Estimating the rate of irreversibility in protein evolution

Specialization restricts the evolutionary paths available to yeast sugar transporters

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence-function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an α-glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning approximately 400 million years of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast α-glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

Intragenic compensation through the lens of deep mutational scanning

A significant fraction of mutations in proteins are deleterious and result in adverse consequences for protein function, stability, or interaction with other molecules. Intragenic compensation is a specific case of positive epistasis when a neutral missense mutation cancels effect of a deleterious mutation in the same protein. Permissive compensatory mutations facilitate protein evolution, since without them all sequences would be extremely conserved. Understanding compensatory mechanisms is an important scientific challenge at the intersection of protein biophysics and evolution. In human genetics, intragenic compensatory interactions are important since they may result in variable penetrance of pathogenic mutations or fixation of pathogenic human alleles in orthologous proteins from related species. The latter phenomenon complicates computational and clinical inference of an allele's pathogenicity. Deep mutational scanning is a relatively new technique that enables experimental studies of functional effects of thousands of mutations in proteins. We review the important aspects of the field and discuss existing limitations of current datasets. We reviewed ten published DMS datasets with quantified functional effects of single and double mutations and described rates and patterns of intragenic compensation in eight of them.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-022-01005-w.

Phylogenetic inference of changes in amino acid propensities with single-position resolution

Fitness conferred by the same allele may differ between genotypes and environments, and these differences shape variation and evolution. Changes in amino acid propensities at protein sites over the course of evolution have been inferred from sequence alignments statistically, but the existing methods are data-intensive and aggregate multiple sites. Here, we develop an approach to detect individual amino acids that confer different fitness in different groups of species from combined sequence and phylogenetic data. Using the fact that the probability of a substitution to an amino acid depends on its fitness, our method looks for amino acids such that substitutions to them occur more frequently in one group of lineages than in another. We validate our method using simulated evolution of a protein site under different scenarios and show that it has high specificity for a wide range of assumptions regarding the underlying changes in selection, while its sensitivity differs between scenarios. We apply our method to the env gene of two HIV-1 subtypes, A and B, and to the HA gene of two influenza A subtypes, H1 and H3, and show that the inferred fitness changes are consistent with the fitness differences observed in deep mutational scanning experiments. We find that changes in relative fitness of different amino acid variants within a site do not always trigger episodes of positive selection and therefore may not result in an overall increase in the frequency of substitutions, but can still be detected from changes in relative frequencies of different substitutions.

Genomic Features and Evolution of the Parapoxvirus during the Past Two Decades

Parapoxvirus (PPV) has been identified in some mammals and poses a great threat to both the livestock production and public health. However, the prevalence and evolution of this virus are still not fully understood. Here, we performed an in silico analysis to investigate the genomic features and evolution of PPVs. We noticed that although there were significant differences of GC contents between orf virus (ORFV) and other three species of PPVs, all PPVs showed almost identical nucleotide bias, that is GC richness. The structural analysis of PPV genomes showed the divergence of different PPV species, which may be due to the specific adaptation to their natural hosts. Additionally, we estimated the phylogenetic diversity of seven different genes of PPV. According to all available sequences, our results suggested that during 2010-2018, ORFV was the dominant virus species under the selective pressure of the optimal gene patterns. Furthermore, we found the substitution rates ranged from 3.56 × 10-5 to 4.21 × 10-4 in different PPV segments, and the PPV VIR gene evolved at the highest substitution rate. In these seven protein-coding regions, purifying selection was the major evolutionary pressure, while the GIF and VIR genes suffered the greatest positive selection pressure. These results may provide useful knowledge on the virus genetic evolution from a new perspective which could help to create prevention and control strategies.

Senescence and entrenchment in evolution of amino acid sites

Amino acid propensities at a site change in the course of protein evolution. This may happen for two reasons. Changes may be triggered by substitutions at epistatically interacting sites elsewhere in the genome. Alternatively, they may arise due to environmental changes that are external to the genome. Here, we design a framework for distinguishing between these alternatives. Using analytical modelling and simulations, we show that they cause opposite dynamics of the fitness of the allele currently occupying the site: it tends to increase with the time since its origin due to epistasis ("entrenchment"), but to decrease due to random environmental fluctuations ("senescence"). By analysing the genomes of vertebrates and insects, we show that the amino acids originating at negatively selected sites experience strong entrenchment. By contrast, the amino acids originating at positively selected sites experience senescence. We propose that senescence of the current allele is a cause of adaptive evolution.

Enzyme Evolution: An Epistatic Ratchet versus a Smooth Reversible Transition

Evolutionary trajectories are deemed largely irreversible. In a newly diverged protein, reversion of mutations that led to the functional switch typically results in loss of both the new and the ancestral functions. Nonetheless, evolutionary transitions where reversions are viable have also been described. The structural and mechanistic causes of reversion compatibility versus incompatibility therefore remain unclear. We examined two laboratory evolution trajectories of mammalian paraoxonase-1, a lactonase with promiscuous organophosphate hydrolase (OPH) activity. Both trajectories began with the same active-site mutant, His115Trp, which lost the native lactonase activity and acquired higher OPH activity. A neo-functionalization trajectory amplified the promiscuous OPH activity, whereas the re-functionalization trajectory restored the native activity, thus generating a new lactonase that lacks His115. The His115 revertants of these trajectories indicated opposite trends. Revertants of the neo-functionalization trajectory lost both the evolved OPH and the original lactonase activity. Revertants of the trajectory that restored the original lactonase function were, however, fully active. Crystal structures and molecular simulations show that in the newly diverged OPH, the reverted His115 and other catalytic residues are displaced, thus causing loss of both the original and the new activity. In contrast, in the re-functionalization trajectory, reversion compatibility of the original lactonase activity derives from mechanistic versatility whereby multiple residues can fulfill the same task. This versatility enables unique sequence-reversible compositions that are inaccessible when the active site was repurposed toward a new function.

Disadvantages and benefits of evolved unicellularity versus multicellularity in budding yeast

Multicellular organisms appeared on Earth through several independent major evolutionary transitions. Are such transitions reversible? Addressing this fundamental question entails understanding the benefits and costs of multicellularity versus unicellularity. For example, some wild yeast strains form multicellular clumps, which might be beneficial in stressful conditions, but this has been untested. Here, we show that unicellular yeast evolve from clump-forming ancestors by propagating samples from suspension after larger clumps have settled. Unicellular yeast strains differed from their clumping ancestors mainly by mutations in the AMN1 (Antagonist of Mitotic exit Network) gene. Ancestral yeast clumps were more resistant to freeze/thaw, hydrogen peroxide, and ethanol stressors than their unicellular counterparts, but they grew slower without stress. These findings suggest disadvantages and benefits to multicellularity and unicellularity that may have impacted the emergence of multicellular life forms.

Compensatory mutations and epistasis for protein function

Adaptive protein evolution may be facilitated by neutral amino acid mutations that confer no benefit when they first arise but which potentiate subsequent function-altering mutations via direct or indirect structural mechanisms. Theoretical and empirical results indicate that such compensatory interactions (intramolecular epistasis) can exert a strong influence on trajectories of protein evolution. For this reason, assessing the form and prevalence of intramolecular epistasis and characterizing biophysical mechanisms of compensatory interaction are important research goals at the nexus of structural biology and molecular evolution. Here I review recent insights derived from protein-engineering studies, and I describe an approach for identifying and characterizing mechanisms of epistasis that integrates experimental data on structure-function relationships with analyses of comparative sequence data.

Pervasive contingency and entrenchment in a billion years of Hsp90 evolution

Interactions among mutations within a protein have the potential to make molecular evolution contingent and irreversible, but the extent to which epistasis actually shaped historical evolutionary trajectories is unclear. To address this question, we experimentally measured how the fitness effects of historical sequence substitutions changed during the billion-year evolutionary history of the heat shock protein 90 (Hsp90) ATPase domain beginning from a deep eukaryotic ancestor to modern Saccharomyces cerevisiae We found a pervasive influence of epistasis. Of 98 derived amino acid states that evolved along this lineage, about half compromise fitness when introduced into the reconstructed ancestral Hsp90. And the vast majority of ancestral states reduce fitness when introduced into the extant S. cerevisiae Hsp90. Overall, more than 75% of historical substitutions were contingent on permissive substitutions that rendered the derived state nondeleterious, became entrenched by subsequent restrictive substitutions that made the ancestral state deleterious, or both. This epistasis was primarily caused by specific interactions among sites rather than a general effect on the protein's tolerance to mutation. Our results show that epistasis continually opened and closed windows of mutational opportunity over evolutionary timescales, producing histories and biological states that reflect the transient internal constraints imposed by the protein's fleeting sequence states.

Substitutions into amino acids that are pathogenic in human mitochondrial proteins are more frequent in lineages closely related to human than in distant lineages

Propensities for different amino acids within a protein site change in the course of evolution, so that an amino acid deleterious in a particular species may be acceptable at the same site in a different species. Here, we study the amino acid-changing variants in human mitochondrial genes, and analyze their occurrence in non-human species. We show that substitutions giving rise to such variants tend to occur in lineages closely related to human more frequently than in more distantly related lineages, indicating that a human variant is more likely to be deleterious in more distant species. Unexpectedly, substitutions giving rise to amino acids that correspond to alleles pathogenic in humans also more frequently occur in more closely related lineages. Therefore, a pathogenic variant still tends to be more acceptable in human mitochondria than a variant that may only be fit after a substantial perturbation of the protein structure.

Genetic code asymmetry supports diversity through experimentation with posttranslational modifications

Protein N-glycosylation has been identified in all three domains of life presumably conserved for its early role in glycoprotein folding. However, the N-glycans added to proteins in the secretory pathway of multicellular organisms are remodeling in the Golgi, increasing structural diversity exponentially and adding new layers of functionality in immunity, metabolism and other systems. The branching and elongation of N-glycan chains found on cell surface receptors generates a gradation of affinities for carbohydrate-binding proteins, the galectin, selectin and siglec families. These interactions adapt cellular responsiveness to environmental conditions, but their complexity presents a daunting challenge to drug design. To gain further insight, I review how N-glycans biosynthesis and biophysical properties provide a selective advantage in the form of tunable and ultrasensitive stimulus-response relationships. In addition, the N-glycosylation motif favors step-wise mutational experimentation with sites. Glycoproteins display accelerated evolution during vertebrate radiation, and the encoding asymmetry of NXS/T(X≠P) has left behind phylogenetic evidence suggesting that the genetic code may have been selected to optimize diversity in part through emerging posttranslational modifications.

Resurrecting ancestral structural dynamics of an antiviral immune receptor: adaptive binding pocket reorganization repeatedly shifts RNA preference

Background

Although resurrecting ancestral proteins is a powerful tool for understanding the molecular-functional evolution of gene families, nearly all studies have examined proteins functioning in relatively stable biological processes. The extent to which more dynamic systems obey the same ‘rules’ governing stable processes is unclear. Here we present the first detailed investigation of the functional evolution of the RIG-like receptors (RLRs), a family of innate immune receptors that detect viral RNA in the cytoplasm.

Results

Using kinetic binding assays and molecular dynamics simulations of ancestral proteins, we demonstrate how a small number of adaptive protein-coding changes repeatedly shifted the RNA preference of RLRs throughout animal evolution by reorganizing the shape and electrostatic distribution across the RNA binding pocket, altering the hydrogen bond network between the RLR and its RNA target. In contrast to observations of proteins involved in metabolism and development, we find that RLR-RNA preference ‘flip flopped’ between two functional states, and shifts in RNA preference were not always coupled to gene duplications or speciation events. We demonstrate at least one reversion of RLR-RNA preference from a derived to an ancestral function through a novel structural mechanism, indicating multiple structural implementations of similar functions.

Conclusions

Our results suggest a model in which frequent shifts in selection pressures imposed by an evolutionary arms race preclude the long-term functional optimization observed in stable biological systems. As a result, the evolutionary dynamics of immune receptors may be less constrained by structural epistasis and historical contingency.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0818-6) contains supplementary material, which is available to authorized users.

Changing preferences: deformation of single position amino acid fitness landscapes and evolution of proteins

The fitness landscape-the function that relates genotypes to fitness-and its role in directing evolution are a central object of evolutionary biology. However, its huge dimensionality precludes understanding of even the basic aspects of its shape. One way to approach it is to ask a simpler question: what are the properties of a function that assigns fitness to each possible variant at just one particular site-a single position fitness landscape-and how does it change in the course of evolution? Analyses of genomic data from multiple species and multiple individuals within a species have proved beyond reasonable doubt that fitness functions of positions throughout the genome do themselves change with time, thus shaping protein evolution. Here, I will briefly review the literature that addresses these dynamics, focusing on recent genome-scale analyses of fitness functions of amino acid sites, i.e. vectors of fitnesses of 20 individual amino acid variants at a given position of a protein. The set of amino acids that confer high fitness at a particular position changes with time, and the rate of this change is comparable with the rate at which a position evolves, implying that this process plays a major role in evolutionary dynamics. However, the causes of these changes remain largely unclear.

Epistasis in protein evolution

The structure, function, and evolution of proteins depend on physical and genetic interactions among amino acids. Recent studies have used new strategies to explore the prevalence, biochemical mechanisms, and evolutionary implications of these interactions-called epistasis-within proteins. Here we describe an emerging picture of pervasive epistasis in which the physical and biological effects of mutations change over the course of evolution in a lineage-specific fashion. Epistasis can restrict the trajectories available to an evolving protein or open new paths to sequences and functions that would otherwise have been inaccessible. We describe two broad classes of epistatic interactions, which arise from different physical mechanisms and have different effects on evolutionary processes. Specific epistasis-in which one mutation influences the phenotypic effect of few other mutations-is caused by direct and indirect physical interactions between mutations, which nonadditively change the protein's physical properties, such as conformation, stability, or affinity for ligands. In contrast, nonspecific epistasis describes mutations that modify the effect of many others; these typically behave additively with respect to the physical properties of a protein but exhibit epistasis because of a nonlinear relationship between the physical properties and their biological effects, such as function or fitness. Both types of interaction are rampant, but specific epistasis has stronger effects on the rate and outcomes of evolution, because it imposes stricter constraints and modulates evolutionary potential more dramatically; it therefore makes evolution more contingent on low-probability historical events and leaves stronger marks on the sequences, structures, and functions of protein families.

Epistasis and the Dynamics of Reversion in Molecular Evolution

Recent studies of protein evolution contend that the longer an amino acid substitution is present at a site, the less likely it is to revert to the amino acid previously occupying that site. Here we study this phenomenon of decreasing reversion rates rigorously and in a much more general context. We show that, under weak mutation and for arbitrary fitness landscapes, reversion rates decrease with time for any site that is involved in at least one epistatic interaction. Specifically, we prove that, at stationarity, the hazard function of the distribution of waiting times until reversion is strictly decreasing for any such site. Thus, in the presence of epistasis, the longer a particular character has been absent from a site, the less likely the site will revert to its prior state. We also explore several examples of this general result, which share a common pattern whereby the probability of having reverted increases rapidly at short times to some substantial value before becoming almost flat after a few substitutions at other sites. This pattern indicates a characteristic tendency for reversion to occur either almost immediately after the initial substitution or only after a very long time.

Causes of molecular convergence and parallelism in protein evolution

To what extent is the convergent evolution of protein function attributable to convergent or parallel changes at the amino acid level? The mutations that contribute to adaptive protein evolution may represent a biased subset of all possible beneficial mutations owing to mutation bias and/or variation in the magnitude of deleterious pleiotropy. A key finding is that the fitness effects of amino acid mutations are often conditional on genetic background. This context dependence (epistasis) can reduce the probability of convergence and parallelism because it reduces the number of possible mutations that are unconditionally acceptable in divergent genetic backgrounds. Here, I review factors that influence the probability of replicated evolution at the molecular level.

Massively parallel enzyme kinetics reveals the substrate recognition landscape of the metalloprotease ADAMTS13

Proteases play important roles in many biologic processes and are key mediators of cancer, inflammation, and thrombosis. However, comprehensive and quantitative techniques to define the substrate specificity profile of proteases are lacking. The metalloprotease ADAMTS13 regulates blood coagulation by cleaving von Willebrand factor (VWF), reducing its procoagulant activity. A mutagenized substrate phage display library based on a 73-amino acid fragment of VWF was constructed, and the ADAMTS13-dependent change in library complexity was evaluated over reaction time points, using high-throughput sequencing. Reaction rate constants (kcat/KM) were calculated for nearly every possible single amino acid substitution within this fragment. This massively parallel enzyme kinetics analysis detailed the specificity of ADAMTS13 and demonstrated the critical importance of the P1-P1' substrate residues while defining exosite binding domains. These data provided empirical evidence for the propensity for epistasis within VWF and showed strong correlation to conservation across orthologs, highlighting evolutionary selective pressures for VWF.

Identification of cis-suppression of human disease mutations by comparative genomics

Patterns of amino acid conservation have served as a tool for understanding protein evolution. The same principles have also found broad application in human genomics, driven by the need to interpret the pathogenic potential of variants in patients. Here we performed a systematic comparative genomics analysis of human disease-causing missense variants. We found that an appreciable fraction of disease-causing alleles are fixed in the genomes of other species, suggesting a role for genomic context. We developed a model of genetic interactions that predicts most of these to be simple pairwise compensations. Functional testing of this model on two known human disease genes revealed discrete cis amino acid residues that, although benign on their own, could rescue the human mutations in vivo. This approach was also applied to ab initio gene discovery to support the identification of a de novo disease driver in BTG2 that is subject to protective cis-modification in more than 50 species. Finally, on the basis of our data and models, we developed a computational tool to predict candidate residues subject to compensation. Taken together, our data highlight the importance of cis-genomic context as a contributor to protein evolution; they provide an insight into the complexity of allele effect on phenotype; and they are likely to assist methods for predicting allele pathogenicity.

Contingency and entrenchment in protein evolution under purifying selection

The phenotypic effect of an allele at one genetic site may depend on alleles at other sites, a phenomenon known as epistasis. Epistasis can profoundly influence the process of evolution in populations and shape the patterns of protein divergence across species. Whereas epistasis between adaptive substitutions has been studied extensively, relatively little is known about epistasis under purifying selection. Here we use computational models of thermodynamic stability in a ligand-binding protein to explore the structure of epistasis in simulations of protein sequence evolution. Even though the predicted effects on stability of random mutations are almost completely additive, the mutations that fix under purifying selection are enriched for epistasis. In particular, the mutations that fix are contingent on previous substitutions: Although nearly neutral at their time of fixation, these mutations would be deleterious in the absence of preceding substitutions. Conversely, substitutions under purifying selection are subsequently entrenched by epistasis with later substitutions: They become increasingly deleterious to revert over time. Our results imply that, even under purifying selection, protein sequence evolution is often contingent on history and so it cannot be predicted by the phenotypic effects of mutations assayed in the ancestral background.

Biophysics of protein evolution and evolutionary protein biophysics

The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence-structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by 'hidden' conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution.

Combining natural sequence variation with high throughput mutational data to reveal protein interaction sites

Many protein interactions are conserved among organisms despite changes in the amino acid sequences that comprise their contact sites, a property that has been used to infer the location of these sites from protein homology. In an inter-species complementation experiment, a sequence present in a homologue is substituted into a protein and tested for its ability to support function. Therefore, substitutions that inhibit function can identify interaction sites that changed over evolution. However, most of the sequence differences within a protein family remain unexplored because of the small-scale nature of these complementation approaches. Here we use existing high throughput mutational data on the in vivo function of the RRM2 domain of the Saccharomyces cerevisiae poly(A)-binding protein, Pab1, to analyze its sites of interaction. Of 197 single amino acid differences in 52 Pab1 homologues, 17 reduce the function of Pab1 when substituted into the yeast protein. The majority of these deleterious mutations interfere with the binding of the RRM2 domain to eIF4G1 and eIF4G2, isoforms of a translation initiation factor. A large-scale mutational analysis of the RRM2 domain in a two-hybrid assay for eIF4G1 binding supports these findings and identifies peripheral residues that make a smaller contribution to eIF4G1 binding. Three single amino acid substitutions in yeast Pab1 corresponding to residues from the human orthologue are deleterious and eliminate binding to the yeast eIF4G isoforms. We create a triple mutant that carries these substitutions and other humanizing substitutions that collectively support a switch in binding specificity of RRM2 from the yeast eIF4G1 to its human orthologue. Finally, we map other deleterious substitutions in Pab1 to inter-domain (RRM2–RRM1) or protein-RNA (RRM2–poly(A)) interaction sites. Thus, the combined approach of large-scale mutational data and evolutionary conservation can be used to characterize interaction sites at single amino acid resolution.

The interactions of proteins with each other are essential for almost all biological processes. Many of the sites of protein contact have evolved to maintain these interactions, but use different sets of amino acid residues. As a result, the residues at a contact site in a protein from one species might not allow a protein interaction when they are tested in a second species. This property underlies the idea of inter-species complementation assays, which test the effect of replacing protein segments from one species by their equivalents from another species. However, this approach has been highly limited in the number of changes that could be analyzed in a single study. Here, we present a novel approach that combines a high-throughput analysis of mutations in a single protein with the set of natural sequences corresponding to evolutionarily divergent variants of this protein. This integration step allows us to map at high resolution both sites of inter-protein interaction as well as intra-protein interaction. Our approach can be used with proteins that have limited functional and structural data, and it can be applied to improve the performance of computational tools that use sequence homology to predict function.

A model of substitution trajectories in sequence space and long-term protein evolution

The nature of factors governing the tempo and mode of protein evolution is a fundamental issue in evolutionary biology. Specifically, whether or not interactions between different sites, or epistasis, are important in directing the course of evolution became one of the central questions. Several recent reports have scrutinized patterns of long-term protein evolution claiming them to be compatible only with an epistatic fitness landscape. However, these claims have not yet been substantiated with a formal model of protein evolution. Here, we formulate a simple covarion-like model of protein evolution focusing on the rate at which the fitness impact of amino acids at a site changes with time. We then apply the model to the data on convergent and divergent protein evolution to test whether or not the incorporation of epistatic interactions is necessary to explain the data. We find that convergent evolution cannot be explained without the incorporation of epistasis and the rate at which an amino acid state switches from being acceptable at a site to being deleterious is faster than the rate of amino acid substitution. Specifically, for proteins that have persisted in modern prokaryotic organisms since the last universal common ancestor for one amino acid substitution approximately ten amino acid states switch from being accessible to being deleterious, or vice versa. Thus, molecular evolution can only be perceived in the context of rapid turnover of which amino acids are available for evolution.

Expanding the mutational spectrum associated to neural tube defects: literature revision and description of novel VANGL1 mutations

BACKGROUND

Neural Tube Defects (NTD) are a common class of birth defects that occur in approximately 1 in 1000 live births. Both genetic and nongenetic factors are involved in the etiology of NTD. Planar cell polarity (PCP) genes plays a critical role in neural tube closure in model organisms. Studies in humans have identified nonsynonymous mutations in PCP pathway genes, including the VANGL genes, that may play a role as risk factors for NTD.

METHODS

Here, we present the results of VANGL1 and VANGL2 mutational screening in a series of 53 NTD patients and 27 couples with a previous NTD affected pregnancy.

RESULTS

We identified three heterozygous missense variants in VANGL1, p.Ala187Val, p.Asp389His, and p.Arg517His, that are absent in controls and predicted to be detrimental on the protein function and, thus, we expanded the mutational spectrum of VANGL1 in NTD cases. We did not identify any new variants having an evident pathogenic effect on protein function in VANGL2. Moreover, we reviewed all the rare nonsynonymous or synonymous variants of VANGL1 and VANGL2 found in patients and controls so far published and re-evaluated them for their pathogenic role by in silico prediction tools. Association tests were performed to demonstrate the enrichment of deleterious variants in reviewed cases versus controls from Exome Variant Server (EVS).

CONCLUSION

We showed a significant (p = 7.0E-5) association between VANGL1 rare genetic variants, especially missense mutations, and NTDs risk.

A structural perspective of compensatory evolution

The study of molecular evolution is important because it reveals how protein functions emerge and evolve. Recently, several types of studies indicated that substitutions in molecular evolution occur in a compensatory manner, whereby the occurrence of a substitution depends on the amino acid residues at other sites. However, a molecular or structural basis behind the compensation often remains obscure. Here, we review studies on the interface of structural biology and molecular evolution that revealed novel aspects of compensatory evolution. In many cases structural studies benefit from evolutionary data while structural data often add a functional dimension to the study of molecular evolution.

Encoding asymmetry of the N-glycosylation motif facilitates glycoprotein evolution

Protein N-glycosylation is found in all domains of life and has a conserved role in glycoprotein folding and stability. In animals, glycoproteins transit through the Golgi where the N-glycans are trimmed and rebuilt with sequences that bind lectins, an innovation that greatly increases structural diversity and redundancy of glycoprotein-lectin interaction at the cell surface. Here we ask whether the natural tension between increasing diversity (glycan-protein interactions) and site multiplicity (backup and status quo) might be revealed by a phylogenic examination of glycoproteins and NXS/T(X≠P) N-glycosylation sites. Site loss is more likely by mutation at Asn encoded by two adenosine (A)-rich codons, while site gain is more probable by generating Ser or Thr downstream of an existing Asn. Thus mutations produce sites at novel positions more frequently than the reversal of recently lost sites, and therefore more paths though sequence space are made available to natural selection. An intra-species comparison of secretory and cytosolic proteins revealed a departure from equilibrium in sequences one-mutation-away from NXS/T and in (A) content, indicating strong selective pressures and exploration of N-glycosylation positions during vertebrate evolution. Furthermore, secretory proteins have evolved at rates proportional to N-glycosylation site number, indicating adaptive interactions between the N-glycans and underlying protein. Given the topology of the genetic code, mutation of (A) is more often nonsynonomous, and Lys, another target of many PTMs, is also encoded by two (A)-rich codons. An examination of acetyl-Lys sites in proteins indicated similar evolutionary dynamics, consistent with asymmetry of the target and recognition portions of modified sites. Our results suggest that encoding asymmetry is an ancient mechanism of evolvability that increases diversity and experimentation with PTM site positions. Strong selective pressures on PTMs may have contributed to the A+T→G+C shift in genome-wide nucleotide composition during metazoan radiation.

An evolutionary perspective on epistasis and the missing heritability

The relative importance between additive and non-additive genetic variance has been widely argued in quantitative genetics. By approaching this question from an evolutionary perspective we show that, while additive variance can be maintained under selection at a low level for some patterns of epistasis, the majority of the genetic variance that will persist is actually non-additive. We propose that one reason that the problem of the “missing heritability” arises is because the additive genetic variation that is estimated to be contributing to the variance of a trait will most likely be an artefact of the non-additive variance that can be maintained over evolutionary time. In addition, it can be shown that even a small reduction in linkage disequilibrium between causal variants and observed SNPs rapidly erodes estimates of epistatic variance, leading to an inflation in the perceived importance of additive effects. We demonstrate that the perception of independent additive effects comprising the majority of the genetic architecture of complex traits is biased upwards and that the search for causal variants in complex traits under selection is potentially underpowered by parameterising for additive effects alone. Given dense SNP panels the detection of causal variants through genome-wide association studies may be improved by searching for epistatic effects explicitly.

In this study we have shown that two independent problems may have a common cause. Why do traits under selection exhibit additive genetic variance, and why is the proportion of the heritability explained by additive effects much smaller than the total heritability estimated to exist? Our results indicate that epistatic interactions can allow deleterious mutations to persist under selection and that these interactions can abate the depletion of additive genetic variation. Furthermore, a much larger element of non-additive genetic variance is maintained, which supports the notion that the heritability estimated from family studies could be a mixture of both additive and non-additive components. We show that searching directly for epistatic effects greatly improves the discovery of variants under selection, despite the multiple testing penalty being much larger. Finally, we demonstrate that common practices in genome-wide association studies could lead to both an ascertainment bias in detecting additive effects and a confirmation bias in perceiving that most of the genetic variance is additive.