Introduction to Bioinformatics - Shandong Universitycourse.sdu.edu.cn/G2S/eWebEditor/uploadfile/20120322211245... · Identity and Similarity Residue: a letter; an amino acid in a

Introduction to BioinformaticsEnglish Courses for Graduate Students


http://1.51.212.243/bioinfo.html

Dr. rer. nat. Jing Gong

Cancer Research Center

School of Medicine, Shandong University

2011.10.12

Chapter 3

Alignment


Similarity Searches on Sequence DatabasesIn 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 databasesFor a protein or DNA sequence, it means finding a similar one from a collection of sequences. It is impossible to compare every pair in the biological databases with your eyes, because there are too many sequences.


…… > 100,000

BLAST

The Importance of SimilaritySimilar 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 SimilaritySimilar 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?

Identity and SimilarityResidue: 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 similar residues relative to their length. Who and who are similar, who and who not? They are defined by a matrix, such as BLOSUM.


My name is Lampy.

Identity and SimilarityResidue: a letter; an amino acid in a protein; a base in a DNA.




seq 1 : CLHKseq 2 : CIHL

Identity = 2/4 = 50%

Similarity = 3/4 = 75%




What happens when two sequences have different lengths?


Identity? Similarity?

seq 1 : CLHKAseq 2 : CIHL

Identity and SimilarityHomologous: In general, if two protein sequences have an identity of 25%, or two DNA sequences have an identity of 70%, they can be regarded as homologous. However,

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 is a quantifiable property: 0%-100%.


The Most Popular Search Tool: BLASTBLAST (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:

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.

Translated nucleotide: A nucleotide sequence translated into six proteins according to the six open reading frames (ORF, in prokaryotes).


= x 6 reading frames

Reading Frame - breaking a DNA sequence into three letter codonswhich can be translated in amino acids.

x 3 x 3

ATG Met (M)

TAA TAG TGA

ORF (Open Reading Frame) - a DNA sequence that contains a start codon but does not contain a stop codon in a given reading frame.

ORF


Nucleotide DatabasesNucleotide DatabasesReading into Genes and Genomes


http://www.ncbi.nlm.nih.gov/

The Most Popular Search Tool: BLASTThe NCBI BLAST server http://www.ncbi.nlm.nih.gov/

The Most Popular Search Tool: BLASTThe NCBI BLAST server : BLASTp


http://blast.ncbi.nlm.nih.gov





blast.fastablast.fasta


http://1.51.212.243/bioinfo.html





query only a part of your sequence

give a name to your job

blast.fasta

BLAST another sequence at the same time




select in which database you want to search




type which species you want to search, e.g. human

select algorithm




Part 1 : a brief summary



The Most Popular Search Tool: BLASTThe NCBI BLAST server

Part 1 : a brief summary

This figure illustrates the sequence length and classification of the input protein.

Part 2 : graphic summary

an overview of similar sequences

……




Part 3 : descriptions

……go to the corresponding database entry

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




Part 4 : Alignment

Upgraded BLAST: PSI-BLASTSometimes 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 missed.

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.


Position-Specific Weight Matrix


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.


Upgraded BLAST: PSI-BLASTThe 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 for the query sequence ABCD, but BCCD that has two different residues is missed.

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 further 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 ……


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


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


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


Upgraded BLAST: PHI-BLASTPHI (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: VGEAAMPRINo: VGEAAYPRI

PHI-BLAST can find very exact “friends”.


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


The Most Popular Search Tool: BLAST

BLAST

PSI-BLAST

PHI-BLAST

Query


Similarity Searches for Free over the Internet

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.

Comparing Two Sequencescan 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 SequencesMethods: 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


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

Comparing Two SequencesThe diagonals indicate the segments of similarity between the two sequences.

1. THEFA2. TCAT3. AT

Seq 1

Seq2

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


Seq1: THEFASTHET H E F A S T H E

T x xH x xE x xF xA xS xT x xH x xE x x

Comparing Two Sequences


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

Comparing Two SequencesDotlet servers http://myhits.isb-sib.ch/cgi-bin/dotlet



dotlet.fasta

seq1

The Sequence Input Dialog



window size zoom

The dots window will display the diagonal plot.

Histogram window defines the grayscale

alignment window


Comparing Two SequencesUse 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.



Tandem repeats: 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



tandem.fasta





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.

AlignmentAn 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. Gaps are inserted between the residues so that identical or similar characters are aligned in the same columns.

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.


AlignmentA substitution matrix BLOSUM62 gives a score for every pair of amino acids, defining “what is similar” and “how similar”.


AlignmentUsages of global alignment:

Checking minor differences between two sequences. This may happen with data that you’ve manipulated and possibly altered. The global alignment is the best way to localize potential problems.

Analyzing polymorphisms (for example, SNPs) between closely related sequences.

Comparing two sequences that partly overlap. In that case, you want to make a global pairwise comparison that doesn’t penalize misalignments at the extremities of the sequences.

Usages of local alignment:

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

Analyzing repeated elements within a single sequence.


Global Alignment


How is a global alignment generated?

Input:

Seq1: PYMNVI

Seq2: PYELF

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 PYMNVIPY-ELF or PYE-LF or … ?** :. ** :.


Seq1: PYMNVISeq2: PYELF

Step 1

IVNMYP

F

L

E

Y

P

Global Alignment


Step 2

IVNMYP

F

L

E

Y

P

-5

-4

-3

-2

-1

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

Global Alignment



Step 3

IVNMYP

F

L

E

Y

P

-5

-4

-3

-2

7-1

-6-5-4-3-2-10S(i, j) =

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

max

Global Alignment




P

P7-1

-10

S(i, j) =


max

S(1, 1) =S(0, 0) + m(s11, s21) = 0 + 7 = 7S(1, 0) + gap = -1 + (-1) = -2S(0, 1) + gap = -1 + (-1) = -2

max

Global Alignment


S(0, 0) S(0, 1)

S(1, 0) S(1, 1)

Seq 1

Seq

2

S(0, 0) + m(s11, s21) = 0 + 7 = 7S(1, 0) + gap = -1 + (-1) = -2S(0, 1) + gap = -1 + (-1) = -2

maxS(1, 1) =S(0, 0) + m(s11, s21) = 0 + 7 = 7S(1, 0) + gap = -1 + (-1) = -2S(0, 1) + gap = -1 + (-1) = -2

max


Step 4

IVNMYP

F

L

E

Y

P

-5

-4

-3

-2

7-1

-6-5-4-3-2-10S(i, j) =max

Global Alignment


S(0, 1) = maxØS(0, 0) + gap = 0 + (-1) = -1Ø



Step 5

IVNMYP

F

L

E

Y

P

-5

-4

-3

-2

234567-1

-6-5-4-3-2-10S(i, j) =max

Global Alignment




Step 6

IVNMYP

F

L

E

Y

P

14131314113-5

14141415124-4

11121312135-3

10111213146-2

234567-1

-6-5-4-3-2-10S(i, j) =max

Global Alignment


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



Step 7

IVNMYP

F

L

E

Y

P

14131314113-5

14141415124-4

11121312135-3

10111213146-2

234567-1

-6-5-4-3-2-10S(i, j) =max

Global Alignment




Step 8IVNMYP

F

L

E

Y

P

14131314113-5

14141415124-4

11121312135-3

10111213146-2

234567-1

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

seq1 PYMNVIseq2 PY-ELF

** :.

There is at less one path from the bottom-right to the top-left!

Global Alignment




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.

Redefinition of Identity and SimilarityIdentity: 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 in their global alignment.


PYMNVIPY-ELF** :.

Identity = 2 / 6 = 33.3%

Similarity = 4 / 6 = 66.7%

Local Alignment


How is a local alignment generated?

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** **


Seq1: PYMNVISeq2: MN

Step 1

IVNMYP

N

M

Local Alignment



Step 2

IVNMYP

N

M

0

0

0000000

Local Alignment

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



Step 3

IVNMYP

N

M

0

00

0000000

Local Alignment

S(i, j) = max


S(i, j) = max


S(i, j) = max


S(i, j) = max


Seq1: PYMNVISeq2: MN S(1, 1) = max

0S(0, 0) + m(s11, s21) = 0 + (-2) = -2S(1, 0) + gap = 0 + (-1) = -1S(0, 1) + gap = 0 + (-1) = -1

Local Alignment

S(i, j) = max


P

M00

00

S(0, 0) S(0, 1)

S(1, 0) S(1, 1)

Seq 1

Seq

2

S(i, j) = max




Step 4

Local Alignment

IVNMYP

N

M

0

5000

0000000

S(i, j) = max




Step 5

Local Alignment

IVNMYP

N

M

910114000

2345000

0000000

S(i, j) = max




Step 6

Local Alignment

IVNMYP

N

M

910114000

2345000

0000000

Find the maximum of the two borders.



Step 7

Local Alignment

IVNMYP

N

M

910114000

2345000

0000000

Trace back until reach 0.



Step 8

Local Alignment

IVNMYP

N

M

910114000

2345000

0000000Result: MNMN**

Making Global Alignment Over the InternetBLAST 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 less than 2 minutes, while calculation of 100,000 alignments needs more than 10,000 minutes.

BLAST uses a heuristic algorithm:


What you need know is just how to use BLAST online.

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



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



global.fastaglobal.fastaglobal.fastaglobal.fastaglobal.fasta








small Gap Open +

large Gap Extend




small Gap Open +

large Gap Extend=

dispersive gaps in alignment



large Gap Open +

small Gap Extend=

concentrative gaps in alignment


adjust the gap openand gap extend

according to your expectation

Gap Open Gap Extend



Making Local Alignment Over the InternetEMBL Alignment Tool: http://www.ebi.ac.uk/Tools/psa/emboss_water


Making Local Alignment Over the InternetEMBL Alignment Tool: http://www.ebi.ac.uk/Tools/psa/emboss_water/

local.fastalocal.fasta

>Seq1SEQUENCEMHHHHHHSSGVDLGTENLYFQSMKTTQEQLKRNVRFHAFISYSEHDSLWVKNELIPNLEKEDGSILICLYESYFDPGKSISENIVSFIEKSYKSIFVLSPNFVQNEWCHYEFYFAHHNLFHENSDHIILILLEPIPFYCIPTRYHKLKALLEKKAYLEWPKDRRKCGLFWANLRAAIN>Seq2GTENLYFQSMKTTQEQLKRNVRFHAFISYSEHDSLWVKNELIPNLEKEDGSILICLYESYFDPGKEWCHYEFYFAHHNLFHENSDHIILILLEPIPFYCIPTRAAAAAAAAAAA


Making Local Alignment Over the InternetEMBL Alignment Tool: http://www.ebi.ac.uk/Tools/psa/emboss_water/

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%)

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

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


Multiple Sequence Alignment


4 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-superposition 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.

Multiple Sequence AlignmentMain 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 AlignmentMain 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).


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.


e.g. This_is_my_favorite_sequence_about_mouse

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 the courtesy of telling you.

e.g. 我的序列壹 [email protected]


e.g. My Seq 1 My_Seq_1

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.

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



ClustalW - the most commonly usedMSA package.

Tcoffee - one of the latest MSA packages that you can use.

MUSCLE - one of the fastest alignment methods around.



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.



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



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



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

msa.fasta

Human TLR1-10’s TIR domains

msa.fasta


msa.fasta










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



Red:hydrophobic

Blue:Acidic

Magenta:Basic

Green:Hydroxyl + Amine + Basic

Gray:Others




(*) A star indicates an entirely conserved column.

(:) A double-dot indicates columns where all the residues have roughly the same size and the same hydropathy.

(.) A single-dot indicates columns where the size or the hydropathy has been preserved in the course of evolution.










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



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



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).



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





msa.fastamsa.fasta










score_html file

clustalw_aln file

fasta_aln file

phylip file



T-Coffee http://tcoffee.crg.catWhen 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 to the format you want.

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

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







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.






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




PDB ID



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 hundredsequences.

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



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

Searching conserved patterns


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

You want to identify important positions!











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


score_html file

clustalw_aln file

fasta_aln file

phylip file

Getting Your Multiple Alignment in the Right Format


Editing and Publishing AlignmentsFor 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 that you install 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.


Editing and Publishing AlignmentsEMBL ClustalW http://www.ebi.ac.uk/Tools/msa/clustalw2


Editing and Publishing AlignmentsJalview http://www.jalview.org/download.html





run



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



results.clustalwresults.clustalw




Editing and Publishing AlignmentsJalview http://www.jalview.org/download.htmlhttp://www.jalview.org/help.html




Editing and Publishing AlignmentsJalview http://www.jalview.org/download.htmlColour -> Clustalx


Editing and Publishing AlignmentsJalview http://www.jalview.org/download.htmlColour -> Clustalx

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


Editing and Publishing Alignments

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.



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.



perform PairwiseAlignment for a pair of selectd sequences



calculate tree for all selected sequences



predict secondary structure for a selected sequence.



JNet Secondary Structure Prediction result


Editing and Publishing Alignmentssave your alignment as a text/picture



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



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


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?


Notice:

Next time (2011/10/19) we will move to

8# building, 2nd floor, west,

多媒体教室DUOMEITIJIAOSHI.

Introduction to Bioinformatics - Shandong Universitycourse.sdu.edu.cn/G2S/eWebEditor/uploadfile/20120322211245... · Identity and Similarity Residue: a letter; an amino acid in a

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