Book reviews

Reports & Opinion
A network of paths toward innovation
The Origins ofEvolutionary Innovations
Andreas Wagner, Oxford UniversityPress, 2011, ISBN: 978-0199692590
hardcover, 253 pages, price: 83 s.

Reviewed byJeremy A. Draghi andJoshua B. Plotkin
Department of Biology, University ofPennsylvania, Philadelphia, PA, USA
E-mail: jdraghi@gmail.com

DOI 10.1002/bies.201200016

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www.bioessays-journal.com

Any mention of neutral change andadaptation in the same breath inevitably
brings to mind the battles over thecauses of molecular evolution that havebeen so prominent and long-running in
the field. While these arguments have
evolved with the development of newmodels and new technologies, the central dichotomy has remained: beneficial
changes, that fix because of natural
selection and contribute to adaptation,
are one thing, and neutral substitutions,that fix only by chance, are somethingquite different. Wagner has been acogent and prolific advocate of a radical
alternative: neutral variation within apopulation can provide an essential
foundation for adaptive change. In
experimental papers [1], numerous
simulation studies, reviews [2], andhis previous book [3], Wagner hasemphasized how epistasis – interactions
among genes that shape the adaptive
consequences of mutations – allows
neutral variation to modulate the effects
of other mutations, producing a vast
range of possible mutant phenotypes
that may lead to an adaptive innovation.
Wagner did not invent the idea ofneutral variation fueling adaptation,
but he has done much of the hard work
to translate the idea into the mainstreamof biology. The early foundations of thisidea came from the pioneering work ofinvestigators who had trained as physicists and chemists, and applied biophysical ideas and computer models
of macromolecules to evolutionary
questions [4–8]. In his 2005 bookEvolvability and Robustness in Living
Systems, Wagner synthesized thesestudies with other evidence for neutral
networks across a broad range of scales,
drawing together the genetic code,macromolecular structures, regulatory
and metabolic networks, and developmental systems. The magnitude of thisevidence for degeneracy and epistasis,and of its implications for evolution,
was exciting and influenced a broadaudience. But Wagner stopped shortof presenting a fully realized theory of
how all this potential for neutral variation could explain the astounding ability of life to produce true innovation in
the face of environmental change andopportunity.
In this new book, Wagner moves his
focus from robustness to ‘‘innovability’’– an evolutionary propensity to innovate – but retains the central theme ofevolution across networks of connected
genotypes. Rather than building to adramatic unveiling of his theory of innovation, Wagner delivers his main argument after less than a third of the book;the remaining chapters each develop
the theory around a specific concern,such as recombination or plasticity.
This structure recalls Darwin’s Origin
of Species, in which the theory ofnatural selection was laid out by chapter
four and then applied for the remaining
11 chapters. In retrospect, we can see thetremendous potential latent in those few
simple ingredients that make up theidea of natural selection. But is
Wagner’s theory of the origins of innovation rich enough to warrant its own
book? To answer this question, we haveto appreciate the scope of Wagner’sgoals.
While Wagner sets out his explicit
goals in an ambitious first chapter, thenext three chapters give the first real
glimpses of what this book is meant toaccomplish. Wagner devotes 50 pages toa quantitative picture of the genotype
networks that underlie metabolic systems, transciptionally regulated gene
networks, and protein and RNA biomolecules. Drawing extensively on published work from the Wagner lab, thesechapters establish the foundation ofBioessays 34: 518–520,ß 2012 WILEY Periodicals, Inc.

for a while. The atomic unit of genetic
change is the substitution of a singlenucleotide in one of the hundreds ofbase pairs that make up a typical gene.
Each of these sites represents a possible
direction of change, and a polygenic
trait may contain not two but thousandsof independent, orthogonal dimensions
for the evolutionary process to search.
This realization makes the existence oftrue ‘‘peaks’’ empirically unverifiable[9], but leaves open the possibility thatcomplex adaptations require deleterious, ‘‘downhill’’ intermediate steps.
Wagner’s main argument is that thegeneric properties of genotype networks– particularly their vast size and theirinterdigitation – obviate this problementirely. Qualitatively different phenotypes may be separated by many steps,
but most of these changes are only
weakly selected. These neutral or nearly
neutral paths bypass much of the apparent difficulty of the evolution of complex traits. While his calculations may
seem abstract, their presence is theessential quantitative foundation forthis new metaphor for adaptation.
While others have highlighted thesignificance of degeneracy for adaptation (e.g. [10]), the strength ofWagner’s book lies in the clarity withwhich these ideas are elucidated, andespecially in the great variety of empirical examples. Many exciting results of
the last decade, from experimental evolution [11] and pathogen adaptation innature [12, 13] in particular, take on
broad significance in light of Wagner’sarguments for the generality of genotype networks in evolution. Wagner
devotes much of the book to illustrative
examples from a very broad sampling of
the evolutionary literature, and thiswillingness to engage with experiments
will make his book much more accessible to molecular biologists than theaverage evolutionary monograph.
The breadth of his presentation,
however, does at times lead to theimpression that Wagner’s theory may
be a little too malleable. Wagner proposes observations about genotype networks that could have invalidated histheory, and he derives novel predictions, but these still do not add up toa readily falsifiable theory. Wagner’s
goal is actually more of a generalexplanatory framework, not a fully predictive theory, and so his presentation

Bioessays 34: 518–520,ß 2012 WILEY Periodicals, Inc.

sometimes brushes past the potential
importance of alternative factors that
may germinate innovation. Factors
such as gene duplication andhorizontal gene transfer are discussed
briefly, and filtered through theperspective of genotype networks.
Wagner’s eagerness to apply his overarching theory to much of evolutionary
biology gives an enjoyable energy to thebook, but readers should not expect thatthe theory of genotype networks willsolve all of the questions of evolutionary
innovation.
In fact, some readers may finish thebook with a lingering doubt about
whether Wagner has been discussing
innovation at all. Sherlock Holmes oncecomplained that his deductions seemed
to change from mystical to trivial after
each step had been explained, and similarly, a persistent problem to any suchtheory is that innovation loses it apparent novelty when we understand theincremental underlying process. The
evolutionary steps on which Wagner
focuses might be called microevolutionary. Consequently it seems reasonable
to ask whether his theory has muchbearing on some of the largest qualitative jumps in the history of life, such as
the transition to multicellularity or theorigin of consciousness. Though somereaders may reject any general, incremental theory for the big innovations intheir field, Wagner’s perspective on genotype networks may eventually reveal
the underlying logic to even the mostdramatic novelties in biology. But for
now, the link between the stepwise
adaptation of Wagner’s models andthe major innovations of biology
remains speculative.
This book will surely be influential
with the next generation of evolutionary
biologists, who will be able to digest
and then apply the significance of a
network-centric view of adaptation.
Such a perspective will be essential
for interpreting the increasing numberof empirical studies that recapitulate
evolutionary innovations in laboratory
experiments. But even those molecularand evolutionary biologists who do not
actively work on problems of innovation
will benefit from the clarity of Wagner’s
theoretical arguments, and the inspiring
wealth of empirical examples that demonstrate a new way to think of thedynamics of adaptation.

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Book reviews

later arguments linking genotype networks to evolutionary innovation. This
foundation is based on degeneracy – theproperty that many genotypes correspond to each phenotype – and therecognition that the genotypes in these
networks may be functionally equivalent but mutationally distinct. This latterphenomenon, which reflects epistastic
interactions among genes and sites
within a gene, is a major theme in
Wagner’s earlier book as well, but here
it forms the central pillar of a networkbased theory of innovation.
One striking feature of these early
chapters is the focus on quantitative
results
fromnumericalmodels.
Numerous figures plot measurements
like the relationships between genetic
and phenotypic distances, or the distributions of the sizes of genotype networks. These simulations are based
upon simplified models of fitness andmutational change and so it is difficult,at first, to appreciate the value of theexact quantitative details. These early
chapters may be tedious for some readers, and indeed, Wagner advises thatthese chapters may be skipped. But
while many of the numerical measurements he presents have only a loose
relation to biology, the goal of his presentation is actually quite exciting:Wagner is trying to inculcate in thereader an intuition for the discrete,high-dimensional spaces that truly
underlie evolution, and in the process
trying to displace the dominant metaphor of adaptive landscapes.
The common metaphor of evolving
populations seeking ‘‘peaks’’ on a landscape of fitness hills and valleys is bothclearly problematic, and difficult toavoid. The concept relies on the mapping of possible genotypes onto two
spatial dimensions, while fitness determines the height of each point. A population is then thought of as a point, orperhaps a small cluster of individuals,
which moves up hills by natural selection and fluctuates down into shallow
valleys by genetic drift. While making
evolution seem easy to grasp, this metaphor also highlights an apparent problem: how can populations atop a modest
hill move to an adjacent, higher peak,when any single change must require adrop in fitness?
The pathology of this metaphor foradaptive evolution has been recognizedBook reviews

References
1. Hayden EJ, Ferrada E, Wagner A. 2011.
Cryptic genetic variation promotes rapid evolutionary adaptation in an RNA enzyme. Nature474: 92–5.
2. Wagner A. 2008. Neutralism and selectionism: a network-based reconciliation. Nat Rev
Genet 9: 965–74.
3. Wagner A. 2005. Robustness and Evolvability
in Living Systems. Princeton, NJ:Princeton University Press.
4. Schuster P, Fontana W, Stadler PF,Hofacker IL. 1994. From sequences toshapes and back: a case study in RNA secondary structures. Proc Biol Sci 255: 279–84.

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5. Huynen MA. 1996. Exploring phenotype
space through neutral evolution. J Mol Evol
43: 165–9.
6. Gavrilets S. 1997. Evolution and speciation
on holey adaptive landscapes. Trends Ecol
Evol 12: 307–12.
7. Govindarajan S, Goldstein RA. 1997.
Evolution of model proteins on a foldability
landscape. Proteins 29: 461–6.
8. Schuster P, Fontana W. 1999. Chance andnecessity in evolution: lessons from RNA.
Physica D 133: 427–52.
9. Whitlock MC, Phillips PC, Moore FB,Tonsor SJ. 1995. Multiple fitness peaks
and epistasis. Annu Rev Ecol Syst 26:601–29.

10. Whitacre J, Bender A. 2010. Degeneracy: adesign principle for achieving robustness andevolvability. J Theor Biol 263: 143–53.
11. Blount ZD, Borland CZ, Lenski RE. 2008.
Historical contingency and the evolution of akey innovation in an experimental populationof Escherichia coli. Proc Natl Acad Sci USA
105: 7899–06.
12. Koelle K, Cobey S, Grenfell B, Pascual M.
2006. Epochal evolution shapes the phylodynamics of interpandemic influenza A (H3N2) inhumans. Science 314: 1898–03.
13. Bloom JD, Gong LI, Baltimore D. 2010.
Permissive secondary mutations enable theevolution of influenza oseltamivir resistance.
Science 328: 1272–5.

Bioessays 34: 518–520,ß 2012 WILEY Periodicals, Inc.