Download PopGen 5: Mutation pressure

PopGen 5: Mutation pressure
Introduction
In the foundations section of this course we introduced the concept of mutation from the molecule genetic
standpoint; that is the different types of spontaneous change and the molecular mechanisms that give rise to
them. A quick review of that topic might be helpful at this time. In this section we will use mutation to mean the
spontaneous change between allele A and a.
In our previous topics in population genetics we addressed the dynamics of genetic variants (alleles) already
existing in a population. As mutation is the ultimate source of such variation we must also address MUTATION
PRESSURE as a force for evolution. To do this we make all the same assumptions of the HW model. In this case
the most important assumption is that natural selection is not acting on these mutants (i.e., they are SELECTIVELY
NEUTRAL).
The rate of spontaneous DNA mutation is typically very small (generally between 10-4 and 10-6 mutations per
nucleotide per generation). These mutations are a result of both replication errors and spontaneous decay of
nucleotides, which occur at a surprisingly high rate. However, the variety of proofreading and repair
mechanisms of the cell is very effective in most organisms. The mutation rates shown in the table below are
those that get past these proofreading and repair mechanisms. So, the capacity of mutation pressure to alter
allele frequencies over short time spans, such as a few generations, is small. However the cumulative effect
over longer time spans can be substantial.
Table 1: Estimates of per generation mutation rates for a range of organisms
Organism
Per nucleotide rate
Genomic rate
RNA GENOMES
Poliovirus
Measles virus
Human Rhinovirus
Vesicular stomatitus virus
Murine leukemia virus
Rous sarcoma virus
Bovine leukemia virus
HIV-1
1.97 × 10-5
1.10 × 10-4
9.40 × 10-5
9.94 × 10-5
7.20 × 10-6
4.60 × 10-5
3.20 × 10-6
2.10 × 10-6
0.15
1.00
0.67
1.11
0.26
0.43
0.03
0.19
DNA MICROBES
Escherichia coli
Sulfolobus acidocaldarius
Saccharomyces cerevisiae
Neurospora crasse
5.4 × 10-10
7.8 × 10-10
2.2 × 10-10
7.2 × 10-10
0.0025
0.0018
0.0027
0.0030
HIGHER EUKARYOTES
C. elegans
Drosophila
Mouse
Human
5.4 × 10-10
7.8 × 10-10
2.2 × 10-10
7.2 × 10-10
0.018
0.058
0.49
0.16
Allele frequencies change slowly under mutation pressure
We will consider the case of mutation between two alleles, that we call A and a.
Let µ = the mutation rate from A ⇒ a
Let ν = the mutation rate from a ⇒ A
Let pt = the frequency of A in the population in generation t.
Let qt = the frequency of a in the population in generation t, with qt = (1 – pt).
An A allele can be present in generation t by one of two mechanisms:
• it could have been present in generation t – 1 and escaped mutation (with probability = 1 - µ)
• it could have been a allele that did mutate to A (with probability = ν).
Then:
pt =
p −1 (1 − µ )
1t4
243
+
probabaility that A allele
did not mutate
qt −1 (v )
123
probability that a allele
mutated to A
By substitution of terms:
pt = pt −1 (1 − µ ) + (1 − pt −1 )v
The above is recursive, with the general solution given by:
pt =
⎛
v
v ⎞
t
+ ⎜⎜ p0 −
⎟⎟(1 − µ − v )
1
4
2
4
3
µ +v ⎝
µ + v ⎠ As t goes to ∞
this term goes to
zero
When t gets very large (e.g., 105 or 106 generations) the term (1 - µ -ν)t becomes approximately 0 and the term
drops out of the above equation. Thus pt eventually attains a value that remains the same from generation to
generation. We call this value of pt an EQUILIBRIUM VALUE. So, at equilibrium:
pˆ =
v
µ +v
and
qˆ =
µ
µ +v
This means that given values of µ and ν the population will always reach the same equilibrium value for pt,
regardless of the initial frequencies of A and a in the population.
Example:
Suppose we have a bacterial system where we can measure the forward and backward mutation rate in a gene
that controls something we can easily measure such as colony morphology. If the mutation rate from
morphology A to a was 4.7 x 10-4 and from a to A was 8.9 x 10-5, what would be the equilibrium frequency of the
A allele, and how long would it take to reach this equilibrium value? Examination of the above table reveals that
the mutation rates used in this example are not unusual.
We can use the above equations to compute the equilibrium values:
pˆ =
pˆ =
v
µ +v
8.9 × 10 −5
4.7 × 10 − 4 + 8.9 × 10 −5
pˆ = 0.1592
We can also determine the theoretical rate of change in the allele frequencies over time.
Time, in generations, to attain equilibrium values under realistic rates of mutations
1
0.9
Frequency of A
0.8
0.7
0.6
0.5
0.4
Equilibrium
0.3
0.2
0.1
0
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
Time in generations
Note that it takes tens of thousands of generations to reach the equilibrium value, indicating that mutation
pressure alone is a weak force for change in allele frequencies in populations
Pathogenic bacteria, Pathogenicity Islands, and mutational amelioration.
With > 150 bacterial genomes completely sequences, we have entered an era where molecular evolution can be
conducted at the genomic scale. Not surprisingly the focus of many of these bacterial sequencing projects has
been pathogens. These sequences have led to fundamental insights into the origins and molecular basis of
pathogenicity.
Particularly striking is the amount of heterogeneity in the gene contents of closely related genomes. Take the
human pathogen Heliobacter pylori as an example. Heliobacter pylori colonize the stomach, and there are a
variety of strains that cause disease symptoms ranging from simple stomach upset to gastric cancer. Using
genome scale molecular techniques (whole genome micro array) a recent study (Salama et al. 2000) found an
amazingly high number of the genes (20%) were strain specific (about 6-7% of genes are specific to any one
strain). Many studies have now shown a strong link between strain specific genes and pathogenicity.
Where does this variability come from? Undoubtedly some of it is simply differential loss of genes that were
present in a common ancestor. However, it seems a large fraction of the strain specific genes were transferred
in from unrelated bacterial lineages. When such genes are located in the same segment of DNA and confer
pathogenicity to the organism that bears them, then that segment of DNA is called a PATHOGENICITY ISLAND.
Note that segments that confer other properties include SYMBIOSIS ISLANDS, METABOLIC ISLANDS, and RESISTANCE
ISLANDS
Below is a diagram of the LIPI-1 pathogenicity island in the bacterium Listeria monocytogenes. It is interesting
that the close relative, L. innocua, does not contain the LIPI-1 island and is not a pathogen. Note that many
other genes contribute to the pathogenicity differences between L. monocytogenes and L. innocua. In this case
LIPI-1 is essential because it confers the ability to enter and move between host cells via phagocyte vacuoles
and exit these vacuoles and enter the cytoplasm.
Pathogenicity Island (LIPI-1) contains a cluster of genes that confer the ability to enter and live within
a host cell
Non pathogenic
Pathogenic
LIPI-1 Pathogenicity Island
Non pathogenic
Modified from Glaser et al.
So, how do we detect these pathogenicity islands? It is often the case that the pathogenicity island represents a
segment of DNA that originated in another genome with equilibrium nucleotide compositions. If we extend the
notion of mutational equilibrium to the four nucleotides (ACGT), then we can think in terms of equilibrium
frequencies such as the G+C% of a genome. Our model above is suitable for this type of mutation pressure as
well. We know from our model that mutation pressure as a force for evolutionary change is VERY SLOW. This
means that pathogenicity islands will have a GC contents that reflects the genome of origin, and that this “signal
will persist for some time.
Anomalous GC content of a metabolism island in Listeria monocytogenes
Obs. GC
38% GC
Of course the mutation pressure of the L. monocytogenes genome will force an island to evolve to the native
equilibrium value. This process is called MUTATIONAL AMELIORATION. Clearly the above island has not been in
the L. monocytogenes genome long enough for complete amelioration. Note that the LIPI-1 island has been in
the L. monocytogenes genome much longer than the above metabolism island, as its GC content is much closer
to the native value. Because this is such a slow process, the signal of old transfer events can be detected in a
genome. This is useful to help detect regions of genomes, and the involved genes, that might have been
transferred from other genomes in their distant past.
Genes specific to L. monocytogenes have lower GC content
Keynotes
•
Mutation pressure is a weak force for changing allele frequencies over the course of a few generations,
having very negligible effect on what we traditionally view as “microevolution”.
•
As a force of evolutionary change mutation pressure is significant over thousands to tens of thousands
of generations. Note this is an example of a microevolutionary process that gives rise to a pattern which
we view as macroevolution.
•
Mutational amelioration is an example of a microevolution process that manifests itself as a
macroevolutionary pattern.
•
A stable equilibrium will be reached as long as µ and ν are unchanging.
•
A change in µ or ν results in mutation pressure for a new equilibrium.