The rate of compensatory mutation in the DNA bacteriophage phiX174

A fundamental and theoretical framework for mutation interactions and epistasis

Many pathological conditions are a result of intragenic epistasis; however, there are ambiguities in current epistasis models. Herein, the new Mutation Interaction Spectrum model defines a discrete outcome, named a Mutation Interaction, for each double point mutation in a gene and its component single mutations. The model is a universal genetic model of all types of mutation interactions and their functional outcomes and is derived from digital logic, commonly used in electrical engineering. Mutation interactions are normally classified as positive and negative epistasis. The model logics unifies common genetic relationships into one model, normalizing biological nomenclature, and disambiguates them with the 16 possible logic-based interactions. The model was tested by assaying transcriptional activity induced by HIV-1 Tat protein, for a random sampling of 3429 double mutations and all 1615 single mutations. All possible types of logic were observed for the Tat mutation interactions.

In-silico assessment of high-risk non-synonymous SNPs in ADAMTS3 gene associated with Hennekam syndrome and their impact on protein stability and function

Hennekam Lymphangiectasia-Lymphedema Syndrome 3 (HKLLS3) is a rare genetical disorder caused by mutations in a few genes including ADAMTS3. It is characterized by lymphatic dysplasia, intestinal lymphangiectasia, severe lymphedema and distinctive facial appearance. Up till now, no extensive studies have been conducted to elucidate the mechanism of the disease caused by various mutations. As a preliminary investigation of HKLLS3, we sorted out the most deleterious nonsynonymous single nucleotide polymorphisms (nsSNPs) that might affect the structure and function of ADAMTS3 protein by using a variety of in silico tools. A total of 919 nsSNPs in the ADAMTS3 gene were identified. 50 nsSNPs were predicted to be deleterious by multiple computational tools. 5 nsSNPs (G298R, C567Y, A370T, C567R and G374S) were found to be the most dangerous and can be associated with the disease as predicted by different bioinformatics tools. Modelling of the protein shows it can be divided into segments 1, 2 and 3, which are connected by short loops. Segment 3 mainly consists of loops without substantial secondary structures. With prediction tools and molecular dynamics simulation, some SNPs were found to significantly destabilize the protein structure and disrupt the secondary structures, especially in segment 2. The deleterious effects of mutations in segment 1 are possibly not from destabilization but from other factors such as the change in phosphorylation as suggested by post-translational modification (PTM) studies. This is the first-ever study of ADAMTS3 gene polymorphism, and the predicted nsSNPs in ADAMST3, some of which have not been reported yet in patients, will serve for diagnostic purposes and further therapeutic implications in Hennekam syndrome, contributing to better diagnosis and treatment.

Fast drug rotation reduces bacterial resistance evolution in a microcosm experiment

Drug rotation (cycling), in which multiple drugs are administrated alternatively, has the potential for limiting resistance evolution in pathogens. The frequency of drug alternation could be a major factor to determine the effectiveness of drug rotation. Drug rotation practices often have low frequency of drug alternation, with an expectation of resistance reversion. Here we, based on evolutionary rescue and compensatory evolution theories, suggest that fast drug rotation can limit resistance evolution in the first place. This is because fast drug rotation would give little time for the evolutionarily rescued populations to recover in population size and genetic diversity, and thus decrease the chance of future evolutionary rescue under alternate environmental stresses. We experimentally tested this hypothesis using the bacterium Pseudomonas fluorescens and two antibiotics (chloramphenicol and rifampin). Increasing drug rotation frequency reduced the chance of evolutionary rescue, and most of the finally surviving bacterial populations were resistant to both drugs. Drug resistance incurred significant fitness costs, which did not differ among the drug treatment histories. A link between population sizes during the early stages of drug treatment and the end-point fates of populations (extinction vs survival) suggested that population size recovery and compensatory evolution before drug shift increase the chance of population survival. Our results therefore advocate fast drug rotation as a promising approach to reduce bacterial resistance evolution, which in particular could be a substitute for drug combination when the latter has safety risks.

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.

GigaAssay - An adaptable high-throughput saturation mutagenesis assay platform

High-throughput assay systems have had a large impact on understanding the mechanisms of basic cell functions. However, high-throughput assays that directly assess molecular functions are limited. Herein, we describe the "GigaAssay", a modular high-throughput one-pot assay system for measuring molecular functions of thousands of genetic variants at once. In this system, each cell was infected with one virus from a library encoding thousands of Tat mutant proteins, with each viral particle encoding a random unique molecular identifier (UMI). We demonstrate proof of concept by measuring transcription of a GFP reporter in an engineered reporter cell line driven by binding of the HIV Tat transcription factor to the HIV long terminal repeat. Infected cells were flow-sorted into 3 bins based on their GFP fluorescence readout. The transcriptional activity of each Tat mutant was calculated from the ratio of signals from each bin. The use of UMIs in the GigaAssay produced a high average accuracy (95%) and positive predictive value (98%) determined by comparison to literature benchmark data, known C-terminal truncations, and blinded independent mutant tests. Including the substitution tolerance with structure/function analysis shows restricted substitution types spatially concentrated in the Cys-rich region. Tat has abundant intragenic epistasis (10%) when single and double mutants are compared.

A Paradigm Shift in the Combination Changes of SARS-CoV-2 Variants and Increased Spread of Delta Variant (B.1.617.2) across the World

Since September 2020, the SARS-CoV-2 variants have gained their dominance worldwide, especially in Kenya, Italy, France, the UK, Turkey, Indonesia, India, Finland, Ireland, Singapore, Denmark, Germany, and Portugal. In this study, we developed a model on the frequency of delta variants across 28 countries (R²= 0.1497), displaying the inheritance of mutations during the generation of the delta variants with 123,526 haplotypes. The country-wise haplotype network showed the distribution of haplotypes in USA (10,174), Denmark (5,637), India (4,089), Germany (2,350), Netherlands (1,899), Sweden (1,791), Italy (1,720), France (1,293), Ireland (1,257), Belgium (1,207), Singapore (1,193), Portugal (1,184) and Spain (1,133). Our analysis shows the highest haplotype in Europe with 84% and the lowest in Australia with 0.00001%. A model of scatter plot was generated with a regression line which provided the estimated rate of mutation, including 24.048 substitutions yearly. Our study concluded that the high global prevalence of the delta variants is due to a high frequency of infectivity, supporting the paradigm shift of the viral variants.

Transcription factors evolve faster than their structural gene targets in the flavonoid pigment pathway

Dissecting the relationship between gene function and substitution rates is key to understanding genome-wide patterns of molecular evolution. Biochemical pathways provide powerful systems for investigating this relationship because the functional role of each gene is often well characterized. Here, we investigate the evolution of the flavonoid pigment pathway in the colorful Petunieae clade of the tomato family (Solanaceae). This pathway is broadly conserved in plants, both in terms of its structural elements and its MYB, basic helix–loop–helix, and WD40 transcriptional regulators, and its function has been extensively studied, particularly in model species of petunia. We built a phylotranscriptomic data set for 69 species of Petunieae to infer patterns of molecular evolution across pathway genes and across lineages. We found that transcription factors exhibit faster rates of molecular evolution (dN/dS) than their targets, with the highly specialized MYB genes evolving fastest. Using the largest comparative data set to date, we recovered little support for the hypothesis that upstream enzymes evolve slower than those occupying more downstream positions, although expression levels do predict molecular evolutionary rates. Although shifts in floral pigmentation were only weakly related to changes affecting coding regions, we found a strong relationship with the presence/absence patterns of MYB transcripts. Intensely pigmented species express all three main MYB anthocyanin activators in petals, whereas pale or white species express few or none. Our findings reinforce the notion that pathway regulators have a dynamic history, involving higher rates of molecular evolution than structural components, along with frequent changes in expression during color transitions.

The cost of evolved constitutive lac gene expression is usually, but not always, maintained during evolution of generalist populations

Beneficial mutations can become costly following an environmental change. Compensatory mutations can relieve these costs, while not affecting the selected function, so that the benefits are retained if the environment shifts back to be similar to the one in which the beneficial mutation was originally selected. Compensatory mutations have been extensively studied in the context of antibiotic resistance, responses to specific genetic perturbations, and in the determination of interacting gene network components. Few studies have focused on the role of compensatory mutations during more general adaptation, especially as the result of selection in fluctuating environments where adaptations to different environment components may often involve trade-offs. We examine whether costs of a mutation in lacI, which deregulated the expression of the lac operon in evolving populations of Escherichia coli bacteria, were compensated. This mutation occurred in multiple replicate populations selected in environments that fluctuated between growth on lactose, where the mutation was beneficial, and on glucose, where it was deleterious. We found that compensation for the cost of the lacI mutation was rare, but, when it did occur, it did not negatively affect the selected benefit. Compensation was not more likely to occur in a particular evolution environment. Compensation has the potential to remove pleiotropic costs of adaptation, but its rarity indicates that the circumstances to bring about the phenomenon may be peculiar to each individual or impeded by other selected mutations.

Adaptive Processes Change as Multiple Functions Evolve

Epistasis influences the gene-environment interactions that shape bacterial fitness through antibiotic exposure, which can ultimately affect the availability of certain resistance phenotypes to bacteria. The substitutions present within bla _TEM-50 confer both cephalosporin and β-lactamase inhibitor resistance. We wanted to compare the evolution of bla _TEM-50 with that of another variant, bla _TEM-85, which differs in that bla _TEM-85 contains only substitutions that contribute to cephalosporin resistance. Differences between the landscapes and epistatic interactions of these TEM variants are important for understanding their separate evolutionary responses to antibiotics. We hypothesized the substitutions within bla _TEM-50 would result in more epistatic interactions than for bla _TEM-85 As expected, we found more epistatic interactions between the substitutions present in bla _TEM-50 than in bla _TEM-85 Our results suggest that selection from many cephalosporins is required to achieve the full potential resistance to cephalosporins but that a single β-lactam and inhibitor combination will drive evolution of the full potential resistance phenotype. Surprisingly, we also found significantly positive increases in growth rates as antibiotic concentration increased for some of the strains expressing bla _TEM-85 precursor genotypes but not the bla _TEM-50 variants. This result further suggests that additive interactions more effectively optimize phenotypes than epistatic interactions, which means that exposure to numerous cephalosporins actually increases the ability of a TEM enzyme to confer resistance to any single cephalosporin.

In-Silico Pangenomics of SARS-CoV-2 Isolates Reveal Evidence for Subtle Adaptive Expression Strategies, Continued Clonal Evolution, and Sub-Clonal Emergences, Despite Genome Stability

The devastating SARS-CoV2 pandemic is worsening with relapsing surges, emerging mutants, and increasing mortalities. Despite enormous efforts, it is not clear how SARS-CoV2 adapts and evolves in a clonal background. Laboratory research is hindered by high biosafety demands. However, the rapid sequence availability opened doors for bioinformatics. Using different bioinformatics programs, we investigated 6305 sequences for clonality, expressions strategies, and evolutionary dynamics. Results showed high nucleotide identity of 99.9% among SARS-CoV2 indicating clonal evolution and genome. High sequence identity and phylogenetic tree concordance were obtained with isolates from different regions. In any given tree topology, ~50% of isolates in a country formed country-specific sub-clusters. However, abundances of subtle overexpression strategies were found including transversions, signature-sequences and slippery-structures. Five different short tracks dominated with identical location patterns in all genomes where Slippery-4 AAGAA was the most abundant. Interestingly, transversion and transition substitutions mostly affected the same amino acid residues implying compensatory changes. To ensure these strategies were independent of sequence clonality, we simultaneously examined sequence homology indicators; tandem-repeats, restriction-site, and 3′UTR, 5′ UTR-caps and stem-loop locations in addition to stringent alignment parameters for 100% identity which all confirmed stability. Nevertheless, two rare events; a rearrangement in two SARS-CoV2 isolates against betacoronavirus ancestor and a polymorphism in S gene, were detected. Thus, we report on abundance of transversions, slippery sequences, and ON/OFF molecular structures, implying adaptive expressions had occurred, despite clonal evolution and genome stability. Furthermore, functional validation of the point mutations would provide insights into mechanisms of SARS-CoV2 virulence and adaptation.

Multiple mutations within individual oncogenes

Recent studies of the cancer genome have identified numerous patients harboring multiple mutations (MM) within individual oncogenes. These MM (de novo MM) in cis synergistically activate the mutated oncogene and promote tumorigenesis, indicating a positive epistatic interaction between mutations. The relatively frequent de novo MM suggest that intramolecular positive epistasis is widespread in oncogenes. Studies also suggest that negative and higher-order epistasis affects de novo MM. Comparison of de novo MM and MM associated with drug-resistant secondary mutations (secondary MM) revealed several similarities with respect to allelic configuration, mutational selection and functionality of individual mutations. Conversely, they have several differences, most notably the difference in drug sensitivities. Secondary MM usually confer resistance to molecularly targeted therapies, whereas several de novo MM are associated with increased sensitivity, implying that both can be useful as therapeutic biomarkers. Unlike secondary MM in which specific secondary resistant mutations are selected, minor (infrequent) functionally weak mutations are convergently selected in de novo MM, which may provide an explanation as to why such mutations accumulate in cancer. The third type of MM is MM from different subclones. This type of MM is associated with parallel evolution, which may contribute to relapse and treatment failure. Collectively, MM within individual oncogenes are diverse, but all types of MM are associated with cancer evolution and therapeutic response. Further evaluation of oncogenic MM is warranted to gain a deeper understanding of cancer genetics and evolution.

Experimental Hybridization Studies Suggest That Pleiotropic Alleles Commonly Underlie Adaptive Divergence between Natural Populations

The alleles used for adaptation can pleiotropically affect traits under stabilizing selection. The fixation of alleles with deleterious pleiotropic side effects causes compensatory alleles to be favored by selection. Such compensatory alleles might segregate in interpopulation hybrids, resulting in segregation variance for traits where parents have indistinguishable phenotypes. If adaptation typically involves pleiotropy and compensation, then the segregation variance for traits under stabilizing selection is expected to increase with the magnitude of adaptive phenotypic divergence between parents. This prediction has not been tested empirically, and I gathered data from experimental hybridization studies to evaluate it. I found that pairs of parents that are more phenotypically divergent beget hybrids with more segregation variance in traits for which the parents are statistically indistinguishable. This result suggests that adaptive divergence between pairs of natural populations proceeds via pleiotropy and compensation and that deleterious transgressive segregation variance accumulates systematically as populations diverge.

Mutation Rate Heterogeneity Increases Odds of Survival in Unpredictable Environments

Mutation rates affect both a population's present fitness and its capacity to adapt to future environmental changes. When the available genetic variability limits adaptation to environmental change, natural selection favors high mutations rates. However, constitutively high mutation rates compromise the fitness of a population in stable environments. This problem may be resolved if an increase in mutation rates is limited to times of stress, restricted to some genomic regions, and occurs only in a subpopulation of cells. Such within-population heterogeneity of mutation rates can result from genetic, environmental, and stochastic effects. The presence of subpopulations of transient mutator cells does not jeopardize the overall fitness of a population under stable environmental conditions. However, they can increase the odds of survival in changing environments because they represent reservoirs of increased genetic variability. This article presents evidence that such heterogeneity of mutation rates is more the norm than the exception.

The Causes and Consequences of Genetic Interactions (Epistasis)

The same mutation can have different effects in different individuals. One important reason for this is that the outcome of a mutation can depend on the genetic context in which it occurs. This dependency is known as epistasis. In recent years, there has been a concerted effort to quantify the extent of pairwise and higher-order genetic interactions between mutations through deep mutagenesis of proteins and RNAs. This research has revealed two major components of epistasis: nonspecific genetic interactions caused by nonlinearities in genotype-to-phenotype maps, and specific interactions between particular mutations. Here, we provide an overview of our current understanding of the mechanisms causing epistasis at the molecular level, the consequences of genetic interactions for evolution and genetic prediction, and the applications of epistasis for understanding biology and determining macromolecular structures.

A large-scale comparative assessment of methods for residue-residue contact prediction

Sequence-based prediction of residue-residue contact in proteins becomes increasingly more important for improving protein structure prediction in the big data era. In this study, we performed a large-scale comparative assessment of 15 locally installed contact predictors. To assess these methods, we collected a big data set consisting of 680 nonredundant proteins covering different structural classes and target difficulties. We investigated a wide range of factors that may influence the precision of contact prediction, including target difficulty, structural class, the alignment depth and distribution of contact pairs in a protein structure. We found that: (1) the machine learning-based methods outperform the direct-coupling-based methods for short-range contact prediction, while the latter are significantly better for long-range contact prediction. The consensus-based methods, which combine machine learning and direct-coupling methods, perform the best. (2) The target difficulty does not have clear influence on the machine learning-based methods, while it does affect the direct-coupling and consensus-based methods significantly. (3) The alignment depth has relatively weak effect on the machine learning-based methods. However, for the direct-coupling-based methods and consensus-based methods, the predicted contacts for targets with deeper alignment tend to be more accurate. (4) All methods perform relatively better on β and α + β proteins than on α proteins. (5) Residues buried in the core of protein structure are more prone to be in contact than residues on the surface (22 versus 6%). We believe these are useful results for guiding future development of new approach to contact prediction.

Additive Phenotypes Underlie Epistasis of Fitness Effects

Gene interactions, or epistasis, play a large role in determining evolutionary outcomes. The ruggedness of fitness landscapes, and thus the predictability of evolution and the accessibility of high-fitness genotypes, is determined largely by the pervasiveness of epistasis and the degree of correlation between similar genotypes. We created all possible pairings of three sets of five beneficial first-step mutations fixed during adaptive walks under three different regimes: selection on growth rate alone, on growth rate and thermal stability, and on growth rate and pH stability. All 30 double-mutants displayed negative, antagonistic epistasis with regard to growth rate and fitness, but positive epistasis and additivity were common for the stability phenotypes. This suggested that biophysically simple phenotypes, such as capsid stability, may on average behave more additively than complex phenotypes like viral growth rate. Growth rate epistasis was also smaller in magnitude when the individual effects of single mutations were smaller. Significant sign epistasis, such that the effect of a mutation that is beneficial in the wild-type background is deleterious in combination with a second mutation, emerged more frequently in intragenic mutational pairings than in intergenic pairs, and was evident in nearly half of the double-mutants, indicating that the fitness landscape is moderately uncorrelated and of intermediate ruggedness. Together, our results indicated that mutations may interact additively with regard to phenotype when considered at a basic, biophysical level, but that epistasis arises as a result of pleiotropic interactions between the individual components of complex phenotypes and diminishing returns arising from intermediate phenotypic optima.

Suppressor Analysis of the Fusogenic Lambda Spanins

The final step of lysis in phage λ infections of Escherichia coli is mediated by the spanins Rz and Rz1. These proteins form a complex that bridges the cell envelope and that has been proposed to cause fusion of the inner and outer membranes. Accordingly, mutations that block spanin function are found within coiled-coil domains and the proline-rich region, motifs essential in other fusion systems. To gain insight into spanin function, pseudorevertant alleles that restored plaque formation for lysis-defective mutants of Rz and Rz1 were selected. Most second-site suppressors clustered within a coiled-coil domain of Rz near the outer leaflet of the cytoplasmic membrane and were not allele specific. Suppressors largely encoded polar insertions within the hydrophobic core of the coiled-coil interface. Such suppressor changes resulted in decreased proteolytic stability of the Rz double mutants in vivo Unlike the wild type, in which lysis occurs while the cells retain a rod shape, revertant alleles with second-site suppressor mutations supported lysis events that were preceded by spherical cell formation. This suggests that destabilization of the membrane-proximal coiled coil restores function for defective spanin alleles by increasing the conformational freedom of the complex at the cost of its normal, all-or-nothing functionality.IMPORTANCECaudovirales encode cell envelope-spanning proteins called spanins, which are thought to fuse the inner and outer membranes during phage lysis. Recent genetic analysis identified the functional domains of the lambda spanins, which are similar to class I viral fusion proteins. While the pre- and postfusion structures of model fusion systems have been well characterized, the intermediate structure(s) formed during the fusion reaction remains elusive. Genetic analysis would be expected to identify functional connections between intermediates. Since most membrane fusion systems are not genetically tractable, only few such investigations have been reported. Here, we report a suppressor analysis of lambda spanin function. To our knowledge this is the first suppression analysis of a class I-like complex and also the first such analysis of a prokaryote membrane fusion system.

Single-mutation fitness landscapes for an enzyme on multiple substrates reveal specificity is globally encoded

Our lack of total understanding of the intricacies of how enzymes behave has constrained our ability to robustly engineer substrate specificity. Furthermore, the mechanisms of natural evolution leading to improved or novel substrate specificities are not wholly defined. Here we generate near-comprehensive single-mutation fitness landscapes comprising >96.3% of all possible single nonsynonymous mutations for hydrolysis activity of an amidase expressed in E. coli with three different substrates. For all three selections, we find that the distribution of beneficial mutations can be described as exponential, supporting a current hypothesis for adaptive molecular evolution. Beneficial mutations in one selection have essentially no correlation with fitness for other selections and are dispersed throughout the protein sequence and structure. Our results further demonstrate the dependence of local fitness landscapes on substrate identity and provide an example of globally distributed sequence-specificity determinants for an enzyme.

Systematically understanding the sequence determinants to substrate specificity for enzymes has implications in areas from evolutionary biology to biocatalysis. Here, Whitehead and colleagues generate and analyse near-comprehensive single-mutation fitness landscapes for an amidase with three different substrates.

The genomic landscape of evolutionary convergence in mammals, birds and reptiles

Many lineage-defining (nodal) mutations possess high functionality. However, differentiating adaptive nodal mutations from those that are functionally compensated remains challenging. To address this challenge, we identified functional nodal mutations (fNMs) in ~3,400 nuclear DNA (nDNA) and 4 mitochondrial DNA (mtDNA) protein structures from 91 and 1,003 species, respectively, representing the entire mammalian, bird and reptile phylogeny. A screen for candidate compensatory mutations among co-occurring amino acid changes in close structural proximity revealed that such compensated fNMs encompass 37% and 27% of the mtDNA and nDNA datasets, respectively. Analysis of the remaining (non-compensated) mutations, which are enriched for adaptive mutations, showed that birds and mammals share most such recurrent fNMs (N = 51). Among the latter, we discovered mutations in thermoregulation-related genes. These represent the best candidates to explain the molecular basis of convergent body thermoregulation in birds and mammals. Our analysis reveals the landscape of possible mutational compensation and convergence in amniote phylogeny.

Long-Range Epistasis Mediated by Structural Change in a Model of Ligand Binding Proteins

Recent analyses of amino acid mutations in proteins reveal that mutations at many pairs of sites are epistatic-i.e., their effects on fitness are non-additive-the combined effect of two mutations being significantly larger or smaller than the sum of their effects considered independently. Interestingly, epistatic sites are not necessarily near each other in the folded structure of a protein, and may even be located on opposite sides of a molecule. However, the mechanistic reasons for long-range epistasis remain obscure. Here, we study long-range epistasis in proteins using a previously developed model in which off-lattice polymers are evolved under ligand binding constraints. Epistatic effects in the model are qualitatively similar to those recently reported for small proteins, and many are long-range. We find that a major reason for long-range epistasis is conformational change-a recurrent theme in both positive and negative epistasis being the transfer, or exchange of material between the ordered nucleus, which supports the binding site, and the liquid-like surface of a folded molecule. These local transitions in phase and folded structure are largely responsible for long-range epistasis in our model.

The pioneering role of PRDM9 indel mutations in tarsier evolution

PRDM9 is currently the sole speciation gene found in vertebrates causing hybrid sterility probably due to incompatible alleles. Its role in defining the double strand break loci during the meiotic prophase I is crucial for proper chromosome segregation. Therefore, the rapid turnover of the loci determining zinc finger array seems to be causative for incompatibilities. We here investigated the zinc finger domain-containing exon of PRDM9 in 23 tarsiers. Tarsiers, the most basal extant haplorhine primates, exhibit two frameshifting indels at the 5'-end of the array. The first mutation event interrupts the reading frame and function while the second compensates both. The fixation of this allele variant in tarsiers led to hypothesize that de- and reactivation of the zinc finger domain drove the speciation in early haplorhine or tarsiiform primates. Moreover, the high allelic diversity within Tarsius points to multiple effects of genetic drift reflecting their phylogeographic history since the Miocene.

The Role of Deleterious Substitutions in Crop Genomes

Populations continually incur new mutations with fitness effects ranging from lethal to adaptive. While the distribution of fitness effects of new mutations is not directly observable, many mutations likely either have no effect on organismal fitness or are deleterious. Historically, it has been hypothesized that a population may carry many mildly deleterious variants as segregating variation, which reduces the mean absolute fitness of the population. Recent advances in sequencing technology and sequence conservation-based metrics for inferring the functional effect of a variant permit examination of the persistence of deleterious variants in populations. The issue of segregating deleterious variation is particularly important for crop improvement, because the demographic history of domestication and breeding allows deleterious variants to persist and reach moderate frequency, potentially reducing crop productivity. In this study, we use exome resequencing of 15 barley accessions and genome resequencing of 8 soybean accessions to investigate the prevalence of deleterious single nucleotide polymorphisms (SNPs) in the protein-coding regions of the genomes of two crops. We conclude that individual cultivars carry hundreds of deleterious SNPs on average, and that nonsense variants make up a minority of deleterious SNPs. Our approach identifies known phenotype-altering variants as deleterious more frequently than the genome-wide average, suggesting that putatively deleterious variants are likely to affect phenotypic variation. We also report the implementation of a SNP annotation tool BAD_Mutations that makes use of a likelihood ratio test based on alignment of all currently publicly available Angiosperm genomes.

Molecular evolution of anthocyanin pigmentation genes following losses of flower color

Background

Phenotypic transitions, such as trait gain or loss, are predicted to carry evolutionary consequences for the genes that control their development. For example, trait losses can result in molecular decay of the pathways underlying the trait. Focusing on the Iochrominae clade (Solanaceae), we examine how repeated losses of floral anthocyanin pigmentation associated with flower color transitions have affected the molecular evolution of three anthocyanin pathway genes (Chi, F3h, and Dfr).

Results

We recovered intact coding regions for the three genes in all of the lineages that have lost floral pigmentation, suggesting that molecular decay is not associated with these flower color transitions. However, two of the three genes (Chi, F3h) show significantly elevated dN/dS ratios in lineages without floral pigmentation. Maximum likelihood analyses suggest that this increase is due to relaxed constraint on anthocyanin genes in the unpigmented lineages as opposed to positive selection. Despite the increase, the values for dN/dS in both pigmented and unpigmented lineages were consistent overall with purifying selection acting on these loci.

Conclusions

The broad conservation of anthocyanin pathway genes across lineages with and without floral anthocyanins is consistent with the growing consensus that losses of pigmentation are largely achieved by changes in gene expression as opposed to structural mutations. Moreover, this conservation maintains the potential for regain of flower color, and indicates that evolutionary losses of floral pigmentation may be readily reversible.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0675-3) contains supplementary material, which is available to authorized users.

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.

Environmental variation alters the fitness effects of rifampicin resistance mutations in Pseudomonas aeruginosa

The fitness effects of antibiotic resistance mutations in antibiotic-free conditions play a key role in determining the long-term maintenance of resistance. Although resistance is usually associated with a cost, the impact of environmental variation on the cost of resistance is poorly understood. Here, we test the impact of heterogeneity in temperature and resource availability on the fitness effects of antibiotic resistance using strains of the pathogenic bacterium Pseudomonas aeruginosa carrying clinically important rifampicin resistance mutations. Although the rank order of fitness was generally maintained across environments, fitness effects relative to the wild type differed significantly. Changes in temperature had a profound impact on the fitness effects of resistance, whereas changes in carbon substrate had only a weak impact. This suggests that environmental heterogeneity may influence whether the costs of resistance are likely to be ameliorated by second-site compensatory mutations or by reversion to wild-type rpoB. Our results highlight the need to consider environmental heterogeneity and genotype-by-environment interactions for fitness in models of resistance evolution.

Reciprocal sign epistasis and truncation selection: When is recombination favorable in a pre-breeding program with a selfing species?

Since the dawn of agriculture, humans have applied artificial selection on traits of interest, regardless of their genetic architecture. Yet, still today, most models used to study and streamline this process overlook genetic interactions. In this study, we determined the conditions in which a target genotype can be fixed when truncation selection is applied on an epistatic trait. Previous studies have shown that reciprocal sign epistasis with two fitness peaks of unequal height involves multiple equilibrium states, i.e. below one critical parameter value, such as a critical recombination rate, one genotype may be fixed, and above it, another one may be fixed. Using a haploid bi-locus model, we identified which genotype would be fixed, and how quickly, in an infinite population selected for a phenotypic trait subject to reciprocal sign epistasis with unequal peak heights, depending on two criteria: the recombination rate and percentage of selected individuals. The critical parameter values at which bistability sets in, were also calculated. These results were complemented by stochastic simulations in finite populations. Our results confirmed that, in the case of fitness under reciprocal sign epistasis, high recombination rates induce blockage at the local optimum or attainment of an equilibrium state between the two peaks. However, if linkage disequilibrium is negative in the initial population, recombination is necessary to create the most favorable genotype. Therefore, in this case, reciprocal sign epistasis favors non-null recombination rates, particularly if selection is intense.

Fifty years of co-evolution and beyond: integrating co-evolution from molecules to species

Fifty years after Ehrlich and Raven's seminal paper, the idea of co-evolution continues to grow as a key concept in our understanding of organic evolution. This concept has not only provided a compelling synthesis between evolutionary biology and community ecology, but has also inspired research that extends beyond its original scope. In this article, we identify unresolved questions about the co-evolutionary process and advocate for the integration of co-evolutionary research from molecular to interspecific interactions. We address two basic questions: (i) What is co-evolution and how common is it? (ii) What is the unit of co-evolution? Both questions aim to explore the heart of the co-evolutionary process. Despite the claim that co-evolution is ubiquitous, we argue that there is in fact little evidence to support the view that reciprocal natural selection and coadaptation are common in nature. We also challenge the traditional view that co-evolution only occurs between traits of interacting species. Co-evolution has the potential to explain evolutionary processes and patterns that result from intra- and intermolecular biochemical interactions within cells, intergenomic interactions (e.g. nuclear-cytoplasmic) within species, as well as intergenomic interactions mediated by phenotypic traits between species. Research that bridges across these levels of organization will help to advance our understanding of the importance of the co-evolutionary processes in shaping the diversity of life on Earth.

Adaptive Landscapes of Resistance Genes Change as Antibiotic Concentrations Change

Most studies on the evolution of antibiotic resistance are focused on selection for resistance at lethal antibiotic concentrations, which has allowed the detection of mutant strains that show strong phenotypic traits. However, solely focusing on lethal concentrations of antibiotics narrowly limits our perspective of antibiotic resistance evolution. New high-resolution competition assays have shown that resistant bacteria are selected at relatively low concentrations of antibiotics. This finding is important because sublethal concentrations of antibiotics are found widely in patients undergoing antibiotic therapies, and in nonmedical conditions such as wastewater treatment plants, and food and water used in agriculture and farming. To understand the impacts of sublethal concentrations on selection, we measured 30 adaptive landscapes for a set of TEM β-lactamases containing all combinations of the four amino acid substitutions that exist in TEM-50 for 15 β-lactam antibiotics at multiple concentrations. We found that there are many evolutionary pathways within this collection of landscapes that lead to nearly every TEM-genotype that we studied. While it is known that the pathways change depending on the type of β-lactam, this study demonstrates that the landscapes including fitness optima also change dramatically as the concentrations of antibiotics change. Based on these results we conclude that the presence of multiple concentrations of β-lactams in an environment result in many different adaptive landscapes through which pathways to nearly every genotype are available. Ultimately this may increase the diversity of genotypes in microbial populations.

Predicting the combined effect of multiple genetic variants

Background

Many genetic variants have been identified in the human genome. The functional effects of a single variant have been intensively studied. However, the joint effects of multiple variants in the same genes have been largely ignored due to their complexity or lack of data. This paper uses HMMvar, a hidden Markov model based approach, to investigate the combined effect of multiple variants from the 1000 Genomes Project. Two tumor suppressor genes, TP53 and phosphatase and tensin homolog (PTEN), are also studied for the joint effect of compensatory indel variants.

Results

Results show that there are cases where the joint effect of having multiple variants in the same genes is significantly different from that of a single variant. The deleterious effect of a single indel variant can be alleviated by their compensatory indels in TP53 and PTEN. Compound mutations in two genes, β-MHC and MyBP-C, leading to severer cardiovascular disease compared to single mutations, are also validated.

Conclusions

This paper extends the functionality of HMMvar, a tool for assigning a quantitative score to a variant, to measure not only the deleterious effect of a single variant but also the joint effect of multiple variants. HMMvar is the first tool that can predict the functional effects of both single and general multiple variations on proteins. The precomputed scores for multiple variants from the 1000 Genomes Project and the HMMvar package are available at https://bioinformatics.cs.vt.edu/zhanglab/HMMvar/

MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins

Motivation: Recent developments of statistical techniques to infer direct evolutionary couplings between residue pairs have rendered covariation-based contact prediction a viable means for accurate 3D modelling of proteins, with no information other than the sequence required. To extend the usefulness of contact prediction, we have designed a new meta-predictor (MetaPSICOV) which combines three distinct approaches for inferring covariation signals from multiple sequence alignments, considers a broad range of other sequence-derived features and, uniquely, a range of metrics which describe both the local and global quality of the input multiple sequence alignment. Finally, we use a two-stage predictor, where the second stage filters the output of the first stage. This two-stage predictor is additionally evaluated on its ability to accurately predict the long range network of hydrogen bonds, including correctly assigning the donor and acceptor residues.

Results: Using the original PSICOV benchmark set of 150 protein families, MetaPSICOV achieves a mean precision of 0.54 for top-L predicted long range contacts—around 60% higher than PSICOV, and around 40% better than CCMpred. In de novo protein structure prediction using FRAGFOLD, MetaPSICOV is able to improve the TM-scores of models by a median of 0.05 compared with PSICOV. Lastly, for predicting long range hydrogen bonding, MetaPSICOV-HB achieves a precision of 0.69 for the top-L/10 hydrogen bonds compared with just 0.26 for the baseline MetaPSICOV.

Availability and implementation: MetaPSICOV is available as a freely available web server at http://bioinf.cs.ucl.ac.uk/MetaPSICOV. Raw data (predicted contact lists and 3D models) and source code can be downloaded from http://bioinf.cs.ucl.ac.uk/downloads/MetaPSICOV.

Contact:d.t.jones@ucl.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

The Utility of Fisher's Geometric Model in Evolutionary Genetics

The accumulation of data on the genomic bases of adaptation has triggered renewed interest in theoretical models of adaptation. Among these models, Fisher Geometric Model (FGM) has received a lot of attention over the last two decades. FGM is based on a continuous multidimensional phenotypic landscape, but it is for the emerging properties of individual mutation effects that it is mostly used. Despite an apparent simplicity and a limited number of parameters, FGM integrates a full model of mutation and epistatic interactions that allows the study of both beneficial and deleterious mutations, and subsequently the fate of evolving populations. In this review, I present the different properties of FGM and the qualitative and quantitative support they have received from experimental evolution data. I later discuss how to estimate the different parameters of the model and outline some future directions to connect FGM and the molecular determinants of adaptation.

The genomic landscape of compensatory evolution

The Genomic Landscape of Compensatory Evolution Laboratory selection experiment explains how organisms compensate for the loss of genes during evolution, and reveals the deleterious side-effects of this process when adapting to novel environments.

Adaptive evolution is generally assumed to progress through the accumulation of beneficial mutations. However, as deleterious mutations are common in natural populations, they generate a strong selection pressure to mitigate their detrimental effects through compensatory genetic changes. This process can potentially influence directions of adaptive evolution by enabling evolutionary routes that are otherwise inaccessible. Therefore, the extent to which compensatory mutations shape genomic evolution is of central importance. Here, we studied the capacity of the baker's yeast genome to compensate the complete loss of genes during evolution, and explored the long-term consequences of this process. We initiated laboratory evolutionary experiments with over 180 haploid baker's yeast genotypes, all of which initially displayed slow growth owing to the deletion of a single gene. Compensatory evolution following gene loss was rapid and pervasive: 68% of the genotypes reached near wild-type fitness through accumulation of adaptive mutations elsewhere in the genome. As compensatory mutations have associated fitness costs, genotypes with especially low fitnesses were more likely to be subjects of compensatory evolution. Genomic analysis revealed that as compensatory mutations were generally specific to the functional defect incurred, convergent evolution at the molecular level was extremely rare. Moreover, the majority of the gene expression changes due to gene deletion remained unrestored. Accordingly, compensatory evolution promoted genomic divergence of parallel evolving populations. However, these different evolutionary outcomes are not phenotypically equivalent, as they generated diverse growth phenotypes across environments. Taken together, these results indicate that gene loss initiates adaptive genomic changes that rapidly restores fitness, but this process has substantial pleiotropic effects on cellular physiology and evolvability upon environmental change. Our work also implies that gene content variation across species could be partly due to the action of compensatory evolution rather than the passive loss of genes.

While core cellular processes are generally conserved during evolution, the constituent genes differ somewhat between related species with similar lifestyles. Why should this be so? In this work, we propose that gene loss may initially be deleterious, but organisms can recover fitness by the accumulation of compensatory mutations elsewhere in the genome. To investigate this process in the laboratory, we investigated 180 haploid yeast strains, each of which initially displayed slow growth owing to the deletion of a single gene. Laboratory evolutionary experiments revealed that defects in a broad range of molecular processes can readily be compensated during evolution. Genomic analyses and functional assays demonstrated that compensatory evolution generates hidden genetic and physiological variation across parallel evolving lines, which can be revealed when the environment changes. Strikingly, despite nearly full recovery of fitness, the wild-type genomic expression pattern is generally not restored. Based on these results, we argue that genomes undergo major changes not simply to adapt to external conditions but also to compensate for previously accumulated deleterious mutations.

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.

Fitness benefits of low infectivity in a spatially structured population of bacteriophages

For a parasite evolving in a spatially structured environment, an evolutionarily advantageous strategy may be to reduce its transmission rate or infectivity. We demonstrate this empirically using bacteriophage (phage) from an evolution experiment where spatial structure was maintained over 550 phage generations on agar plates. We found that a single substitution in the major capsid protein led to slower adsorption of phage to host cells with no change in lysis time or burst size. Plaques formed by phage isolates containing this mutation were not only larger but also contained more phage per unit area. Using a spatially explicit, individual-based model, we showed that when there is a trade-off between adsorption and diffusion (i.e. less 'sticky' phage diffuse further), slow adsorption can maximize plaque size, plaque density and overall productivity. These findings suggest that less infective pathogens may have an advantage in spatially structured populations, even when well-mixed models predict that they will not.

Rescue of deleterious mutations by the compensatory Y30F mutation in ketosteroid isomerase

Proteins have evolved to compensate for detrimental mutations. However, compensatory mechanisms for protein defects are not well understood. Using ketosteroid isomerase (KSI), we investigated how second-site mutations could recover defective mutant function and stability. Previous results revealed that the Y30F mutation rescued the Y14F, Y55F and Y14F/Y55F mutants by increasing the catalytic activity by 23-, 3- and 1.3-fold, respectively, and the Y55F mutant by increasing the stability by 3.3 kcal/mol. To better understand these observations, we systematically investigated detailed structural and thermodynamic effects of the Y30F mutation on these mutants. Crystal structures of the Y14F/Y30F and Y14F/Y55F mutants were solved at 2.0 and 1.8 previoulsy solved structures of wild-type and other mutant KSIs. Structural analyses revealed that the Y30F mutation partially restored the active-site cleft of these mutant KSIs. The Y30F mutation also increased Y14F and Y14F/Y55F mutant stability by 3.2 and 4.3 kcal/mol, respectively, and the melting temperatures of the Y14F, Y55F and Y14F/Y55F mutants by 6.4°C, 5.1°C and 10.0°C, respectively. Compensatory effects of the Y30F mutation on stability might be due to improved hydrophobic interactions because removal of a hydroxyl group from Tyr30 induced local compaction by neighboring residue movement and enhanced interactions with surrounding hydrophobic residues in the active site. Taken together, our results suggest that perturbed active-site geometry recovery and favorable hydrophobic interactions mediate the role of Y30F as a secondsite suppressor.

Evolutionary reversals of antibiotic resistance in experimental populations of Pseudomonas aeruginosa

Antibiotic resistance mutations are accompanied by a fitness cost, and two mechanisms allow bacteria to adapt to this cost once antibiotic use is halted. First, it is possible for resistance to revert; second, it is possible for bacteria to adapt to the cost of resistance by compensatory mutations. Unfortunately, reversion to antibiotic sensitivity is rare, but the underlying factors that prevent reversion remain obscure. Here, we directly study the evolutionary dynamics of reversion by experimentally mimicking reversion mutations-sensitives-in populations of rifampicin-resistant Pseudomonas aeruginosa. We show that, in our populations, most sensitives are lost due to genetic drift when they are rare. However, clonal interference from lineages carrying compensatory mutations causes a dramatic increase in the time to fixation of sensitives that escape genetic drift, and mutations surpassing the sensitives' fitness are capable of driving transiently common sensitive lineages to extinction. Crucially, we show that the constraints on reversion arising from clonal interference are determined by the potential for compensatory adaptation of the resistant population. Although the cost of resistance provides the incentive for reversion, our study demonstrates that both the cost of resistance and the intrinsic evolvability of resistant populations interact to determine the rate and likelihood of reversion.

Estimating the rate of irreversibility in protein evolution

Whether or not evolutionary change is inherently irreversible remains a controversial topic. Some examples of evolutionary irreversibility are known; however, this question has not been comprehensively addressed at the molecular level. Here, we use data from 221 human genes with known pathogenic mutations to estimate the rate of irreversibility in protein evolution. For these genes, we reconstruct ancestral amino acid sequences along the mammalian phylogeny and identify ancestral amino acid states that match known pathogenic mutations. Such cases represent inherent evolutionary irreversibility because, at the present moment, reversals to these ancestral amino acid states are impossible for the human lineage. We estimate that approximately 10% of all amino acid substitutions along the mammalian phylogeny are irreversible, such that a return to the ancestral amino acid state would lead to a pathogenic phenotype. For a subset of 51 genes with high rates of irreversibility, as much as 40% of all amino acid evolution was estimated to be irreversible. Because pathogenic phenotypes do not resemble ancestral phenotypes, the molecular nature of the high rate of irreversibility in proteins is best explained by evolution with a high prevalence of compensatory, epistatic interactions between amino acid sites. Under such mode of protein evolution, once an amino acid substitution is fixed, the probability of its reversal declines as the protein sequence accumulates changes that affect the phenotypic manifestation of the ancestral state. The prevalence of epistasis in evolution indicates that the observed high rate of irreversibility in protein evolution is an inherent property of protein structure and function.

Patterns of Epistasis between beneficial mutations in an antibiotic resistance gene

Understanding epistasis is central to biology. For instance, epistatic interactions determine the topography of the fitness landscape and affect the dynamics and determinism of adaptation. However, few empirical data are available, and comparing results is complicated by confounding variation in the system and the type of mutations used. Here, we take a systematic approach by quantifying epistasis in two sets of four beneficial mutations in the antibiotic resistance enzyme TEM-1 β-lactamase. Mutations in these sets have either large or small effects on cefotaxime resistance when present as single mutations. By quantifying the epistasis and ruggedness in both landscapes, we find two general patterns. First, resistance is maximal for combinations of two mutations in both fitness landscapes and declines when more mutations are added due to abundant sign epistasis and a pattern of diminishing returns with genotype resistance. Second, large-effect mutations interact more strongly than small-effect mutations, suggesting that the effect size of mutations may be an organizing principle in understanding patterns of epistasis. By fitting the data to simple phenotype resistance models, we show that this pattern may be explained by the nonlinear dependence of resistance on enzyme stability and an unknown phenotype when mutations have antagonistically pleiotropic effects. The comparison to a previously published set of mutations in the same gene with a joint benefit further shows that the enzyme's fitness landscape is locally rugged but does contain adaptive pathways that lead to high resistance.

The environment affects epistatic interactions to alter the topology of an empirical fitness landscape

The fitness effect of mutations can be influenced by their interactions with the environment, other mutations, or both. Previously, we constructed 32 ( = 2⁵) genotypes that comprise all possible combinations of the first five beneficial mutations to fix in a laboratory-evolved population of Escherichia coli. We found that (i) all five mutations were beneficial for the background on which they occurred; (ii) interactions between mutations drove a diminishing returns type epistasis, whereby epistasis became increasingly antagonistic as the expected fitness of a genotype increased; and (iii) the adaptive landscape revealed by the mutation combinations was smooth, having a single global fitness peak. Here we examine how the environment influences epistasis by determining the interactions between the same mutations in two alternative environments, selected from among 1,920 screened environments, that produced the largest increase or decrease in fitness of the most derived genotype. Some general features of the interactions were consistent: mutations tended to remain beneficial and the overall pattern of epistasis was of diminishing returns. Other features depended on the environment; in particular, several mutations were deleterious when added to specific genotypes, indicating the presence of antagonistic interactions that were absent in the original selection environment. Antagonism was not caused by consistent pleiotropic effects of individual mutations but rather by changing interactions between mutations. Our results demonstrate that understanding adaptation in changing environments will require consideration of the combined effect of epistasis and pleiotropy across environments.

The fitness effect of beneficial mutations can depend on how they interact with their genetic and external environment. The form of these interactions is important because it can alter adaptive outcomes, selecting for or against certain combinations of beneficial mutations. Here, we examine how interactions between beneficial mutations favored during adaptation of a lab strain of Escherichia coli to one simple environment are altered when the strain is grown in two novel environments. We found that fitness effects were greatly influenced by both the genetic and external environments. In several instances a change in environment reversed the effect of a mutation from beneficial to deleterious or caused combinations of beneficial mutations to become deleterious. Our results suggest that a complex or fluctuating environment may favor combinations of mutations whose interactions may be less sensitive to external conditions.

Intrahost mechanisms governing emergence of resistance-breaking variants of Potato virus Y

The emergence of resistance breaking (RB) variants starting from the avirulent Potato virus Y NN strain (PVY(NN)) was analyzed after imposing different selective host constraints. Tobacco resistance to PVY(NN) is conferred by va in both NC745 and VAM genotypes, but VAM carries an extra resistance gene, va2. RB-variants emerged only in NC745 and unexpectedly accumulated higher in the original host, tobacco B21, than the parental PVY(NN). However, the recovery of RB-variants was interfered by PVY(NN) in mixed infections. Further analysis indicated that RB-variants also arose in tobacco VAM, but they were limited to subliminal local infections. Their inability to breakout was associated with absence of a mutational adaptation in the viral VPg gene, which implied a loss of fitness in tobacco B21. Altogether, the emergence of RB-variants was conditioned by inherited host constraints, interference by co-infecting avirulent virus genotypes, and fitness tradeoff of virus adaptations.

Compensatory evolution and the origins of innovations

Cryptic genetic sequences have attenuated effects on phenotypes. In the classic view, relaxed selection allows cryptic genetic diversity to build up across individuals in a population, providing alleles that may later contribute to adaptation when co-opted--e.g., following a mutation increasing expression from a low, attenuated baseline. This view is described, for example, by the metaphor of the spread of a population across a neutral network in genotype space. As an alternative view, consider the fact that most phenotypic traits are affected by multiple sequences, including cryptic ones. Even in a strictly clonal population, the co-option of cryptic sequences at different loci may have different phenotypic effects and offer the population multiple adaptive possibilities. Here, we model the evolution of quantitative phenotypic characters encoded by cryptic sequences and compare the relative contributions of genetic diversity and of variation across sites to the phenotypic potential of a population. We show that most of the phenotypic variation accessible through co-option would exist even in populations with no polymorphism. This is made possible by a history of compensatory evolution, whereby the phenotypic effect of a cryptic mutation at one site was balanced by mutations elsewhere in the genome, leading to a diversity of cryptic effect sizes across sites rather than across individuals. Cryptic sequences might accelerate adaptation and facilitate large phenotypic changes even in the absence of genetic diversity, as traditionally defined in terms of alternative alleles.

Role of transmitted Gag CTL polymorphisms in defining replicative capacity and early HIV-1 pathogenesis

Initial studies of 88 transmission pairs in the Zambia Emory HIV Research Project cohort demonstrated that the number of transmitted HLA-B associated polymorphisms in Gag, but not Nef, was negatively correlated to set point viral load (VL) in the newly infected partners. These results suggested that accumulation of CTL escape mutations in Gag might attenuate viral replication and provide a clinical benefit during early stages of infection. Using a novel approach, we have cloned gag sequences isolated from the earliest seroconversion plasma sample from the acutely infected recipient of 149 epidemiologically linked Zambian transmission pairs into a primary isolate, subtype C proviral vector, MJ4. We determined the replicative capacity (RC) of these Gag-MJ4 chimeras by infecting the GXR25 cell line and quantifying virion production in supernatants via a radiolabeled reverse transcriptase assay. We observed a statistically significant positive correlation between RC conferred by the transmitted Gag sequence and set point VL in newly infected individuals (p = 0.02). Furthermore, the RC of Gag-MJ4 chimeras also correlated with the VL of chronically infected donors near the estimated date of infection (p = 0.01), demonstrating that virus replication contributes to VL in both acute and chronic infection. These studies also allowed for the elucidation of novel sites in Gag associated with changes in RC, where rare mutations had the greatest effect on fitness. Although we observed both advantageous and deleterious rare mutations, the latter could point to vulnerable targets in the HIV-1 genome. Importantly, RC correlated significantly (p = 0.029) with the rate of CD4+ T cell decline over the first 3 years of infection in a manner that is partially independent of VL, suggesting that the replication capacity of HIV-1 during the earliest stages of infection is a determinant of pathogenesis beyond what might be expected based on set point VL alone.

In the majority of HIV-1 cases, a single virus establishes infection. However, mutations in the viral genome accumulate over time in order to avoid recognition by the host immune response. Certain mutations in the main structural protein, Gag, driven by cytotoxic T lymphocytes are detrimental to viral replication, and we showed previously that, upon transmission, viruses with higher numbers of escape mutations in Gag were associated with lower early set point viral loads. We hypothesized that this could be attributed to attenuation of the transmitted virus. Here, we have cloned the gag gene from 149 newly infected individuals from linked transmission pairs into a clade C proviral vector and determined the replicative capacity in vitro. We found that the replicative capacity conferred by the transmitted Gag correlated with set point viral loads in newly infected individuals, as well as with the viral load of the transmitting partner, and we identified previously unrecognized residues associated with increasing and decreasing replicative capacity. Importantly, we demonstrate that transmitted viruses with high replicative capacity cause more rapid CD4+ decline over the first three years, independent of viral load. This suggests that the trajectory of pathogenesis may be affected very early in infection, before adaptive immunity can respond.

Weak selection and protein evolution

The "nearly neutral" theory of molecular evolution proposes that many features of genomes arise from the interaction of three weak evolutionary forces: mutation, genetic drift, and natural selection acting at its limit of efficacy. Such forces generally have little impact on allele frequencies within populations from generation to generation but can have substantial effects on long-term evolution. The evolutionary dynamics of weakly selected mutations are highly sensitive to population size, and near neutrality was initially proposed as an adjustment to the neutral theory to account for general patterns in available protein and DNA variation data. Here, we review the motivation for the nearly neutral theory, discuss the structure of the model and its predictions, and evaluate current empirical support for interactions among weak evolutionary forces in protein evolution. Near neutrality may be a prevalent mode of evolution across a range of functional categories of mutations and taxa. However, multiple evolutionary mechanisms (including adaptive evolution, linked selection, changes in fitness-effect distributions, and weak selection) can often explain the same patterns of genome variation. Strong parameter sensitivity remains a limitation of the nearly neutral model, and we discuss concave fitness functions as a plausible underlying basis for weak selection.

Mutual information and variants for protein domain-domain contact prediction

BACKGROUND

Predicting protein contacts solely based on sequence information remains a challenging problem, despite the huge amount of sequence data at our disposal. Mutual Information (MI), an information theory measure, has been extensively employed and modified to identify residues within a protein (intra-protein) that are in contact. More recently MI and its variants have also been used in the prediction of contacts between proteins (inter-protein).

METHODS

Here we assess the predictive power of MI and variants for domain-domain contact prediction. We test original MI and these variants, which are called MIp, MIc and ZNMI, on 40 domain-domain test cases containing 10,753 sequences. We also propose and evaluate two new versions of MI that consider triangles of residues and the physiochemical properties of the amino acids, respectively.

RESULTS

We found that all versions of MI are skewed towards predicting surface residues. Since domain-domain contacts are on the surface of each domain, we considered only surface residues when attempting to predict contacts. Our analysis shows that MIc is the best current MI domain-domain contact predictor. At 20% recall MIc achieved a precision of 44.9% when only surface residues were considered. Our triangle and reduced alphabet variants of MI highlight the delicate trade-off between signal and noise in the use of MI for domain-domain contact prediction. We also examine a specific "successful" case study and demonstrate that here, when considering surface residues, even the most accurate domain-domain contact predictor, MIc, performs no better than random.

CONCLUSIONS

All tested variants of MI are skewed towards predicting surface residues. When considering surface residues only, we find MIc to be the best current MI domain-domain contact predictor. Its performance, however, is not as good as a non-MI based contact predictor, i-Patch. Additionally, the intra-protein contact prediction capabilities of MIc outperform its domain-domain contact prediction abilities.