The pleiotropic structure of the genotype-phenotype map: the evolvability of complex organisms

It was first noticed 100 years ago that mutations tend to affect more than one phenotypic characteristic, a phenomenon that was called 'pleiotropy'. Because pleiotropy was found so frequently, the notion arose that pleiotropy is 'universal'. However, quantitative estimates of pleiotropy have not been available until recently. These estimates show that pleiotropy is highly restricted and are more in line with the notion of variational modularity than with universal pleiotropy. This finding has major implications for the evolvability of complex organisms and the mapping of disease-causing mutations.     

The effect of genetic robustness on evolvability in digital organisms

Background  

Recent work has revealed that many biological systems keep functioning in the face of mutations and therefore can be considered genetically robust. However, several issues related to robustness remain poorly understood, such as its implications for evolvability (the ability to produce adaptive evolutionary innovations).     

The effect of mutational robustness on the evolvability of multicellular organisms and eukaryotic cells

Canalization involves mutational robustness, the lack of phenotypic change as a result of genetic mutations. Given the large divergence in phenotype across species, understanding the relationship between high robustness and evolvability has been of interest to both theorists and experimentalists. Although canalization was originally proposed in the context of multicellular organisms, the effect of multicellularity and other classes of hierarchical organization on evolvability has not been considered by theoreticians. We address this issue using a Boolean population model with explicit representation of an environment in which individuals with explicit genotype and a hierarchical phenotype representing multicellularity evolve. Robustness is described by a single real number between zero and one which emerges from the genotype–phenotype map. We find that high robustness is favoured in constant environments, and lower robustness is favoured after environmental change. Multicellularity and hierarchical organization severely constrain robustness: peak evolvability occurs at an absolute level of robustness of about 0.99 compared with values of about 0.5 in a classical neutral network model. These constraints result in a sharp peak of evolvability in which the maximum is set by the fact that the fixation of adaptive mutations becomes more improbable as robustness decreases. When robustness is put under genetic control, robustness levels leading to maximum evolvability are selected for, but maximal relative fitness appears to require recombination.     

Altruism, sex, and inbreeding when the genotype-phenotype map is additive

Recently published theoretical results suggest that, in a sexual population, when genotypes code for phenotypes in a complex manner, it is possible for altruistic genotypes to spread through a metapopulation (i.e. through a collection of subpopulations). This spread tends to occur during periods when the environment deteriorates throughout the metapopulation. By contrast, under asexual reproduction, non-altruistic genotypes seem to be favoured, at least when subpopulations are substantial in size. The most relevant previous study makes use of Kauffman and Levin's "NK model" as a way to relate genotypes to fitness. Unfortunately, there are both conceptual and technical problems with the application of the NK model to populations that contain many different genotypes (e.g. polymorphic diploid populations with more than a few loci under selection). The present study presents a more tractable and biologically plausible model to study the causal relationship between sexual reproduction and altruism. In particular, phenotypes are determined by additive interactions among alleles at different loci in a diploid genome, with up to 200 loci under selection. In addition, subpopulations are substantially larger than those considered in the most relevant previous work. The results show that, so long as there are multiple "fitness peaks" in "phenotype space", the additive genotype-phenotype map leads to results that are similar to those from the NK model. Various parameters are manipulated in an effort to discover the determinants of altruistic and non-altruistic outcomes. The findings should facilitate further investigations, and they should help to establish the plausibility of the suggested relationship between sexual reproduction and altruism. The results also suggest that inbreeding can lead to a similar result as asexuality. That is, inbreeding seems to enhance the probability that altruistic phenotypes will be eliminated.     

A Bayesian framework for inference of the genotype-phenotype map for segregating populations

Complex genetic interactions lie at the foundation of many diseases. Understanding the nature of these interactions is critical to developing rational intervention strategies. In mammalian systems hypothesis testing in vivo is expensive, time consuming, and often restricted to a few physiological endpoints. Thus, computational methods that generate causal hypotheses can help to prioritize targets for experimental intervention. We propose a Bayesian statistical method to infer networks of causal relationships among genotypes and phenotypes using expression quantitative trait loci (eQTL) data from genetically randomized populations. Causal relationships between network variables are described with hierarchical regression models. Prior distributions on the network structure enforce graph sparsity and have the potential to encode prior biological knowledge about the network. An efficient Monte Carlo method is used to search across the model space and sample highly probable networks. The result is an ensemble of networks that provide a measure of confidence in the estimated network topology. These networks can be used to make predictions of system-wide response to perturbations. We applied our method to kidney gene expression data from an MRL/MpJ × SM/J intercross population and predicted a previously uncharacterized feedback loop in the local renin-angiotensin system.     

Coordination sphere and structure of the Mn cluster of the oxygen-evolving complex in photosynthetic organisms

The great similarity between the binding of Fe(II) and the high-affinity Mn-binding site in the Mn-depleted PSII membranes (Semin et al. (1996) FEBS Lett. 375, 223–226) suggests that the coordination sphere of Mn in PSII is also suitable for iron. A comparison is performed between the primary amino acid sequences of D1 and D2 and diiron-oxo enzymes with the function of oxygen activation. All conservative motifs (EXXH) and residues binding and stabilizing the diiron cluster in diiron-oxo enzymes have been found in the C-terminal domains of D1 and D2 polypeptides. On the basis of these sequence similarities we suggest a structural model for the manganese cluster in the oxygen-evolving complex.     

On the universality of nuclear pore complex structure

Summary Substructural details of the nuclear pore complex were studied in diverse plant and animal cells with both section technique and negative staining of isolated nuclear envelope pieces. The structures observed after the different techniques, including a variety of fixation procedures, are compared and their significance is discussed. It is shown that, down to the 15–20 Å level, the architecture of the nuclear pore complex is universal among such diverse cell types as from, e. g., onion root tips, bean leaves, mammalian liver parenchyma, HeLa cell cultures, and amphibian germ material. The fundamental substructures of the pore complex such as (1) the annular granules, (2) the fibrils attached to the annuli, (3) the central granules, (4) the fibrils in the pore interior including those which make up the inner ring and/or those which connect the central granule to the pore margin, are recognized in all cell types studied. The dynamic variability of the central granule morphology is emphasized and observations are presented which suggest that the view of such centrally located material as representing ribonucleoproteins in a transitory state of nucleocytoplasmic migration can be extended to generality. General concepts of the nuclear pore complex structure are presented as alternative model views revealing either a more compact, predominantly granular, or a more fibrillar aspect.The author gratefully acknowledges the frequent discussions and cooperation with his team-colleagues Drs. H. Falk (in the work on leaf material) and U. Scheer (in working with amphibian oocytes) as well as the skillful technical assistance of Miss Marianne Winter and Miss Sigrid Krien. The work was supported by the Deutsche Forschungsgemeinschaft.     

Selfish cellular networks and the evolution of complex organisms

Human gametogenesis takes years and involves many cellular divisions, particularly in males. Consequently, gametogenesis provides the opportunity to acquire multiple de novo mutations. A significant portion of these is likely to impact the cellular networks linking genes, proteins, RNA and metabolites, which constitute the functional units of cells. A wealth of literature shows that these individual cellular networks are complex, robust and evolvable. To some extent, they are able to monitor their own performance, and display sufficient autonomy to be termed "selfish". Their robustness is linked to quality control mechanisms which are embedded in and act upon the individual networks, thereby providing a basis for selection during gametogenesis. These selective processes are equally likely to affect cellular functions that are not gamete-specific, and the evolution of the most complex organisms, including man, is therefore likely to occur via two pathways: essential housekeeping functions would be regulated and evolve during gametogenesis within the parents before being transmitted to their progeny, while classical selection would operate on other traits of the organisms that shape their fitness with respect to the environment.     

Biological diversity and the community structure of organisms

Biological diversity and the complexity of the community structure of benthic animals in different bodies of water are evaluated using the Shannon index. The literature data on the communities in Lake Krasnoye (Karelian Isthmus, Leningrad Oblast), Shchuchy Bay of Lake Ladoga, Neva Bay, and the eastern part of the Gulf of Finland have been analyzed. The extrema (maxima and minima) and the inflection point of the curve of functions are determined with the help of derivatives. The rate of the secondary succession is evaluated for the first time by the example of benthic communities. It is shown that the community structure of bottom animals in the Shchuchy Bay ecosystem formed in the process of succession proves to be more complex than in Lake Krasnoye and the Neva Bay communities that have been formed for a long time. Communities of bottom animals are less complex in polluted waters of the top of the eastern part of the Gulf of Finland. It has taken 12 years to reach the maximum diversity of the bottom animal communities in Shchuchy Bay, 16 years in Lake Krasnoye, and 7–10 years in Neva Bay. It is supposed that, under favorable conditions in the waterbodies of a moderate climate and in the absence of heavy pollution or eutrophication, it takes 12–14 years on average to form the most complex community structure of bottom animals (3–4 bit/spec.). The structure of communities in polluted waters remains simple.     

On the inference of function from structure using biomechanical modelling and simulation of extinct organisms

Biomechanical modelling and simulation techniques offer some hope for unravelling the complex inter-relationships of structure and function perhaps even for extinct organisms, but have their limitations owing to this complexity and the many unknown parameters for fossil taxa. Validation and sensitivity analysis are two indispensable approaches for quantifying the accuracy and reliability of such models or simulations. But there are other subtleties in biomechanical modelling that include investigator judgements about the level of simplicity versus complexity in model design or how uncertainty and subjectivity are dealt with. Furthermore, investigator attitudes toward models encompass a broad spectrum between extreme credulity and nihilism, influencing how modelling is conducted and perceived. Fundamentally, more data and more testing of methodology are required for the field to mature and build confidence in its inferences.     

Speciation accelerated and stabilized by pleiotropic major histocompatibility complex immunogenes

Speciation and the maintenance of recently diverged species has been subject of intense research in evolutionary biology for decades. Although the concept of ecological speciation has been accepted, its mechanisms and genetic bases are still under investigation. Here, we present a mechanism for speciation that is orchestrated and strengthened by parasite communities acting on polymorphic genes of the immune system. In vertebrates, these genes have a pleiotropic role with regard to parasite resistance and mate choice. In contrasting niches, parasite communities differ and thus the pools of alleles of the adapted major histocompatibility complex (MHC) also differ between niches. Mate choice for the best-adapted MHC genotype will favour local adaptations and will accelerate separation of both populations: thus immune genes act as pleiotropic speciation genes –'magic traits'. This mechanism should operate not only in sympatric populations but also under allopatry or parapatry. Each individual has a small subset of the many MHC alleles present in the population. If all individuals could have all MHC alleles from the pool, MHC-based adaptation is neither necessary nor possible. However, the typically small optimal individual number of MHC loci thus enables MHC-based speciation. Furthermore, we propose a new mechanism selecting against species hybrids. Hybrids are expected to have super-optimal individual MHC diversity and should therefore suffer more from parasites in all habitats.     

On the origins of morphological variation, canalization, robustness, and evolvability

Canalization is a concept, introduced by Waddington that describesthe reduced sensitivity of a phenotype to genetic and environmentalperturbations. Some research in canalization assumes that lackof variation in a trait in one genotype with respect to anothergenotype in a population, is due to the existence of bufferingmechanisms against environmental and/or genetic variation. Thisarticle criticizes this assumption and out points out otherpossible problems with the concepts of canalization, robustness,and evolvability. These involve: the neglect of alternativeexplanations for the lack of variation in a trait, the incompatibilitywith current understanding of development, the way the mutivariatenature of morphological variation is considered. In addition,this article tries to explain that these concepts implicitlyassume, although not generally acknowledged, that without bufferingany genetic or environmental variation should give rise to adistinct phenotypic outcome. This can be avoided by restrictingthe use of canalization to cases in which, as in hsp90, thereis direct evidence of buffering. For the other cases it wouldbe clearer to talk about variational properties or simply typeof variation. The concept of evolvability is also biased towardsunivariate comparisons and is dependent on selective pressures.It is suggested that this can be replaced by "type of phenotypicvariation" from a genotype or variational properties. Overall,this article proposes that the concepts of canalization andevolvability involve some assumptions that, in most situations,unnecessarily complicate the study of evolution and development.     

Sexual selection and the evolution of evolvability

Here we show that sexual selection can have an effect on the rate of mutation. We simulated the fate of a genetic modifier of the mutation rate in a sexual population with and without sexual selection (modelled using a female choice mechanism). Female choice for 'good genes' should reduce variability among male subjects, leaving insufficient differences to maintain female preferences. However, female choice can actually increase genetic variability by supporting a higher mutation rate in sexually selected traits. Increasing the mutation rate will be selected against because of the resulting decline in mean fitness. However, it also increases the probability of rare beneficial mutations arising, and mating skew caused by female preferences for male subjects carrying those beneficials with few deleterious mutations ('good genes') can lead to a mutation rate above that expected under natural selection. A choice of two male subjects was sufficient for there to be a twofold increase in the mutation rate as opposed to a decrease found under random mating.     

Electroreception and magnetoreception in simple and complex organisms

A considerable body of evidence now indicates that electromagnetic and geomagnetic detection systems exist in both simple, unicellular organisms and in more complex species such as avians, bees, and marine animals. A major challenge that faces researchers in this field is the identification of physiological mechanisms through which the detection of weak fields provides significant somatosensory cues for direction finding, foraging, and predation. Many of the anatomical, physiological, and biophysical approaches that are being taken in studies of this nature are described in the series of review articles that appear in this issue of Bioelectromagnetics.     

On the structure of the iron-sulfur complex in the two-iron ferredoxins

Recent spectroscopic and magnetic susceptibility studies of the iron center in the two-iron ferredoxins provide criteria which any model for the iron-sulfur complex in these proteins must satisfy. These criteria are most stringent for parsley and spinach ferredoxin: the reduced proteins contain a high-spin ferric atom antiferromagnetically exchange-coupled (presumably via sulfide bridging ligands) to a high-spin ferrous atom. In the oxidized proteins the iron atoms are antiferromagnetically spin-coupled, high-spin ferric atoms. Arguments are given to substantiate the claim that the ferrous atom in the reduced protein is ligated by four sulfur atoms in a distorted tetrahedral configuration: two are the bridging sulfides, two are cysteinyl sulfurs. A treatment of proton contact shifts based upon the above model is pertinent to proton magnetic resonance data already available and provides a means to identify directly the ligands at both iron atoms via further PMR experiments.     

Chromosome organizaton in simple and complex unicellular organisms

The genomes of unicellular organisms form complex 3-dimensional structures. This spatial organization is hypothesized to have a significant role in genomic function. Spatial organization is not limited solely to the three-dimensional folding of the chromosome(s) in genomes but also includes genome positioning, and the folding and compartmentalization of any additional genetic material (e.g. episomes) present within complex genomes. In this comment, I will highlight similarities in the spatial organization of eukaryotic and prokaryotic unicellular genomes.     

The mutation matrix and the evolution of evolvability

Evolvability is a key characteristic of any evolving system, and the concept of evolvability serves as a unifying theme in a wide range of disciplines related to evolutionary theory. The field of quantitative genetics provides a framework for the exploration of evolvability with the promise to produce insights of global importance. With respect to the quantitative genetics of biological systems, the parameters most relevant to evolvability are the G-matrix, which describes the standing additive genetic variances and covariances for a suite of traits, and the M-matrix, which describes the effects of new mutations on genetic variances and covariances. A population's immediate response to selection is governed by the G-matrix. However, evolvability is also concerned with the ability of mutational processes to produce adaptive variants, and consequently the M-matrix is a crucial quantitative genetic parameter. Here, we explore the evolution of evolvability by using analytical theory and simulation-based models to examine the evolution of the mutational correlation, r(mu), the key parameter determining the nature of genetic constraints imposed by M. The model uses a diploid, sexually reproducing population of finite size experiencing stabilizing selection on a two-trait phenotype. We assume that the mutational correlation is a third quantitative trait determined by multiple additive loci. An individual's value of the mutational correlation trait determines the correlation between pleiotropic effects of new alleles when they arise in that individual. Our results show that the mutational correlation, despite the fact that it is not involved directly in the specification of an individual's fitness, does evolve in response to selection on the bivariate phenotype. The mutational variance exhibits a weak tendency to evolve to produce alignment of the M-matrix with the adaptive landscape, but is prone to erratic fluctuations as a consequence of genetic drift. The interpretation of this result is that the evolvability of the population is capable of a response to selection, and whether this response results in an increase or decrease in evolvability depends on the way in which the bivariate phenotypic optimum is expected to move. Interestingly, both analytical and simulation results show that the mutational correlation experiences disruptive selection, with local fitness maxima at -1 and +1. Genetic drift counteracts the tendency for the mutational correlation to persist at these extreme values, however. Our results also show that an evolving M-matrix tends to increase stability of the G-matrix under most circumstances. Previous studies of G-matrix stability, which assume nonevolving M-matrices, consequently may overestimate the level of instability of G relative to what might be expected in natural systems. Overall, our results indicate that evolvability can evolve in natural systems in a way that tends to result in alignment of the G-matrix, the M-matrix, and the adaptive landscape, and that such evolution tends to stabilize the G-matrix over evolutionary time.