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Blast, PSI–blast, and Homology
Are two similar sequences homologous (i.e.,
is their similarity due to shared ancestry)
?
One way to quantify the similarity between two sequences is to
1.
compare the actual sequences and calculate alignment score
2.
randomize (scramble) one (or both) of the sequences and calculate the
alignment score for the randomized sequences.
3.
repeat step 2 at least 100 times
4.
describe distribution of randomized alignment scores
5.
do a statistical test to determine if the score obtained for the real
sequences is significantly better than the score for the randomized sequences
To
illustrate the assessment of similarity/homology we will use a program
from Pearson's FASTA package called PRSS.
This and many other programs by Bill Pearson are available from his web
page at ftp://ftp.virginia.edu/pub/fasta/.
A
version for PCs is here,
a web version is available here.
Go
through example. Sequences are here
(fl), here
(B), here
(A) and here
(A2)
There are many other alignment programs. BLAST is a program
that is widely used and offered through the NCBI (go here for more info). It also offers
to do pairwise comparisons
(go here do example).
To force the program to report an alignment increase the
E-value.
Rules of thumb:
If you can demonstrate significant similarity using either
randomization or an unweighted blast search, your sequences are homologous
(i.e. related by common ancestry). Convergent evolution has not been
shown to lead to sequence similarities detectable by these means (see
above - this might not be true for scores in PSI-blast)
If the actual alignment score is more than three standard
deviations (of the randomized sequences) better than the mean for the
randomized sequences, the two sequences are homologous (i.e. related by
common ancestry). PRSS and many other program use more accurate distributions
to describe the distribution of random hits. The expectation value for
the alignment-score of the actual sequences is based on these statistics.
Usually E values (in a blast search or through randomization)
smaller than 10-4 are convincing.
Terminology
E-values give the expected number of matches with an alignment score
this good or better,
P-values give the probability of to find a match of this quality or better.
P values are [0,1], E-values are [0,infinity). For small values E=P
z-values, give the distance between the actual alignment score and the
mean of the scores for the randomized sequences expressed as multiples
of the standard deviation calculated for the randomized scores. For example:
a z-value of 3 means that the actual alignment score is 3 standard deviations
better than the average for the randomized sequences. Z-values > 3
are usually considered as suggestive of homology, z-values > 5 are
considered as sufficient demonstration. (see the but below).
A somewhat readable description of E, P HSP and other values is here.
BUT:
Failure to detect significant similarity does only shows our inability
to detect homology, it does not prove that the sequences are not homologous.
Examples:
Jim Knox (MCB-UConn) has studied many proteins
involved in bacterial cell wall biosynthesis and antibiotic binding, synthesis
or destruction. Many of these proteins have identical 3-D structure, and
therefore can be assumed to be homologous, however, the above tests fail
to detect this homologies. (for example, enzymes with GRASP nucleotide
binging sites are depicted here)
DNA replication involves many different enzymes.
Some of the proteins do the same thing in bacteria, archaea and eukaryotes;
they have similar 3-D structures (e.g.: sliding clamp, E. coli
dnaN and eukaryotic PCNA, see Edgell and Doolittle, Cell 89, 995-998),
but again, the above tests fail to detect homology.
Helicase and F1-ATPase. Both form hexamers
with something rotating in the middle (either the gamma subunit or the
DNA; D. Crampton, pers. communication). The monomers have the same type
of nucleotide binding fold (picture)
BLAST and PSI BLAST
Run a blast trial with
this sequence
A tutorial for standard blast search is here.
An easy way to force the program to report less significant
matches is to increase the expect value in the advanced blast
page.
PSI-blast provides an enormous advantage over
normal blast in the detection of distantly related sequences. It only
works if some closely related sequences are already available, but if
this is the case it finds a lot of other distantly related sequences.
The NCBI page describes PSI blast as follows:
Position-Specific Iterated BLAST (PSI-BLAST) provides an automated, easy-to-use
version of a "profile" search, which is a sensitive way to look
for sequence homologues. The program first performs a gapped BLAST database
search. The PSI-BLAST program uses the information from any significant
alignments returned to construct a position-specific score matrix, which
replaces the query sequence for the next round of database searching.
PSI-BLAST may be iterated until no new significant alignments are found.
At this time PSI-BLAST may be used only for comparing protein queries
with protein databases.
A diagram giving an overviw over the PSI-blast procedure
is here.
The results of a normal blast search are aligned and a
pattern of conserved residues is extracted from the alignment. This pattern
is used for the next iteration. An important parameter to adjust is the
E-value threshold down to which matches are included in the alignment
and pattern extraction.
At higher iterations a PSI blast profile can be corrupted and false positives
are identified with “significant” E-values. I.e., in a traditional blast
search one can be quite certain that a match with an E-value of 10^-13
represents a homologue; this is not clear with PSI blast. Test studies
indicate that profile corruptions are likely after
more than 5 iterations. On the positive side: there are many fewer
false negatives with PSI blast than with normal blast.
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