Protein Sequence Evolution Research Articles

CASS: Protein sequence simulation with explicit genotype-phenotype mapping

CASS (coarse-grained artificial sequence simulator) is a software package for simulating protein sequences with an explicit genotype-to-phenotype mapping that takes protein structure and function into account. It is capable of reproducing many structure-specific properties of protein sequence evolution, most notably spatial and temporal variation in rates, and has been used to investigate several hypotheses about the influence of thermodynamics on molecular evolution. The software is implemented in object-oriented C++, is supported on Linux, and the source code is made freely available under the GPL v3 license at http://www.wyomingbioinformatics.org/Liberle sGroup/CASS/.

Evolution at Two Levels in Fire Ants: The Relationship between Patterns of Gene Expression and Protein Sequence Evolution

Variation in protein sequence and gene expression each contribute to phenotypic diversity, and may be subject to similar selective pressures. Eusocial insects are particularly useful for investigating the evolutionary link between protein sequence and condition-dependent patterns of gene expression because gene expression plays a central role in determining differences between eusocial insect sexes and castes. We investigated the relationship between protein coding sequence evolution and gene expression patterns in the fire ants Solenopsis invicta, S. richteri, and their hybrids to gain greater insight into how selection jointly operates on gene expression and coding sequence. We found that genes with high expression variability within castes and sexes were frequently differentially expressed between castes and sexes, as well as between species and hybrids. These results indicate that genes showing high variation in expression in one context also tend to show high variation in expression in other contexts. Our analyses further revealed that variation in both intra- and interspecific gene expression was positively associated with rate of protein sequence evolution in Solenopsis. This suggests that selective constraints on a gene operate both at the level of protein sequence and at the level of gene expression regulation. Overall, our study provides one of the strongest demonstrations that selective constraints mediate both protein sequence evolution and gene expression variability across different biological contexts and timescales.

Gene duplication and the evolution of hemoglobin isoform differentiation in birds.

The majority of bird species co-express two functionally distinct hemoglobin (Hb) isoforms in definitive erythrocytes as follows: HbA (the major adult Hb isoform, with α-chain subunits encoded by the α(A)-globin gene) and HbD (the minor adult Hb isoform, with α-chain subunits encoded by the α(D)-globin gene). The α(D)-globin gene originated via tandem duplication of an embryonic α-like globin gene in the stem lineage of tetrapod vertebrates, which suggests the possibility that functional differentiation between the HbA and HbD isoforms may be attributable to a retained ancestral character state in HbD that harkens back to a primordial, embryonic function. To investigate this possibility, we conducted a combined analysis of protein biochemistry and sequence evolution to characterize the structural and functional basis of Hb isoform differentiation in birds. Functional experiments involving purified HbA and HbD isoforms from 11 different bird species revealed that HbD is characterized by a consistently higher O(2) affinity in the presence of allosteric effectors such as organic phosphates and Cl(-) ions. In the case of both HbA and HbD, analyses of oxygenation properties under the two-state Monod-Wyman-Changeux allosteric model revealed that the pH dependence of Hb-O(2) affinity stems primarily from changes in the O(2) association constant of deoxy (T-state)-Hb. Ancestral sequence reconstructions revealed that the amino acid substitutions that distinguish the adult-expressed Hb isoforms are not attributable to the retention of an ancestral (pre-duplication) character state in the α(D)-globin gene that is shared with the embryonic α-like globin gene.

Highlight--Tracking Adaptation's Role: Do Larger Populations Evolve Faster?

Highlight--Tracking Adaptation's Role: Do Larger Populations Evolve Faster?

Mechanisms of Speciation

Mechanisms of Speciation

REvolver: Modeling Sequence Evolution under Domain Constraints

Simulating the change of protein sequences over time in a biologically realistic way is fundamental for a broad range of studies with a focus on evolution. It is, thus, problematic that typically simulators evolve individual sites of a sequence identically and independently. More realistic simulations are possible; however, they are often prohibited by limited knowledge concerning site-specific evolutionary constraints or functional dependencies between amino acids. As a consequence, a protein's functional and structural characteristics are rapidly lost in the course of simulated evolution. Here, we present REvolver (www.cibiv.at/software/revolver), a program that simulates protein sequence alteration such that evolutionarily stable sequence characteristics, like functional domains, are maintained. For this purpose, REvolver recruits profile hidden Markov models (pHMMs) for parameterizing site-specific models of sequence evolution in an automated fashion. pHMMs derived from alignments of homologous proteins or protein domains capture information regarding which sequence sites remained conserved over time and where in a sequence insertions or deletions are more likely to occur. Thus, they describe constraints on the evolutionary process acting on these sequences. To demonstrate the performance of REvolver as well as its applicability in large-scale simulation studies, we evolved the entire human proteome up to 1.5 expected substitutions per site. Simultaneously, we analyzed the preservation of Pfam and SMART domains in the simulated sequences over time. REvolver preserved 92% of the Pfam domains originally present in the human sequences. This value drops to 15% when traditional models of amino acid sequence evolution are used. Thus, REvolver represents a significant advance toward a realistic simulation of protein sequence evolution on a proteome-wide scale. Further, REvolver facilitates the simulation of a protein family with a user-defined domain architecture at the root.

Identification and functional characterization of a primate‐specific E2F1 binding motif regulating MCPH1 expression

MCPH1 (also named BRIT1) is one of the known genes responsible for autosomal recessive primary microcephaly (small head syndrome), suggesting its important role in brain development. The interaction of MCPH1 with transcriptional factors like E2F1 is required for the activation of cell cycle checkpoint, DNA repair and apoptosis. However, the molecular mechanism of MCPH1 regulation is currently unclear. Here, we cloned the human MCPH1 promoter and we identified a novel E2F1 binding motif located in the proximal promoter region of MCPH1. The experiments using electrophoretic mobility shift and promoter assays showed that E2F1 could stimulate MCPH1 transcription by direct binding to the E2F1 motif. Overexpression of E2F1 led to the upregulation of MCPH1 transcription, and knocking down the endogenous E2F1 resulted in the inhibition of the MCPH1 promoter activity. Surprisingly, sequence comparison of vertebrate species suggested that the identified E2F1 binding motif is primate specific, consistent with the previous observation of rapid evolution of MCPH1 protein sequence in primates. We propose that during primate evolution MCPH1 has acquired a novel E2F1 binding motif in its promoter which may act as a parallel mechanism, acting together with the rapid protein sequence changes in primates, and eventually contributed to brain enlargement during primate evolution and human origin. Database The MCPH1 promoter region was sequenced in human, chimpanzee and rhesus macaque. Nucleotide sequence data are available in the GenBank database (http://www.ncbi.nlm.nih.gov/genbank/) under accession numbers JN573214, JN573215 and JN573216.

Chaperones Divide Yeast Proteins into Classes of Expression Level and Evolutionary Rate

It has long been known that many proteins require folding via molecular chaperones for their function. Although it has become apparent that folding imposes constraints on protein sequence evolution, the effects exerted by different chaperone classes are so far unknown. We have analyzed data of protein interaction with the chaperones in Saccharomyces cerevisiae using network methods. The results reveal a distinct community structure within the network that was hitherto undetectable with standard statistical tools. Sixty-four yeast chaperones comprise ten distinct modules that are defined by interaction specificity for their 2,691 interacting proteins. The classes of interacting proteins that are in turn defined by their dedicated chaperone modules are distinguished by various physiochemical protein properties and are characterized by significantly different protein expression levels, codon usage, and amino acid substitution rates. Correlations between substitution rate, codon bias, and gene expression level that have long been known for yeast are apparent at the level of the chaperone-defined modules. This indicates that correlated expression, conservation, and codon bias levels for yeast genes are attributable to previously unrecognized effects of protein folding. Proteome-wide categories of chaperone–substrate specificity uncover novel hubs of functional constraint in protein evolution that are conserved across 20 fungal genomes.

Complex patterns of divergence among green-sensitive (RH2a) African cichlid opsins revealed by Clade model analyses

BackgroundGene duplications play an important role in the evolution of functional protein diversity. Some models of duplicate gene evolution predict complex forms of paralog divergence; orthologous proteins may diverge as well, further complicating patterns of divergence among and within gene families. Consequently, studying the link between protein sequence evolution and duplication requires the use of flexible substitution models that can accommodate multiple shifts in selection across a phylogeny. Here, we employed a variety of codon substitution models, primarily Clade models, to explore how selective constraint evolved following the duplication of a green-sensitive (RH2a) visual pigment protein (opsin) in African cichlids. Past studies have linked opsin divergence to ecological and sexual divergence within the African cichlid adaptive radiation. Furthermore, biochemical and regulatory differences between the RH2aα and RH2aβ paralogs have been documented. It thus seems likely that selection varies in complex ways throughout this gene family.ResultsClade model analysis of African cichlid RH2a opsins revealed a large increase in the nonsynonymous-to-synonymous substitution rate ratio (ω) following the duplication, as well as an even larger increase, one consistent with positive selection, for Lake Tanganyikan cichlid RH2aβ opsins. Analysis using the popular Branch-site models, by contrast, revealed no such alteration of constraint. Several amino acid sites known to influence spectral and non-spectral aspects of opsin biochemistry were found to be evolving divergently, suggesting that orthologous RH2a opsins may vary in terms of spectral sensitivity and response kinetics. Divergence appears to be occurring despite intronic gene conversion among the tandemly-arranged duplicates.ConclusionsOur findings indicate that variation in selective constraint is associated with both gene duplication and divergence among orthologs in African cichlid RH2a opsins. At least some of this variation may reflect an adaptive response to differences in light environment. Interestingly, these patterns only became apparent through the use of Clade models, not through the use of the more widely employed Branch-site models; we suggest that this difference stems from the increased flexibility associated with Clade models. Our results thus bear both on studies of cichlid visual system evolution and on studies of gene family evolution in general.

Duplication and diversification of the LEAFY HULL STERILE1 and Oryza sativa MADS5 SEPALLATA lineages in graminoid Poales

BackgroundGene duplication and the subsequent divergence in function of the resulting paralogs via subfunctionalization and/or neofunctionalization is hypothesized to have played a major role in the evolution of plant form. The LEAFY HULL STERILE1 (LHS1) SEPALLATA (SEP) genes have been linked with the origin and diversification of the grass spikelet, but it is uncertain 1) when the duplication event that produced the LHS1 clade and its paralogous lineage Oryza sativa MADS5 (OSM5) occurred, and 2) how changes in gene structure and/or expression might have contributed to subfunctionalization and/or neofunctionalization in the two lineages.MethodsPhylogenetic relationships among 84 SEP genes were estimated using Bayesian methods. RNA expression patterns were inferred using in situ hybridization. The patterns of protein sequence and RNA expression evolution were reconstructed using maximum parsimony (MP) and maximum likelihood (ML) methods, respectively.ResultsPhylogenetic analyses mapped the LHS1/OSM5 duplication event to the base of the grass family. MP character reconstructions estimated a change from cytosine to thymine in the first codon position of the first amino acid after the Zea mays MADS3 (ZMM3) domain converted a glutamine to a stop codon in the OSM5 ancestor following the LHS1/OSM5 duplication event. RNA expression analyses of OSM5 co-orthologs in Avena sativa, Chasmanthium latifolium, Hordeum vulgare, Pennisetum glaucum, and Sorghum bicolor followed by ML reconstructions of these data and previously published analyses estimated a complex pattern of gain and loss of LHS1 and OSM5 expression in different floral organs and different flowers within the spikelet or inflorescence.ConclusionsPrevious authors have reported that rice OSM5 and LHS1 proteins have different interaction partners indicating that the truncation of OSM5 following the LHS1/OSM5 duplication event has resulted in both partitioned and potentially novel gene functions. The complex pattern of OSM5 and LHS1 expression evolution is not consistent with a simple subfunctionalization model following the gene duplication event, but there is evidence of recent partitioning of OSM5 and LHS1 expression within different floral organs of A. sativa, C. latifolium, P. glaucum and S. bicolor, and between the upper and lower florets of the two-flowered maize spikelet.

Markovian and Non-Markovian Protein Sequence Evolution: Aggregated Markov Process Models

Over the years, there have been claims that evolution proceeds according to systematically different processes over different timescales and that protein evolution behaves in a non-Markovian manner. On the other hand, Markov models are fundamental to many applications in evolutionary studies. Apparent non-Markovian or time-dependent behavior has been attributed to influence of the genetic code at short timescales and dominance of physicochemical properties of the amino acids at long timescales. However, any long time period is simply the accumulation of many short time periods, and it remains unclear why evolution should appear to act systematically differently across the range of timescales studied. We show that the observed time-dependent behavior can be explained qualitatively by modeling protein sequence evolution as an aggregated Markov process (AMP): a time-homogeneous Markovian substitution model observed only at the level of the amino acids encoded by the protein-coding DNA sequence. The study of AMPs sheds new light on the relationship between amino acid-level and codon-level models of sequence evolution, and our results suggest that protein evolution should be modeled at the codon level rather than using amino acid substitution models.

Protein coalitions in a core mammalian biochemical network linked by rapidly evolving proteins

BackgroundCellular ATP levels are generated by glucose-stimulated mitochondrial metabolism and determine metabolic responses, such as glucose-stimulated insulin secretion (GSIS) from the β-cells of pancreatic islets. We describe an analysis of the evolutionary processes affecting the core enzymes involved in glucose-stimulated insulin secretion in mammals. The proteins involved in this system belong to ancient enzymatic pathways: glycolysis, the TCA cycle and oxidative phosphorylation.ResultsWe identify two sets of proteins, or protein coalitions, in this group of 77 enzymes with distinct evolutionary patterns. Members of the glycolysis, TCA cycle, metabolite transport, pyruvate and NADH shuttles have low rates of protein sequence evolution, as inferred from a human-mouse comparison, and relatively high rates of evolutionary gene duplication. Respiratory chain and glutathione pathway proteins evolve faster, exhibiting lower rates of gene duplication. A small number of proteins in the system evolve significantly faster than co-pathway members and may serve as rapidly evolving adapters, linking groups of co-evolving genes.ConclusionsOur results provide insights into the evolution of the involved proteins. We find evidence for two coalitions of proteins and the role of co-adaptation in protein evolution is identified and could be used in future research within a functional context.

Measuring the evolutionary rate of protein–protein interaction

Despite our extensive knowledge about the rate of protein sequence evolution for thousands of genes in hundreds of species, the corresponding rate of protein function evolution is virtually unknown, especially at the genomic scale. This lack of knowledge is primarily because of the huge diversity in protein function and the consequent difficulty in gauging and comparing rates of protein function evolution. Nevertheless, most proteins function through interacting with other proteins, and protein-protein interaction (PPI) can be tested by standard assays. Thus, the rate of protein function evolution may be measured by the rate of PPI evolution. Here, we experimentally examine 87 potential interactions between Kluyveromyces waltii proteins, whose one to one orthologs in the related budding yeast Saccharomyces cerevisiae have been reported to interact. Combining our results with available data from other eukaryotes, we estimate that the evolutionary rate of protein interaction is (2.6 ± 1.6) × 10(-10) per PPI per year, which is three orders of magnitude lower than the rate of protein sequence evolution measured by the number of amino acid substitutions per protein per year. The extremely slow evolution of protein molecular function may account for the remarkable conservation of life at molecular and cellular levels and allow for studying the mechanistic basis of human disease in much simpler organisms.

Prestin and high frequency hearing in mammals

Recent evidence indicates that the evolution of ultrasonic hearing in echolocating bats and cetaceans has involved adaptive amino acid replacements in the cochlear gene prestin. A substantial number of these changes have occurred in parallel in both groups, suggesting that particular amino acid residues might confer greater auditory sensitivity to high frequencies. Here we review some of these findings, and consider whether similar signatures of prestin protein sequence evolution also occur in mammals that possess high frequency hearing for passive localization, and, conversely, whether this gene has undergone less change in mammals that lack high frequency hearing.

What's in a Likelihood? Simple Models of Protein Evolution and the Contribution of Structurally Viable Reconstructions to the Likelihood

Most phylogenetic models of protein evolution assume that sites are independent and identically distributed. Interactions between sites are ignored, and the likelihood can be conveniently calculated as the product of the individual site likelihoods. The calculation considers all possible transition paths (also called substitution histories or mappings) that are consistent with the observed states at the terminals, and the probability density of any particular reconstruction depends on the substitution model. The likelihood is the integral of the probability density of each substitution history taken over all possible histories that are consistent with the observed data. We investigated the extent to which transition paths that are incompatible with a protein's three-dimensional structure contribute to the likelihood. Several empirical amino acid models were tested for sequence pairs of different degrees of divergence. When simulating substitutional histories starting from a real sequence, the structural integrity of the simulated sequences quickly disintegrated. This result indicates that simple models are clearly unable to capture the constraints on sequence evolution. However, when we sampled transition paths between real sequences from the posterior probability distribution according to these same models, we found that the sampled histories were largely consistent with the tertiary structure. This suggests that simple empirical substitution models may be adequate for interpolating changes between observed sequences during phylogenetic inference despite the fact that the models cannot predict the effects of structural constraints from first principles. This study is significant because it provides a quantitative assessment of the biological realism of substitution models from the perspective of protein structure, and it provides insight on the prospects for improving models of protein sequence evolution.

Characterization of phylogenetic networks with NetTest

BackgroundTypical evolutionary events like recombination, hybridization or gene transfer make necessary the use of phylogenetic networks to properly depict the evolution of DNA and protein sequences. Although several theoretical classes have been proposed to characterize these networks, they make stringent assumptions that will likely not be met by the evolutionary process. We have recently shown that the complexity of simulated networks is a function of the population recombination rate, and that at moderate and large recombination rates the resulting networks cannot be categorized. However, we do not know whether these results extend to networks estimated from real data.ResultsWe introduce a web server for the categorization of explicit phylogenetic networks, including the most relevant theoretical classes developed so far. Using this tool, we analyzed statistical parsimony phylogenetic networks estimated from ~5,000 DNA alignments, obtained from the NCBI PopSet and Polymorphix databases. The level of characterization was correlated to nucleotide diversity, and a high proportion of the networks derived from these data sets could be formally characterized.ConclusionsWe have developed a public web server, NetTest (freely available from the software section at http://darwin.uvigo.es), to formally characterize the complexity of phylogenetic networks. Using NetTest we found that most statistical parsimony networks estimated with the program TCS could be assigned to a known network class. The level of network characterization was correlated to nucleotide diversity and dependent upon the intra/interspecific levels, although no significant differences were detected among genes. More research on the properties of phylogenetic networks is clearly needed.

Relative Contributions of Intrinsic Structural–Functional Constraints and Translation Rate to the Evolution of Protein-Coding Genes

A long-standing assumption in evolutionary biology is that the evolution rate of protein-coding genes depends, largely, on specific constraints that affect the function of the given protein. However, recent research in evolutionary systems biology revealed unexpected, significant correlations between evolution rate and characteristics of genes or proteins that are not directly related to specific protein functions, such as expression level and protein–protein interactions. The strongest connections were consistently detected between protein sequence evolution rate and the expression level of the respective gene. A recent genome-wide proteomic study revealed an extremely strong correlation between the abundances of orthologous proteins in distantly related animals, the nematode Caenorhabditis elegans and the fruit fly Drosophila melanogaster. We used the extensive protein abundance data from this study along with short-term evolutionary rates (ERs) of orthologous genes in nematodes and flies to estimate the relative contributions of structural–functional constraints and the translation rate to the evolution rate of protein-coding genes. Together the intrinsic constraints and translation rate account for approximately 50% of the variance of the ERs. The contribution of constraints is estimated to be 3- to 5-fold greater than the contribution of translation rate.

Impact of Extracellularity on the Evolutionary Rate of Mammalian Proteins

It is of fundamental importance to understand the determinants of the rate of protein evolution. Eukaryotic extracellular proteins are known to evolve faster than intracellular proteins. Although this rate difference appears to be due to the lower essentiality of extracellular proteins than intracellular proteins in yeast, we here show that, in mammals, the impact of extracellularity is independent from the impact of gene essentiality. Our partial correlation analysis indicated that the impact of extracellularity on mammalian protein evolutionary rate is also independent from those of tissue-specificity, expression level, gene compactness, and the number of protein–protein interactions and, surprisingly, is the strongest among all the factors we examined. Similar results were also found from principal component regression analysis. Our findings suggest that different rules govern the pace of protein sequence evolution in mammals and yeasts.

Impact of translational error‐induced and error‐free misfolding on the rate of protein evolution

What determines the rate of protein evolution is a fundamental question in biology. Recent genomic studies revealed a surprisingly strong anticorrelation between the expression level of a protein and its rate of sequence evolution. This observation is currently explained by the translational robustness hypothesis in which the toxicity of translational error-induced protein misfolding selects for higher translational robustness of more abundant proteins, which constrains sequence evolution. However, the impact of error-free protein misfolding has not been evaluated. We estimate that a non-negligible fraction of misfolded proteins are error free and demonstrate by a molecular-level evolutionary simulation that selection against protein misfolding results in a greater reduction of error-free misfolding than error-induced misfolding. Thus, an overarching protein-misfolding-avoidance hypothesis that includes both sources of misfolding is superior to the translational robustness hypothesis. We show that misfolding-minimizing amino acids are preferentially used in highly abundant yeast proteins and that these residues are evolutionarily more conserved than other residues of the same proteins. These findings provide unambiguous support to the role of protein-misfolding-avoidance in determining the rate of protein sequence evolution.

Evidence for an episodic model of protein sequence evolution

The evolution of protein function appears to involve alternating periods of conservative evolution and of relatively rapid change. Evidence for such episodic evolution, consistent with some theoretical expectations, comes from the application of increasingly sophisticated models of evolution to large sequence datasets. We present here some of the recent methods to detect functional shifts, using amino acid or codon models. Both provide evidence for punctual shifts in patterns of amino acid conservation, including the fixation of key changes by positive selection. Although a link to gene duplication, a presumed source of functional changes, has been difficult to establish, this episodic model appears to apply to a wide variety of proteins and organisms.