Download Chapter 4 The role of mutation in evolution

Chapter 4 The role of mutation in evolution
Objective
Darwin pointed out the importance of variation in evolution. Without variation, there
would be nothing for natural selection to act upon. Any change in the environmental
conditions could be disastrous for a population lacking variation. If variation is so important
to evolution, it is only fair to ask, where does the variation come from? The very next
question that arises is whether the variation is random, or whether there is some tendency for
novel mutations to be favorable. A very clever experiment established that mutations are
random with respect to fitness, but more recently this has been challenged. Let's review the
data.
The low but critical rate of mutations
At one level it would appear that mutations are mistakes. The elaborate machinery
that cells use to copy their DNA, to proofread and correct replication errors, and to assure that
the chromosomes divide properly into daughter cells suggests that cells are doing everything in
their power to prevent mistakes. In fact, estimates of the error rate of DNA replication in
many higher organisms are on the order of one mistake per billion nucleotides copied. As
fantastically low as this error rate seems, it might seem that mutations could not be terribly
important. But an organism that was able to copy its DNA perfectly every time would find its
supply of variation would soon dwindle to the point that its extinction would be assured.
Mutations and wristwatches
Most mutations, being random changes in a complex mechanism, are deleterious. One
can make the analogy to a mechanical wristwatch. Randomly tapping or poking at the insides
of the watch almost always decrease the chance that it will keep good time, and many such
tamperings would make the watch stop outright. But sometimes there might be a piece of dust
on a critical gear, and a small tap might dislodge that dust. The end result of the small,
random tap would be to make the watch run more accurately. It is these improbable small
improvements that allow adaptive evolution to progress.
Types of mutations
All mutations result from changes in DNA. The changes may be single base changes,
or they may involve many bases at once. We distinguish between two major classes of single
base changes. Transitions are changes from purine to purine (G - A) or pyrimidine to
pyrimidine (C - T), and transversions are changes from purine to pyrimidine or vice versa. In
addition to these single bases changes, DNA may mutate by having insertions or deletions of
bases. Such insertions and deletions may be as small as a single base, or they may involve
thousands of bases, as when a transposable element inserts (we'll get to that in chapter 7).
Pieces of chromosomes may also break and rejoin the chromosome to give rise to an
inversion. Some populations of Drosophila have an abundance of different inversions
maintained in the population. These inversions are readily examined in heterozygotes because
the chromosomes have to twist around to be able to pair up gene-for-gene. This twisting
around is visible under a light microscope as an inversion loop.
Finally, whole pieces of chromosomes may be broken off and moved to other
chromosomes. Some of the most interesting translocations involve movements of DNA
material onto or off from the Y chromosome. We can follow these movements by examining
Y chromosomes from many different species, and seeing that there is a low rate of movement
of genetic material onto and off of the Y chromosome. Of course, when a gene finds itself on
the Y chromosome, unless it retains a copy on other chromosomes it is found only in males.
The gene for rapid channel changing with a TV remote is one such gene (just kidding).
Mutations exhibit an excess of transitions
One wonderful aspect of being able to sequence DNA is that we can compare DNA
sequences and determine what the differences are. If we take a group of individuals and
compare their DNA sequences, however, we will not necessarily get a good picture of the
relative rates of the various kind of mutations. The reason is that mutations that have a
deleterious effect will be under-represented in our sample because natural selection will have
removed many of them. A solution to this problem is to consider only variation in
pseudogenes. Pseudogenes are genes that have suffered a mutation that completely knocks out
the function of the gene, for example, by introducing a premature termination codon. Once a
gene is a pseudogene, it does not matter if it gets additional mutations, because it is dead
already. Pseudogenes are almost ideal for finding out what kind of neutral mutations occur.
In comparing a series of pseudogenes in mammals, Wen-Hsiung Li and colleagues tallied this
table of change in bases:
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A
To this
base
From this base:
T
C
G
A
-
4
6
21
T
5
-
21
7
C
5
8
-
5
G
9
3
4
-
Note that not all cells have equal counts. Transition mutations occur on the diagonal from the
upper right down to the lower left. The excess of transitions is observed in nearly all
organisms, and is called a transition bias. The transition bias is caused by an inherent
increased error rate of DNA polymerase when it copies DNA strands.
Mutations change allele frequency very slowly
We are now in a position of being able to ask how allele frequencies change in
populations. Many forces will affect allele frequencies, and we have already seen that random
genetic drift can have a big effect, especially if enough time elapses. Now let us consider the
effects of mutation on allele frequency.
In order to isolate the effects of mutation, we need to assume that the population is so
enormously huge that we can ignore random genetic drift. We will also assume that
mutations are all neutral (just to get things started). Further assume that the population starts
out with all A alleles, and that these mutate at just one site to a new allele a at rate u per
generation. The mathematical treatment of models like this is much simpler if we also
assume that the generations are non-overlapping. If the initial frequency of allele A is p, then
the frequency the next generation is simply p times the probability that the A allele does not
mutate. We let p' be the expression for "p the next generation" and the equation that expresses
how p changes is a recursion that looks like this:
p' = p(1-u)
This is a nice simple equation, and from it we can draw a nice simple conclusion.
Typical mutation rates are around 10-9 per base pair, or around 10-6 per gene with 1000
nucleotides. With this mutation rate, the time required to go from p=1 to p=0.5 is 693,147
generations. The nice simple conclusion is that pure mutation, with no other force changing
allele frequencies, is an extremely ineffective force in evolution. A much more reasonable
view is that mutation introduces the variation into the population, and then either natural
selection (or random genetic drift) causes the allele frequency to change. Referring back to
chapter 2, we saw that an allele with initial frequency of 0.5 will take an expected 2.77N
generations to go to fixation or loss. This means that drift will change the allele frequency
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faster than mutation even if the population is 693,147/2.77 = 250,233 or smaller. Of course, a
smaller population would have random genetic drift change the allele frequencies even faster.
How Drosophila balancer chromosomes work
Before we can understand some important experiments on the effects of mutations, we
need to know about one trick that Drosophila geneticists have used to maintain severely
deleterious mutations in stocks. The method makes use of what are called balancer
chromosomes. These are chromosomes having multiple overlapping inversions and a
recessive lethal mutation with a dominant visible phenotype. The inversions keep the
chromosome from recombining with its homolog, and the lethal mutation prevents a culture
from becoming homozygous for the balancer. A stock that has a deleterious mutation m can
be kept in a population with an appropriate balancer chromosome. Suppose m is on the
second chromosome, and we have a stock that looks like m/SM5, where SM5 is a balancer
chromosome that happens to carry the Curly wing mutation. This line is expected to produce
zygotes in a 1:2:1 ratio of m/m, m/SM5, and SM5/SM5. If m is recessive lethal, then we see
no m/m offspring. SM5 is lethal when homozygous, so we get no SM5/SM5 offspring. This
leaves only the m/SM5 offspring. See why they are called balancer chromosomes!
Measuring mutation and effects on fitness
Starting in the early 1960's Terumi Mukai set up and followed a large experiment that
has had considerable impact on our thinking about mutation. The basic idea of the experiment
was to make 104 lines of Drosophila melanogaster that were initially all genetically identical.
These lines were then maintained in such a way that mutations could accumulate generation
after generation. The mutations were kept from becoming homozygous within any line by
continually crossing the line to an outside line carrying a balancer chromosome.
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The average chance of survival of these lines declined over time, and Mukai calculated
that a mutation occurs somewhere on the second chromosome every seven generations. As
the mutations accumulated, the variation in fitness across lines increased because some lines
suffered several mutations and others suffered fewer.
Poisson distribution of mutations
Mukai's reasoning depended in part on an
assumption about the distribution of the number of mutations that occur per line. If mutations
are relatively rare, and each mutation occurs at random with a constant probability
independent of any other mutation, and we examine many lines of flies, then the number of
mutations per line will have a Poisson distribution. We won't derive the Poisson distribution,
but its formula is:
Pr(x mutations) =
u − x e −u
x!
Where u is the mutation rate. The Poisson has an interesting property that the mean and the
variance are both equal to u. The probability that a line will have zero mutations is Pr(x=0) =
u0 e-u/0! = e-u. If the mutation rate is 10-6, then you can see that this probability is very close to
1. However, Mukai was not estimating the mutation rate for a single gene -- he was estimating
the mutation rate for the entire second chromosome, which probably has 2000 genes. The
Poisson distribution arises frequently in biology, especially in the study of rare events, like
mutations.
Bacterial populations
Bacteria seem to be able to adapt to changes quickly, as though they recognize a
metabolic need and they somehow change accordingly. Biologists in the 1940's were not sure
whether bacteria were like other organisms, or whether they had unique properties of selfreplication that allowed them to produce all kinds of variant offspring in response to
environmental stress. Salvadore Luria was bothered by this idea, because he believed that
bacteria were like other organisms, and that the apparent ability of bacteria to adapt to new
culture media or other environmental changes was due to the fact that their population size
was so large that even random mutations would hit upon the successful mutation relatively
quickly. The challenge was to devise an experiment that determined whether the bacteria
mutated specifically in response to the stress, or whether the mutations were occurring at
random. The experiment described in the following section Salvadore Luria and Max
Delbrück devised a subtle and clever way to test this.
Luria and Delbrück's fluctuation test
The basic problem was that as soon as bacteria are placed on a selective medium and
we subsequently see bacteria that have responded to the selection, it is hard to know whether
the mutation that allows the bacteria to respond occurred before or after the bacteria were put
on the selective medium. Here is how Luria and Delbrück solved this problem. They started
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with E. coli bacteria that was sensitive to T1-phage. This means that the phage would infect
and lyse the E. coli. They picked individual colonies of E. coli grown on a petri dish, and from
each they grew up a culture in a test-tube. They then spread the cells from this culture onto a
petri dish in the presence of T1. If no mutations occurred, all the E. coli cells would be killed,
and E. coli colonies would not grow. If a T1-resistance mutation occurred, then the cells with
those mutations could grow and form colonies.
The subtle part comes next, and it has to do with a careful analysis of the results. If no
mutations occurred in the E. coli until the very final step, when the T1 phage are present, and
the E. coli mutate only in response to presence of the phage, then each cell at the end has an
equal chance of getting the mutation, so each culture should produce a smattering of resistant
colonies. If one petri dish spread were made from each culture, and each petri dish has 1000
cells spread on it, and the chance of a resistance mutation is 0.002, then we would expect to
see 2 resistant E. coli cells per plate. In fact, the distribution of the number of resistant colonies
per plate is expected under this model to be a Poisson distribution with a mean of 2. This is
the expectation if the mutations only occur at the last step, when the T1 phage is added.
Another possibility is that each time the E. coli divides, there is a certain random chance
of mutation to T1 resistance, even if no T1 phage are present. When the cultures start growing
from a single cell, they undergo many cell divisions before there are enough cells for us to plate
out on the petri dish. If mutations had been occurring all along during this growth, then
consider what should happen to the distribution of resistant colonies. In some cultures one
might see a mutation occurring relatively early in the process of cell division. If this occurred,
then all descendant cells would also be resistant, and we would end up with a petri dish having
many, many resistant E. coli. At the same time, there would be other petri dishes which, by
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chance, had no mutations at all. Luria and Delbrück called this a "jackpot" distribution,
because some of the petri dishes had hit the jackpot in having so many resistance colonies.
The variation from one petri dish to another in this case would have much greater variability
from one to another than predicted from the Poisson distribution.
What they saw was a very clear jackpot distribution. The counts of resistant E. coli per
petri dish was not at all a Poisson distribution, but rather there were plates with very large
numbers of resistant colonies. This simple observation allowed them to conclude that the
mutations did not occur in specific response to the T1, but rather that the mutations are
occurring randomly all the time at a certain low frequency.
Despite the elegance and power of the Luria and Delbruck experiments, many
researchers have continued to wonder if mutations might actually occur more frequently when
they might benefit the organism. This could be a valuable adaptation if conditions sometimes
grew so unfavorable that it was likely that the current genotype would not fare well. Then, a
“gamble” such as producing more genetically variable progeny, might actually pay off with an
increased chance of fit offspring. Several recent studies have identifed an interesting group of
enzymes known as DNA mutases, which are versions of DNA polymerase which produce
errors at a very high rate. These sloppy polymerases are present in bacteria and yeast, and
similar enzymes may be common in eukaryotes as well. They have the special ability to
replicate DNA even if an error (mutation) is detected in the template DNA, instead of
stopping to wait for a DNA repair enzyme to fix the mistake. If DNA mutases are expressed
under challenging or highly stressful conditions, then some of the elements would be in place
for organisms to generate ‘adaptive mutations.’
Summary
1. Mutations are absolutely necessary for evolution to proceed. They are the ultimate source
of all variation.
2. The classes of mutations are: a) single base changes, b) insertions and deletions, c)
inversions, d) translocations
3. Single base changes are not equally frequent, suggesting that there are chemical constraints
to the errors that polymerase makes when DNA is replicated.
4. Mukai's experiments with mutation accumulation lines used balancer chromosomes to
retain mutations in lines over many generations. This allowed him to quantify the rate of
accumulation of deleterious effects of mutations.
5. The Luria-Delbrück experiment established that mutations in bacteria occur at random,
and that bacteria do not have a mechanism that makes adaptive mutations more likely.
However, new evidence keeps open the possibility that bacteria and yeast (at least) ‘turn
on’ DNA replication that is more error prone than usual during time of stress; this again
opens the possibility of a mechanisms that could increase the chances of ‘adaptive’
mutations.
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