xE x x

Seq 1

Seq1






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http://arbl.cvmbs.colostate.edu/molkit/dnadotDnadot

http://sonnhammer.sbc.su.se/Dotter.htmlDotterhttp://emboss.sourceforge.netDottup

http://myhits.isb-sib.ch/cgi-bin/dotletDotletURLName

Dot plot servers






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Dot plot servers: Dotlet http://myhits.isb-sib.ch/cgi-bin/dotlet


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dotlet.fasta

The Sequence Input Dialog







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The dots window will display the diagonal plot.

Histogram window defines the grayscale

alignment window





Substitution matrix, e.g. Blosum62 window size zoom


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Use Dot Plot to detect tandem repeats in a sequence.

Tandem repeat: two or more repeated units directly adjacent to each other.

Example: CCCABCABCABCDDD

They are often used by evolution to create new proteins or make them function more efficiently.

Short Tandem Repeat (STR) in DNA describes a pattern that helps determine an individual's inherited traits. A short tandem repeat polymorphism (STRP) occurs when homologous STR loci differ in the number of repeats between individuals. By identifying repeats of a specific sequence at specific locations in the genome, it is possible to create a genetic profile of an individual. There are currently over 10,000 published STR sequences in the human genome. STR analysis has become the prevalent analysis method for determining genetic profiles in forensic cases.







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Tandem repeat: two or more repeated units directly adjacent to each other.Example: CCCABCABCABCDDD

C C C A B C A B C A B C D D DC x C x C x A x x xB x x xC x x xA x x xB x x xC x x xA x x xB x x xC x x xD xD xD x







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tandem.fasta








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1. The number of repeats is equal to the number of diagonals including the main diagonal.

2. The distance between two adjacent diagonals represents the length of the repeat.

3. The shortest diagonal gives you a single repeat unit.


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Tandem repeat: two or more repeated units directly adjacent to each other.Example: CCCABCABCABCDDD

C C C A B C A B C A B C D D DC x C x C x A x x xB x x xC x x xA x x xB x x xC x x xA x x xB x x xC x x xD xD xD x





Comparing Two Sequences: Dot plotDot plot servers: Dotlet http://myhits.isb-sib.ch/cgi-bin/dotlet

1. The number of repeats is equal to the number of diagonals including the main diagonal.

2. The distance between two adjacent diagonals represents the length of the repeat.

3. The shortest diagonal gives you a single repeat unit.

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An alignment is an arrangement of two protein or DNA sequences to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences.

Global alignment is most useful when the two sequences are similar and of roughly equal size.

Local alignment is more useful for dissimilar sequences that are suspected to contain segments of similarity.





Comparing Two Sequences: Alignment

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A substitution matrixBLOSUM62 gives a score for every pair of amino acids, defining “what is similar” and “how similar”.


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Usages of global alignment:

Checking minor differences between two sequences.

Analyzing polymorphisms between closely related sequences.

Comparing two sequences that partly overlap.

Usages of local alignment:

Comparing two distantly related sequences that share only a few noncontiguous domains.

Analyzing repeated elements within a single sequence.






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How to generate a global alignment?

Input:

Seq1: PYMNVI

Seq2: PYELF

substitution matrix (BLOSUM62)

gap penalty (-1 by default ): The score of a residue vs. another residue is given by the substitution matrix; a gap penalty gives the score of a residue vs. a gap.

Output:

PYMNVI PYMNVI PYMNVI--PY-ELF or PYE-LF or PY---ELF or … ?





Comparing Two Sequences: Global Alignment

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Seq1: PYMNVISeq2: PYELF

Step 1

IVNMYP-

F

L

E

Y

P

-






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Step 2

IVNMYP-

F

L

E

Y

P

-

-5

-4

-3

-2

-1

-6-5-4-3-2-10







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Step 3

IVNMYP-

F

L

E

Y

P

-

14131314113-5

14141415124-4

11121312135-3

10111213146-2

234567-1

-6-5-4-3-2-10


S(3, 3) = maxS(2, 2) + m(s13, s23) = 14+(-2) = 12S(3, 2) + gap = 13 + (-1) = 12S(2, 3) + gap = 13 + (-1) = 12






S(i, j) =maxS(i-1, j-1) + m(s1i, s2j)S(i, j-1) + gapS(i-1, j) + gap

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Step 4

IVNMYP-

F

L

E

Y

P

-

14131314113-5

14141415124-4

11121312135-3

10111213146-2

234567-1

-6-5-4-3-2-10

S(i, j) =max


S(i-1, j-1) + m(s1i, s2j)S(i, j-1) + gapS(i-1, j) + gap





Output:seq1 PYMNVIseq2 PY-ELF

** :.

There is at less one path from the lower right corner to the top left corner!


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Residue: a letter; an amino acid in a protein; a base in a DNA.


Similarity: If two sequences (protein or DNA) have the same length, the similarity between them is defined as the percent of similar residues (including identical residues) relative to their length. Who and who are similar, who and who not? They are defined by a matrix, such as BLOSUM.

What happens when two sequences have different lengths?

Identity? Similarity?

seq 1 : CVHKAseq 2 : CIHL

So far, we can define them for sequences with different lengths with the help of global alignment.






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Identity: The identity between two sequences is defined as the percent ofidentical residues in their global alignment.

Similarity: The similarity between two sequences is defined as the percent of similar residues (including identical residues) in their global alignment.

global alignment

PYMNVIPY-ELF** :.

Identity = 2 / 6 = 33.3%

Similarity = 3 / 6 = 50.0%





Redefinition of Identity and Similarity

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How to generate a local alignment?

Input:

Seq1: PYMNVI

Seq2: MN

substitution matrix (BLOSUM62)

gap penalty (-1 by default ): The score of an arbitrary residue vs. another arbitrary residue is given in the substitution matrix; a gap penalty gives the score of an arbitrary residue vs. a gap.

Output:

PYMNVI MN--MN-- or MN or … ?** **





Comparing Two Sequences: Local Alignment

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Seq1: PYMNVISeq2: MN

IVNMYP-

N

M

-

910114000

2345000

0000000

S(i, j) = max

0S(i-1, j-1) + m(s1i, s2j)S(i, j-1) + gapS(i-1, j) + gap





Output:MNMN**

Comparing Two Sequences: Local Alignment

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BLAST is an abbreviation of Basic Local Alignment Search Tool.

In a BLAST search, how does the most similar sequence found? Is the query sequence aligned to each sequence of the entire database?

–No. A BLAST search among 100,000 sequences needs ˂ 2 minutes, while calculation of 100,000 alignments needs > 10,000 minutes.

BLAST uses a heuristic algorithm:





Making Global Alignment Over the Internet

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EMBL Alignment Tool: http://www.ebi.ac.uk






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global.fastaglobal.fastaglobal.fastaglobal.fastaglobal.fasta






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Making Global Alignment Over the InternetEMBL Alignment Tool: http://www.ebi.ac.uk

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small Gap Open +

large Gap Extend







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small Gap Open +

large Gap Extend=

dispersive gaps in alignment






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large Gap Open +

small Gap Extend=

concentrative gaps in alignment






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adjust the gap openand gap extend

according to your expectation

Gap Open Gap Extend







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Making Local Alignment Over the Internet

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local.fastalocal.fasta







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>Seq1SEQUENCEMHHHHHHSSGVDLGTENLYFQSMKTTQEQLKRNVRFHAFISYSEHDSLWVKNELIPNLEKEDGSILICLYESYFDPGKSISENIVSFIEKSYKSIFVLSPNFVQNEWCHYEFYFAHHNLFHENSDHIILILLEPIPFYCIPTRYHKLKALLEKKAYLEWPKDRRKCGLFWANLRAAIN>Seq2GTENLYFQSMKTTQEQLKRNVRFHAFISYSEHDSLWVKNELIPNLEKEDGSILICLYESYFDPGKEWCHYEFYFAHHNLFHENSDHIILILLEPIPFYCIPTRAAAAAAAAAAA







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Different between Global and Local Alignments

Global alignment

Length: 186Identity: 103/186 (55.4%)Similarity: 103/186 (55.4%)

Local alignment

Length: 130Identity: 103/130 (79.2%)Similarity: 103/130 (79.2%)





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Free Pairwise Alignment over the Internet

http://www.bioinfo.mpg.de/AlignMe/AlignMe.html

Alignment of Membrane Proteins

AlignMe

http://pir.georgetown.edu/pirwww/search/pairwise.shtml

GlobalPIR

http://homepages.ed.ac.uk/eang33/mcalign/mcinstructions.html

alignment of non-coding DNA sequences

MCALIGN

http://lagan.stanford.edu/lagan_web/index.shtml

GlobalLAGAN

http://www.ebi.ac.uk/Tools/psaGlobal/LocalEMBL

http://www.ch.embnet.org/software/LALIGN_form.html

Global/LocalLalign

URLAlignment TypeNameOnline Pairwise Alignment Programs





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Multiple Sequence AlignmentA multiple sequence alignment (MSA) is a global sequence alignment of three or more sequences.





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Multiple Sequence Alignment4 main criteria for building a multiple sequence alignment :

• Structural similarity - Amino acids that play the same role in each structure are expected in the same column. This is very difficult; only structure-superimposition programs can satisfy this criterion.

• Evolutionary similarity - Amino acids in the common ancestor of all the sequences are put in the same column. Indeed, no automatic program exactly uses this criterion, but they all try to respect it.

• Functional similarity - Amino acids with the same function are in the same column. Also, no automatic program exactly uses this criterion, but if the information is available, you can edit your alignmentmanually.

• Sequence similarity - Amino acids in the same column are those that yield an alignment with maximum similarity. Most programs take this, because it is the easiest criterion.





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Main applications of MSA:

1. Extrapolation: whether an uncharacterized sequence is really a member of a protein family.

2. Phylogenetic analysis: the phylogenetic tree of aligned sequences can be reconstructed.

3. Pattern identification: very conserved positions with a certain function can be sent to generate sequence pattern or sequence logo.

4. Domain identification: to turn an MSA into a profile (position-specific weight matrix) that describes a protein domain.

Multiple Sequence Alignment





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Main applications of MSA:

5. DNA regulatory elements: to turn a DNA MSA of a binding site into a profile and scan other DNA sequences for potential binding sites.

6. Structure prediction: to predict protein/RNA secondary structures by similarity.

7. nsSNP analysis: MSA can help you predict whether a non-synonymous single-nucleotide polymorphism is likely to be harmful.

8. PCR analysis: a good multiple alignment can help you identify the less degenerated portions of a protein family, in order to fish out new members by PCR (polymerase chain reaction).

Multiple Sequence Alignment





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Choosing the Right SequencesMSA is not for an arbitrary group of sequences. Instead, the sequences should be members of the same protein family, and they all share a common ancestor.





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Choosing the Right SequencesNaming sequences in the right way:

Never use white spaces in your sequence names. Use the underline (_) to replace spaces.

Do not use special symbols. (such as Chinese symbols, @, #, &, ^ etc.).

Never use names longer than 15 characters.

Never give the same name to two different sequences in your set.

If you don’t obey these naming rules, some MSA programs may automatically change the name of your sequences, without telling you.

e.g. This_is_my_favorite_sequence_about_mouse

e.g. 我的序列壹 [email protected]

e.g. My Seq 1 My_Seq_1





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Choosing the Right SequencesChoosing the right number of sequences:

start with a relatively small number of sequence (10-15)

increase its size, after you get something interesting happening with this small set.

In any case, it’s hard to see any reason for generating a MSA with > 50 sequences.

If you start with hundreds of sequences, you immediately hit troubles:

Computing big alignments is difficult.

Building big alignments is difficult.

Displaying big alignments is difficult.

Using big alignments is difficult.

Making accurate big alignments is difficult.





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The most commonly used MSA packages.

Before you start making multiple sequence alignments, you must know that none of the methods available today is perfect. They all use approximations.

IVNMYP

F

L

E

Y

P

14131314113-5

14141415124-4

11121312135-3

10111213146-2

234567-1

-6-5-4-3-2-10

3 sequences = 3D

seq1

seq2 seq2seq1

seq3

2 sequences = 2D n sequences = nD





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ClustalW - the most commonly usedMSA package.

Tcoffee - one of the latest MSA packages.

MUSCLE - one of the fastest alignment methods.






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ClustalW is the latest of the Clustal software series. Clustal was the first multiple sequence alignment program. These days, with more than 35,000 citations, ClustalW is one of the most widely cited scientific publications in the history of biology.

ClustalW uses a progressive algorithm. This means that it adds sequences one by one, instead of aligning all the sequences at the same time.






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http://clustalw.ddbj.nig.ac.jp/top-j.htmlJapanDDBJhttp://bips.u-strasbg.fr/fr/Documentation/ClustalW

EuropeStrasbourg

http://www.genome.jp/tools/clustalwJapanGenomeNet

http://pir.georgetown.edu/pirwww/search/multialn.shtml

USAPIR

http://searchlauncher.bcm.tmc.edu/multi-align/Options/clustalw.html

USABCM

http://www.ebi.ac.uk/Tools/msa/clustalw2EuropeEBI

http://www.ch.embnet.org/software/ClustalW.html

EuropeEMBnet

URLLocationNameA List of ClustalW Servers






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EMBL ClustalW http://www.ebi.ac.uk






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msa.fasta

Human TLR1-10’s TIR domains

msa.fasta







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The sequences in the alignment are sorted by the pairwise identity.







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Red:hydrophobic

Blue:Acidic

Magenta:Basic

Green:Hydroxyl + Amine + Basic

Gray:Others







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* Asterisk - an entirely conserved column.

: Double-dot - columns where all the residues have roughly the same size and the same hydropathy.

. Single-dot - columns where the size or the hydropathyhas been preserved in the course of evolution.







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The guide tree is NOT a phylogenetic tree!

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Tcoffee is a recent method developed for conducting multiple sequence alignments. It uses a principle that’s a bit similar to ClustalW, but it yields more accurate alignments at the cost of a slightly longer running time. Tcoffeebuilds a progressive alignment like ClustalW, but it compares segments across the entire sequence set.

Home page : http://www.tcoffee.org

http://tcoffee.crg.cat






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http://www.es.embnet.org/Services/MolBio/t-coffeeEMBnethttp://cbsuapps.tc.cornell.edu/t_coffee.aspxCBSU

http://www.ebi.ac.uk/Tools/msa/tcoffeeEBI

http://toolkit.tuebingen.mpg.de/t_coffeeMax-Planck

http://tcoffee.vital-it.chSIB

http://www.igs.cnrs-mrs.fr/Tcoffee/tcoffee_cgi/ index.cgiCNRS

URLNameT-Coffee Mirror sites






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Incorporate all the available structural information in your alignment. Will produce the best sequence alignments if the structures are available.

EXPRESSO

Evaluate the reliability of an existing multiple alignmentCORERun any requested Multiple sequence Alignment package and combine all the output into one final alignment.

MCOFFEE

Produce a multiple sequence alignment with Tcoffee.TCOFFEEDescriptionUsage

Available Tools on www.tcoffee.org

Aside from its accuracy, the main specificity of Tcoffee is its ability to align sequences and structures (EXPRESSO), the possibility of evaluating the accuracy of an alignment (CORE) and the possibility of combining many alternative multiple sequence alignments into one (Mcoffee).






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T-Coffee http://tcoffee.crg.cat






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Human TLR1-10’s TIR domains

msa.fasta






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http://tcoffee.crg.cat

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score_html file

clustalw_aln file

fasta_aln file

phylip file







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When you choose to store your data in a specific format, you must ask yourself four questions:

Do most programs support this format?

Will my collaborators be able to use it?

Can I store all the information I need with this format?

Is it easy to manipulate?

If the program you’re using doesn’t produce alignments in the format you need, it is possible to use a third-party conversion tool to get the format you want.

fmtseq : http://www.bioinformatics.org/JaMBW/1/2 or

http://evol.mcmaster.ca/Pise/5.a/fmtseq.html







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EXPRESSO is the latest development of Tcoffee, replacing what was known as 3D-Coffee. When you run Expresso, the program uses BLAST to search the PDB for structures whose sequences are similar to your sequences. It then uses theses structures to guide the alignment. Alignments based on structures are expected to be much more accurate than simple sequence alignments.







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EXPRESSO T-Coffee







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PDB ID







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MUSCLE - is a newcomer in the MSA area but it is aremarkably efficient package for making fast, high-quality multiple sequence alignments. MUSCLE is ideal if you want to align several hundredssequences.

Home page : http://www.drive5.com/muscle






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MUSCLE http://www.ebi.ac.uk/Tools/msa/muscle






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Searching conserved patternsOne sentence summarizes what you really want from your multiple alignment:

You want to identify important positions!





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Sequence Logos: WebLogo

Sequence logos - are a graphical representation of an amino acid or nucleic acid multiple sequence alignment developed by Tom Schneider and Mike Stephens. Each logo consists of stacks of symbols, one stack for each position in the sequence. The overall height of the stack indicates the sequence conservation at that position, while the height of symbols within the stack indicates the relative frequency of each amino or nucleic acid at that position. In general, a sequence logo provides a richer and precise description of, for example, a binding site.

Searching conserved patterns





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WebLogo - is a web based application designed to make the generation of sequence logos easy and painless. WebLogo has featured in over 150 scientific publications. http://weblogo.berkeley.edu

Sequence Logos: WebLogo http://weblogo.berkeley.edu






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promoter.seqs

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11720 30







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In the promoter region of genes, we usually found a special fragment, called TATA box (also called Goldberg-Hogness box). The TATA box has the core DNA sequence 5'-TATAAT-3' or a variant. It is usually found as the binding site of RNA polymerase.

http://correlogo.abcc.ncifcrf.gov







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Sequence Motif - a nucleotide or amino-acid sequence pattern that is widespread and has a biological significance.

Example: N-glycosylation site motif

Asn, followed by anything but Pro, followed by either Ser or Thr, followed by anything but Pro

This pattern can be written as N{P}[ST]{P}(Regular expression), where N=Asn, P=Pro, S=Ser, T=Thr; {X} means any amino acid except X; and [XY] means either X or Y. The notation [XY] does not give any indication of the probability of X or Yoccurring in the pattern. Observed probabilities can be graphically represented using sequence logos.






Sequence Motifs: MEME http://meme.sdsc.edu/meme/intro.html

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The MEME Suite - Motif-based sequence analysis tools.

The MEME Suite allows you to:• discover motifs on groups of related DNA or protein sequences, • search sequence databases using motifs, • compare a motif to all motifs in a database of motifs. Home page : http://meme.sdsc.edu/meme/intro.html







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meme.seqs

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One sentence summarizes what you really want from your multiple alignment:

You want to identify important positions!







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BB-Loop

BB-Loop - is important for the TIR domain dimerizationand interaction with downstream adaptors or inhibitors.

Human TLR 1-TIRHuman TLR 2-TIRHuman TLR 10-TIR






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score_html file

clustalw_aln file

fasta_aln file

phylip file





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Editing and Publishing Alignments

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For editing and publishing a multiple sequence alignment, bioinformaticanshave developed text editors that are specific for multiple sequence alignment. They make it easy for you to see exactly what’s going on.

Most of these editors require the installation of something on your computer. However, if you want to stick to your browser, you can use Jalview.

Jalview is a Java applet that you need only load into your Web browser for instant action. Home page : http://www.jalview.org

Do not load confidential sequences!Web interface is NOT secure.





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EMBL ClustalW http://www.ebi.ac.uk/Tools/msa/clustalw2






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Jalview http://www.jalview.org/download.html






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run







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Close ALL the windows that appear within the Jalview Window, as they only contain sample data.





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results.clustalwresults.clustalw







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Jalview http://www.jalview.org/download.htmlhttp://www.jalview.org/help.html






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Jalview http://www.jalview.org/download.htmlColour -> Clustalx






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Jalview http://www.jalview.org/download.htmlColour -> Clustalx






http://www.jalview.org/help.html

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When you edit an alignment, you usually want to do is collectively modify the alignment. To do this, you need to define them as a group, as follows:

Keep the Ctrl key pressed while you click names of sequences 1, 2, 3 and 4 to select them.






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1. Keep the Ctrl key pressed.2. Put your mouse pointer right where you want to insert or remove the gap.3. Drag to the left or to the right to shift your sequences.

You can edit one sequence at a time by pressing the Shift key instead of Ctrl.






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perform PairwiseAlignment for a pair of selected sequences






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calculate tree for all selected sequences






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predict secondary structure for a selected sequence.






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JNet Secondary Structure Prediction result






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save your alignment as a text/picture






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Showtime has finally come: You have the multiple alignment you want, and you’re determined to show the world!






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A multiple alignment editor written in Java

http://www.jalview.orgJalView

A very powerful shading and-coloring tool

http://espript.ibcp.fr/ESPript/ESPriptESPript

Shading in black and whitehttp://www.ch.embnet.org/software/BOX_form.html

Boxshade

Adding optional HTML markup to control coloring and web page layout

http://bio-mview.sourceforge.netMView

DescriptionURLNameMultiple Alignment Beautifying Tools






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exercise.fasta

Can you make a MSA for these 5 protein sequences?Which two sequences are the most similar ones?How similar are they? (i.e. How about their sequence identity?)What kind of proteins are they?





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