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Robustness (evolution)

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Inevolutionary biology,robustnessof abiological system(also called biological or genetic robustness[1]) is the persistence of a certain characteristic or trait in a system under perturbations or conditions of uncertainty.[2][3]Robustness in development is known ascanalization.[4][5]According to the kind of perturbation involved, robustness can be classified asmutational,environmental,recombinational,orbehavioralrobustnessetc.[6][7][8]Robustness is achieved through the combination of manygeneticandmolecular mechanismsand canevolveby either direct or indirectselection.Severalmodel systemshave been developed to experimentally study robustness and its evolutionary consequences.

A network ofgenotypeslinked by mutations. Each genotype is made up of 3genes:a, b & c. Each gene can be one of twoalleles.Lines link different phenotypes bymutation.Thephenotypeis indicated by colour. Genotypes abc, Abc, aBc and abC lie on aneutral networksince all have the same, dark phenotype. Genotype abc is robust since any single mutation retains the same phenotype. Other genotypes are less robust as mutations change the phenotype (e.g. ABc).

Classification[edit]

Mutational robustness[edit]

Mutational robustness (also called mutation tolerance) describes the extent to which an organism's phenotype remains constant in spite ofmutation.[9]Robustness can be empirically measured for severalgenomes[10][11]and individualgenes[12]by inducing mutations and measuring what proportion of mutants retain the samephenotype,function orfitness.More generally robustness corresponds to the neutral band in thedistribution of fitness effectsof mutation (i.e. the frequencies of different fitnesses of mutants). Proteins so far investigated have shown a tolerance to mutations of roughly 66% (i.e. two thirds of mutations are neutral).[13]

Conversely, measured mutational robustnesses of organisms vary widely. For example, >95% of point mutations inC. eleganshave no detectable effect[14]and even 90% of single gene knockouts inE. coliare non-lethal.[15]Viruses, however, only tolerate 20-40% of mutations and hence are much more sensitive to mutation.[10]

Robustness to stochasticity[edit]

Biological processes at the molecular scale are inherently stochastic.[16]They emerge from a combination of stochastic events that happen given the physico-chemical properties of molecules. For instance, gene expression is intrinsically noisy. This means that two cells in exactly identicalregulatory stateswill exhibit differentmRNAcontents.[17][18]The cell population level log-normal distribution of mRNA content[19]follows directly from the application of theCentral Limit Theoremto the multi-step nature ofgene expression regulation.[20]

Environmental robustness[edit]

In varyingenvironments,perfectadaptationto one condition may come at the expense of adaptation to another. Consequently, the total selection pressure on an organism is the average selection across all environments weighted by the percentage time spent in that environment. Variable environment can therefore select for environmental robustness where organisms can function across a wide range of conditions with little change inphenotypeorfitness (biology).Some organisms show adaptations to tolerate large changes in temperature, water availability, salinity or food availability. Plants, in particular, are unable to move when the environment changes and so show a range of mechanisms for achieving environmental robustness. Similarly, this can be seen in proteins as tolerance to a wide range ofsolvents,ion concentrationsortemperatures.

Genetic, molecular and cellular causes[edit]

Core eukaryoticmetabolic network.Circles indicatemetabolitesand lines indicate conversions byenzymes.Many metabolites can be produced via more than one route, therefore the organism is robust to the loss of some metabolic enzymes

Genomes mutate by environmental damage and imperfect replication, yet they display remarkable tolerance. This comes from robustness both at many different levels.

Organism mutational robustness[edit]

There are many mechanisms that provide genome robustness. For example,genetic redundancyreduces the effect of mutations in any one copy of a multi-copy gene.[21]Additionally thefluxthrough ametabolic pathwayis typically limited by only a few of the steps, meaning that changes in function of many of the enzymes have little effect on fitness.[22][23]Similarlymetabolic networkshave multiple alternate pathways to produce many keymetabolites.[24]

Protein mutational robustness[edit]

Protein mutation tolerance is the product of two main features: the structure of thegenetic codeandprotein structuralrobustness.[25][26]Proteins are resistant to mutations because many sequences can fold into highly similarstructural folds.[27]A protein adopts a limited ensemble of native conformations because those conformers have lower energy than unfolded and mis-folded states (ΔΔG of folding).[28][29]This is achieved by a distributed, internal network of cooperative interactions (hydrophobic,polarandcovalent).[30]Protein structural robustness results from few single mutations being sufficiently disruptive to compromise function. Proteins have also evolved to avoidaggregation[31]as partially folded proteins can combine to form large, repeating, insolubleprotein fibrilsand masses.[32]There is evidence that proteins show negative design features to reduce the exposure of aggregation-pronebeta-sheetmotifs in their structures.[33] Additionally, there is some evidence that thegenetic codeitself may be optimised such that most point mutations lead to similar amino acids (conservative).[34][35]Together these factors create adistribution of fitness effectsof mutations that contains a high proportion of neutral and nearly-neutral mutations.[12]

Gene expression robustness[edit]

Duringembryonic development,gene expression must be tightly controlled in time and space in order to give rise to fully functional organs. Developing organisms must therefore deal with the random perturbations resulting from gene expression stochasticity.[36]Inbilaterians,robustness of gene expression can be achieved viaenhancerredundancy. This happens when the expression of a gene under the control of several enhancers encoding the same regulatory logic (ie. displaying binding sites for the same set oftranscription factors). InDrosophila melanogastersuch redundant enhancers are often calledshadow enhancers.[37]

Furthermore, in developmental contexts were timing of gene expression in important for the phenotypic outcome, diverse mechanisms exist to ensure proper gene expression in a timely manner.[36]Poised promotersare transcriptionally inactivepromotersthat displayRNA polymerase IIbinding, ready for rapid induction.[38]In addition, because not all transcription factors can bind their target site in compactedheterochromatin,pioneer transcription factors(such asZldorFoxA) are required to open chromatin and allow the binding of other transcription factors that can rapidly induce gene expression. Open inactive enhancers are callpoised enhancers.[39]

Cell competitionis a phenomenon first described inDrosophila[40]where mosaicMinutemutant cells (affectingribosomal proteins) in a wild-type background would be eliminated. This phenomenon also happens in the early mouse embryo where cells expressing high levels ofMycactively kill their neighbors displaying low levels ofMycexpression. This results in homogeneously high levels ofMyc.[41][42]

Developmental patterning robustness[edit]

Patterning mechanisms such as those described by theFrench flag modelcan be perturbed at many levels (production and stochasticity of the diffusion of the morphogen, production of the receptor, stochastic of thesignaling cascade,etc). Patterning is therefore inherently noisy. Robustness against this noise and genetic perturbation is therefore necessary to ensure proper that cells measure accurately positional information. Studies of thezebrafishneural tubeand antero-posterior patternings has shown that noisy signaling leads to imperfect cell differentiation that is later corrected by transdifferentiation, migration or cell death of the misplaced cells.[43][44][45]

Additionally, the structure (or topology) ofsignaling pathwayshas been demonstrated to play an important role in robustness to genetic perturbations.[46]Self-enhanced degradation has long been an example of robustness inSystem biology.[47]Similarly, robustness of dorsoventral patterning in many species emerges from the balanced shuttling-degradation mechanisms involved inBMP signaling.[48][49][50]

Evolutionary consequences[edit]

Since organisms are constantly exposed to genetic and non-genetic perturbations, robustness is important to ensure the stability ofphenotypes.Also, under mutation-selection balance, mutational robustness can allowcryptic genetic variationto accumulate in a population. While phenotypically neutral in a stable environment, these genetic differences can be revealed as trait differences in an environment-dependent manner (seeevolutionary capacitance), thereby allowing for the expression of a greater number of heritable phenotypes in populations exposed to a variable environment.[51]

Being robust may even be a favoured at the expense of total fitness as anevolutionarily stable strategy(also called survival of the flattest).[52]A high but narrow peak of afitness landscapeconfers high fitness but low robustness as most mutations lead to massive loss of fitness. High mutation rates may favour population of lower, but broader fitness peaks. More critical biological systems may also have greater selection for robustness as reductions in function are more damaging tofitness.[53]Mutational robustness is thought to be one driver for theoreticalviral quasispeciesformation.

Each circle represents a functional gene variant and lines represent point mutations between them. Light grid-regions have lowfitness,dark regions have high fitness. (a) White circles have few neutral neighbours, black circles have many. Light grid-regions contain no circles because those sequences have low fitness. (b) Within a neutral network, the population is predicted to evolve towards the centre and away from 'fitness cliffs' (dark arrows).

Emergent mutational robustness[edit]

See also:Neutral network (evolution)

Natural selectioncan select directly or indirectly for robustness. Whenmutation ratesare high andpopulation sizesare large, populations are predicted to move to more densely connected regions ofneutral networkas less robust variants have fewer surviving mutant descendants.[54]The conditions under which selection could act to directly increase mutational robustness in this way are restrictive, and therefore such selection is thought to be limited to only a fewviruses[55]andmicrobes[56]having large population sizes and high mutation rates. Such emergent robustness has been observed in experimental evolution ofcytochrome P450s[57]andB-lactamase.[58]Conversely, mutational robustness may evolve as a byproduct of natural selection for robustness to environmental perturbations.[59][60][61][62][63]

Robustness and evolvability[edit]

See also:EvolvabilityandCanalisation (genetics)

Mutational robustness has been thought to have a negative impact onevolvabilitybecause it reduces the mutational accessibility of distinct heritable phenotypes for a single genotype and reduces selective differences within a genetically diverse population.[citation needed]Counter-intuitively however, it has been hypothesized that phenotypic robustness towards mutations may actually increase the pace of heritable phenotypic adaptation when viewed over longer periods of time.[64][65][66][67]

One hypothesis for how robustness promotes evolvability in asexual populations is that connected networks of fitness-neutral genotypes result in mutational robustness which, while reducing accessibility of new heritable phenotypes over short timescales, over longer time periods, neutral mutation andgenetic driftcause the population to spread out over a largerneutral networkin genotype space.[68]This genetic diversity gives the population mutational access to a greater number of distinct heritable phenotypes that can be reached from different points of the neutral network.[64][65][67][69][70][71][72]However, this mechanism may be limited to phenotypes dependent on a single genetic locus; for polygenic traits, genetic diversity in asexual populations does not significantly increase evolvability.[73]

In the case of proteins, robustness promotes evolvability in the form of an excess free energy offolding.[74]Since most mutations reduce stability, an excess folding free energy allows toleration of mutations that are beneficial to activity but would otherwise destabilise the protein.

In sexual populations, robustness leads to the accumulation of cryptic genetic variation with high evolutionary potential.[75][76]

Evolvability may be high when robustness is reversible, withevolutionary capacitanceallowing a switch between high robustness in most circumstances and low robustness at times of stress.[77]

Methods and model systems[edit]

There are many systems that have been used to study robustness.In silicomodels have been used to modelpromoters,[78][79]RNA secondary structure,protein lattice models,orgene networks.Experimental systems for individual genes include enzyme activity ofcytochrome P450,[57]B-lactamase,[58]RNA polymerase,[13]andLacI[13]have all been used. Whole organism robustness has been investigated inRNA virusfitness,[10]bacterialchemotaxis,Drosophilafitness,[15]segment polarity network, neurogenic network andbone morphogenetic proteingradient,C. elegansfitness[14]andvulvaldevelopment, and mammaliancircadian clock.[9]

See also[edit]

References[edit]

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