Evolvability: the huge space of regulatory regions implies a huge reservoir of neutral


Robustness, evolvability, and neutrality








Andreas Wagner, Ph.D.
Associate Professor of Biology

Department of Biology,
167 Castetter Hall,
The University of New Mexico,
Albuquerque, NM, 87131
email:
wagnera@unm.edu

Phone: (505)-277-2021
FAX: (505) 277-0304




Abstract

Biological systems, from macromolecules to whole organisms, are robust if they continue
to function, survive, or reproduce when faced with mutations, environmental change, and
internal noise. I focus here on biological systems that are robust to mutations and ask
whether such systems are more or less evolvable, in the sense that they can acquire novel
properties. The more robust a system is, the more mutations in it are neutral, that is,
without phenotypic effect. I argue here that such neutral change and thus robustness
can be a key to future evolutionary innovation, if one accepts that neutrality is not an
essential feature of a mutation. That is, a once neutral mutation may cause phenotypic
effects in a changed environment or genetic background. I argue that most, if not all,
neutral mutations are of this sort, and that the essentialist notion of neutrality should be
abandoned. This perspective reconciles two opposing views on the forces dominating
organismal evolution, natural selection and random drift: Neutral mutations occur and are
especially abundant in robust systems, but they do not remain neutral indefinitely, and
eventually become visible to natural selection, where some of them lead to evolutionary
innovations.

The word evolvability has two main usages [1-4]. According to the first of them

a biological system is evolvable
if its properties show heritable genetic variation,
and if natural selection can thus change these properties.

A second usage ties evolvability to evolutionary innovations:

a biological system is evolvable
if it can acquire novel functions through genetic change,
functions that help the organism survive and reproduce.

These definitions apply to biological systems on all levels of biological organization,
such as macromolecules like RNA and proteins, metabolic pathways, gene regulation
networks, macroscopic traits, and whole organisms. In consequence, functional
innovation also comes in many different sizes and shapes, from enzymes with new
catalytic activities, to novel complex organs such as eyes or wings [5].
The two usages are far from synonymous. Most importantly, not all systems that
are evolvable in the first sense are evolvable in the second sense. Consider an enzyme-
coding gene that is subject to different mutations in different individuals of a population.
These mutations cause the enzymes activity to fluctuate among different individuals. If
such heritable genetic variation affects fitness, perhaps through variations in metabolic
flux, then natural selection can change enzyme activity. The enzymes activity is thus
evolvable in the first sense. However, even after millions of years, no mutation might
endow this enzyme with a new catalytic activity, an activity perhaps that might permit
survival in a completely new environment. Thus, even though it is evolvable in the first
sense, the enzymes activity need not be evolvable in the second sense. The converse,
however, does not hold. Every system that is evolvable in the sense of being innovative
can evolve by means of natural selection. Put differently, the ability to innovate is the
more profound usage of evolvability. It encompasses the first usage and much more.
Naturally, we know much less about it.
Living things are unimaginably complex, yet also highly robust to genetic change
on all levels of organization. Proteins can tolerate thousands of amino acid changes,
metabolic networks can continue to sustain life even after removal of important chemical
reactions, gene regulation networks continue to function after alteration of key gene
interactions, and radical genetic change in embryonic development can lead to an
essentially unchanged adult organism [6-9]. Such robustness is one of several factors that
can affect evolvability in either sense [1]. My central question here is whether robustness
fosters or hinders evolvability. Clearly, robustness will not increase evolvability in the
first sense. In a highly robust system, a given number of mutations will have smaller
phenotypic effects than in a less robust system: Thus, robustness reduces the amount of
heritable genetic variation on which selection can act. But, more importantly, does
robustness hinder or foster innovation? This is a more difficult problem, and my focus in
this aryicle.
One can adopt two conflicting perspectives on this problem. The first arises from
the observation that robustness causes many mutations to be neutral, mutations with no phenotypic effect on the system. Neutral mutations, by definition, are invisible to natural
selection and can thus not be the source of innovation. Thus, increased robustness means
fewer evolutionary innovations. The second perspective, in contrast, gives neutral
mutations a key role in innovation: Although many mutations in a robust system do not
change its primary function, they can change other system features, features that harbor
the seeds of future evolutionary change. Put differently, a system capable to fulfill its
primary function in many different configurations explorable through mutation has
sufficient flexibility and degrees of freedom to adopt other features. To use Goulds term
[10] of exaptations organismal features that may become adaptations only long after
they arise robustness facilitates exaptations. From this perspective, neutral mutations
themselves are the key to evolutionary innovation: Robustness implies that many
mutations are neutral and such neutrality fosters innovation.
Neutrality, can it be assessed experimentally? A key difference between the
two perspectives of the last two paragraphs is their tacit understanding of neutrality. I will
now examine this notion more closely. Neutral genetic change, made prominent by
Kimura in his neutral theory of molecular evolution [11], is commonly understood as
genetic change that does not affect an organisms fitness. In addition, neutral change has
to be neutral in any environment, physiological condition, or genetic background. I will
call this the essentialist view of neutral change, where being neutral is a property only
of a mutation itself it is part of the essence of that mutation and not of any other
factor such as the genetic background.
These two aspects of neutralitys definition also encapsulate its biggest problems.
First, how can we determine whether a mutation does not affect fitness? Beyond the
commonplace that fitness means the ability to survive and reproduce, fitness is difficult to
define properly, and nearly impossible to measure rigorously [12]. To give a simple
example, laboratory evolution experiments in microbes often use cell division rates of
bacterial strains as an indicator of fitness. While growth rate is certainly an important
aspect of fitness, a myriad other equally important aspects exist, including survival under
starvation conditions, heat-resistance, sporulation efficiency, germination rates, and so
on. In addition, growth rates themselves could be measured in countless different
laboratory environments. Which of these would be most representative of the
environments a microbe encountered in its recent evolutionary past? The answer is
usually unknown and perhaps often unknowable. Such problems are exacerbated in
higher organisms, where sexual reproduction, age-specific mortality and fertility, an
increased ability to change the environment, and smaller population sizes pose daunting
principal and technical problems. Taken together, these difficulties mean that an
unassailable measurement of any organisms fitness does in practice not exist.

A second candidate approach to identify neutral mutations applies to well-
understood systems inside an organism. For example, assume you are concerned with the
neutrality of a mutation in a mundane gene, such as that encoding the glycolytic enzyme
phosphoglucose isomerase. This enzyme interconverts glucose 6-phosphate and fructose
6-phosphate. To determine whether a mutation in its gene is neutral, you could simply
measure the mutations effect on enzyme activity. The approach seems simple enough,
but it is doomed to fail. The reason is that many proteins have multiple and unforeseeable
biochemical activities or biological functions. Phosphoglucose isomerase itself serves as
an example [13]. In vertebrates, it is the same protein as neuroleukin, a cytokine causing immune cell maturation, and survival of some embryonic spinal nerve cells [14,15]. In
addition, phosphoglucose isomerase also serves as autocrine motility factor [16], a
cytokine that stimulates cell migration. As if that were not enough, it can also cause
differentiation of human myeloid leukemia cells [17]. Who knows what other functions
await discovery?
Phosphoglucose isomerase is no exception in its multifunctionality. Aminoacyl
tRNA synthetases, the enzymes t