Individuals within a wild population show remarkably little morphological variation,
given the amount of environmental variation they encounter during development and the
amount of genetic variation within the population. This phenotypic constancy led to the
proposal that individuals were somehow buffered, or canalized, against genetic and
environmental variation (Waddington 1942). Clearly, such a mechanism would have important
evolutionary consequences; because natural selection acts upon phenotypic variation within
a population, canalization first appears to reduce the evolvability of the trait upon which
it is acting (Gibson and Wagner 2000). However, canalization also reduces the effects of
new mutations (which may be deleterious), potentially allowing individuals to store this
genetic variation without suffering the consequences. If canalization breaks down due to
genetic or environmental circumstances, then the stored genetic variation will be released,
providing an additional substrate for natural selection. In this way, individuals could
potentially undergo large, rapid phenotypic changes.
Experiments in both
Drosophila and
Arabidopsis have suggested that Hsp90 (heat shock protein 90), a
member of a family of proteins expressed at high temperatures (heat shock), may be an
excellent candidate for bringing about canalization (Rutherford and Lindquist 1998;
Queitsch et al. 2002). Several features of Hsp90 suggest that it is an evolutionary buffer,
capable of hiding and then releasing genetic variation: (1) individuals heterozygous for
mutations in
Hsp83 (the gene encoding Hsp90) show increased levels of morphological
abnormalities; (2) individuals treated with a pharmacological inhibitor of Hsp90 show
severe morphological abnormalities; (3) the normal function of Hsp90 is to stabilise the
tertiary structure of signal transduction molecules involved in developmental pathways; and
(4) this function may be compromised by environmental factors, e.g., heat shock.
Gene Networks Generate Canalization
Hsp90 may not, however, be uniquely placed to act as an evolutionary buffer producing
canalization. Recent theoretical work has suggested that canalization may be an emergent
property of complex gene networks and may not require specific mechanisms of protein
stabilisation and environmental coupling such as those provided by Hsp90 (Siegal and
Bergman 2002). Siegal and Bergman (2002) proposed that when a network is compromised by
‘knocking out’ one of several genes, buffering may be lost or compromised, releasing
variation that was hidden in the intact network. To test this, Bergman and Siegal (2003)
used numerical simulations of a complex network of ten genes in which each gene is capable
of influencing the expression of other genes as well as itself (Figure 1A). This network
essentially defines the genotype of the individuals within the population, and the amount
of gene expression at equilibrium defines the phenotype. Comparison of populations founded
by either wild-type individuals or those with a single gene ‘knockout’ revealed much higher
levels of phenotypic variation in populations derived from the ‘knockouts’.
Thus, populations derived from ‘knockouts’ express phenotypic variation that was not
expressed by the wild-type network, suggesting that any of the genes within the network may
buffer genetic variation. This suggests that at least one aspect of generating evolutionary
buffering is not unique to Hsp90. But can genes that, unlike Hsp90, are not conditional
upon the environment act as evolutionary buffers? To test this, Bergman and Siegal (2003)
simulated a gene network that incorporated a mutation process in which single genes may be
‘knocked out’ and then, at a later time, restored. The simulated populations were allowed
to evolve whilst being selected for an optimum phenotype (i.e., the populations were
exposed to an environment in which a particular phenotype was optimal). A new optimum
phenotype was then specified in which the expression of three of the ten network genes
changed from on to off or vice versa (i.e., there was a shift in the environmental
conditions favouring a different phenotype). Populations evolving with the mutation process
reached the new optimum before populations without the mutation process. Thus, the
‘knockout’ mutations were clearly beneficial because they sped up adaptation to a new
phenotypic optimum by releasing hidden genetic variation, thereby providing a new substrate
upon which natural selection may act. Yet these mutations were not coupled to the new
environment, suggesting that the release of the hidden genetic variation does not have to
be linked to an environmental change in order to be beneficial.
The simulations described by Bergman and Siegal (2003) suggest that the key properties
of an evolutionary buffer, the ability to store and then release genetic variation in
response to environmental or genetic change, are not unique to Hsp90. Indeed, the
simulations suggest that evolutionary buffering may be a widespread property of gene
networks. They also suggest that the hidden genetic variation does not have to be revealed
by an environmental change, but can be produced by a gene ‘knockout’. These results may go
some way to explain the original observation by Waddington (1942) of phenotypic constancy,
yet many questions remain (Stearns 2003). One of the major outstanding questions must be
whether it is possible to verify these results experimentally. Bergman and Siegal (2003)
used data from the yeast
Sacchromyces cerevisiae , in which each gene may be ‘knocked
out’ in turn and the expression of the remaining genes determined, to demonstrate that
their simulations also had application to biological gene networks. Using these data, they
showed that ‘knockouts’ show greater variability in gene expression than wild-type yeast,
suggesting that buffering has been disrupted.
Ion Channels as Evolutionary Buffers
Given the results of Bergman and Siegal (2003), it should be possible to find gene
networks in which the elimination of single genes reveals variation in gene expression and
hence in phenotype. One class of gene network that may conform to the structure outlined by
Bergman and Siegal (2003) is that of the gene networks regulating ion channel expression in
neurons. Neurons contain an array of voltage-dependent Na
+ and K
+ channels as well as numerous Cl
− , Ca
2+ , and voltage-independent leak channels. The electrical properties of
a single neuron are dependent, though not exclusively, upon the suite of ion channels
expressed within that neuron. The properties of a neural network, which generates
behaviour, are determined both by the intrinsic expression patterns of ion channels within
neurons and the connectivity between neurons. The nervous system develops as an interaction
between experience and genetically programmed events. One mechanism by which this
interaction is achieved is ion channel compensation (Turrigiano 1999); individual neurons
can change their sensitivity to inputs by altering the relative proportion of ion channels,
enabling them to maintain stable properties in the face of changing experience (Turrigiano
et al. 1994; Brickley et al. 2001; Maclean et al. 2003; Niven et al. 2003a) (Figure
1B).
Many studies of ion channel ‘knockouts’ show relatively little change in overall
neuronal activity, although predictions based upon pharmacological blockade of the ion
channels suggest there should be a more severe phenotypic change (Marder and Prinz 2002).
Subsequent work has shown that the loss of an ion channel may often be compensated by a
change in the expression of other ion channels. For example, the neurons upon which I work
are
Drosophila photoreceptors. In these neurons, loss of the one
particular ion channel leads to compensatory changes in other ion channels linked to the
activity of the neuron to restore the ability to process visual information (Niven et al.
2003a, 2003b). However, these changes do not restore the original phenotype completely, and
the compensated photoreceptors still show a reduced ability to process visual information.
In many neurons, it appears that the intracellular Ca
2+ concentration acts as an internal sensor of neural activity (Marder
and Prinz 2002). Ca
2+ , along with other second messengers, may influence the expression of
genes encoding ion channels, allowing their expression to be coupled to neural activity
(Berridge 1998) (Figure 1B and 1C). Additionally, activity-independent mechanisms of ion
channel compensation have been described in which the expression of one ion channel is
linked to the expression of other opposing ion channels within a neuron (Maclean et al.
2003). These two systems of activity-dependent and activity-independent ion channel
compensation bear a close resemblance to the gene network simulated by Bergman and Siegal
(2003) in which each gene regulates its own expression and that of other network genes.
It is possible, therefore, that the networks of genes regulating ion channel expression
may act as evolutionary buffers. The relationship between neural activity and the network
of ion channel encoding genes may stabilise the neural activity in relation to both the
genetic and environmental variation. The stabilisation of neural activity may have
consequences for the generation of adaptive behaviour, which is constructed from neural
activity. It is possible that ion channels could canalize the evolution of the nervous
system by reducing behavioural variation and therefore removing the substrate on which
natural selection may act. For example, changes in voltage-dependent Na
+ channel properties (such as the activation voltage) may be compensated
for by regulating the expression of other ion channels. ‘Knockout’ of one of these
compensating ion channels may reveal the change in voltage-dependent Na
+ channel properties, resulting in a shift in the output of the neuron.
This hypothesis has several testable predictions. For example, ‘knocking out’ an ion
channel should increase the variation in the activity of particular neurons among
individuals in a population. This variation in neural activity may produce an effect on the
behaviour of the whole organism.
Studying canalization in ion channel gene networks may have significant advantages over
studying developmental gene networks because it is relatively straightforward to measure
the amounts of ion channels expressed in single identified neurons, to alter the expression
of individual ion channels, and to relate these alterations to behaviour. I am currently
pursuing the impact of ion channel compensation in
Drosophila photoreceptors (Niven et al. 2003a, 2003b, 2003c). In
this system, changes in ion channel expression produce changes in the coding of visual
information, which may lead to behavioural differences. The possible role of ion channel
compensation in canalizing the evolution of the nervous system may have important
implications not just for understanding this system, but also for understanding the
contribution of ion channel compensation to the function of the nervous system and its
evolution.
