Evolutionary genomics: codon bias and selection on single genomes

Detection of positive selection acting on protein surfaces at the whole-genome scale in the human malaria parasite Plasmodium falciparum

The host-parasite evolutionary arms race is a fundamental process with medical implications. During this process, the host develops parasite resistance, and the parasite develops host immune evasion strategies. Thus, this process accelerates relevant protein evolution. This study test hypothesizes that proteins subject to sequence evolution structural constraints play a crucial role and that these constraints hinder the modification of such proteins in this process. These hypotheses were tested using Plasmodium falciparum model and evaluated protein structures predicted for the entire proteome by the AlphaFold method. Based on dN/dS test results and P. falciparum and P. reichenowi comparisons, the presented approach identified proteins subject to purifying selection acting on the whole sequence and buried residues (dN < dS) and positive selection on nonburied residues. Of the 26 proteins, some known antigens (ring-exported protein 3, RAP protein, erythrocyte binding antigen-140, and protein P47) targeted by the host immune system are promising vaccine candidates. The set also contained 11 enzymes, including FIKK kinase, which modifies host proteins. This set was compared with genes for which the dN/dS test suggested that positive selection acts on the whole gene (i.e., dN > dS). The present study found that such genes encode enzymes and antigenic vaccine candidates less frequently than genes for which evolution is not subject to selection constraints and positive selection acts on only exposed residues. The analysis was repeated comparing P. falciparum with P. alderi, which is more distantly related. The study discusses the potential implications of the presented methodology for rational vaccine design and the parasitology and evolutionary biology fields.

Integrated analysis of individual codon contribution to protein biosynthesis reveals a new approach to improving the basis of rational gene design

Gene codon optimization may be impaired by the misinterpretation of frequency and optimality of codons. Although recent studies have revealed the effects of codon usage bias (CUB) on protein biosynthesis, an integrated perspective of the biological role of individual codons remains unknown. Unlike other previous studies, we show, through an integrated framework that attributes of codons such as frequency, optimality and positional dependency should be combined to unveil individual codon contribution for protein biosynthesis. We designed a codon quantification method for assessing CUB as a function of position within genes with a novel constraint: the relativity of position-dependent codon usage shaped by coding sequence length. Thus, we propose a new way of identifying the enrichment, depletion and non-uniform positional distribution of codons in different regions of yeast genes. We clustered codons that shared attributes of frequency and optimality. The cluster of non-optimal codons with rare occurrence displayed two remarkable characteristics: higher codon decoding time than frequent-non-optimal cluster and enrichment at the 5'-end region, where optimal codons with the highest frequency are depleted. Interestingly, frequent codons with non-optimal adaptation to tRNAs are uniformly distributed in the Saccharomyces cerevisiae genes, suggesting their determinant role as a speed regulator in protein elongation.

In Arabidopsis thaliana codon volatility scores reflect GC3 composition rather than selective pressure

BACKGROUND

Synonymous codon usage bias has typically been correlated with, and attributed to translational efficiency. However, there are other pressures on genomic sequence composition that can affect codon usage patterns such as mutational biases. This study provides an analysis of the codon usage patterns in Arabidopsis thaliana in relation to gene expression levels, codon volatility, mutational biases and selective pressures.

RESULTS

We have performed synonymous codon usage and codon volatility analyses for all genes in the A. thaliana genome. In contrast to reports for species from other kingdoms, we find that neither codon usage nor volatility are correlated with selection pressure (as measured by dN/dS), nor with gene expression levels on a genome wide level. Our results show that codon volatility and usage are not synonymous, rather that they are correlated with the abundance of G and C at the third codon position (GC3).

CONCLUSIONS

Our results indicate that while the A. thaliana genome shows evidence for synonymous codon usage bias, this is not related to the expression levels of its constituent genes. Neither codon volatility nor codon usage are correlated with expression levels or selective pressures but, because they are directly related to the composition of G and C at the third codon position, they are the result of mutational bias. Therefore, in A. thaliana codon volatility and usage do not result from selection for translation efficiency or protein functional shift as measured by positive selection.

POSITIVE DARWINIAN SELECTION: DOES THE COMPARATIVE METHOD RULE?

To detect positive Darwinian selection it is thought essential to compare two sequences. Despite its defects, "the comparative method rules." However, genes evolving rapidly under positive selection conflict more with internal forces (the genome phenotype) than genes evolving slowly under negative selection. In particular, there is conflict with stem-loop potential. The conflict between protein-encoding potential (primary information) and stem-loop potential (secondary information) permits detection of positive selection in a single sequence. The degree to which secondary information is compromised provides a measure of the speed of transmission of primary information. Thus, the sovereignty of the comparative method is challenged not only by its own defects, but also by the availability of a single-sequence method. However, while of limited utility for positive selection, the comparative method casts new light on Darwin's great question — the origin of species. Comparison of rates of synonymous and non-synonymous mutation suggests that branching into new species begins with synonymous mutations.

Genetic robustness at the codon level as a measure of selection

Selection at the DNA level is usually detected by analysing substitution rates from multiple-species comparisons. It has been suggested that measures of genetic robustness at the codon level, which can be measured by analysing a single coding sequence, can be used to estimate selection, but the validity of these measures has been questioned. Here I test the efficiency of different measures of genetic robustness at the codon level to estimate the level of selection acting on a gene. I find that volatility and other measures of robustness are correlated with dN/dS, and that this is not simply the effect of a preference for translationally optimal codons. I discuss the possible implications and the possible problems of these methods based on single-sequence codon usage analysis.

An exploration of the genetic robustness landscape of surface protein families in the human protozoan parasite Trypanosoma cruzi

The ability of genes to be robust to mutations at the codon level has been suggested as a key factor for understanding adaptation features. It has been proposed that genes relevant to host-parasite interactions will tend to exhibit high volatility or "antirobust" patterns, which may be related to the capacity of the parasite to evade the host immune system. We compared two superfamilies of surface proteins, trans-sialidase (TS)-like proteins and putative surface protein dispersed gene family-1 (DGF-1), in the parasite Trypanosoma cruzi in terms of a measure of gene volatility. We proposed alternative codon robustness indicators based on cross entropy and impurity of amino acids encoded by point-mutations, which were compared to a volatility estimator previously published. This allowed us to present a more detailed description of the differences between families. A significant difference was observed in terms of these scores, with the TS-MVar1 and the DGF-1 families showing the highest and lowest gene volatility values respectively. The cross entropy and impurity estimators suggest that the MVar1 levels of volatility are linearly correlated with their capacity to generate diverse sets of amino acids as a consequence of potential mutations. This study indicates the feasibility of applying different measures of genetic robustness to detect variations between potential drug targets at the protein level.

Codon usage and selection on proteins

Selection pressures on proteins are usually measured by comparing homologous nucleotide sequences (Zuckerkandl and Pauling 1965). Recently we introduced a novel method, termed volatility, to estimate selection pressures on proteins on the basis of their synonymous codon usage (Plotkin and Dushoff 2003; Plotkin et al. 2004). Here we provide a theoretical foundation for this approach. Under the Fisher-Wright model, we derive the expected frequencies of synonymous codons as a function of the strength of selection on amino acids, the mutation rate, and the effective population size. We analyze the conditions under which we can expect to draw inferences from biased codon usage, and we estimate the time scales required to establish and maintain such a signal. We find that synonymous codon usage can reliably distinguish between negative selection and neutrality only for organisms, such as some microbes, that experience large effective population sizes or periods of elevated mutation rates. The power of volatility to detect positive selection is also modest--requiring approximately 100 selected sites--but it depends less strongly on population size. We show that phenomena such as transient hyper-mutators can improve the power of volatility to detect selection, even when the neutral site heterozygosity is low. We also discuss several confounding factors, neglected by the Fisher-Wright model, that may limit the applicability of volatility in practice.

Differences in potential for amino acid change after mutation reveals distinct strategies for kappa and lambda light-chain variation

B cells generate varied yet functional clones under high rates of mutation of their V genes. It has been proposed that as a result of the opposing demands of diversification and preservation of integrity, the V genes of heavy and light chains have evolved to overexpress codons prone to amino acid change in their complementarity determining regions (CDR) compared with the framework (FW) regions. We have analyzed the germ-line V genes of heavy and light chains (both kappa and lambda), comparing codons of CDR and FW of the germ-line V regions both to each other and to control regions. We found that in both germ-line heavy chains and lambda chains, CDR codons are prone to replacement mutations, whereas in the FW, the opposite is true. Furthermore, the difference between CDR and FW in heavy chains and lambda chains is based on codons that are prone to nonconservative changes of amino acid. In contrast, in germ-line kappa chains, the codons in both CDR and FW are more prone to replacement mutations. We also demonstrated that negative selection during immune responses is more sensitive to nonconservative amino acid substitutions than overall amino acid change, demonstrating the applicability of our analysis to real-time process of selection in the immune system. The differences in germ-line kappa and lambda light chains' potential reaction to mutation suggests that via these two differently evolved light-chain types, the B cell repertoire encompasses two different strategies to balance diversity and stability in an immune response.

A systematic map of genetic variation in Plasmodium falciparum

Discovering novel genes involved in immune evasion and drug resistance in the human malaria parasite, Plasmodium falciparum, is of critical importance to global health. Such knowledge may assist in the development of new effective vaccines and in the appropriate use of antimalarial drugs. By performing a full-genome scan of allelic variability in 14 field and laboratory strains of P. falciparum, we comprehensively identified ≈500 genes evolving at higher than neutral rates. The majority of the most variable genes have paralogs within the P. falciparum genome and may be subject to a different evolutionary clock than those without. The group of 211 variable genes without paralogs contains most known immunogens and a few drug targets, consistent with the idea that the human immune system and drug use is driving parasite evolution. We also reveal gene-amplification events including one surrounding pfmdr1, the P. falciparum multidrug-resistance gene, and a previously uncharacterized amplification centered around the P. falciparum GTP cyclohydrolase gene, the first enzyme in the folate biosynthesis pathway. Although GTP cyclohydrolase is not the known target of any current drugs, downstream members of the pathway are targeted by several widely used antimalarials. We speculate that an amplification of the GTP cyclohydrolase enzyme in the folate biosynthesis pathway may increase flux through this pathway and facilitate parasite resistance to antifolate drugs.

Variability in the genome of the human malaria parasite, Plasmodium falciparum, is key to the parasite's ability to cause disease and overcome therapeutic interventions such as drugs and vaccines. Elucidating the extent of genetic variation in the malaria parasite will therefore be central to decreasing the malaria disease burden. The authors performed a full-genome scan of variability in different strains of P. falciparum and observed a nonrandom distribution of variation. In particular, those genes that are predicted to have roles in evading the host immune response or antimalarial drugs show significantly higher levels of variation. In addition, the authors speculate that a previously unreported genome amplification in the folate biosynthesis pathway correlates with resistance to the antimalarial drug sulfadoxine. Such data enable hypotheses to be made about the function of many of the unknown elements in the parasite's genome, which may permit the identification of new targets that can be investigated for incorporation into a malaria vaccine and may aid in the understanding of how the parasite withstands drug pressure.

Genetic robustness and selection at the protein level for synonymous codons

Synonymous codons are neutral at the protein level, therefore natural selection at the protein level should have no effect on their frequencies. Synonymous codons, however, differ in their capacity to reduce the effects of errors: after mutation, certain codons keep on coding for the same amino acid or for amino acids with similar properties, while other synonymous codons produce very different amino acids. Therefore, the impact of errors on a coding sequence (genetic robustness) can be measured by analysing its codon usage. I analyse the codon usage of sequenced nuclear and cytoplasmic genomes and I show that there is an extensive variation in genetic robustness at the DNA sequence level, both among genomes and among genes of the same genome. I also show theoretically that robustness can be adaptive, that is natural selection may lead to a preference for codons that reduce the impact of errors. If selection occurs only among the mutants of a codon (e.g. among the progeny before the adult phase), however, the codons that are more sensitive to the effects of mutations may increase in frequency because they manage to get rid more easily of deleterious mutations. I also suggest other possible explanations for the evolution of genetic robustness at the codon level.

Estimating selection pressures from limited comparative data

We recently introduced a novel method for estimating selection pressures on proteins, termed "volatility," which requires only a single genome sequence. Some criticisms that have been levied against this approach are valid, but many others are based on misconceptions of volatility, or they apply equally to comparative methods of estimating selection. Here, we introduce a simple regression technique for estimating selection pressures on all proteins in a genome, on the basis of limited comparative data. The regression technique does not depend on an underlying population-genetic mechanism. This new approach to estimating selection across a genome should be more powerful and more widely applicable than volatility itself.

A new method for estimating nonsynonymous substitutions and its applications to detecting positive selection

The standard methods for computing the number of nonsynonymous substitutions (Ka) lump all amino acid changes into one single class, even though their rates of substitution vary by at least 10-fold (Tang et al., 2004). Classifying these changes by their physicochemical properties has not been suitably effective in isolating the fastest evolving classes of changes. We now propose to use the Universal index U of Tang et al. (2004) to classify the 75 elementary amino acid changes (codons differing by 1 bp) by their evolutionary exchangeability. Let Ki denote the Ka value of each class (i = 1, ..., 75 from the most to the least exchangeable). The cumulative Ki for the top 10 classes, denoted Kh (for high-exchangeability types), has two important properties: (1) Kh usually accounts for 25%-30% of total amino acid changes and (2) when the observed number of amino acid substitutions is large, Kh is predictably twice the value of Ka. This shall be referred to as the twofold approximation. The new method for estimating Kh is applied to the comparisons between human and macaque and between mouse and rat. The twofold approximation holds well in these data sets, and the signature of positive selection can be more easily discerned using the Kh statistic than using Ka. Many genes with Ka/Ks > 0.5 can now be shown to have Kh/Ks > 1 and to have evolved adaptively, at least for the high-exchangeability group of amino acid changes.

Evolution of genetic potential

Organisms employ a multitude of strategies to cope with the dynamical environments in which they live. Homeostasis and physiological plasticity buffer changes within the lifetime of an organism, while stochastic developmental programs and hypermutability track changes on longer time-scales. An alternative long-term mechanism is "genetic potential"--a heightened sensitivity to the effects of mutation that facilitates rapid evolution to novel states. Using a transparent mathematical model, we illustrate the concept of genetic potential and show that as environmental variability decreases, the evolving population reaches three distinct steady state conditions: (1) organismal flexibility, (2) genetic potential, and (3) genetic robustness. As a specific example of this concept we examine fluctuating selection for hydrophobicity in a single amino acid. We see the same three stages, suggesting that environmental fluctuations can produce allele distributions that are distinct not only from those found under constant conditions, but also from the transient allele distributions that arise under isolated selective sweeps.

Codon volatility does not reflect selective pressure on the HIV-1 genome

Codon volatility is defined as the proportion of a codon's point-mutation neighbors that encode different amino acids. The cumulative volatility of a gene in relation to its associated genome was recently reported to be an indicator of selection pressure. We used this approach to measure selection on all available full-length HIV-1 subtype B genomes in the Los Alamos HIV Sequence Database, and compared these estimates against those obtained via established likelihood- and distance-based comparative methods. Volatility failed to correlate with the results of any of the comparative methods demonstrating that it is not a reliable indicator of selection pressure.

A dissection of volatility in yeast

It has been suggested that volatility, the proportion of mutations which change an amino acid, can be used to infer the level of natural selection acting upon a gene. This conjecture is supported by a correlation between volatility and the rate of nonsynonymous substitution (dN), or the ratio of nonsynonymous and synonymous substitution rates, in a variety of organisms. These organisms include yeast, in which the correlations are quite strong. Here we show that these correlations are a by-product of a correlation between synonymous codon bias toward translationally optimal codons and dN. Although this analysis suggests that volatility is not a good measure of the selection, we suggest that it might be possible to infer something about the level of natural selection, from a single genome sequence, using translational codon bias.