The relationship between the hierarchical position of proteins in the human signal transduction network and their rate of evolution

Richard Dickerson, Molecular Clocks, and Rates of Protein Evolution

Proteins approximately behave as molecular clocks, accumulating amino acid replacements at a more or less constant rate. Nonetheless, each protein displays a characteristic rate of evolution: whereas some proteins remain largely unaltered over large periods of time, others can rapidly accumulate amino acid replacements. An article by Richard Dickerson, published in the first issue of the Journal of Molecular Evolution (J Mol Evol 1:26-45, 1971), described the first analysis in which the rates of evolution of many proteins were compared, and the differences were interpreted in the light of their function. When comparing the sequences of fibrinopeptides, hemoglobin, and cytochrome c of different species, he observed a linear relationship between the number of amino acid replacements and divergence time. Remarkably, fibrinopeptides had evolved fast, cytochrome c had evolved slowly, and hemoglobin exhibited an intermediate rate of evolution. As the Journal of Molecular Evolution celebrates its 50th anniversary, I highlight this landmark article and reflect on its impact on the field of Molecular Evolution.

Balancing selection in Pattern Recognition Receptor signalling pathways is associated with gene function and pleiotropy in a wild rodent

Pathogen-mediated balancing selection is commonly considered to play an important role in the maintenance of genetic diversity, in particular in immune genes. However, the factors that may influence which immune genes are the targets of such selection are largely unknown. To address this, here we focus on Pattern Recognition Receptor (PRR) signalling pathways, which play a key role in innate immunity. We used whole-genome resequencing data from a population of bank voles (Myodes glareolus) to test for associations between balancing selection, pleiotropy and gene function in a set of 123 PRR signalling pathway genes. To investigate the effect of gene function, we compared genes encoding (a) receptors for microbial ligands versus downstream signalling proteins, and (b) receptors recognizing components of microbial cell walls, flagella and capsids versus receptors recognizing features of microbial nucleic acids. Analyses based on the nucleotide diversity of full coding sequences showed that balancing selection primarily targeted receptor genes with a low degree of pleiotropy. Moreover, genes encoding receptors recognizing components of microbial cell walls etc. were more important targets of balancing selection than receptors recognizing nucleic acids. Tests for localized signatures of balancing selection in coding and noncoding sequences showed that such signatures were mostly located in introns, and more evenly distributed among different functional categories of PRR pathway genes. The finding that signatures of balancing selection in full coding sequences primarily occur in receptor genes, in particular those encoding receptors for components of microbial cell walls etc., is consistent with the idea that coevolution between hosts and pathogens is an important cause of balancing selection on immune genes.

Metabolic Determinants of Enzyme Evolution in a Genome-Scale Bacterial Metabolic Network

Different genes and proteins evolve at very different rates. To identify the factors that explain these differences is an important aspect of research in molecular evolution. One such factor is the role a protein plays in a large molecular network. Here, we analyze the evolutionary rates of enzyme-coding genes in the genome-scale metabolic network of Escherichia coli to find the evolutionary constraints imposed by the structure and function of this complex metabolic system. Central and highly connected enzymes appear to evolve more slowly than less connected enzymes, but we find that they do so as a by-product of their high abundance, and not because of their position in the metabolic network. In contrast, enzymes catalyzing reactions with high metabolic flux-high substrate to product conversion rates-evolve slowly even after we account for their abundance. Moreover, enzymes catalyzing reactions that are difficult to by-pass through alternative pathways, such that they are essential in many different genetic backgrounds, also evolve more slowly. Our analyses show that an enzyme's role in the function of a metabolic network affects its evolution more than its place in the network's structure. They highlight the value of a system-level perspective for studies of molecular evolution.

Position Matters: Network Centrality Considerably Impacts Rates of Protein Evolution in the Human Protein-Protein Interaction Network

The proteins of any organism evolve at disparate rates. A long list of factors affecting rates of protein evolution have been identified. However, the relative importance of each factor in determining rates of protein evolution remains unresolved. The prevailing view is that evolutionary rates are dominantly determined by gene expression, and that other factors such as network centrality have only a marginal effect, if any. However, this view is largely based on analyses in yeasts, and accurately measuring the importance of the determinants of rates of protein evolution is complicated by the fact that the different factors are often correlated with each other, and by the relatively poor quality of available functional genomics data sets. Here, we use correlation, partial correlation and principal component regression analyses to measure the contributions of several factors to the variability of the rates of evolution of human proteins. For this purpose, we analyzed the entire human protein–protein interaction data set and the human signal transduction network—a network data set of exceptionally high quality, obtained by manual curation, which is expected to be virtually free from false positives. In contrast with the prevailing view, we observe that network centrality (measured as the number of physical and nonphysical interactions, betweenness, and closeness) has a considerable impact on rates of protein evolution. Surprisingly, the impact of centrality on rates of protein evolution seems to be comparable, or even superior according to some analyses, to that of gene expression. Our observations seem to be independent of potentially confounding factors and from the limitations (biases and errors) of interactomic data sets.

Stronger selective constraint on downstream genes in the oxidative phosphorylation pathway of cetaceans

The oxidative phosphorylation (OXPHOS) pathway is an efficient way to produce energy via adenosine triphosphate (ATP), which is critical for sustaining an energy supply for cetaceans in a hypoxic environment. Several studies have shown that natural selection may shape the evolution of the genes involved in OXPHOS. However, how network architecture drives OXPHOS protein sequence evolution remains poorly explored. Here, we investigated the evolutionary patterns of genes in the OXPHOS pathway across six cetacean genomes within the framework of a functional network. Our results show a negative correlation between the strength of purifying selection and pathway position. This result indicates that downstream genes were subjected to stronger evolutionary constraints than upstream genes, which may be due to the dual function of ATP synthase in the OXPHOS pathway. Additionally, there was a positive correlation between codon usage bias and omega (ω = dN/dS) and a negative correlation with synonymous substitution rate (dS), indicating that the stronger selective constraint on genes (with less biased codon usage) along the OXPHOS pathway is attributable to an increase in the rate of synonymous substitution. Surprisingly, there was no significant correlation between protein-protein interactions and the evolutionary estimates, implying that highly connected enzymes may not always show greater evolutionary constraints. Compared with that observed for terrestrial mammals, we found that the signature of positive selection detected in five genes (ATP5J, LHPP, PPA1, UQCRC1 and UQCRQ) was cetacean-specific, reflecting the importance of OXPHOS for survival in hypoxic, aquatic environments.

Essentiality Is a Strong Determinant of Protein Rates of Evolution during Mutation Accumulation Experiments in Escherichia coli

The Neutral Theory of Molecular Evolution is considered the most powerful theory to understand the evolutionary behavior of proteins. One of the main predictions of this theory is that essential proteins should evolve slower than dispensable ones owing to increased selective constraints. Comparison of genomes of different species, however, has revealed only small differences between the rates of evolution of essential and nonessential proteins. In some analyses, these differences vanish once confounding factors are controlled for, whereas in other cases essentiality seems to have an independent, albeit small, effect. It has been argued that comparing relatively distant genomes may entail a number of limitations. For instance, many of the genes that are dispensable in controlled lab conditions may be essential in some of the conditions faced in nature. Moreover, essentiality can change during evolution, and rates of protein evolution are simultaneously shaped by a variety of factors, whose individual effects are difficult to isolate. Here, we conducted two parallel mutation accumulation experiments in Escherichia coli, during 5,500–5,750 generations, and compared the genomes at different points of the experiments. Our approach (a short-term experiment, under highly controlled conditions) enabled us to overcome many of the limitations of previous studies. We observed that essential proteins evolved substantially slower than nonessential ones during our experiments. Strikingly, rates of protein evolution were only moderately affected by expression level and protein length.

Selection on metabolic pathway function in the presence of mutation-selection-drift balance leads to rate-limiting steps that are not evolutionarily stable

Background

While commonly assumed in the biochemistry community that the control of metabolic pathways is thought to be critical to cellular function, it is unclear if metabolic pathways generally have evolutionarily stable rate limiting (flux controlling) steps.

Results

A set of evolutionary simulations using a kinetic model of a metabolic pathway was performed under different conditions to evaluate the evolutionary stability of rate limiting steps. Simulations used combinations of selection for steady state flux, selection against the cost of molecular biosynthesis, and selection against the accumulation of high concentrations of a deleterious intermediate. Two mutational regimes were used, one with mutations that on average were neutral to molecular phenotype and a second with a preponderance of activity-destroying mutations. The evolutionary stability of rate limiting steps was low in all simulations with non-neutral mutational processes. Clustering of parameter co-evolution showed divergent inter-molecular evolutionary patterns under different evolutionary regimes.

Conclusions

This study provides a null model for pathway evolution when compensatory processes dominate with potential applications to predicting pathway functional change. This result also suggests a possible mechanism in which studies in statistical genetics that aim to associate a genotype to a phenotype assuming independent action of variants may be mis-specified through a mis-characterization of the link between individual gene function and pathway function. A better understanding of the genotype-phenotype map has potential applications in differentiating between compensatory changes and directional selection on pathways as well as detecting SNPs and fixed differences that might have phenotypic effects.

Reviewers

This article was reviewed by Arne Elofsson, David Ardell, and Shamil Sunyaev.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-016-0133-6) contains supplementary material, which is available to authorized users.

Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks

Proteins within a molecular network are expected to be subject to different selective pressures depending on their relative hierarchical positions. However, it is not obvious what genes within a network should be more likely to evolve under positive selection. On one hand, only mutations at genes with a relatively high degree of control over adaptive phenotypes (such as those encoding highly connected proteins) are expected to be “seen” by natural selection. On the other hand, a high degree of pleiotropy at these genes is expected to hinder adaptation. Previous analyses of the human protein-protein interaction network have shown that genes under long-term, recurrent positive selection (as inferred from interspecific comparisons) tend to act at the periphery of the network. It is unknown, however, whether these trends apply to other organisms. Here, we show that long-term positive selection has preferentially targeted the periphery of the yeast interactome. Conversely, in flies, genes under positive selection encode significantly more connected and central proteins. These observations are not due to covariation of genes' adaptability and centrality with confounding factors. Therefore, the distribution of proteins encoded by genes under recurrent positive selection across protein-protein interaction networks varies from one species to another.

Flux Control in Glycolysis Varies Across the Tree of Life

Biochemical thought posits that rate-limiting steps (defined here as points of flux control) are strongly selected as points of pathway regulation and control and are thus expected to be evolutionarily conserved. Conversely, population genetic thought based upon the concepts of mutation-selection-drift balance at the pathway level might suggest variation in flux controlling steps over evolutionary time. Glycolysis, as one of the most conserved and best characterized pathways, was studied to evaluate its evolutionary conservation. The flux controlling step in glycolysis was found to vary over the tree of life. Further, phylogenetic analysis suggested at least 60 events of gene duplication and additional events of putative positive selection that might alter pathway kinetic properties. Together, these results suggest that even with presumed largely negative selection on pathway output on glycolysis, the co-evolutionary process under the hood is dynamic.

Expression Divergence Is Correlated with Sequence Evolution but Not Positive Selection in Conifers

The evolutionary and genomic determinants of sequence evolution in conifers are poorly understood, and previous studies have found only limited evidence for positive selection. Using RNAseq data, we compared gene expression profiles to patterns of divergence and polymorphism in 44 seedlings of lodgepole pine (Pinus contorta) and 39 seedlings of interior spruce (Picea glauca × engelmannii) to elucidate the evolutionary forces that shape their genomes and their plastic responses to abiotic stress. We found that rapidly diverging genes tend to have greater expression divergence, lower expression levels, reduced levels of synonymous site diversity, and longer proteins than slowly diverging genes. Similar patterns were identified for the untranslated regions, but with some exceptions. We found evidence that genes with low expression levels had a larger fraction of nearly neutral sites, suggesting a primary role for negative selection in determining the association between evolutionary rate and expression level. There was limited evidence for differences in the rate of positive selection among genes with divergent versus conserved expression profiles and some evidence supporting relaxed selection in genes diverging in expression between the species. Finally, we identified a small number of genes that showed evidence of site-specific positive selection using divergence data alone. However, estimates of the proportion of sites fixed by positive selection (α) were in the range of other plant species with large effective population sizes suggesting relatively high rates of adaptive divergence among conifers.

Evolutionary patterns of Toll-like receptor signaling pathway genes in the Suidae

BACKGROUND

The Toll-like receptor (TLR) signaling pathway constitutes an essential component of the innate immune system. Highly conserved proteins, indicative of their critical roles in host survival, characterize this pathway. Selective constraints could vary depending on the gene's position within the pathway as TLR signaling is a sequential process and that genes downstream of the TLRs may be more selectively constrained to ensure efficient immune responses given the important role of downstream genes in the signaling process. Thus, we investigated whether gene position influenced protein evolution in the TLR signaling pathway of the Suidae. The members of the Suidae examined included the European Sus scrofa (wild boar), Asian Sus scrofa (wild boar), Sus verrucosus, Sus celebensis, Sus scebifrons, Sus barbatus, Babyrousa babyrussa, Potamochoerus larvatus, Potamochoerus porcus and Phacochoerus africanus.

RESULTS

A total of 33 TLR signaling pathway genes in the Suidae were retrieved from resequencing data. The evolutionary parameter ω (dn/ds) had an overall mean of 0.1668 across genes, indicating high functional conservation within the TLR signaling pathway. A significant relationship was inferred for the network parameters gene position, number of protein-protein interactions, protein length and the evolutionary parameter dn (nonsynonymous substitutions) such that downstream genes had lower nonsynonymous substitution rates, more interactors and shorter protein length than upstream genes. Gene position was significantly correlated with the number of protein-protein interactions and protein length. Thus, the polarity in the selective constraint along the TLR signaling pathway was due to the number of molecules a protein interacted with and the protein's length.

CONCLUSION

Results indicate that the level of selective constraints on genes within the TLR signaling pathway of the Suidae is dependent on the gene's position and network parameters. In particular, downstream genes evolve more slowly as a result of being highly connected and having shorter protein lengths. These findings highlight the critical role of gene network parameters in gene evolution.

Recent positive selection has acted on genes encoding proteins with more interactions within the whole human interactome

Genes vary in their likelihood to undergo adaptive evolution. The genomic factors that determine adaptability, however, remain poorly understood. Genes function in the context of molecular networks, with some occupying more important positions than others and thus being likely to be under stronger selective pressures. However, how positive selection distributes across the different parts of molecular networks is still not fully understood. Here, we inferred positive selection using comparative genomics and population genetics approaches through the comparison of 10 mammalian and 270 human genomes, respectively. In agreement with previous results, we found that genes with lower network centralities are more likely to evolve under positive selection (as inferred from divergence data). Surprisingly, polymorphism data yield results in the opposite direction than divergence data: Genes with higher centralities are more likely to have been targeted by recent positive selection during recent human evolution. Our results indicate that the relationship between centrality and the impact of adaptive evolution highly depends on the mode of positive selection and/or the evolutionary time-scale.

Patterns of variation during adaptation in functionally linked loci

An understanding of the distribution of natural patterns of genetic variation is relevant to such fundamental biological fields as evolution and development. One recent approach to understanding such patterns has been to focus on the constraints that may arise as a function of the network or pathway context in which genes are embedded. Despite theoretical expectations of higher evolutionary constraint for genes encoding upstream versus downstream enzymes in metabolic pathways, empirical results have varied. Here we combine two complementary models from population genetics and enzyme kinetics to explore genetic variation as a function of pathway position when selection acts on whole-pathway flux. We are able to qualitatively reproduce empirically observed patterns of polymorphism and divergence and suggest that expectations should vary depending on the evolutionary trajectory of a population. Upstream genes are initially more polymorphic and diverge faster after an environmental change, while we see the opposite trend as the population approaches its fitness optimum.

Molecular evolution constraints in the floral organ specification gene regulatory network module across 18 angiosperm genomes

The gene regulatory network of floral organ cell fate specification of Arabidopsis thaliana is a robust developmental regulatory module. Although such finding was proposed to explain the overall conservation of floral organ types and organization among angiosperms, it has not been confirmed that the network components are conserved at the molecular level among flowering plants. Using the genomic data that have accumulated, we address the conservation of the genes involved in this network and the forces that have shaped its evolution during the divergence of angiosperms. We recovered the network gene homologs for 18 species of flowering plants spanning nine families. We found that all the genes are highly conserved with no evidence of positive selection. We studied the sequence conservation features of the genes in the context of their known biological function and the strength of the purifying selection acting upon them in relation to their placement within the network. Our results suggest an association between protein length and sequence conservation, evolutionary rates, and functional category. On the other hand, we found no significant correlation between the strength of purifying selection and gene placement. Our results confirm that the studied robust developmental regulatory module has been subjected to strong functional constraints. However, unlike previous studies, our results do not support the notion that network topology plays a major role in constraining evolutionary rates. We speculate that the dynamical functional role of genes within the network and not just its connectivity could play an important role in constraining evolution.

Metabolic flux is a determinant of the evolutionary rates of enzyme-encoding genes

Relationships between evolutionary rates and gene properties on a genomic, functional, pathway, or system level are being explored to unravel the principles of the evolutionary process. In particular, functional network properties have been analyzed to recognize the constraints they may impose on the evolutionary fate of genes. Here we took as a case study the core metabolic network in human erythrocytes and we analyzed the relationship between the evolutionary rates of its genes and the metabolic flux distribution throughout it. We found that metabolic flux correlates with the ratio of nonsynonymous to synonymous substitution rates. Genes encoding enzymes that carry high fluxes have been more constrained in their evolution, while purifying selection is more relaxed in genes encoding enzymes carrying low metabolic fluxes. These results demonstrate the importance of considering the dynamical functioning of gene networks when assessing the action of selection on system-level properties.

Comment on "The Molecular Evolutionary Patterns of the Insulin/FOXO Signaling Pathway"

Letter to the Editor on Wang M, Wang Q, Wang Z, Zhang X, Pan Y. The molecular evolutionary patterns of the insulin/FOXO signaling pathway. Evol Bioinform. 2013;9:1–16. doi: 10.4137/EBO.S10539.

Evolutionary rate and duplicability in the Arabidopsis thaliana protein-protein interaction network

Genes show a bewildering variation in their patterns of molecular evolution, as a result of the action of different levels and types of selective forces. The factors underlying this variation are, however, still poorly understood. In the last decade, the position of proteins in the protein-protein interaction network has been put forward as a determinant factor of the evolutionary rate and duplicability of their encoding genes. This conclusion, however, has been based on the analysis of the limited number of microbes and animals for which interactome-level data are available (essentially, Escherichia coli, yeast, worm, fly, and humans). Here, we study, for the first time, the relationship between the position of proteins in the high-density interactome of a plant (Arabidopsis thaliana) and the patterns of molecular evolution of their encoding genes. We found that genes whose encoded products act at the center of the network are more evolutionarily constrained than those acting at the network periphery. This trend remains significant when potential confounding factors (gene expression level and breadth, duplicability, function, and length of the encoded products) are controlled for. Even though the correlation between centrality measures and rates of evolution is generally weak, for some functional categories, it is comparable in strength to (or even stronger than) the correlation between evolutionary rates and expression levels or breadths. In addition, genes encoding interacting proteins in the network evolve at relatively similar rates. Finally, Arabidopsis proteins encoded by duplicated genes are more highly connected than those encoded by singleton genes. This observation is in agreement with the patterns observed in humans, but in contrast with those observed in E. coli, yeast, worm, and fly (whose duplicated genes tend to act at the periphery of the network), implying that the relationship between duplicability and centrality inverted at least twice during eukaryote evolution. Taken together, these results indicate that the structure of the A. thaliana network constrains the evolution of its components at multiple levels.

Gene similarity networks provide tools for understanding eukaryote origins and evolution

The complexity and depth of the relationships between the three domains of life challenge the reliability of phylogenetic methods, encouraging the use of alternative analytical tools. We reconstructed a gene similarity network comprising the proteomes of 14 eukaryotes, 104 prokaryotes, 2,389 viruses and 1,044 plasmids. This network contains multiple signatures of the chimerical origin of Eukaryotes as a fusion of an archaebacterium and a eubacterium that could not have been observed using phylogenetic trees. A number of connected components (gene sets with stronger similarities than expected by chance) contain pairs of eukaryotic sequences exhibiting no direct detectable similarity. Instead, many eukaryotic sequences were indirectly connected through a "eukaryote-archaebacterium-eubacterium-eukaryote" similarity path. Furthermore, eukaryotic genes highly connected to prokaryotic genes from one domain tend not to be connected to genes from the other prokaryotic domain. Genes of archaebacterial and eubacterial ancestry tend to perform different functions and to act at different subcellular compartments, but in such an intertwined way that suggests an early rather than late integration of both gene repertoires. The archaebacterial repertoire has a similar size in all eukaryotic genomes whereas the number of eubacterium-derived genes is much more variable, suggesting a higher plasticity of this gene repertoire. Consequently, highly reduced eukaryotic genomes contain more genes of archaebacterial than eubacterial affinity. Connected components with prokaryotic and eukaryotic genes tend to include viral and plasmid genes, compatible with a role of gene mobility in the origin of Eukaryotes. Our analyses highlight the power of network approaches to study deep evolutionary events.

Three independent determinants of protein evolutionary rate

One of the most widely accepted ideas related to the evolutionary rates of proteins is that functionally important residues or regions evolve slower than other regions, a reasonable outcome of which should be a slower evolutionary rate of the proteins with a higher density of functionally important sites. Oddly, the role of functional importance, mainly measured by essentiality, in determining evolutionary rate has been challenged in recent studies. Several variables other than protein essentiality, such as expression level, gene compactness, protein-protein interactions, etc., have been suggested to affect protein evolutionary rate. In the present review, we try to refine the concept of functional importance of a gene, and consider three factors-functional importance, expression level, and gene compactness, as independent determinants of evolutionary rate of a protein, based not only on their known correlation with evolutionary rate but also on a reasonable mechanistic model. We suggest a framework based on these mechanistic models to correctly interpret the correlations between evolutionary rates and the various variables as well as the interrelationships among the variables.