49 research outputs found
Evolution of Robustness to Noise and Mutation in Gene Expression Dynamics
Phenotype of biological systems needs to be robust against mutation in order
to sustain themselves between generations. On the other hand, phenotype of an
individual also needs to be robust against fluctuations of both internal and
external origins that are encountered during growth and development. Is there a
relationship between these two types of robustness, one during a single
generation and the other during evolution? Could stochasticity in gene
expression have any relevance to the evolution of these robustness? Robustness
can be defined by the sharpness of the distribution of phenotype; the variance
of phenotype distribution due to genetic variation gives a measure of `genetic
robustness' while that of isogenic individuals gives a measure of
`developmental robustness'. Through simulations of a simple stochastic gene
expression network that undergoes mutation and selection, we show that in order
for the network to acquire both types of robustness, the phenotypic variance
induced by mutations must be smaller than that observed in an isogenic
population. As the latter originates from noise in gene expression, this
signifies that the genetic robustness evolves only when the noise strength in
gene expression is larger than some threshold. In such a case, the two
variances decrease throughout the evolutionary time course, indicating increase
in robustness. The results reveal how noise that cells encounter during growth
and development shapes networks' robustness to stochasticity in gene
expression, which in turn shapes networks' robustness to mutation. The
condition for evolution of robustness as well as relationship between genetic
and developmental robustness is derived through the variance of phenotypic
fluctuations, which are measurable experimentally.Comment: 25 page
Degeneracy: a link between evolvability, robustness and complexity in biological systems
A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology.
This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability
Proportionality between variances in gene expression induced by noise and mutation: consequence of evolutionary robustness
<p>Abstract</p> <p>Background</p> <p>Characterization of robustness and plasticity of phenotypes is a basic issue in evolutionary and developmental biology. The robustness and plasticity are concerned with changeability of a biological system against external perturbations. The perturbations are either genetic, i.e., due to mutations in genes in the population, or epigenetic, i.e., due to noise during development or environmental variations. Thus, the variances of phenotypes due to genetic and epigenetic perturbations provide quantitative measures for such changeability during evolution and development, respectively.</p> <p>Results</p> <p>Using numerical models simulating the evolutionary changes in the gene regulation network required to achieve a particular expression pattern, we first confirmed that gene expression dynamics robust to mutation evolved in the presence of a sufficient level of transcriptional noise. Under such conditions, the two types of variances in the gene expression levels, i.e. those due to mutations to the gene regulation network and those due to noise in gene expression dynamics were found to be proportional over a number of genes. The fraction of such genes with a common proportionality coefficient increased with an increase in the robustness of the evolved network. This proportionality was generally confirmed, also under the presence of environmental fluctuations and sexual recombination in diploids, and was explained from an evolutionary robustness hypothesis, in which an evolved robust system suppresses the so-called error catastrophe - the destabilization of the single-peaked distribution in gene expression levels. Experimental evidences for the proportionality of the variances over genes are also discussed.</p> <p>Conclusions</p> <p>The proportionality between the genetic and epigenetic variances of phenotypes implies the correlation between the robustness (or plasticity) against genetic changes and against noise in development, and also suggests that phenotypic traits that are more variable epigenetically have a higher evolutionary potential.</p
An Analytically Solvable Model for Rapid Evolution of Modular Structure
Biological systems often display modularity, in the sense that they can be
decomposed into nearly independent subsystems. Recent studies have suggested
that modular structure can spontaneously emerge if goals (environments) change
over time, such that each new goal shares the same set of sub-problems with
previous goals. Such modularly varying goals can also dramatically speed up
evolution, relative to evolution under a constant goal. These studies were based
on simulations of model systems, such as logic circuits and RNA structure, which
are generally not easy to treat analytically. We present, here, a simple model
for evolution under modularly varying goals that can be solved analytically.
This model helps to understand some of the fundamental mechanisms that lead to
rapid emergence of modular structure under modularly varying goals. In
particular, the model suggests a mechanism for the dramatic speedup in evolution
observed under such temporally varying goals
Effects of Ploidy and Recombination on Evolution of Robustness in a Model of the Segment Polarity Network
Many genetic networks are astonishingly robust to quantitative variation,
allowing these networks to continue functioning in the face of mutation and
environmental perturbation. However, the evolution of such robustness remains
poorly understood for real genetic networks. Here we explore whether and how
ploidy and recombination affect the evolution of robustness in a detailed
computational model of the segment polarity network. We introduce a novel
computational method that predicts the quantitative values of biochemical
parameters from bit sequences representing genotype, allowing our model to
bridge genotype to phenotype. Using this, we simulate 2,000 generations of
evolution in a population of individuals under stabilizing and truncation
selection, selecting for individuals that could sharpen the initial pattern of
engrailed and wingless expression. Robustness was measured by simulating a
mutation in the network and measuring the effect on the engrailed and wingless
patterns; higher robustness corresponded to insensitivity of this pattern to
perturbation. We compared robustness in diploid and haploid populations, with
either asexual or sexual reproduction. In all cases, robustness increased, and
the greatest increase was in diploid sexual populations; diploidy and sex
synergized to evolve greater robustness than either acting alone. Diploidy
conferred increased robustness by allowing most deleterious mutations to be
rescued by a working allele. Sex (recombination) conferred a robustness
advantage through “survival of the compatible”: those
alleles that can work with a wide variety of genetically diverse partners
persist, and this selects for robust alleles
Facilitated Variation: How Evolution Learns from Past Environments To Generalize to New Environments
One of the striking features of evolution is the appearance of novel structures in organisms. Recently, Kirschner and Gerhart have integrated discoveries in evolution, genetics, and developmental biology to form a theory of facilitated variation (FV). The key observation is that organisms are designed such that random genetic changes are channeled in phenotypic directions that are potentially useful. An open question is how FV spontaneously emerges during evolution. Here, we address this by means of computer simulations of two well-studied model systems, logic circuits and RNA secondary structure. We find that evolution of FV is enhanced in environments that change from time to time in a systematic way: the varying environments are made of the same set of subgoals but in different combinations. We find that organisms that evolve under such varying goals not only remember their history but also generalize to future environments, exhibiting high adaptability to novel goals. Rapid adaptation is seen to goals composed of the same subgoals in novel combinations, and to goals where one of the subgoals was never seen in the history of the organism. The mechanisms for such enhanced generation of novelty (generalization) are analyzed, as is the way that organisms store information in their genomes about their past environments. Elements of facilitated variation theory, such as weak regulatory linkage, modularity, and reduced pleiotropy of mutations, evolve spontaneously under these conditions. Thus, environments that change in a systematic, modular fashion seem to promote facilitated variation and allow evolution to generalize to novel conditions
Control of Canalization and Evolvability by Hsp90
Partial reduction of Hsp90 increases expression of morphological novelty in qualitative traits of Drosophila and Arabidopsis, but the extent to which the Hsp90 chaperone also controls smaller and more likely adaptive changes in natural quantitative traits has been unclear. To determine the effect of Hsp90 on quantitative trait variability we deconstructed genetic, stochastic and environmental components of variation in Drosophila wing and bristle traits of genetically matched flies, differing only by Hsp90 loss-of-function or wild-type alleles. Unexpectedly, Hsp90 buffering was remarkably specific to certain normally invariant and highly discrete quantitative traits. Like the qualitative trait phenotypes controlled by Hsp90, highly discrete quantitative traits such as scutellor and thoracic bristle number are threshold traits. When tested across genotypes sampled from a wild population or in laboratory strains, the sensitivity of these traits to many types of variation was coordinately controlled, while continuously variable bristle types and wing size, and critically invariant left-right wing asymmetry, remained relatively unaffected. Although increased environmental variation and developmental noise would impede many types of selection response, in replicate populations in which Hsp90 was specifically impaired, heritability and ‘extrinsic evolvability’, the expected response to selection, were also markedly increased. However, despite the overall buffering effect of Hsp90 on variation in populations, for any particular individual or genotype in which Hsp90 was impaired, the size and direction of its effects were unpredictable. The trait and genetic-background dependence of Hsp90 effects and its remarkable bias toward invariant or canalized traits support the idea that traits evolve independent and trait-specific mechanisms of canalization and evolvability through their evolution of non-linearity and thresholds. Highly non-linear responses would buffer variation in Hsp90-dependent signaling over a wide range, while over a narrow range of signaling near trait thresholds become more variable with increasing probability of triggering all-or-none developmental responses
Cis-regulatory evolution spotlights species differences in the adaptive potential of gene expression plasticity
Plasticity allows organisms to respond to environmental change. Here the authors compare the distribution of cis-regulatory variants in the transcriptomes of Arabidopsis lyrata and A. halleriafter exposure to stress, to trace the role of polygenic selection in the evolution of gene expression plasticity