Sequence
alignment
Pairwise
alignment
A)
DOT PLOT
The easiest
way to align two sequences is to use a dotplot. In its most straight forward implementation
the two sequences to be aligned are written along the coordinate axis.
In
more realistic implementations a window of 5 to 20 nucleotides or amino acids
is slid along one of the axes (i.e., sequences) and compared to every possible
window on the other axis (sequence). The dot intensity is adjusted to reflect
the percent identity (or similarity) in the two windows.
Optimal
global and local alignments.
There
are many different algorithms to calculate pairwise sequence alignments. For two
sequences it is "easy" to calculate an optimal global alignment. (According
to the motto: "It can be easily shown" -- see here).
The so called Needleman-Wunsch algorithm is widely used, it optimizes a positive
alignment score, a related (and under some conditions equivalent approach) is
to minimize the differences between to sequences.
Multiple
Sequence Alignments
CLUSTAL,
CLUSTALW and CLUSTALX
Usually
global alignments are the easiest
to calculate (local see discussion of blast )
One
of the easiest to use and most versatile alignment programs
is clustalw
(Higgins
DG, Sharp PM (1988) CLUSTAL: a package for performing multiple sequence alignment
on a microcomputer. Gene 73:237-244;
Thompson, J.D., Higgins, D.G. and Gibson, T.J.
(1994). CLUSTAL W: improving the sensitivity of progressive multiple sequence
alignment through sequence weighting, positions-specific gap penalties and weight
matrix choice. Nucleic Acids Research, 22, 4673-4680).
Clustalw
runs on all possible platforms (unix, mac, pc), and it is part of most multiprogram
packages, and it is also available via different web interfaces (for examples here,
and here).
Clustalw uses a
very simple menu driven command-line interface, and you also can run it from the
command line only (i.e. it is easy to incorporate into scripts.)
Clustalx uses
the same algorithms as clustalw. However, it has a much nicer interface, it displays
information on the level of similarity, and it uses color in the alignment. Especially
for amino acids the use of color greatly enhances the ability to recognize conservative
replacements. Clustalx2.1 is available for different platforms at the ebi's ftp site (follow your platform,
clustalx is stored in the clustalw folders)
Clustal
reads and writes most formats used by different programs. The easiest format
is the FASTA format:
>
name of sequence or any other information goes in the first line. This line starts
with ">". The line can be longer than 80 characters. The first line
ends with the first paragraph sign.p
The second line contains the sequence
itself; numbers and other non standard characters
are ignored. Be careful if you download sequences. Often the transfer
programs introduce paragraph signs every 100 characters, and the end of a command
line frequently ends up as the beginning of the sequence.
All sequences to
be read should be in a single file.
(sample clustalw input file)
(sample clustalw output file)
Clustal
also reads aligned sequences. If you input aligned sequences you can go directly
to the tree section.
!! Be careful if you make a mistake, and the sequences are
not aligned, your tree will look strange!!
!!! ALWAYS CHECK YOUR ALIGNMENT!!!
Clustal
also is useful to reformat and edit alignments, it is very forgiving in reading
formats, e.g., you can open the clustal format (*.aln) in a text editor and delete
columns and reload the file into clustalw, and output it in the other formats
available.
For
calculating an alignment, you can select different substitution matrices, and
gap penalties (end-gaps can be considered differently!)
Clustal
is better than its reputation. It is doing a great job in handling gaps, especially
terminal gaps, and it makes good use of different substitution matrices.
To
align sequences clustal performs the following steps (aka as progressive alignment):
1) Pairwise distance calculation
2) Clustering analysis
of the sequences
3) Iterated alignment of two most similar sequences or groups
of sequences.
It is important to realize
that the second step is the most important. The relationships found here will
create a serious bias in the final alignment. The better your guide tree, the
better your final alignment. You can load a guide tree into clustal. This tree
will then be used instead of the neighbor joining tree calculated by clustalw
as a default. (The guide tree needs to be in normal parenthesis notation WITH
branch lengths).
Other
programs often used for multiple sequence alignment
(We
will not use
these program in this course; if you are already confused by the information provided,
skip to the assignments):
A program
available via the www is SAM (sequence alignment and modeling system)
by Richard Hughey, Anders Krogh, Christian Barrett, & Leslie Grate at UCSC.
The input consists of a multiple sequence file (aligned or not aligned) in FASTA
format. The program uses secondary structure predictions, neighboring sites, etc.
to place gaps. The program can be accessed at http://www.cse.ucsc.edu/research/compbio/sam.html
If
your sequences are not very similar, and if you are not able to generate a trustworthy
multiple sequence alignment, you can calculate distance trees based on pairwise
alignments only. The best program for this purpose is statalign from Jeff Thorne (Thorne JL, Kishino H (1992) Freeing phylogenies from artifacts
of alignment. Mol Bio Evol 9:1148-1162). It runs under standard UNIX. It's
only worth your effort if you are getting gray hairs because of a data set you
cannot reliably align. Very out of fashion these days.
MUSCLE is the current alignment program of choice. It is thought to give better alignments compared to clustal, it is faster and works with larger datasets. The program is available through a webserver at the ebi, and as a commandline program to download here.
Most multiple sequence alignment programs produce alignments that are pleasing to the human eye by placing only a few large gaps into the sequences. However, for many applications it is better to align a particular amino acid to gaps in the other sequences, if one is not certain about the homology of the position. These programs that introduce more gaps are at present underutilized. An example is PRANK.
In case of divergent sequences, a popular program that combines phylogenetic reconstruction and multiple sequence alignment is SATe.
If you need to use MSA in your work, the current recommendation is to use muscle, and test if an alignment calculated under PKANK gives similar results. Also, if you use less than 100 sequences, try SATe2. (Note the time needed for computation is very different!).
In order to avoid artifacts reflecting the guide tree used for the alignment, many prefer to filter the alignment using only sites that are reliably aligned. One such approach is GBLOCK (implemented in seaview, see below, web server is here), another is guidance from Tal Pupko's lab at TAU (I like this one, because it allows to remove positions from poorly aligned individual sequences, not only complete columns).
