Evolution of protein-coding genes in Drosophila

Several contributing factors have been implicated in evolutionary rate heterogeneity among proteins, but their evolutionary mechanisms remain poorly characterized. The recently sequenced 12 Drosophila genomes provide a unique opportunity to shed light on these unresolved issues. Here, we focus on the role of natural selection in shaping evolutionary rates. We use the Drosophila genomic data to distinguish between factors that increase the strength of purifying selection on proteins and factors that affect the amount of positive selection experienced by proteins. We confirm the importance of translational selection in shaping protein evolution in Drosophila and show that factors such as tissue bias in expression, gene essentiality, intron number, and recombination rate also contribute to evolutionary rate variation among proteins.     

Gene expression intensity shapes evolutionary rates of the proteins encoded by the vertebrate genome

Natural selection leaves its footprints on protein-coding sequences by modulating their silent and replacement evolutionary rates. In highly expressed genes in invertebrates, these footprints are seen in the higher codon usage bias and lower synonymous divergence. In mammals, the highly expressed genes have a shorter gene length in the genome and the breadth of expression is known to constrain the rate of protein evolution. Here we have examined how the rates of evolution of proteins encoded by the vertebrate genomes are modulated by the amount (intensity) of gene expression. To understand how natural selection operates on proteins that appear to have arisen in earlier and later phases of animal evolution, we have contrasted patterns of mouse proteins that have homologs in invertebrate and protist genomes (Precambrian genes) with those that do not have such detectable homologs (vertebrate-specific genes). We find that the intensity of gene expression relates inversely to the rate of protein sequence evolution on a genomic scale. The most highly expressed genes actually show the lowest total number of substitutions per polypeptide, consistent with cumulative effects of purifying selection on individual amino acid replacements. Precambrian genes exhibit a more pronounced difference in protein evolutionary rates (up to three times) between the genes with high and low expression levels as compared to the vertebrate-specific genes, which appears to be due to the narrower breadth of expression of the vertebrate-specific genes. These results provide insights into the differential relationship and effect of the increasing complexity of animal body form on evolutionary rates of proteins.     

Structural mapping of protein interactions reveals differences in evolutionary pressures correlated to mRNA level and protein abundance

Genome-wide studies in Saccharomyces cerevisiae concluded that the dominant determinant of protein evolutionary rates is expression level: highly expressed proteins generally evolve most slowly. To determine how this constraint affects the evolution of protein interactions, we directly measure evolutionary rates of protein interface, surface, and core residues by structurally mapping domain interactions to yeast genomes. We find that mRNA level and protein abundance, though correlated, report on pressures affecting regions of proteins differently. Pressures proportional to mRNA level slow evolutionary rates of all structural regions and reduce the variability in rate differences between interfaces and other surfaces. In contrast, the evolutionary rate variation within a domain is much less correlated to protein abundance. Distinct pressures may be associated primarily with the cost (mRNA level) and functional (protein abundance) benefit of protein production. Interfaces of proteins with low mRNA levels may have higher evolutionary flexibility and could constitute the raw material for new functions.     

Decoupling of rapid and adaptive evolution among seminal fluid proteins in heliconius butterflies with divergent mating systems

Reproductive proteins often diverge rapidly between species. This pattern is frequently attributed to postmating sexual selection. Heliconius butterflies offer a good opportunity to examine this hypothesis by contrasting patterns of reproductive protein evolution between clades with divergent mating systems. Pupal-mating Heliconius females typically mate only once, limiting opportunity for postmating sexual selection. In contrast, adult-mating females remate throughout life. Reproductive protein evolution is therefore predicted to be slower and show little evidence of positive selection in the pupal-mating clade. We examined this prediction by sequencing 18 seminal fluid protein genes from a dozen Heliconius species and a related outgroup. Two proteins exhibited dN/dS > 1, implicating positive selection in the rapid evolution of at least a few Heliconius seminal fluid proteins. However, contrary to predictions, the average evolutionary rate of seminal fluid proteins was greater among pupal-mating Heliconius. Based on these results, we suggest that positive selection and relaxed constraint can generate conflicting patterns of reproductive protein evolution between mating systems. As predicted, some loci may show elevated evolutionary rates in promiscuous taxa relative to monandrous taxa resulting from adaptations to postmating sexual selection. However, when monandry is derived (as in Heliconius), the opposite pattern may result from relaxed selective constraints.     

Sexual selection halts the relaxation of protamine 2 among rodents

Sexual selection has been proposed as the driving force promoting the rapid evolutionary changes observed in some reproductive genes including protamines. We test this hypothesis in a group of rodents which show marked differences in the intensity of sexual selection. Levels of sperm competition were not associated with the evolutionary rates of protamine 1 but, contrary to expectations, were negatively related to the evolutionary rate of cleaved- and mature-protamine 2. Since both domains were found to be under relaxation, our findings reveal an unforeseen role of sexual selection: to halt the degree of degeneration that proteins within families may experience due to functional redundancy. The degree of relaxation of protamine 2 in this group of rodents is such that in some species it has become dysfunctional and it is not expressed in mature spermatozoa. In contrast, protamine 1 is functionally conserved but shows directed positive selection on specific sites which are functionally relevant such as DNA-anchoring domains and phosphorylation sites. We conclude that in rodents protamine 2 is under relaxation and that sexual selection removes deleterious mutations among species with high levels of sperm competition to maintain the protein functional and the spermatozoa competitive.     

Understanding hierarchical protein evolution from first principles.

We propose a model that explains the hierarchical organization of proteins in fold families. The model, which is based on the evolutionary selection of proteins by their native state stability, reproduces patterns of amino acids conserved across protein families. Due to its dynamic nature, the model sheds light on the evolutionary time-scales. By studying the relaxation of the correlation function between consecutive mutations at a given position in proteins, we observe separation of the evolutionary time-scales: at short time intervals families of proteins with similar sequences and structures are formed, while at long time intervals the families of structurally similar proteins that have low sequence similarity are formed. We discuss the evolutionary implications of our model. We provide a "profile" solution to our model and find agreement between predicted patterns of conserved amino acids and those actually observed in nature.     

Modularity in the evolution of yeast protein interaction network

Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction networks became to exhibit modularity in their evolution? Here, we propose a hypothesis of modularity in the evolution of yeast protein interaction network based on molecular evolutionary evidence. We assigned yeast proteins into six evolutionary ages by constructing a phylogenetic profile. We found that all the almost half of hub proteins are evolutionarily new. Examining the evolutionary processes of protein complexes, functional modules and topological modules, we also found that member proteins of these modules tend to appear in one or two evolutionary ages. Moreover, proteins in protein complexes and topological modules show significantly low evolutionary rates than those not in these modules. Our results suggest a hypothesis of modularity in the evolution of yeast protein interaction network as systems evolution.     

Thermodynamics and kinetics of protein folding: an evolutionary perspective

This article appeals to an evolutionary model which postulates that primordial proteins were described by small polypeptide chains which (i) lack disulfide bridges, and (ii) display slow folding rates with multi-state kinetics, to determine relations between structural properties of proteins and their folding kinetics. We parameterize the energy landscape of proteins in terms of thermodynamic activation variables. The model studies evolutionary changes in these thermodynamic parameters, and we invoke relations between these activation variables and structural properties of the protein to predict the following correspondence between protein structure and folding kinetics. 1. Proteins with inter- and intra-chain disulfide bridges: large variability in both folding rates and stability of intermediates, multi-state kinetics. 2. Proteins which lack inter and intra-chain disulfide bridges. 2.1 Single-domain chains: fast folding rates; unstable intermediates; two-state kinetics. 2.2 Multi-domain monomers: intermediate rates; metastable intermediates; multi-state kinetics. 2.3 Multi-domain oligomers: slow rates; metastable intermediates; multi-state kinetics. The evolutionary model thus provides a kinetic characterization of one important subfamily of proteins which we describe by the following properties: Folding dynamics of single-domain proteins which lack disulfide bridges are described by two-state kinetics. Folding rate of this class of proteins is positively correlated with the thermodynamic stability of the folded state.     

Expression Differentiation Is Constrained to Low-Expression Proteins over Ecological Timescales

Protein expression level is one of the strongest predictors of protein sequence evolutionary rate, with high-expression protein sequences evolving at slower rates than low-expression protein sequences largely because of constraints on protein folding and function. Expression evolutionary rates also have been shown to be negatively correlated with expression level across human and mouse orthologs over relatively long divergence times (i.e., ∼100 million years). Long-term evolutionary patterns, however, often cannot be extrapolated to microevolutionary processes (and vice versa), and whether this relationship holds for traits evolving under directional selection within a single species over ecological timescales (i.e., <5000 years) is unknown and not necessarily expected. Expression is a metabolically costly process, and the expression level of a particular protein is predicted to be a tradeoff between the benefit of its function and the costs of its expression. Selection should drive the expression level of all proteins close to values that maximize fitness, particularly for high-expression proteins because of the increased energetic cost of production. Therefore, stabilizing selection may reduce the amount of standing expression variation for high-expression proteins, and in combination with physiological constraints that may place an upper bound on the range of beneficial expression variation, these constraints could severely limit the availability of beneficial expression variants. To determine whether rapid-expression evolution was restricted to low-expression proteins owing to these constraints on highly expressed proteins over ecological timescales, we compared venom protein expression levels across mainland and island populations for three species of pit vipers. We detected significant differentiation in protein expression levels in two of the three species and found that rapid-expression differentiation was restricted to low-expression proteins. Our results suggest that various constraints on high-expression proteins reduce the availability of beneficial expression variants relative to low-expression proteins, enabling low-expression proteins to evolve and potentially lead to more rapid adaptation.     

Structure and age jointly influence rates of protein evolution

What factors determine a protein's rate of evolution are actively debated. Especially unclear is the relative role of intrinsic factors of present-day proteins versus historical factors such as protein age. Here we study the interplay of structural properties and evolutionary age, as determinants of protein evolutionary rate. We use a large set of one-to-one orthologs between human and mouse proteins, with mapped PDB structures. We report that previously observed structural correlations also hold within each age group - including relationships between solvent accessibility, designabililty, and evolutionary rates. However, age also plays a crucial role: age modulates the relationship between solvent accessibility and rate. Additionally, younger proteins, despite being less designable, tend to evolve faster than older proteins. We show that previously reported relationships between age and rate cannot be explained by structural biases among age groups. Finally, we introduce a knowledge-based potential function to study the stability of proteins through large-scale computation. We find that older proteins are more stable for their native structure, and more robust to mutations, than younger ones. Our results underscore that several determinants, both intrinsic and historical, can interact to determine rates of protein evolution.     

A thermodynamic model of protein structure evolution explains empirical amino acid substitution matrices

Proteins evolve under a myriad of biophysical selection pressures that collectively control the patterns of amino acid substitutions. These evolutionary pressures are sufficiently consistent over time and across protein families to produce substitution patterns, summarized in global amino acid substitution matrices such as BLOSUM, JTT, WAG, and LG, which can be used to successfully detect homologs, infer phylogenies, and reconstruct ancestral sequences. Although the factors that govern the variation of amino acid substitution rates have received much attention, the influence of thermodynamic stability constraints remains unresolved. Here we develop a simple model to calculate amino acid substitution matrices from evolutionary dynamics controlled by a fitness function that reports on the thermodynamic effects of amino acid mutations in protein structures. This hybrid biophysical and evolutionary model accounts for nucleotide transition/transversion rate bias, multi‐nucleotide codon changes, the number of codons per amino acid, and thermodynamic protein stability. We find that our theoretical model accurately recapitulates the complex yet universal pattern observed in common global amino acid substitution matrices used in phylogenetics. These results suggest that selection for thermodynamically stable proteins, coupled with nucleotide mutation bias filtered by the structure of the genetic code, is the primary driver behind the global amino acid substitution patterns observed in proteins throughout the tree of life.     

IMPACT: integrated multiprogram platform for analyses in ConTest

In this paper, we introduce a new Graphical User Interface that estimates evolutionary rates on protein sequences by assessing changes in biochemical constraints. We describe IMPACT, a platform-independent (tested in Linux, Windows, and MacOS), easy to install software written in Java. IMPACT integrates the use of a built-in multiple sequence alignment editor, with programs that perform phylogenetic and protein structure analyses (ConTest, PhyML, ATV, and Jmol) allowing the user to quickly and efficiently perform evolutionary analyses on protein sequences, including the detection of selection (negative and positive) signatures at the amino acid scale, which can provide fundamental insight about species evolution and ecological fitness. IMPACT provides the user with a working platform that combines a number of bioinformatics tools and utilities in one place, transferring information directly among the various programs and therefore increasing the overall performance of evolutionary analyses on proteins.     

Predicting Protein Function and Binding Profile via Matching of Local Evolutionary and Geometric Surface Patterns

Inferring protein functions from structures is a challenging task, as a large number of orphan protein structures from structural genomics project are now solved without their biochemical functions characterized. For proteins binding to similar substrates or ligands and carrying out similar functions, their binding surfaces are under similar physicochemical constraints, and hence the sets of allowed and forbidden residue substitutions are similar. However, it is difficult to isolate such selection pressure due to protein function from selection pressure due to protein folding, and evolutionary relationship reflected by global sequence and structure similarities between proteins is often unreliable for inferring protein function. We have developed a method, called pevoSOAR (pocket-based evolutionary search of amino acid residues), for predicting protein functions by solving the problem of uncovering amino acids residue substitution pattern due to protein function and separating it from amino acids substitution pattern due to protein folding. We incorporate evolutionary information specific to an individual binding region and match local surfaces on a large scale with millions of precomputed protein surfaces to identify those with similar functions. Our pevoSOAR method also generates a probablistic model called the computed binding a profile that characterizes protein-binding activities that may involve multiple substrates or ligands. We show that our method can be used to predict enzyme functions with accuracy. Our method can also assess enzyme binding specificity and promiscuity. In an objective large-scale test of 100 enzyme families with thousands of structures, our predictions are found to be sensitive and specific: At the stringent specificity level of 99.98%, we can correctly predict enzyme functions for 80.55% of the proteins. The overall area under the receiver operating characteristic curve measuring the performance of our prediction is 0.955, close to the perfect value of 1.00. The best Matthews coefficient is 86.6%. Our method also works well in predicting the biochemical functions of orphan proteins from structural genomics projects.     

Evidence of adaptive evolution of accessory gland proteins in closely related species of the Drosophila repleta group

Accessory gland proteins (Acps) are part of the seminal fluid of Drosophila species. These proteins have important reproductive functions, being responsible for the proper functioning of several steps of the fertilization process. Acps also contribute indirectly for the reproductive success of males by modulating female behavior. Evidence that Acps participate in sperm competition and sexual conflict includes findings that, on average, Acps have fast evolutionary rates, suggestive of adaptive evolution. This is especially true in species of the Drosophila repleta group. Nevertheless, only in a few occasions have robust statistical tests been used to determine whether observed evolutionary rates are in fact due to positive selection on amino acid substitutions between related species. Here we apply maximum likelihood tests for positive selection on 14 Acps of the D. repleta group. To increase statistical robustness, we use at least 8 sequences, all belonging to species of the Drosophila mulleri complex, for each gene analyzed. We found significant evidence of adaptive evolution for 10 of the tested genes. Among these, the ones with a conserved protein domain had positively selected sites within the functional region of the sequence. We also detected one instance of lineage-specific adaptive evolution in a clade formed by 2 sister species.     

Strategies for Selection from Protein Libraries Composed of de Novo Designed Secondary Structure Modules

As more and more protein structures are determined, it has become clear that there is only a limited number of protein folds in nature. To explore whether the protein folds found in nature are the only solutions to the protein folding problem, or that a lack of evolutionary pressure causes the paucity of different protein folds found, we set out to construct protein libraries without any restriction on topology. We generated different libraries (all alpha-helix, all beta-strand and alpha-helix plus beta-strand) with an average length of 100 amino acid residues, composed of designed secondary structure modules (alpha-helix, beta-strand and beta-turn) in various proportions, based primarily on the patterning of polar and non-polar residues. From the analysis of proteins chosen randomly from the libraries, we found that a substantial portion of pure alpha-helical proteins show properties similar to native proteins. Using these libraries as a starting point, we aim to establish a selection system which allows us to enrich proteins with favorable folding properties (non-aggregating, compactly folded) from the libraries. We have developed such a method based on ribosome display. This selection is based on two concepts: (1) misfolded proteins are more sensitive to proteolysis, (2) misfolded and/or aggregated proteins are more hydrophobic. We show that by applying each of these selection criteria proteins that are compactly folded and soluble can be enriched over insoluble and random coil proteins.     

Protein evolution with dependence among codons due to tertiary structure

Markovian models of protein evolution that relax the assumption of independent change among codons are considered. With this comparatively realistic framework, an evolutionary rate at a site can depend both on the state of the site and on the states of surrounding sites. By allowing a relatively general dependence structure among sites, models of evolution can reflect attributes of tertiary structure. To quantify the impact of protein structure on protein evolution, we analyze protein-coding DNA sequence pairs with an evolutionary model that incorporates effects of solvent accessibility and pairwise interactions among amino acid residues. By explicitly considering the relationship between nonsynonymous substitution rates and protein structure, this approach can lead to refined detection and characterization of positive selection. Analyses of simulated sequence pairs indicate that parameters in this evolutionary model can be well estimated. Analyses of lysozyme c and annexin V sequence pairs yield the biologically reasonable result that amino acid replacement rates are higher when the replacements lead to energetically favorable proteins than when they destabilize the proteins. Although the focus here is evolutionary dependence among codons that is associated with protein structure, the statistical approach is quite general and could be applied to diverse cases of evolutionary dependence where surrogates for sequence fitness can be measured or modeled.     

Levels of selection in positive-strand virus dynamics

Conflicting selection pressures occurring over the life cycle of an organism constitute serious challenges to the robustness of replication. Viruses present a credible model system for analysing problems that arise through evolutionary conflicts of interest. We present a multi-level selection model for the life cycle of positive-strand RNA viruses. The model combines within-cell replication kinetics and protein synthesis, and between-cell population dynamics of virion production and transmission. We show how these two levels of within-host selection interact to produce tradeoffs in the life history strategy of a virus without consideration of host mortality. We find that viruses evolve towards intermediate rather than maximum encapsidation rates. This can be interpreted as selection for intermediate virulence through cellular persistence. We characterize a theoretical persistence threshold arising from the trade-off between genome replication and genetic translation within the cell. We present counter-intuitive relationships whereby increasing genome decay rates and rates of encapsidation lead to increases in the abundance of virus-encoded proteins. Data from poliovirus suggest that viruses might be unable to resolve the vertical conflicts of interests among different levels of selection.     

Functional divergence outlines the evolution of novel protein function in NifH/BchL protein family

Biological nitrogen fixation is accomplished by prokaryotes through the catalytic action of complex metalloenzyme, nitrogenase. Nitrogenase is a two-protein component system comprising MoFe protein (NifD&K) and Fe protein (NifH). NifH shares structural and mechanistic similarities as well as evolutionary relationships with light-independent protochlorophyllide reductase (BchL), a photosynthesis-related metalloenzyme belonging to the same protein family. We performed a comprehensive bioinformatics analysis of the NifH/BchL family in order to elucidate the intrinsic functional diversity and the underlying evolutionary mechanism among the members. To analyse functional divergence in the NifH/BchL family, we have conducted pair-wise estimation in altered evolutionary rates between the member proteins. We identified a number of vital amino acid sites which contribute to predicted functional diversity. We have also made use of the maximum likelihood tests for detection of positive selection at the amino acid level followed by the structure-based phylogenetic approach to draw conclusion on the ancient lineage and novel characterization of the NifH/BchL protein family. Our investigation provides ample support to the fact that NifH protein and BchL share robust structural similarities and have probably deviated from a common ancestor followed by divergence in functional properties possibly due to gene duplication     

A role for selection in regulating the evolutionary emergence of disease-causing and other coding CAG repeats in humans and mice

The evolutionary expansion of CAG repeats in human triplet expansion disease genes is intriguing because of their deleterious phenotype. In the past, this expansion has been suggested to reflect a broad genomewide expansion of repeats, which would imply that mutational and evolutionary processes acting on repeats differ between species. Here, we tested this hypothesis by analyzing repeat- and flanking-sequence evolution in 28 repeat-containing genes that had been sequenced in humans and mice and by considering overall lengths and distributions of CAG repeats in the two species. We found no evidence that these repeats were longer in humans than in mice. We also found no evidence for preferential accumulation of CAG repeats in the human genome relative to mice from an analysis of the lengths of repeats identified in sequence databases. We then investigated whether sequence properties, such as base and amino acid composition and base substitution rates, showed any relationship to repeat evolution. We found that repeat-containing genes were enriched in certain amino acids, presumably as the result of selection, but that this did not reflect underlying biases in base composition. We also found that regions near repeats showed higher nonsynonymous substitution rates than the remainder of the gene and lower nonsynonymous rates in genes that contained a repeat in both the human and the mouse. Higher rates of nonsynonymous mutation in the neighborhood of repeats presumably reflect weaker purifying selection acting in these regions of the proteins, while the very low rate of nonsynonymous mutation in proteins containing a CAG repeat in both species presumably reflects a high level of purifying selection. Based on these observations, we propose that the mutational processes giving rise to polyglutamine repeats in human and murine proteins do not differ. Instead, we propose that the evolution of polyglutamine repeats in proteins results from an interplay between mutational processes and selection.