Evolvability

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Evolvability is defined as the capacity of a system for adaptive evolution. Evolvability is the ability of a population of organisms to not merely generate genetic diversity, but to generate adaptive genetic diversity, and thereby evolve through natural selection. [1] [2] [3]

Contents

In order for a biological organism to evolve by natural selection, there must be a certain minimum probability that new, heritable variants are beneficial. Random mutations, unless they occur in DNA sequences with no function, are expected to be mostly detrimental. Beneficial mutations are always rare, but if they are too rare, then adaptation cannot occur. Early failed efforts to evolve computer programs by random mutation and selection [4] showed that evolvability is not a given, but depends on the representation of the program as a data structure, because this determines how changes in the program map to changes in its behavior. [5] Analogously, the evolvability of organisms depends on their genotype–phenotype map. [6] [7] [8] This means that genomes are structured in ways that make beneficial changes more likely. This has been taken as evidence that evolution has created fitter populations of organisms that are better able to evolve.

Alternative definitions

Andreas Wagner [9] describes two definitions of evolvability. According to the first definition, a biological system is evolvable:

According to the second definition, a biological system is evolvable:

For example, consider an enzyme with multiple alleles in the population. Each allele catalyzes the same reaction, but with a different level of activity. However, even after millions of years of evolution, exploring many sequences with similar function, no mutation might exist that gives this enzyme the ability to catalyze a different reaction. Thus, although the enzyme's activity is evolvable in the first sense, that does not mean that the enzyme's function is evolvable in the second sense. However, every system evolvable in the second sense must also be evolvable in the first.

Massimo Pigliucci [10] recognizes three classes of definition, depending on timescale. The first corresponds to Wagner's first, and represents the very short timescales that are described by quantitative genetics. [11] [12] He divides Wagner's second definition into two categories, one representing the intermediate timescales that can be studied using population genetics, and one representing exceedingly rare long-term innovations of form.

Pigliucci's second definition of evolvability includes Altenberg's [3] quantitative concept of evolvability, being not a single number, but the entire upper tail of the fitness distribution of the offspring produced by the population. This quantity was considered a "local" property of the instantaneous state of a population, and its integration over the population's evolutionary trajectory, and over many possible populations, would be necessary to give a more global measure of evolvability.

Generating more variation

More heritable phenotypic variation means more evolvability. While mutation is the ultimate source of heritable variation, its permutations and combinations also make a big difference. Sexual reproduction generates more variation (and thereby evolvability) relative to asexual reproduction (see evolution of sexual reproduction). Evolvability is further increased by generating more variation when an organism is stressed, [13] and thus likely to be less well adapted, but less variation when an organism is doing well. The amount of variation generated can be adjusted in many different ways, for example via the mutation rate, via the probability of sexual vs. asexual reproduction, via the probability of outcrossing vs. inbreeding, via dispersal, and via access to previously cryptic variants through the switching of an evolutionary capacitor. A large population size increases the influx of novel mutations in each generation. [14]

Enhancement of selection

Rather than creating more phenotypic variation, some mechanisms increase the intensity and effectiveness with which selection acts on existing phenotypic variation. [15] For example:

Robustness and evolvability

The relationship between robustness and evolvability depends on whether recombination can be ignored. [16] Recombination can generally be ignored in asexual populations and for traits affected by single genes.

Without recombination

Robustness in the face of mutation does not increase evolvability in the first sense. In organisms with a high level of robustness, mutations have smaller phenotypic effects than in organisms with a low level of robustness. Thus, robustness reduces the amount of heritable genetic variation on which selection can act. However, robustness may allow exploration of large regions of genotype space, increasing evolvability according to the second sense. [9] [16] Even without genetic diversity, some genotypes have higher evolvability than others, and selection for robustness can increase the "neighborhood richness" of phenotypes that can be accessed from the same starting genotype by mutation. For example, one reason many proteins are less robust to mutation is that they have marginal thermodynamic stability, and most mutations reduce this stability further. Proteins that are more thermostable can tolerate a wider range of mutations and are more evolvable. [17] For polygenic traits, neighborhood richness contributes more to evolvability than does genetic diversity or "spread" across genotype space. [18]

With recombination

Temporary robustness, or canalisation, may lead to the accumulation of significant quantities of cryptic genetic variation. In a new environment or genetic background, this variation may be revealed and sometimes be adaptive. [16] [19]

Factors affecting evolvability via robustness

Different genetic codes have the potential to change robustness and evolvability by changing the effect of single-base mutational changes. [20] [21]

Exploration ahead of time

When mutational robustness exists, many mutants will persist in a cryptic state. Mutations tend to fall into two categories, having either a very bad effect or very little effect: few mutations fall somewhere in between. [22] [23] Sometimes, these mutations will not be completely invisible, but still have rare effects, with very low penetrance. When this happens, natural selection weeds out the very bad mutations, while leaving the others relatively unaffected. [24] [25] While evolution has no "foresight" to know which environment will be encountered in the future, some mutations cause major disruption to a basic biological process, and will never be adaptive in any environment. Screening these out in advance leads to preadapted stocks of cryptic genetic variation.

Another way that phenotypes can be explored, prior to strong genetic commitment, is through learning. An organism that learns gets to "sample" several different phenotypes during its early development, and later sticks to whatever worked best. Later in evolution, the optimal phenotype can be genetically assimilated so it becomes the default behavior rather than a rare behavior. This is known as the Baldwin effect, and it can increase evolvability. [26] [27]

Learning biases phenotypes in a beneficial direction. But an exploratory flattening of the fitness landscape can also increase evolvability even when it has no direction, for example when the flattening is a result of random errors in molecular and/or developmental processes. This increase in evolvability can happen when evolution is faced with crossing a "valley" in an adaptive landscape. This means that two mutations exist that are deleterious by themselves, but beneficial in combination. These combinations can evolve more easily when the landscape is first flattened, and the discovered phenotype is then fixed by genetic assimilation. [28] [29] [30]

Modularity

If every mutation affected every trait, then a mutation that was an improvement for one trait would be a disadvantage for other traits. This means that almost no mutations would be beneficial overall. But if pleiotropy is restricted to within functional modules, then mutations affect only one trait at a time, and adaptation is much less constrained. In a modular gene network, for example, a gene that induces a limited set of other genes that control a specific trait under selection may evolve more readily than one that also induces other gene pathways controlling traits not under selection. [15] Individual genes also exhibit modularity. A mutation in one cis-regulatory element of a gene's promoter region may allow the expression of the gene to be altered only in specific tissues, developmental stages, or environmental conditions rather than changing gene activity in the entire organism simultaneously. [15]

Evolution of evolvability

While variation yielding high evolvability could be useful in the long term, in the short term most of that variation is likely to be a disadvantage. For example, naively it would seem that increasing the mutation rate via a mutator allele would increase evolvability. But as an extreme example, if the mutation rate is too high then all individuals will be dead or at least carry a heavy mutation load. Short-term selection for low variation most of the time is likely to be more powerful than long-term selection for evolvability, making it difficult for natural selection to cause the evolution of evolvability. Other forces of selection also affect the generation of variation; for example, mutation and recombination may in part be byproducts of mechanisms to cope with DNA damage. [31]

When recombination is low, mutator alleles may still sometimes hitchhike on the success of adaptive mutations that they cause. In this case, selection can take place at the level of the lineage. [32] This may explain why mutators are often seen during experimental evolution of microbes. Mutator alleles can also evolve more easily when they only increase mutation rates in nearby DNA sequences, not across the whole genome: this is known as a contingency locus.

The evolution of evolvability is less controversial if it occurs via the evolution of sexual reproduction, or via the tendency of variation-generating mechanisms to become more active when an organism is stressed. The yeast prion [PSI+] may also be an example of the evolution of evolvability through evolutionary capacitance. [33] [34] An evolutionary capacitor is a switch that turns genetic variation on and off. This is very much like bet-hedging the risk that a future environment will be similar or different. [35] Theoretical models also predict the evolution of evolvability via modularity. [36] When the costs of evolvability are sufficiently short-lived, more evolvable lineages may be the most successful in the long-term. [37] However, the hypothesis that evolvability is an adaptation is often rejected in favor of alternative hypotheses, e.g. minimization of costs. [10]

Applications

Evolvability phenomena have practical applications. For protein engineering we wish to increase evolvability, and in medicine and agriculture we wish to decrease it. Protein evolvability is defined as the ability of the protein to acquire sequence diversity and conformational flexibility which can enable it to evolve toward a new function. [38]

In protein engineering, both rational design and directed evolution approaches aim to create changes rapidly through mutations with large effects. [39] [40] Such mutations, however, commonly destroy enzyme function or at least reduce tolerance to further mutations. [41] [42] Identifying evolvable proteins and manipulating their evolvability is becoming increasingly necessary in order to achieve ever larger functional modification of enzymes. [43] Proteins are also often studied as part of the basic science of evolvability, because the biophysical properties and chemical functions can be easily changed by a few mutations. [44] [45] More evolvable proteins can tolerate a broader range of amino acid changes and allow them to evolve toward new functions. The study of evolvability has fundamental importance for understanding very long term evolution of protein superfamilies. [46] [47] [48] [49] [50]

Many human diseases are capable of evolution. Viruses, bacteria, fungi and cancers evolve to be resistant to host immune defences, as well as pharmaceutical drugs. [51] [52] [53] These same problems occur in agriculture with pesticide [54] and herbicide [55] resistance. It is possible that we are facing the end of the effective life of most of available antibiotics. [56] Predicting the evolution and evolvability [57] of our pathogens, and devising strategies to slow or circumvent the development of resistance, demands deeper knowledge of the complex forces driving evolution at the molecular level. [58]

A better understanding of evolvability is proposed to be part of an Extended Evolutionary Synthesis. [59] [60] [61]

See also

Related Research Articles

<span class="mw-page-title-main">Evolution</span> Change in the heritable characteristics of biological populations

Evolution is the change in the heritable characteristics of biological populations over successive generations. It occurs when evolutionary processes such as natural selection and genetic drift act on genetic variation, resulting in certain characteristics becoming more or less common within a population over successive generations. The process of evolution has given rise to biodiversity at every level of biological organisation.

<span class="mw-page-title-main">Heredity</span> Passing of traits to offspring from the species parents or ancestor

Heredity, also called inheritance or biological inheritance, is the passing on of traits from parents to their offspring; either through asexual reproduction or sexual reproduction, the offspring cells or organisms acquire the genetic information of their parents. Through heredity, variations between individuals can accumulate and cause species to evolve by natural selection. The study of heredity in biology is genetics.

Microevolution is the change in allele frequencies that occurs over time within a population. This change is due to four different processes: mutation, selection, gene flow and genetic drift. This change happens over a relatively short amount of time compared to the changes termed macroevolution.

<span class="mw-page-title-main">Phenotype</span> Composite of the organisms observable characteristics or traits

In genetics, the phenotype is the set of observable characteristics or traits of an organism. The term covers the organism's morphology, its developmental processes, its biochemical and physiological properties, its behavior, and the products of behavior. An organism's phenotype results from two basic factors: the expression of an organism's genetic code and the influence of environmental factors. Both factors may interact, further affecting the phenotype. When two or more clearly different phenotypes exist in the same population of a species, the species is called polymorphic. A well-documented example of polymorphism is Labrador Retriever coloring; while the coat color depends on many genes, it is clearly seen in the environment as yellow, black, and brown. Richard Dawkins in 1978 and then again in his 1982 book The Extended Phenotype suggested that one can regard bird nests and other built structures such as caddisfly larva cases and beaver dams as "extended phenotypes".

Molecular evolution is the process of change in the sequence composition of cellular molecules such as DNA, RNA, and proteins across generations. The field of molecular evolution uses principles of evolutionary biology and population genetics to explain patterns in these changes. Major topics in molecular evolution concern the rates and impacts of single nucleotide changes, neutral evolution vs. natural selection, origins of new genes, the genetic nature of complex traits, the genetic basis of speciation, the evolution of development, and ways that evolutionary forces influence genomic and phenotypic changes.

Population genetics is a subfield of genetics that deals with genetic differences within and among populations, and is a part of evolutionary biology. Studies in this branch of biology examine such phenomena as adaptation, speciation, and population structure.

Evolutionary capacitance is the storage and release of variation, just as electric capacitors store and release charge. Living systems are robust to mutations. This means that living systems accumulate genetic variation without the variation having a phenotypic effect. But when the system is disturbed, robustness breaks down, and the variation has phenotypic effects and is subject to the full force of natural selection. An evolutionary capacitor is a molecular switch mechanism that can "toggle" genetic variation between hidden and revealed states. If some subset of newly revealed variation is adaptive, it becomes fixed by genetic assimilation. After that, the rest of variation, most of which is presumably deleterious, can be switched off, leaving the population with a newly evolved advantageous trait, but no long-term handicap. For evolutionary capacitance to increase evolvability in this way, the switching rate should not be faster than the timescale of genetic assimilation.

<span class="mw-page-title-main">Canalisation (genetics)</span> Measure of the ability of a population to produce the same phenotype

Canalisation is a measure of the ability of a population to produce the same phenotype regardless of variability of its environment or genotype. It is a form of evolutionary robustness. The term was coined in 1942 by C. H. Waddington to capture the fact that "developmental reactions, as they occur in organisms submitted to natural selection...are adjusted so as to bring about one definite end-result regardless of minor variations in conditions during the course of the reaction". He used this word rather than robustness to consider that biological systems are not robust in quite the same way as, for example, engineered systems.

Neutral mutations are changes in DNA sequence that are neither beneficial nor detrimental to the ability of an organism to survive and reproduce. In population genetics, mutations in which natural selection does not affect the spread of the mutation in a species are termed neutral mutations. Neutral mutations that are inheritable and not linked to any genes under selection will be lost or will replace all other alleles of the gene. That loss or fixation of the gene proceeds based on random sampling known as genetic drift. A neutral mutation that is in linkage disequilibrium with other alleles that are under selection may proceed to loss or fixation via genetic hitchhiking and/or background selection.

Genetic assimilation is a process described by Conrad H. Waddington by which a phenotype originally produced in response to an environmental condition, such as exposure to a teratogen, later becomes genetically encoded via artificial selection or natural selection. Despite superficial appearances, this does not require the (Lamarckian) inheritance of acquired characters, although epigenetic inheritance could potentially influence the result. Waddington stated that genetic assimilation overcomes the barrier to selection imposed by what he called canalization of developmental pathways; he supposed that the organism's genetics evolved to ensure that development proceeded in a certain way regardless of normal environmental variations.

The nearly neutral theory of molecular evolution is a modification of the neutral theory of molecular evolution that accounts for the fact that not all mutations are either so deleterious such that they can be ignored, or else neutral. Slightly deleterious mutations are reliably purged only when their selection coefficient are greater than one divided by the effective population size. In larger populations, a higher proportion of mutations exceed this threshold for which genetic drift cannot overpower selection, leading to fewer fixation events and so slower molecular evolution.

The evolution of biological complexity is one important outcome of the process of evolution. Evolution has produced some remarkably complex organisms – although the actual level of complexity is very hard to define or measure accurately in biology, with properties such as gene content, the number of cell types or morphology all proposed as possible metrics.

<span class="mw-page-title-main">Robustness (evolution)</span> Persistence of a biological trait under uncertain conditions

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Recurrent evolution is the repeated evolution of a particular trait, character, or mutation. Most evolution is the result of drift, often interpreted as the random chance of some alleles being passed down to the next generation and others not. Recurrent evolution is said to occur when patterns emerge from this stochastic process when looking across multiple distinct populations. These patterns are of particular interest to evolutionary biologists, as they can demonstrate the underlying forces governing evolution.

A neutral network is a set of genes all related by point mutations that have equivalent function or fitness. Each node represents a gene sequence and each line represents the mutation connecting two sequences. Neutral networks can be thought of as high, flat plateaus in a fitness landscape. During neutral evolution, genes can randomly move through neutral networks and traverse regions of sequence space which may have consequences for robustness and evolvability.

The Extended Evolutionary Synthesis (EES) consists of a set of theoretical concepts argued to be more comprehensive than the earlier modern synthesis of evolutionary biology that took place between 1918 and 1942. The extended evolutionary synthesis was called for in the 1950s by C. H. Waddington, argued for on the basis of punctuated equilibrium by Stephen Jay Gould and Niles Eldredge in the 1980s, and was reconceptualized in 2007 by Massimo Pigliucci and Gerd B. Müller.

<span class="mw-page-title-main">Epistasis</span> Dependence of a gene mutations phenotype on mutations in other genes

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This glossary of genetics and evolutionary biology is a list of definitions of terms and concepts used in the study of genetics and evolutionary biology, as well as sub-disciplines and related fields, with an emphasis on classical genetics, quantitative genetics, population biology, phylogenetics, speciation, and systematics. Overlapping and related terms can be found in Glossary of cellular and molecular biology, Glossary of ecology, and Glossary of biology.

In evolutionary biology, developmental bias refers to the production against or towards certain ontogenetic trajectories which ultimately influence the direction and outcome of evolutionary change by affecting the rates, magnitudes, directions and limits of trait evolution. Historically, the term was synonymous with developmental constraint, however, the latter has been more recently interpreted as referring solely to the negative role of development in evolution.

Bias in the introduction of variation is a theory in the domain of evolutionary biology that asserts biases in the introduction of heritable variation are reflected in the outcome of evolution. It is relevant to topics in molecular evolution, evo-devo, and self-organization. In the context of this theory, "introduction" ("origination") is a technical term for events that shift an allele frequency upward from zero. Formal models demonstrate that when an evolutionary process depends on introduction events, mutational and developmental biases in the generation of variation may influence the course of evolution by a first come, first served effect, so that evolution reflects the arrival of the likelier, not just the survival of the fitter. Whereas mutational explanations for evolutionary patterns are typically assumed to imply or require neutral evolution, the theory of arrival biases distinctively predicts the possibility of mutation-biased adaptation. Direct evidence for the theory comes from laboratory studies showing that adaptive changes are systematically enriched for mutationally likely types of changes. Retrospective analyses of natural cases of adaptation also provide support for the theory. This theory is notable as an example of contemporary structuralist thinking, contrasting with a classical functionalist view in which the course of evolution is determined by natural selection.

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