Physicochemical Amino Acid Properties Better Describe Substitution Rates in Large Populations

Amino Acid Properties, Substitution Rates, and the Nearly Neutral Theory

Do the properties of amino acids affect their rates of substitution? The neutral theory predicts that greater selective constraint leads to slower rates of evolution; similarly, we expect amino acids that are more different from each other to have lower rates of exchange because such changes are most likely to affect protein structure and function. Here, we test these predictions, using substitution rates estimated from empirical amino acid exchangeability matrices. To measure degree of amino acid difference, we focused on two physicochemical properties, charge and size, uncorrelated metrics that are known to have important implications for protein structure and function. We find that for both charge and size, amino acid pairs with large differences had lower rates of substitution. We also found that amino acids that differed in both properties had the lowest rates of substitution, suggesting that both physicochemical properties are under selective constraint. Mutation properties, such as the number of mutations or the number of transitions as opposed to transversions separating amino acid pairs, were also important predictors of substitution rates. The relationship between amino acid substitution rates and differences in their physiochemical properties holds across several taxonomically restricted datasets. This finding suggests that purifying selection affects amino acid substitution rates in a similar manner across taxonomic groups with different effective population sizes.

How Big Is Big? The Effective Population Size of Marine Bacteria

Genome-reduced bacteria constitute most of the cells in surface-ocean bacterioplankton communities. Their extremely large census population sizes (N c) have been unfoundedly translated to huge effective population sizes (N e)-the size of an ideal population carrying as much neutral genetic diversity as the actual population. As N e scales inversely with the strength of genetic drift, constraining the magnitude of N e is key to evaluating whether natural selection can overcome the power of genetic drift to drive evolutionary events. Determining the N e of extant species requires measuring the genomic mutation rate, a challenging step for most genome-reduced bacterioplankton lineages. Results for genome-reduced Prochlorococcus and CHUG are surprising-their N e values are an order of magnitude lower than those of less abundant lineages carrying large genomes, such as Ruegeria and Vibrio. As bacterioplankton genome reduction commonly occurred in the distant past, appreciating their population genetic mechanisms requires constraining their ancient N e values by other methods.

Molecular evolution and genetic diversity of defective chorion 1 in Anastrepha fraterculus and Anastrepha obliqua (Diptera, Tephritidae)

The family Tephritidae comprises numerous fruit fly species, some of which are economically significant, such as several in the genus Anastrepha. Most pest species in this genus belong to the fraterculus group, characterized by closely related species that are difficult to differentiate due to recent divergence and gene flow. Identifying genetic markers for their study is paramount for understanding the group's evolution and eventual phytosanitary control. Because there is variation in eggshell morphology among species in the genus, the study of the rapidly evolving defective chorion 1 (dec-1) gene, which is crucial for chorion formation and reproduction, could provide relevant information for Anastrepha differentiation. We compared transcriptome sequences of dec-1 from two of the most important pest species in the genus, Anastrepha fraterculus and Anastrepha obliqua to dec-1 sequences from Anastrepha ludens, which was used for structure prediction. Furthermore, we amplified a conserved exon across populations of these species. These data revealed three alternative transcripts in A. fraterculus and A. obliqua, consistent with patterns found in other Tephritidae; we obtained orthologous sequences for these other tephritids from NCBI to investigate patterns of selection affecting this gene at different hierarchical levels using different methods. These analyses show a general pattern of purifying selection across the whole gene and throughout its history at different hierarchical levels, from populations to more distantly related species. That notwithstanding, we still found evidence of positive and episodic diversifying selection at different levels. Different parts of the gene have shown distinct evolutionary rates, which were associated with the diverse proproteins produced by posttranslational changes of DEC-1, with proproteins that are incorporated in the chorion earlier in egg formation being in general more conserved than others that are incorporated later. This correlation appears more evident in certain lineages, including the branch that separates Anastrepha, as well as other internal branches that differentiate species within the genus. Our data showed that this gene shows remarkable variation across its different exons, which has proven to be informative at different evolutionary levels. These changes hold promise not only for studying differentiation in Anastrepha but also for the eventual management of selected pest species.

Disentangling cobionts and contamination in long-read genomic data using sequence composition

The recent acceleration in genome sequencing targeting previously unexplored parts of the tree of life presents computational challenges. Samples collected from the wild often contain sequences from several organisms, including the target, its cobionts, and contaminants. Effective methods are therefore needed to separate sequences. Though advances in sequencing technology make this task easier, it remains difficult to taxonomically assign sequences from eukaryotic taxa that are not well represented in databases. Therefore, reference-based methods alone are insufficient. Here, I examine how we can take advantage of differences in sequence composition between organisms to identify symbionts, parasites, and contaminants in samples, with minimal reliance on reference data. To this end, I explore data from the Darwin Tree of Life project, including hundreds of high-quality HiFi read sets from insects. Visualizing two-dimensional representations of read tetranucleotide composition learned by a variational autoencoder can reveal distinct components of a sample. Annotating the embeddings with additional information, such as coding density, estimated coverage, or taxonomic labels allows rapid assessment of the contents of a dataset. The approach scales to millions of sequences, making it possible to explore unassembled read sets, even for large genomes. Combined with interactive visualization tools, it allows a large fraction of cobionts reported by reference-based screening to be identified. Crucially, it also facilitates retrieving genomes for which suitable reference data are absent.

A fitness distribution law for amino-acid replacements

The effect of replacing the amino acid at a given site in a protein is difficult to predict. Yet, evolutionary comparisons have revealed highly regular patterns of interchangeability between pairs of amino acids, and such patterns have proved enormously useful in a range of applications in bioinformatics, evolutionary inference, and protein design. Here we reconcile these apparently contradictory observations using fitness data from over 350,000 experimental amino acid replacements. Almost one-quarter of the 20 × 19 = 380 types of replacements have broad distributions of fitness effects (DFEs) that closely resemble the background DFE for random changes, indicating an overwhelming influence of protein context in determining mutational effects. However, we also observe that the 380 pair-specific DFEs closely follow a maximum entropy distribution, specifically a truncated exponential distribution. The shape of this distribution is determined entirely by its mean, which is equivalent to the chance that a replacement of the given type is fitter than a random replacement. In this type of distribution, modest deviations in the mean correspond to much larger changes in the probability of falling in the far right tail, so that modest differences in mean exchangeability may result in much larger differences in the chance of a highly fit mutation. Indeed, we show that under the assumption that purifying selection filters out the vast majority of mutations, the maximum entropy distributions of fitness effects inferred from deep mutational scanning experiments predict the characteristic patterns of amino acid change observed in molecular evolution. These maximum entropy distributions of mutational effects not only provide a tuneable model for molecular evolution, but also have implications for mutational effect prediction and protein engineering.

Moderating the neutralist-selectionist debate: exactly which propositions are we debating, and which arguments are valid?

Half a century after its foundation, the neutral theory of molecular evolution continues to attract controversy. The debate has been hampered by the coexistence of different interpretations of the core proposition of the neutral theory, the 'neutral mutation-random drift' hypothesis. In this review, we trace the origins of these ambiguities and suggest potential solutions. We highlight the difference between the original, the revised and the nearly neutral hypothesis, and re-emphasise that none of them equates to the null hypothesis of strict neutrality. We distinguish the neutral hypothesis of protein evolution, the main focus of the ongoing debate, from the neutral hypotheses of genomic and functional DNA evolution, which for many species are generally accepted. We advocate a further distinction between a narrow and an extended neutral hypothesis (of which the latter posits that random non-conservative amino acid substitutions can cause non-ecological phenotypic divergence), and we discuss the implications for evolutionary biology beyond the domain of molecular evolution. We furthermore point out that the debate has widened from its initial focus on point mutations, and also concerns the fitness effects of large-scale mutations, which can alter the dosage of genes and regulatory sequences. We evaluate the validity of neutralist and selectionist arguments and find that the tested predictions, apart from being sensitive to violation of underlying assumptions, are often derived from the null hypothesis of strict neutrality, or equally consistent with the opposing selectionist hypothesis, except when assuming molecular panselectionism. Our review aims to facilitate a constructive neutralist-selectionist debate, and thereby to contribute to answering a key question of evolutionary biology: what proportions of amino acid and nucleotide substitutions and polymorphisms are adaptive?

Phylogenetic analyses of 5-hydroxytryptamine 3 (5-HT3) receptors in Metazoa

The 5-hydroxytrptamine 3 (5-HT3) receptor is a member of the 'Cys-loop' family and the only pentameric ligand gated ion channel among the serotonin receptors. 5-HT3 receptors play an important role in controlling growth, development, and behaviour in animals. Several 5-HT3 receptor antagonists are used to treat diseases (e.g., irritable bowel syndrome, nausea and emesis). Humans express five different subunits (A-E) enabling a variety of heteromeric receptors to form but all contain 5HT3A subunits. However, the information available about the 5-HT3 receptor subunit occurrence among the metazoan lineages is minimal. In the present article we searched for 5-HT3 receptor subunit homologs from different phyla in Metazoa. We identified more than 1000 5-HT3 receptor subunits in Metazoa in different phyla and undertook simultaneous phylogenetic analysis of 526 5HT3A, 358 5HT3B, 239 5HT3C, 70 5HT3D, and 173 5HT3E sequences. 5-HT3 receptor subunits were present in species belonging to 11 phyla: Annelida, Arthropoda, Chordata, Cnidaria, Echinodermata, Mollusca, Nematoda, Orthonectida, Platyhelminthes, Rotifera and Tardigrada. All subunits were most often identified in Chordata phylum which was strongly represented in searches. Using multiple sequence alignment, we investigated variations in the ligand binding region of the 5HT3A subunit protein sequences in the metazoan lineage. Several critical amino acid residues important for ligand binding (common structural features) are commonly present in species from Nematoda and Platyhelminth gut parasites through to Chordata. Collectively, this better understanding of the 5-HT3 receptor evolutionary patterns raises possibilities of future pharmacological challenges facing Metazoa including effects on parasitic and other species in ecosystems that contain 5-HT3 receptor ligands.

Proteome-Wide Structural Computations Provide Insights into Empirical Amino Acid Substitution Matrices

The relative contribution of mutation and selection to the amino acid substitution rates observed in empirical matrices is unclear. Herein, we present a neutral continuous fitness-stability model, inspired by the Arrhenius law (qij=aije-ΔΔGij). The model postulates that the rate of amino acid substitution (i→j) is determined by the product of a pre-exponential factor, which is influenced by the genetic code structure, and an exponential term reflecting the relative fitness of the amino acid substitutions. To assess the validity of our model, we computed changes in stability of 14,094 proteins, for which 137,073,638 in silico mutants were analyzed. These site-specific data were summarized into a 20 square matrix, whose entries, ΔΔGij, were obtained after averaging through all the sites in all the proteins. We found a significant positive correlation between these energy values and the disease-causing potential of each substitution, suggesting that the exponential term accurately summarizes the fitness effect. A remarkable observation was that amino acids that were highly destabilizing when acting as the source, tended to have little effect when acting as the destination, and vice versa (source → destination). The Arrhenius model accurately reproduced the pattern of substitution rates collected in the empirical matrices, suggesting a relevant role for the genetic code structure and a tuning role for purifying selection exerted via protein stability.

dN/dS-H, a New Test to Distinguish Different Selection Modes in Protein Evolution and Cancer Evolution

One of the most popular measures in the analysis of protein sequence evolution is the ratio of nonsynonymous distance (d_N) to synonymous distance (d_S). Under the assumption that synonymous substitutions in the coding region are selectively neutral, the d_N/d_S ratio can be used to statistically detect the adaptive evolution (or purifying selection) if d_N/d_S > 1 (or d_N/d_S < 1) significantly. However, due to strong structural constraints and/or variable functional constraints imposed on amino acid sites, most encoding genes in most species have demonstrated d_N/d_S < 1. Consequently, the statistical power for testing d_N/d_S = 1 may be insufficient to distinguish between different selection modes. In this paper, we propose a more powerful test, called d_N/d_S-H, in which a new parameter H, a relative measure of rate variation among sites, was introduced. Given the condition of strong purifying selections at some sites, the d_N/d_S-H model predicts d_N/d_S = 1-H for neutral evolution, d_N/d_S < 1-H for nearly neutral selection, and d_N/d_S > 1-H for adaptive evolution. The potential of this new method for resolving the neutral-adaptive debates is illustrated by the protein sequence evolution in vertebrates, Drosophila and yeasts, as well as somatic cancer evolution (specialized as the C_N/C_S-H test).

Hotspots for mutations in the SARS-CoV-2 spike glycoprotein: a correspondence analysis

Spike glycoprotein (Sgp) is liable for binding of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the host receptors. Since Sgp is the main target for vaccine and drug designing, elucidating its mutation pattern could help in this regard. This study is aimed at investigating the correspondence of specific residues to the SgpSARS-CoV-2 functionality by explorative interpretation of sequence alignments. Centrality analysis of the Sgp dissects the importance of these residues in the interaction network of the RBD-ACE2 (receptor-binding domain) complex and furin cleavage site. Correspondence of RBD to threonine500 and asparagine501 and furin cleavage site to glutamine675, glutamine677, threonine678, and alanine684 was observed; all residues are exactly located at the interaction interfaces. The harmonious location of residues dictates the RBD binding property and the flexibility, hydrophobicity, and accessibility of the furin cleavage site. These species-specific residues can be assumed as real targets of evolution, while other substitutions tend to support them. Moreover, all these residues are parts of experimentally identified epitopes. Therefore, their substitution may affect vaccine efficacy. Higher rate of RBD maintenance than furin cleavage site was predicted. The accumulation of substitutions reinforces the probability of the multi-host circulation of the virus and emphasizes the enduring evolutionary events.

Causes and Consequences of Purifying Selection on SARS-CoV-2

Owing to a lag between a deleterious mutation's appearance and its selective removal, gold-standard methods for mutation rate estimation assume no meaningful loss of mutations between parents and offspring. Indeed, from analysis of closely related lineages, in SARS-CoV-2, the Ka/Ks ratio was previously estimated as 1.008, suggesting no within-host selection. By contrast, we find a higher number of observed SNPs at 4-fold degenerate sites than elsewhere and, allowing for the virus's complex mutational and compositional biases, estimate that the mutation rate is at least 49-67% higher than would be estimated based on the rate of appearance of variants in sampled genomes. Given the high Ka/Ks one might assume that the majority of such intrahost selection is the purging of nonsense mutations. However, we estimate that selection against nonsense mutations accounts for only ∼10% of all the "missing" mutations. Instead, classical protein-level selective filters (against chemically disparate amino acids and those predicted to disrupt protein functionality) account for many missing mutations. It is less obvious why for an intracellular parasite, amino acid cost parameters, notably amino acid decay rate, is also significant. Perhaps most surprisingly, we also find evidence for real-time selection against synonymous mutations that move codon usage away from that of humans. We conclude that there is common intrahost selection on SARS-CoV-2 that acts on nonsense, missense, and possibly synonymous mutations. This has implications for methods of mutation rate estimation, for determining times to common ancestry and the potential for intrahost evolution including vaccine escape.

Are Nonsynonymous Transversions Generally More Deleterious than Nonsynonymous Transitions?

It has been suggested that, due to the structure of the genetic code, nonsynonymous transitions are less likely than transversions to cause radical changes in amino acid physicochemical properties so are on average less deleterious. This view was supported by some but not all mutagenesis experiments. Because laboratory measures of fitness effects have limited sensitivities and relative frequencies of different mutations in mutagenesis studies may not match those in nature, we here revisit this issue using comparative genomics. We extend the standard codon model of sequence evolution by adding the parameter η that quantifies the ratio of the fixation probability of transitional nonsynonymous mutations to that of transversional nonsynonymous mutations. We then estimate η from the concatenated alignment of all protein-coding DNA sequences of two closely related genomes. Surprisingly, η ranges from 0.13 to 2.0 across 90 species pairs sampled from the tree of life, with 51 incidences of η < 1 and 30 incidences of η >1 that are statistically significant. Hence, whether nonsynonymous transversions are overall more deleterious than nonsynonymous transitions is species-dependent. Because the corresponding groups of amino acid replacements differ between nonsynonymous transitions and transversions, η is influenced by the relative exchangeabilities of amino acid pairs. Indeed, an extensive search reveals that the large variation in η is primarily explainable by the recently reported among-species disparity in amino acid exchangeabilities. These findings demonstrate that genome-wide nucleotide substitution patterns in coding sequences have species-specific features and are more variable among evolutionary lineages than are currently thought.

Patterns and Causes of Signed Linkage Disequilibria in Flies and Plants

Most empirical studies of linkage disequilibrium (LD) study its magnitude, ignoring its sign. Here, we examine patterns of signed LD in two population genomic data sets, one from Capsella grandiflora and one from Drosophila melanogaster. We consider how processes such as drift, admixture, Hill–Robertson interference, and epistasis may contribute to these patterns. We report that most types of mutations exhibit positive LD, particularly, if they are predicted to be less deleterious. We show with simulations that this pattern arises easily in a model of admixture or distance-biased mating, and that genome-wide differences across site types are generally expected due to differences in the strength of purifying selection even in the absence of epistasis. We further explore how signed LD decays on a finer scale, showing that loss of function mutations exhibit particularly positive LD across short distances, a pattern consistent with intragenic antagonistic epistasis. Controlling for genomic distance, signed LD in C. grandiflora decays faster within genes, compared with between genes, likely a by-product of frequent recombination in gene promoters known to occur in plant genomes. Finally, we use information from published biological networks to explore whether there is evidence for negative synergistic epistasis between interacting radical missense mutations. In D. melanogaster networks, we find a modest but significant enrichment of negative LD, consistent with the possibility of intranetwork negative synergistic epistasis.

Partial DnaK protein expression from Coxiella-like endosymbiont of Rhipicephalus annulatus tick

Q fever is one of the most important zoonotic diseases caused by the obligate intracellular bacteria, Coxiella burnetii. This bacterial infection has been frequently reported in both humans and animals, especially ruminants. Ticks are important ectoparasite and serve as reservoir hosts of Coxiella-like endosymbionts (CLEs). In this study, we have attempted to express chaperone-coding genes from CLEs of Rhipicephalus annulatus ticks collected fromcow path. The partial DnaK coding sequence has been amplified and expressed by Escherichia coli. Amino acid sequences have been analyzed by MS-MS spectrometry and the UniProt database. Despites nucleotide sequences indicating high nucleotide variation and diversity, many nucleotide substitutions are synonymous. In addition, amino acid substitutions compensate for the physicochemical properties of the original amino acids. Immune Epitope Database and Analysis Resource (IEDB-AR) was employed to indicate the antigenicity of the partial DnaK protein and predict the epitopes of B-and T-cells. Interestingly, some predicted HLA-A and B alleles of the MHC-I and HLA-DR alleles belonging to MHC-II were similar to T-cell responses to C. burnetii in Q fever patients. Therefore, the partial DnaK protein of CLE from R. annulatus could be considered a vaccine candidate and immunogenic marker with future prospects.

DGINN, an automated and highly-flexible pipeline for the detection of genetic innovations on protein-coding genes

Adaptive evolution has shaped major biological processes. Finding the protein-coding genes and the sites that have been subjected to adaptation during evolutionary time is a major endeavor. However, very few methods fully automate the identification of positively selected genes, and widespread sources of genetic innovations such as gene duplication and recombination are absent from most pipelines. Here, we developed DGINN, a highly-flexible and public pipeline to Detect Genetic INNovations and adaptive evolution in protein-coding genes. DGINN automates, from a gene's sequence, all steps of the evolutionary analyses necessary to detect the aforementioned innovations, including the search for homologs in databases, assignation of orthology groups, identification of duplication and recombination events, as well as detection of positive selection using five methods to increase precision and ranking of genes when a large panel is analyzed. DGINN was validated on nineteen genes with previously-characterized evolutionary histories in primates, including some engaged in host-pathogen arms-races. Our results confirm and also expand results from the literature, including novel findings on the Guanylate-binding protein family, GBPs. This establishes DGINN as an efficient tool to automatically detect genetic innovations and adaptive evolution in diverse datasets, from the user's gene of interest to a large gene list in any species range.

Ambiguity Coding Allows Accurate Inference of Evolutionary Parameters from Alignments in an Aggregated State-Space

How can we best learn the history of a protein’s evolution? Ideally, a model of sequence evolution should capture both the process that generates genetic variation and the functional constraints determining which changes are fixed. However, in practical terms the most suitable approach may simply be the one that combines the convenience of easily available input data with the ability to return useful parameter estimates. For example, we might be interested in a measure of the strength of selection (typically obtained using a codon model) or an ancestral structure (obtained using structural modeling based on inferred amino acid sequence and side chain configuration).

But what if data in the relevant state-space are not readily available? We show that it is possible to obtain accurate estimates of the outputs of interest using an established method for handling missing data. Encoding observed characters in an alignment as ambiguous representations of characters in a larger state-space allows the application of models with the desired features to data that lack the resolution that is normally required. This strategy is viable because the evolutionary path taken through the observed space contains information about states that were likely visited in the “unseen” state-space. To illustrate this, we consider two examples with amino acid sequences as input. We show that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$$\omega$$\end{document}, a parameter describing the relative strength of selection on nonsynonymous and synonymous changes, can be estimated in an unbiased manner using an adapted version of a standard 61-state codon model. Using simulated and empirical data, we find that ancestral amino acid side chain configuration can be inferred by applying a 55-state empirical model to 20-state amino acid data. Where feasible, combining inputs from both ambiguity-coded and fully resolved data improves accuracy. Adding structural information to as few as 12.5% of the sequences in an amino acid alignment results in remarkable ancestral reconstruction performance compared to a benchmark that considers the full rotamer state information. These examples show that our methods permit the recovery of evolutionary information from sequences where it has previously been inaccessible. [Ancestral reconstruction; natural selection; protein structure; state-spaces; substitution models.]

Molecular Evolution in Small Steps under Prevailing Negative Selection: A Nearly Universal Rule of Codon Substitution

The widely accepted view that evolution proceeds in small steps is based on two premises: 1) negative selection acts strongly against large differences and 2) positive selection favors small-step changes. The two premises are not biologically connected and should be evaluated separately. We now extend a previous approach to studying codon evolution in the entire genome. Codon substitution rate is a function of the physicochemical distance between amino acids (AAs), equated with the step size of evolution. Between nine pairs of closely related species of plants, invertebrates, and vertebrates, the evolutionary rate is strongly and negatively correlated with a set of AA distances (Δ_U, scaled to [0, 1]). Δ_U, a composite measure of evolutionary rates across diverse taxa, is influenced by almost all of the 48 physicochemical properties used here. The new analyses reveal a crucial trend hidden from previous studies: Δ_U is strongly correlated with the evolutionary rate (R² > 0.8) only when the genes are predominantly under negative selection. Because most genes in most taxa are strongly constrained by negative selection, Δ_U has indeed appeared to be a nearly universal measure of codon evolution. In conclusion, molecular evolution at the codon level generally takes small steps due to the prevailing negative selection. Whether positive selection may, or may not, follow the small-step rule is addressed in a companion study.

Characterizing lineage-specific evolution and the processes driving genomic diversification in chordates

Background

Understanding the origins of genome content has long been a goal of molecular evolution and comparative genomics. By examining genome evolution through the guise of lineage-specific evolution, it is possible to make inferences about the evolutionary events that have given rise to species-specific diversification. Here we characterize the evolutionary trends found in chordate species using The Adaptive Evolution Database (TAED). TAED is a database of phylogenetically indexed gene families designed to detect episodes of directional or diversifying selection across chordates. Gene families within the database have been assessed for lineage-specific estimates of dN/dS and have been reconciled to the chordate species to identify retained duplicates. Gene families have also been mapped to the functional pathways and amino acid changes which occurred on high dN/dS lineages have been mapped to protein structures.

Results

An analysis of this exhaustive database has enabled a characterization of the processes of lineage-specific diversification in chordates. A pathway level enrichment analysis of TAED determined that pathways most commonly found to have elevated rates of evolution included those involved in metabolism, immunity, and cell signaling. An analysis of protein fold presence on proteins, after normalizing for frequency in the database, found common folds such as Rossmann folds, Jelly Roll folds, and TIM barrels were overrepresented on proteins most likely to undergo directional selection. A set of gene families which experience increased numbers of duplications within short evolutionary times are associated with pathways involved in metabolism, olfactory reception, and signaling. An analysis of protein secondary structure indicated more relaxed constraint in β-sheets and stronger constraint on alpha Helices, amidst a general preference for substitutions at exposed sites. Lastly a detailed analysis of the ornithine decarboxylase gene family, a key enzyme in the pathway for polyamine synthesis, revealed lineage-specific evolution along the lineage leading to Cetacea through rapid sequence evolution in a duplicate gene with amino acid substitutions causing active site rearrangement.

Conclusion

Episodes of lineage-specific evolution are frequent throughout chordate species. Both duplication and directional selection have played large roles in the evolution of the phylum. TAED is a powerful tool for facilitating this understanding of lineage-specific evolution.

Intracellular pH dynamics and charge-changing somatic mutations in cancer

An unresolved question critical for understanding cancer is how recurring somatic mutations are retained and how selective pressures drive retention. Increased intracellular pH (pHi) is common to most cancers and is an early event in cancer development. Recent work shows that recurrent somatic mutations can confer an adaptive gain in pH sensing to mutant proteins, enhancing tumorigenic phenotypes specifically at the increased pHi of cancer. Newly identified amino acid mutation signatures in cancer suggest charge-changing mutations define and shape the mutational landscape of cancer. Taken together, these results support a new perspective on the functional significance of somatic mutations in cancer. In this review, we explore existing data and new directions for better understanding how changes in dynamic pH sensing by somatic mutation might be conferring a fitness advantage to the high pH of cancer.