Download Max Planck Institute for the History of Science graphing genes, cells

Max-Planck-Institut für Wissenschaftsgeschichte
Max Planck Institute for the Histor y of Science
2009
P r epr i n t 3 8 0
Sabine Brauckmann, Christina Brandt,
Denis Thief fr y, Gerd B. Müller (eds.)
Graphing Genes, Cells, and Embr yos
Cultures of Seeing 3D and Beyond
Contents
Introduction
Sabine Brauckmann and Denis Thieffry �������������������� 5
Acknowledgments����������������������������� 13
I Forma
Dimensions of Embryos, Cells, and Molecules
The Problem of Assessing the Dimensionality of Information
Richard Burian������������������������������ 17
Building Simple Two-Dimensional Molecular Models to Illustrate
a Complex Subcellular World
Costis Papanayotou ���������������������������� 23
Imaging Fate: Tracking Cell Migration in the Developing Embryo
Sema K. Sgaier������������������������������ 29
Pander, d’Alton and the Representation of Epigenesis
Stephane Schmitt ����������������������������� 33
Pattern of Scanning, Tracing and Assemblage
Refined Concentration of Botanical Expert Knowledge and Images
for Gaining Passions for Plants
Marianne Klemun ���������������������������� 41
Viewing Chromosomes
Soraya de Chadarevian��������������������������� 57
Scales of Line, Circle, and Arrow
Adaptive versus Epigenetic Landscape. A Visual Chapter in the History
of Evolution and Development
Silvia Caianiello ����������������������������� 65
Cellular Dimensions and Cell Dynamics, or how to Capture Time
and Space in the Era of Electron Microscopy
Ariane Dröscher ����������������������������� 83
II Instrumentaria
Tools Matter
Agnes Arber: The Mind and the Eye
Maura C. Flannery ���������������������������� 95
In Three Small Dimensions: X-Ray Microtomography as a Way of Seeing
Brian D. Metscher�����������������������������105
Optical Projection Tomography: Revealing the Visible
James Sharpe ������������������������������111
Tracing the mtDNA Trail
Mait Metspalu ������������������������������117
Patterns of Perception
Embryos and Empathy: The Model Experiments of Wilhelm His
Thomas Brandstetter����������������������������123
“Placing Oneself at an Adequate Point of View”. Santiago Ramón y Cajal’s
Drawings and the Histological Look
Erna Fiorentini������������������������������133
The Cell as a Technical Image
Matthias Bruhn �����������������������������143
Movement and the Creation of Images
Silver Rattasepp �����������������������������153
Spaces of Interpretation
What do Genetic Maps Represent (and How)?
Marion Vorms ������������������������������161
Visualising the Invisible in Cell Biology: The New Face of the
Cell from the Late 1980s
Norberto Serpente�����������������������������177
III Rhetorica
Visual Pedagogy
Science Joins the Arts: The Collection of Watercolors and Drawings
of Marine Organisms at the Stazione Zoologica Anton Dohrn
Christiane Groeben ����������������������������195
Visualizing Sexual Differentiation: The Rhetoric of Diagrams
Shelley Wall �������������������������������203
Authors and Editors ����������������������������209
Adaptive versus Epigenetic Landscape. A Visual Chapter in the History of
Evolution and Development
Silvia Caianiello
The main characters of my narrative are two graphic representations that both played a pivotal
role in establishing a new visual imagery for conceiving evolutionary and developmental change
in the twentieth century.
Notwithstanding their divergences, both in the time scale, as well as in the quite opposing
directions of the processes they describe, they share some common features. They both aimed at
visualizing the behavior of complex dynamic systems in terms of spatial relationships, and so
aimed at being landscapes of “moving equilibria” (Wright 1931, p. 147; Waddington 1940, p. 92).
Moreover, they share a basic constructional strategy, the collapsing of multidimensional phasespaces into three-dimensional diagrammatic representations; a choice that, although differently
nuanced, was aimed at conveying complex processes in the immediacy of a visual device.
Furthermore, beyond the explicit primacy of a communicative as well as a didactic intention,
the major feature they have in common is the epistemic status of models, whose efficacy in this
sense is testified to, at least wirkungsgeschichtlich, by the subsequent genealogy of models still
referring to them as their ancestors, while also acting at the same time as images in the wider
sense I just mentioned.
The further and formal main link between the two representations is a genealogical one. By
adopting the idea of landscape, Waddington deliberately referred to Wright’s visual device, and I
will try to work out some hypothesis about this historical connection in the context of the
relationship between evolutionary and developmental research, in a span of time – 1932 to 1957 –
that extends from the rise of Modern Synthesis to the beginning of its “hardening” (Gould 1983).
I will not directly tackle the question of the ambiguity of their status between “algorithm and
image,” and the ways they exceeded their original modelling function, but I hope to contribute
somehow to the exploration of the imagery repertoire they drew upon, which might be assumed
to be another possible factor substantiating the autonomy of models both from theories and
data.
Evolutionary progress
The adaptive landscape was the expedient by which Wright – as he had been explicitly requested –
presented his evolutionary theory in a concise and not technical way in 1932 (Provine 1986,
p. 275). His model is therefore, first of all, a “model for” his shifting balance theory, which proved
useful from the start as a general tool for visualizing other possible modellings of the evolution of
Mendelian populations. More generally, it became the favored visual tool for the new style of
See Wright 1932, p. 163-165; a discussion of the consequences of this collapsing of dimensions was
conducted in his correspondence with Fisher in 1931, see Provine 1986, pp. 272-275; Waddington 1940,
p. 27.
Gayon 1998, p. 341, with reference to Wright’s landscape.
See M. Morrison 1999; see also Sismondo 1999; de Chadarevian and Hopwood 2004; Levins 1966. The
notion of “model for” relates to Keller 2000.
Skipper 2004 emphasizes the role of the adaptive landscape model as a tool for evaluating different
evolutionary theories. I would rather support the broader view that it was primarily also a tool for
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biomathematical modelling, which provided the reconciliation between Mendelian genetics and
biometrical statistics, which is at the core of Modern Synthesis. As such, its historical relevance
could perhaps be compared to the branching trees of nineteenth-century Darwinism.
As Dobzhansky observed, this reconciliation was mainly brought about by three mathematical
geniuses, Fisher, Haldane, and Wright, whose work placed biological science in general, and
evolutionary genetics in particular, “in the position in which physics has been for many years.”
The reduction of quantitative traits to the interaction among Mendelian particulate genes removed
the last obstacle at representing evolution as the behavior of a population composed of atomized
entities whose frequency was determined by the action of opposing forces, mainly natural selection
and mutation. This original conception, which received a complete formulation in Fisher’s
Fundamental Theorem, relied heavily on an explicit analogy drawing upon Boltzmann’s statistical
mechanics of ideal gases, and secondarily upon the second principle of thermodynamics, where
mutation played the role of entropy and natural selection the role of the main counterentropic
factor.
This approach is also characterized, somewhat paradoxically, by a highly probabilistic stance
as well as by an evident foundationalist intention, the one explicitly celebrated in Dobzhansky’s
commentary. As has been observed, the goal of the founders of mathematical population genetics
was “the theoretical-mathematical refoundation of biological science more than the application of
mathematical techniques to particular contexts.”
This is relevant in so far as Fisher and Wright soon agreed that the divergences in their theories
were mostly related not to quantitative issues, but to qualitative stances. The many differences
characterizing their scientific backgrounds and approaches amounted to an evident divide in their
representational horizons, even within the shared context of a thermodynamic imagery. In his
statistical mechanical analogy, Fisher evidently starts with a very large, panmictic population of
atomistic genes, as the one modelled in Hardy-Weinberg equilibrium, to further manipulate its
parameters in order to test and establish the prevailing power of natural selection on its evolution.
According to Wright, on the contrary, the representation of the population structure that better
“agrees with the apparent course of evolution in the majority of cases” is the case of “a large species
which is subdivided into many small local races, each breeding largely within itself but occasionally
crossbreeding,” as portrayed in the last of the six possible landscapes presented in his 1932 paper
(p. 166).
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visualizing them and evolutionary processes in general.
Dobzhansky 1962, p. 500-501, quoted in Provine 1986, p. 277: “Genetics is the first biological science
which got in the position in which physics has been in for many years. One can justifiably speak about
such a thing as theoretical mathematical genetics, and experimental genetics, just as in physics. There
are some mathematical geniuses who work out what to an ordinary person seems a fantastic kind of
theory. This fantastic kind of theory nevertheless leads to experimentally verifiable prediction, which an
experimental physicist then has to test the validity of. Since the times of Wright, Haldane and Fisher,
evolutionary genetics has been in a similar position.”
Hodge 1992 distinguishes analytically between the two and the different contexts in which Fisher makes
use of them. Fisher was nonetheless keenly aware of the many disanalogies between evolution and
thermodynamic processes. For a comprehensive assessment of the role of Fisher’s Fundamental Theorem
in evolutionary theory, see Plutynski 2006.
See Israel 2004 and 1993; see also Hodge 1992, pp. 287-288.
Fisher 1930, p. 35; see Provine 1992, p. 149 and Skipper 2009, p. 311-312. Plutynski 2006, in a recent
reassessment of Fisher’s Fundamental Theorem, denies that such assumptions are central to Fisher’s
research program, basing mostly on later writings.
Adaptive versus Epigenetic Landscape. A Visual Chapter in the History of Evolution and Development
Figure 1: “Field of gene combinations occupied by a population within the general field of possible
combinations”. From Wright 1932, fig. 4, p. 166.
This qualitative feature in the representation of the ideal conditions for the evolution of Mendelian
populations is actually the result of Wright’s life-long experimental practice in physiological
genetics and inbreeding, as well as of the wider research tradition on geographic speciation, which
had established the primary relevance of nonadaptive morphological characters differentiating
related species. But, at a different level, a conspicuous number of Spencerian metaphors can also
be detected in his way of representing evolutionary change, such as the idea of a moving
equilibrium resulting from the three-phases balancing process, whereby evolution comes to be
depicted as a journey (or a walk) across adaptive hills and valleys – although with the crucial
difference, with regard to Spencer, that here chance plays a new, creative role as the main factor
preventing populations from sticking at less optimal peaks.10 Nonetheless, as far as the structure
of the population is concerned, a background role might also have been played by Spencer’s view
that social growth, as well as biological growth, which involves an increase not in numbers but in
organizational complexity, “results only by combination of these smaller societies; which occurs
without obliterating the divisions previously caused by separations” (Spencer 1877, pp. 226-228),
very similar to Wright’s view of genetic differentiation occurring in the subgroups and later
spreading out through migration and crossbreeding of the fitter genotypes.
One of Wright’s main concerns in building his adaptive landscape was to emphasize, in an
intuitive fashion, the major role played by epistatic interactions among genes – an idea as crucial
to his theory as it was statistically immaterial in Fisher’s representation of large panmictic
10
Provine 1986, Chap. 7, reconstructs the persistent controversies about this issue since Darwin.
See Gayon 1998; Ruse 1996 and 2004; Steffes 2007. The most macroscopic Spencerian influence is,
however, the subsumption of the different factors involved in the balancing process into the two major
Spencerian categories of factors endorsing homogeneity and those endorsing heterogeneity.
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populations. Thus the direct inspiration for his model was a 1931 article by Haldane that included
a diagrammatic representation of selection upon two epistatic genes.11
Figure 2: Illustrating a case of “Slow selection involving more than one gene”. From Haldane 1932,
fig. 10, p. 107.
The result demonstrated the presence of two stable states of equilibrium separated by an unstable
state. Wright’s invention was the addition of a fitness surface, which highlights the stable states as
hills and the unstable ones as valleys.
The relevance of epistatic interactions in making the adaptive landscape rugged has been
further emphasized in Kauffman’s model, outlining a range from the lowest degree of epistasis,
resulting in the Fujiyama landscape – rather resembling Fisher’s model – up to the highest degree
of epistasis, resulting in a wildly rugged and indented landscape.12
11
Haldane 1931, pp. 139-141. A much clearer account of the image and its underlying assumptions for the
layman is to be found in the Appendix “Outline of the Mathematical Theory of Natural Selection” to
Haldane 1932, pp. 106-108, in a paragraph entitled: “Slow selection involving more than one gene.”
12
Figure 4, reproduced by courtesy of McGhee (see McGhee 2007, p. 20, Figure 2.12), is applied to
morphological traits, not to gene frequencies as in the original “NK fitness landscapes” (Kaufmann
1995). Kaufmann, unlike Wright, provides his model with a multidimensional extension, employing
computer simulations. McGhee 2007 establishes and explores the continuity between evolutionary
landscapes and the latest developments in theoretical morphospaces modelling.
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Adaptive versus Epigenetic Landscape. A Visual Chapter in the History of Evolution and Development
Figure 3: “A hypothetical adaptive landscape”, representing adaptive morphologies, “portrayed as a
three-dimensional grid at the top of the figure and a two-dimensional contour map at the bottom“.
From McGhee 2007, fig. 1.1, p. 2. Courtesy of G.R. McGhee.
Figure 4: “Contrasting topologies of adaptive landscapes. The dashed line depicts a ‘Fujiyama’
landscape, with a single adaptive peak with very high adaptive value, versus the solid line depicting
a ‘rugged’ landscape, with multiple peaks of varying height but all of much lower adaptive value
than the Fujiyama peak”. The original Kauffman’s 1995 model did not include any picture. From
McGhee 2007, fig. 2.12, p. 20. Courtesy of G.R. McGhee.
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There is, however, a trick about Wright’s adaptive landscape that led Provine to discard it as
“meaningless in any precise sense.”13 While in Haldane’s diagram each dot represents a population,
Wright switches the meaning of the dots on the surface to representing gene combinations, that is,
single genotypes, which Provine has argued could never result in a continuous surface of any
kind.
Such a mindless blurriness in the definition of a crucial parameter in an outstanding
mathematical genius is extremely interesting, the more so as this genotypic version of the
landscape has been the most fruitful, especially in its impact upon the founders of Modern
Synthesis, such as Dobzhansky and Simpson. It is difficult to resist the temptation to look for
some hidden reason for such a macroscopic flaw and imagine that it might have been prompted by
Wright’s urge to convey a qualitative feature in his model.14 My guess is that he was trying to fill
visually the gap between the qualitative implications of his theory and the necessary mathematical
simplification of its actual extension. This surmise could account for the fact that Wright received
so favorably the apparent betrayals of his own model, such as by Dobzhansky, who eventually
made of the dots entire species, or Simpson who made them represent morphological traits
(Simpson 1944, Dobzhansky 1951).
Wright’s most general conclusion of his 1932 paper, “that evolution depends on a certain
balance among its factors,” together with the further specification that such a balance is also to be
found “at all levels of organization” (Wright 1932, p. 170), could suggest that he considered these
wider applications of his model, rather than as misunderstandings, as veritable amplifications,
reaching, by means of a metaphorical escalation, further organizational levels in the biological
hierarchy.15
Developmental resilience
If we look at the origin of Waddington’s model of epigenetic landscape, we find a much longer
gestation.
I can’t illustrate here in detail what I consider to be the first paragraph of the visual history of
Waddington’s epigenetic landscape, the images proposed by Needham in Order and Life of 1936.
The alleged Waddington’s cones – alleged, because Waddington never actually drew them – that
Needham introduces provide him an entry into biomathematical modelling, mainly inspired by
Lotka, to conceive of development, or “progressive restriction of potencies,” as a cascade of states
moving from the unstable toward the more and more stable (Needham 1936, pp. 58-59).
What is relevant in Needham’s evocation of Lotka’s diagrams is that in the three-dimensional
visualization, equilibrium is represented as the bottom of a valley – the exact opposite of Wright’s
quite progressivist peaks, and a foreshadowing of the fashion by which Waddington would
visualize equilibria in his epigenetic landscape. But the resemblance of this three-dimensional
image to Waddington’s slopes and valleys is actually deceptive, as it is obviously the reverse, uphill
movement that the line of the valley is depicting here. That is why Needham, in appropriating this
visual idea, first of all reverses the movement, from uphill – or from the homogeneous, unstable
state – towards downhill or the more differentiated steady state, as it is to be seen in his volcanolike image of development.
13
Provine 1986, p. 310. He refers to his discussion of this early flaw with Wright, who eventually corrected
it in later writings.
14
See Gayon 1998 for a similar suggestion.
15
Wright 1953; see Hodge 1992 and Steffes 2007.
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Adaptive versus Epigenetic Landscape. A Visual Chapter in the History of Evolution and Development
Figure 5 A: “Map of integral curves for the Ross malaria equations”and model of surface
corresponding to the former figure. From Lotka 1924, fig. 28, p. 149.
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Figure 5 B: “Map of integral curves for the Ross malaria equations”and model of surface
corresponding to the former figure. From Lotka 1924, fig. 29, p. 150.
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Figure 5 C: Represents an application of Lotka’s model for the case of development: “Qualitative
three-dimensional model of embryonic determination. Illustrating the passage from unstable to
stable equilibria”. From Needham 1936, fig. 11.
Adaptive versus Epigenetic Landscape. A Visual Chapter in the History of Evolution and Development
Waddington’s pioneering attempt at reunifying the divided fields of genetics and embryology has
received increasing attention by evolution researchers, particularly in the recent discipline of EvoDevo.16 More specifically, in 1991, Gilbert dedicated a paper to the origin of the epigenetic
landscape model, relating it mainly to the tradition of embryological diagrams of cell lineages in
experimental embryology, which resulted in a branching track of differentiating cells. In 1939, in
the diagram representing pigment formation in the eye of Drosophila, Waddington indeed created
an interesting substitution; instead of cell divisions, bifurcations represent the alternative action
of genes and their products that determine the fate of the cells. So, the “branching system of lines
symbolizes all the possible ways of development controlled by different genes” (Waddington 1939,
p. 182). Gilbert’s general point is that the epigenetic landscape is but an extension of this original
track system, and that by remaining faithful to this visual tradition, Waddington was emphasizing
his intention of unifying the two fields.17
As a matter of fact, however, Waddington states rather clearly that if a new symbolic
representation is needed, it is precisely because of the inadequacy of the branching track one. In
1939, Waddington introduces therefore a “valley model” or geological model of gene reactions, of
which he provides at the time a purely verbal description, although the analogy with the
“probability surface” of Wright’s landscape (also called here “valley model”) is already
acknowledged, without further argumentation, in the framework of the long section dedicated to
the work of Fisher, Haldane and Wright (Waddington 1939 p. 183 and 293 ff). The question at
stake is namely that although single genes “often define alternative courses along which the
[developmental] reactions may go [...] the course of any developmental process is determined by
many genes,” that is “by the whole genotype.”18
This is at least the explicit reason why Waddington turned to the landscape representation in
1939 as well as in Organisers and Genes in 1940, always cursorily acknowledging the connection to
Wright’s model. Moreover it is not surprising that, exactly because of his commitment to the
unification of genetics and embryology, he might have been willing to keep to the same
representational horizon as mainstream mathematical evolutionary genetics. It was only in 1957
however that an image was added to the text to visualize the embedding of the single branching
track into a system constituting the “genotypic milieu.”19
Here, the visualization of the genetic interaction pervading the whole genotype possesses a
genuine intuitive appeal:
These pegs represent the genes, and the tensions on the guy ropes the chemical forces which
the genes exert. As the diagram indicates, the course and slope of any particular valley is
affected by the chemical tendencies of many genes; and if any gene mutates, altering the
tension in a certain set of guy ropes, the result will not depend on that gene alone, but on its
interaction with all other guys. (Waddington 1957, p. 35)
16
See Alberch 1980; Hall 1992, 2004, 2008; Slack 2002; Gilbert 1991, 2000.
Gilbert 1991, pp. 141-142. Hall 1992 shows a similar kind of attitude towards Waddington’s endeavor,
attributing it to the integration of embryology and genetics rather than of embryology and evolution.
Their interpretation of Waddington’s role appears more wide-ranging in later writings however.
18
Waddington 1939, pp. 182-183; in Waddington 1940, p. 83, he rejects even more sharply the image of
single branching tracks as “rather a clumsy method of expression,” as “the course of each branch of the
complex track is controlled [...] by the whole genotype or the greater part of it.”
19
Waddington 1939, p. 163 ff., with reference to Timofeeff-Ressovsky 1934.
17
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Figure 6: “The complex system of interactions underlying the epigenetic landscape”.
From Waddington, Conrad H. 1957, The Strategy of the Genes. London: George Allen & Unwin Ltd., fig. 5, p. 36.
My working hypothesis is that, in The Strategy of the Genes in 1957, the epigenetic landscape
enhances its status as a visual device, exactly because it serves a new function, that of a visual
instrument no longer just for merging evolutionary and developmental theories, but for revising
the former by means of the latter; the same stance – as Gilbert has shown – that led to Dobzhansky
actually promoting Schmalhausen’s formulation of the principle of stabilizing selection rather
than Waddington’s.20
20
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Gilbert 1994. But the actual extent of Waddington’s impact on the Modern Synthesis workers appears to
be much broader and subtler, as, for instance, some of Mayr’s references to Waddington in Mayr 1963
indicate. (Whether such a link could be interpreted as the clue to a common organicism, sensu El-Hani
and Emmeche 2000, is a further question). According to Schubert 1985, Waddington had elaborated his
criticism of Modern Synthesis as early as 1940, and the delay in its formulation was mainly due to the
war. The coincidence of these dates with the formalization of the epigenetic landscape seems to fit my
scheme.
Adaptive versus Epigenetic Landscape. A Visual Chapter in the History of Evolution and Development
In this respect, it appears rather intriguing that only by assuming this new function does the
epigenetic landscape really turn into a model, against the background of a new sophisticated
epistemological stance concerning the function of models, which actually dismisses any
foundationalist implication in favor of an exploratory one (Waddington 1957, p. 249). In fact, in
1939, Waddington did not include any visualization of the epigenetic landscape, and when he
finally did, in the frontispiece of Organisers and Genes, it was not as a diagrammatic representation
but as a pictorial one, provided by his friend the painter John Piper.
Figure 7: “Pictorial” epigenetic landscape. From Waddington, Conrad H., 1940, Organisers &
Genes. Cambridge: Cambridge University Press, Frontispiece (drawing by John Piper).
The choice of Piper is a sort of redundant one of commissioning the presentation of a symbolic
landscape to a painter of real landscapes. In his later book Behind Appearances dealing with the
“relations between painting and natural science” in the antirealistic and indeterministic context
of the “Third Science,” Waddington projected into Piper a still deeper affinity, and the terms by
which he described Piper’s visual poetics appear suprisingly similar to the system dynamic
language he employed for introducing his landscape”.21
21
Waddington 1969; for the definition of “Third Science,” see p. 5 ff. Among the British “Geometricizers,”
he confesses to a personal preference for Piper (p. 58), but it is the general characterization of the whole
group’s poetics that resounds astonishingly with the kind of linguistic images he employs for his
epigenetic landscape: “Putting it in the broadest way, they saw the external world in terms of equilibria
which resolved tensions; and these tensions operated in a world of objects which were refractory, hard,
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The overall conception deployed in 1969, emphasizing the creative and imaginative character of
scientific activity, can retrospectively help clarify the theoretical approach to modelling already
on display in the Strategy of the Genes. Models provide neither explanations nor proofs, but may
“lead the re-orientation of experimental approaches,” and also help reformulate the “new
problems” emerging from the “newer methods and techniques” (Waddington 1957, p. 249).
And actually, in this same book, Waddington devotes much energy to testing the exploratory
power of different models in the search for a visual representation of canalized development. In
the chapter entitled “The cybernetics of development,” he first significantly evokes Galton’s model
of organic stability (without including the original diagram), a kind of “mechanic” model for
explaining the tendency of organic structures to re-establish themselves in the former position of
equilibrium, as long as a precise “range” is not “overpassed.”22 Then he tests the possibility of
building, after Ashby, a veritable cybernetic model for development, complete with a graphic
device, particularly fit for describing the self-regulatory properties of developmental systems and
their threshold mechanisms. But, in the end, Waddington dismisses both Galton’s mechanostatistical model as Ashby’s cybernetic one, and comes back to the epigenetic landscape
(Waddington 1957, p. 13-27).
Why does Waddington return to the epigenetic landscape, in a section invoking cybernetics
as the domain into which it is desirable to embed developmental biology? I think that, of the
several reasons that prompted him to stick to the epigenetic landscape, a primary one is connected
to his criticism concerning the mathematical foundations of synthetic theory, in which Wright
appears to play a new, strategic role.23 This polemical intention is introduced by contrasting the
“geometrical mode of expression,” appropriate to the epigenetic landscape with the algebraic one.
The general flaw of the “mathematical theory” of evolution is precisely its “algebraic
formulation” of the selective value of a single allele “whatever its frequency in the population and
whatever other genes it is combined with.” But in this context, Wright, although “responsible for
much of the theoretical work in [that] field,” is presented as the only researcher who took “into
account the necessity to argue in terms of complete genotypes rather than individual alleles”
(Waddington 1957, p. 84).
Thus Wright’s landscape, with his topologic, geometric effort, was credited as challenging the
atomistic notion of fitness, as far as it emphasized “the importance of [...] different adaptive
facies.” In Waddington’s view, fitness is namely a systemic property, “a quality of the organism as
a whole” that cannot be accounted for by simply breaking it down “into a number of immediate
components” (Waddington 1957, p. 110). But Wright, although focusing on the species rather than
on the organismic level of analysis, had also emphasized a few years earlier that “natural selection”
is actually an “abstraction of the complicated reciprocal process” linking the species and the
dense, difficult to work, the contrary of ductile, flowing, emollient. [...] This sense of the real world as an
area of interlocking energies, of a line as a path of minumum energy through orderly fields of force is of
course an expression of some of the basic notions of modern science” (p. 55; italics mine). A later
development in Waddington’s attitude to art is deployed in Tools for Thought (1977) where he lets his text
be punctuated by creative and often humourous illustrations by the artist Yolanda Sonnabend (a fashion
recently reappraised by Jablonka and Lamb 2005, with illustrations by Anna Zeligowski).
22
Galton 1889, Chap. III, p. 27; where his definition of “mechanic” stability is actually more in the sense of
statistical mechanics than of machinery. See also Wilkie 1955.
23
In 1957, the evaluation of Wright’s work was more significant than in 1939, where Waddington
(Waddington 1953) rather seemed to incline towards Fisher’s interpretation of the evolution of
dominance. For Waddington’s criticism of population genetics in 1953, partly echoed by Mayr, see
Provine 1986, p. 280.
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Adaptive versus Epigenetic Landscape. A Visual Chapter in the History of Evolution and Development
world, situated “in a general trend through the progressive elaboration of the pattern of
organization of both” (Wright 1948, p. 538).
The major step that even Wright however misses, according to Waddington, is not having
envisaged the crucial relationship between “changes in gene frequencies” and “phenotypic
characters of organisms” – a critique that will constitute the bulk of his ongoing argument against
contemporary evolutionary theory.24
An interesting aspect of the shift in Waddington’s use of the epigenetic landscape in 1957 is
that it entails a sort of double movement, which has the effect of drawing it nearer to Wright’s
landscape. First of all, by reducing the distance between the professed quantitative scope of
Wright’s model and his own, which he always presented as merely symbolic and qualitative. He
dismisses Wright’s epistemic pretensions, downsizing his model to a mere “qualitative expression
of the possibilities,” which has to be supported by “an examination of the actual phenomena in
Nature” (Waddington 1957, p. 84-85). But, at the same time, Waddington introduces the
epigenetic landscape in a new, diagrammatic version, and employs it as a visual device for
representing the behavior of different developmental/epigenetic systems, and especially the
particular features of genetic assimilation, endowing it finally with all the properties of a model,
that is a framework as valuable as Wright’s landscape for depicting developmental – instead of
evolutionary – possibilities.
24
Figure 8: Representation by means of epigenetic landscapes of “‘Organic selection’ (the Baldwin
effect) and genetic assimilation”. From Waddington 1957, The Strategy of the Genes. London:
George Allen & Unwin Ltd., fig. 30, p. 167.
Waddington 1957, p. 110. Waddington 1969, while committing himself to an even clearer appreciation of
Wright’s peculiar position in Evolutionary Mathematical Genetics, inasmuch as he dealt with the
“multiple gene situation,” formulates the same criticism in a more straightforward fashion: Wright did
conceive his fitness surface as a genotypic instead of a phenotypic space. See also Waddington 1975, p. 280:
“In my opinion the conventional Neo-Darwinian theories of Haldane and Fisher (and to a lesser extent,
Sewall Wright) are inadequate both because they leave out the importance of behaviour in influencing
the nature of selective forces, and because they attach coefficients of selective value directly to genes,
whereas really they belong primarily to phenotypes and only secondarily to genes.”
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Silvia Caianiello
From a contemporary perspective, perhaps, a more general, positive continuity between these
first evolutionary and developmental landscapes stands out beyond the macroscopic opposition of
the processes they describe. They both define a space of evolutionary possibilities for modelling
the narrowing of possible trajectories of “moving equilibria” throughout the system. Whereas in
Wright’s view the evolutionary possibilities of a population are constrained by its structure and
size, Waddington, with his notion of “resistance to developmental change” foreshadows the
concept of “developmental constraints,” which acts at the same time as a “resistance to evolutionary
change,”25 thereby further affecting the possible directions of evolution.
25
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Waddington 1955; for Waddington’s role in the genesis of the notion of “developmental constraint,” see
Maynard Smith et al. 1985, p. 60.