Robustness and Evolvability in Living Systems:

Robustness and Evolvability in Living Systems:

Andreas Wagner
Copyright Date: 2005
Pages: 384
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  • Book Info
    Robustness and Evolvability in Living Systems:
    Book Description:

    All living things are remarkably complex, yet their DNA is unstable, undergoing countless random mutations over generations. Despite this instability, most animals do not grow two heads or die, plants continue to thrive, and bacteria continue to divide. Robustness and Evolvability in Living Systems tackles this perplexing paradox. The book explores why genetic changes do not cause organisms to fail catastrophically and how evolution shapes organisms' robustness. Andreas Wagner looks at this problem from the ground up, starting with the alphabet of DNA, the genetic code, RNA, and protein molecules, moving on to genetic networks and embryonic development, and working his way up to whole organisms. He then develops an evolutionary explanation for robustness.

    Wagner shows how evolution by natural selection preferentially finds and favors robust solutions to the problems organisms face in surviving and reproducing. Such robustness, he argues, also enhances the potential for future evolutionary innovation. Wagner also argues that robustness has less to do with organisms having plenty of spare parts (the redundancy theory that has been popular) and more to do with the reality that mutations can change organisms in ways that do not substantively affect their fitness.

    Unparalleled in its field, this book offers the most detailed analysis available of all facets of robustness within organisms. It will appeal not only to biologists but also to engineers interested in the design of robust systems and to social scientists concerned with robustness in human communities and populations.

    eISBN: 978-1-4008-4938-3
    Subjects: Ecology & Evolutionary Biology, Developmental & Cell Biology

Table of Contents

  1. Front Matter
    (pp. i-vi)
  2. Table of Contents
    (pp. vii-viii)
  3. List of Figures
    (pp. ix-xii)
  4. Acknowledgments
    (pp. xiii-xvi)
  5. 1 Introduction
    (pp. 1-12)

    Living things are unimaginably complex, yet they have withstood a withering assault of harmful influences over several billion years. These influences include cataclysmic changes in the environment, as well as a constant barrage of internal mutations. And not only has life survived, it has thrived and radiated into millions of diverse species. Such resilience may be surprising, because complexity suggests fragility. If you have ever built a house of cards, you will know what I mean: The house eventually comes tumbling down. Why is an organism not a molecular house of cards? Why do not slight disturbances (especially genetic disturbances...

    • 2 The Genetic Alphabet
      (pp. 15-24)

      Why does the genetic material have four letters, and why are they exactly the four letters we know: A, T(U), C, and G? One might think that there is no other way to ensure accurate replication. However, that is far from certain, as we will see here.

      Because we do not know of any organisms that have genetic material with a different alphabet, this chapter contains a fair dose of speculation, but I included it for two reasons. First, it illustrates that a careful look may reveal robustness—and possibly traces of its evolution—even on the lowest level of...

    • 3 The Genetic Code
      (pp. 25-38)

      The genetic code is responsible for translating a sequence of nucleotide triplets (codons) into a protein’s amino acid sequence. The vast majority of extant organisms use the code shown in Figure 3.1. Ever since this “universal” genetic code was discovered, the question of why this code and not another has received much attention. This question becomes especially significant if one considers how many possible genetic codes there are. That is, how many ways are there to encode 20 amino acids with 64 nucleotide triplets? The number of possible genetic codes is astronomical, even if one considers only codes that preserve...

    • 4 RNA Structure
      (pp. 39-61)

      The currently most explicit and deepest analyses of mutational robustness regard the structure of RNA. These analyses not only show that RNA structures can be very robust to changes in individual RNA nucleotides, they also characterize the vast neutral space associated with many RNA structures and show how RNA robustness can evolve within this neutral space; they demonstrate that neutral mutations can be critical to evolutionary innovation in RNA structure; and they point to a link between mutational robustness and robustness to nongenetic change.

      RNA is an attractive molecule for studies of mutational robustness, because of its importance in past...

    • 5 Proteins and Point Mutations
      (pp. 62-77)

      The main factor hindering the experimental analysis of robustness in RNA structure is the difficulty of determining this structure experimentally. Powerful computational techniques for RNA structure prediction have alleviated this problem. The situation in proteins is the converse. There is abundant experimental data on protein structures and their robustness. In contrast, fewer systematic computational analyses of problems that are difficult to address experimentally exist for proteins. However, where they ask similar questions, experimental and computational analyses of protein structure have often yielded answers similar to those obtained for RNAs. Specifically, such analyses show that the structure and function of many...

    • 6 Proteins and Recombination
      (pp. 78-90)

      Recombination is a much more drastic genetic change than the point mutations in individual nucleotides and amino acids I have discussed thus far. It can replace multiple contiguous amino acids in a protein. On a larger scale, it can lead to complicated rearrangements of many genes. Are the chimeras that recombination creates true monsters, or are they often still well-functioning biological systems? In other words, how robust is protein structure and function to recombination? Unfortunately, compared to robustness to point mutations, the robustness of biological systems to recombination is little understood. However, because of recombination’s importance, I will survey what...

    • 7 Regulatory DNA Regions and Their Reorganization in Evolution
      (pp. 93-103)

      As I discussed in chapter 1, two main approaches can provide information on a biological system’s robustness. The first consists of many experimental perturbations of the system’s parts. An example is the generation of thousands of amino acid changes in a protein. The second consists of comparing systems in related species, systems that derive from a common ancestor and that represent different solutions to the same biological problem. An example is the comparison of proteins with similar function and a common ancestor in widely divergent species. Such a comparison can show that alternative—sometimes drastically different—solutions to a biological...

    • 8 Metabolic Pathways
      (pp. 104-119)

      In diploid organisms, null mutations—mutations in which a gene loses its function—at one out of its two alleles often have no or little phenotypic effect. This observation encapsulates the phenomenon of dominance. Dominance is the facet of genetic robustness that first received major attention in the literature. This chapter discusses the origin and evolution of dominance in metabolic systems, where the mechanistic basis of dominance is especially well understood. However, the material in the chapter also speaks to robustness in metabolic systems beyond the phenomenon of dominance.

      In the most general terms, dominance means that a phenotypic feature...

    • 9 Metabolic Networks
      (pp. 120-142)

      The metabolic pathways of the previous chapters are but figments of the complex chemical reaction networks sustaining life. To understand robustness of metabolism ultimately requires understanding such larger metabolic networks. Metabolic control analysis, whose basic principles were discussed in the previous chapter, can be used to study such networks, but it also faces severe practical limitations (150). First, applying metabolic control analysis to large reaction networks comprising thousands of reactions poses formidable mathematical problems. Second, metabolic control analysis requires much quantitative information, in particular about the rate at which enzymatic reactions proceed inside cells. Unfortunately, with the exception of a...

    • 10 Drosophila Segmentation and Other Gene Regulatory Networks
      (pp. 143-160)

      This chapter illustrates how one can make educated guesses about the robustness of a genetic network, even when hobbled by incomplete information. The chapter uses one main example (571), the network responsible for subdividing the Drosophila embryo into multiple segments. This example comes from a growing body of work on quantitative models of gene regulation networks, models that are firmly grounded in empirical information (14, 23, 51, 136, 142, 334, 369, 370, 387, 458, 497, 560). Such models integrate an enormous volume of data into a mathematical network representation. The large amounts of necessary data—usually accumulated by hundreds of...

    • 11 Phenotypic Traits, Cryptic Variation, and Human Diseases
      (pp. 161-174)

      This chapter focuses on robustness in the developmental processes that produce macroscopic characters such as eyes and wings. Specifically, it discusses evidence that many phenotypic characters vary little, despite much variation in the genes involved in their development. Because such cryptic variation is the result of past mutations, this phenomenon shows that developmental pathways and the characters they produce are robust to mutations. I first review some of the historically earliest experiments demonstrating widespread mutational robustness in embryonic development. I then discuss more recent experimental work on the striking role of one specific gene, the gene encoding the heat shock...

    • 12 The Many Ways of Building the Same Body
      (pp. 175-192)

      This chapter deals with a level of biological organization far removed from DNA: many-celled organisms and their embryonic development. It makes two central observations. First, there are many and sometimes radically different ways to build the same body or body part. Nature has found some of these ways and transitions between them on surprisingly short timescales. This observation connects this chapter’s examples to a common thread of previous chapters, a thread I revisit in chapter 13. Specifically, the observation provides a hint that the process of building a body shows great robustness to genetic changes. In other words, there must...

    • 13 Neutral Spaces
      (pp. 195-216)

      I argue here that the following concept of a neutral space can provide a unified view of robustness in many different systems I discussed earlier:

      A neutral space is a collection of equivalent solutions to the same biological problem. It can also be thought of as a set of alternative configurations of a biological system, configurations that solve the same problem.

      Biological systems embody solutions to a wide variety of problems, from the faithful replication of genetic information to the making of a body. Most of these problems have more than one solution, and many of them have an astronomical...

    • 14 Evolvability and Neutral Mutations
      (pp. 217-227)

      This chapter’s central question is whether robustness fosters or hinders evolvability. To begin with, what is evolvability? The word “evolvability” has two main usages (101, 183, 287, 445). 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.

      Functional innovation comes in many different sizes and shapes, from enzymes with new catalytic activities,...

    • 15 Redundancy of Parts or Distributed Robustness?
      (pp. 228-246)

      This chapter asks which of two possible mechanistic causes of robustness is more important in genetic systems. These two causes are redundancy of a system’s parts and distributed robustness, which emerges from the distributed nature of biological systems, where many (and different) parts contribute to system functions.

      Much like robustness and evolvability, biologists use the term redundancy in more than one way. One usage invokes redundancy if a gene’s activity can be changed or a system’s part can be removed without affecting key system properties (306). Another usage refers to redundancy only if two parts of a system perform the...

    • 16 Robustness as an Evolved Adaptation to Mutations
      (pp. 247-269)

      This chapter focuses on the question of how natural selection can increase a biological system’s robustness to mutations. As I argued earlier (chapter 13), robustness to mutations can have two major ultimate causes. First, it may be a by-product of how evolution searches for solutions to problems that organisms face. Second, in a system that embodies any one such solution, robustness can further vary and increase in evolution, as examples scattered through earlier chapters showed. Specifically, we saw earlier that robustness in systems as different as macromolecules and genetic networks can increase in evolution. In addition, in systems like the...

    • 17 Robustness as an Evolved Adaptation to Environmental Change and Noise
      (pp. 270-280)

      The previous chapter discussed the role mutations play in the evolution of robustness. This chapter focuses on an alternative explanation for the evolution of mutational robustness, an explanation that is really very simple. Mutational robustness can be a by-product of an organism’s need to survive and reproduce in the face of nongenetic changes. These include changes in the organism’s environment and continual changes inside the organism itself, for which the term noise is often used (22, 454).

      At first sight, it seems self-evident that evolved robustness to mutations should be an adaptation to mutations. However, we saw that this notion...

    • 18 Robustness and Fragility: Advantages to Variation and Trade-offs
      (pp. 281-294)

      Robustness in living systems deserves explanation, because such systems are complex and one might thus expect them to be fragile, much like a house of cards. In contrast, we saw that most living systems can tolerate much mutational pressure, and often to an astonishing extent. However, there are notable exceptions. Some systems inside organisms can be exceedingly fragile, in the sense that their properties vary extensively in response to mutations. Although some such fragility may be a simple by-product of complexity, fragility may also have two other causes. First, it can be advantageous. Second, even where fragility is disadvantageous, trade-offs...

    • 19 Robustness in Natural Systems and Self-Organization
      (pp. 297-309)

      In this chapter, I point out parallels and, more importantly, differences between robustness in living systems—organisms and their parts—and other, nonliving systems. One important commonality between robustness in living and other systems is obvious: Something—either the state of a system or the system itself—persists in the face of perturbations. However, at least two differences are more significant than this commonality. First, only organisms have genetic material and can thus be robust to mutations in this material. Second, and more importantly, most nonliving systems are not subject to the force of natural selection, which may favor robust...

    • 20 Robustness in Man-made Systems
      (pp. 310-320)

      Biological systems perform complex tasks. But so do nonliving engineered systems. Are the principles that govern their design different? Or are they fundamentally similar? Do they achieve robustness in similar or different ways? The answers to these questions could fill another book. In this chapter—really more of an afterthought—I make a few comparisons between living and nonliving engineered systems. I first point out two fundamental differences in their architecture, differences that have implications for questions related to robustness. These are the erratic behavior of parts of many biological systems, as well as the apparently unnecessarily complex architecture of...

  10. Epilogue: Seven Open Questions for Systems Biology
    (pp. 321-322)

    The following are key open questions and problems that emerged from the preceding chapters. We will understand mutational robustness to the extent that we answer these questions for a wide variety of biological systems. Currently, however, none of these questions have conclusive answers in any system. I note that most of these questions are empirical, not theoretical questions. This reflects the view that major theoretical developments in this area are in place, but that empirical data are still sorely lacking.

    Which of the two main evolutionary causes of robustness is most important? The first cause comes into play whenever evolution...

  11. Bibliography
    (pp. 323-358)
  12. Index
    (pp. 359-367)