Determinants of the rate of protein sequence evolution

Metabolic Determinants of Enzyme Evolution in a Genome-Scale Bacterial Metabolic Network

Different genes and proteins evolve at very different rates. To identify the factors that explain these differences is an important aspect of research in molecular evolution. One such factor is the role a protein plays in a large molecular network. Here, we analyze the evolutionary rates of enzyme-coding genes in the genome-scale metabolic network of Escherichia coli to find the evolutionary constraints imposed by the structure and function of this complex metabolic system. Central and highly connected enzymes appear to evolve more slowly than less connected enzymes, but we find that they do so as a by-product of their high abundance, and not because of their position in the metabolic network. In contrast, enzymes catalyzing reactions with high metabolic flux-high substrate to product conversion rates-evolve slowly even after we account for their abundance. Moreover, enzymes catalyzing reactions that are difficult to by-pass through alternative pathways, such that they are essential in many different genetic backgrounds, also evolve more slowly. Our analyses show that an enzyme's role in the function of a metabolic network affects its evolution more than its place in the network's structure. They highlight the value of a system-level perspective for studies of molecular evolution.

The Contribution of Purifying Selection, Linkage, and Mutation Bias to the Negative Correlation between Gene Expression and Polymorphism Density in Yeast Populations

The negative correlation between the rate of protein evolution and expression level of a gene has been recognized as a universal law of the evolutionary biology (Koonin 2011). In our study, we apply a population-based approach to systematically investigate the relative importance of unequal mutation rate, linkage, and selection in the origin of the expression-polymorphism anticorrelation. We analyzed the DNA sequence of protein coding genes of 24 Saccharomyces cerevisiae and 58 Schizosaccharomyces pombe strains. We found that highly expressed genes had a substantially decreased number of polymorphic sites when compared with genes transcribed less extensively. This expression-dependent reduction was especially strong in the nonsynonymous sites, although it was also present in the synonymous sites and untranslated regions, both up and down of a gene. Most importantly, no such trend was found in introns. We used these observations, as well as analyses of site frequency spectra and data from mutation accumulation experiments, to show that the purifying selection acting on nonsynonymous sites was the main, but not exclusive, factor impeding molecular evolution within the coding sequences of highly expressed genes. Linkage could not fully explain the observed pattern of polymorphism within the untranslated regions and synonymous sites, although the contribution of selection acting directly on synonymous variants was extremely small. Finally, we found that the impact of mutational bias was rather negligible.

Comparative Transcriptomics in Two Bivalve Species Offers Different Perspectives on the Evolution of Sex-Biased Genes

Comparative genomics has become a central tool for evolutionary biology, and a better knowledge of understudied taxa represents the foundation for future work. In this study, we characterized the transcriptome of male and female mature gonads in the European clam Ruditapes decussatus, compared with that in the Manila clam Ruditapes philippinarum providing, for the first time in bivalves, information about transcription dynamics and sequence evolution of sex-biased genes. In both the species, we found a relatively low number of sex-biased genes (1,284, corresponding to 41.3% of the orthologous genes between the two species), probably due to the absence of sexual dimorphism, and the transcriptional bias is maintained in only 33% of the orthologs. The dN/dS is generally low, indicating purifying selection, with genes where the female-biased transcription is maintained between the two species showing a significantly higher dN/dS. Genes involved in embryo development, cell proliferation, and maintenance of genome stability show a faster sequence evolution. Finally, we report a lack of clear correlation between transcription level and evolutionary rate in these species, in contrast with studies that reported a negative correlation. We discuss such discrepancy and call into question some methodological approaches and rationales generally used in this type of comparative studies.

WRKY transcription factors in legumes

BACKGROUND

WRKY transcription factors, so named because of the WRKYGQK heptapeptide at the N-terminal end, are widely distributed in plants and play an important role in physiological changes and response to biotic and abiotic stressors. Many previous studies have focused on the evolution of WRKY transcription factors in a given plant; however, little is known about WRKY evolution in legumes. The gene expression pattern of duplicated WRKY transcription factors remains unclear.

RESULTS

We first identified the WRKY proteins in 12 legumes. We found that the WRKYGQK heptapeptide tended to mutate into WRKYGKK. The Q site in WRKYGQK preferentially mutated, while W, K, and Y were conserved. The phylogenetic tree shows that the WRKY proteins in legumes have multiple origins, especially group IIc. For example, WRKY64 from Lupinus angustifolius (LaWRKY64) contains three WRKY domains, of which the first two clustered together in the N-terminal WRKY domain of the group I WRKY protein, and the third WRKY domain grouped in the C-terminal WRKY domain of the group I WRKY protein. Orthologous WRKY genes have a faster evolutionary rate and are subject to constrained selective pressure, unlike paralogous WRKY genes. Different gene features were observed between duplicated WRKY genes and singleton WRKY genes. Duplicated Glycine max WRKY genes with similar gene features have gene expression divergence.

CONCLUSIONS

We analyzed the WRKY number and type in 12 legumes, concluding that the WRKY proteins have multiple origins. A novel WRKY protein, LaWRKY64, was found in L. angustifolius. The first two WRKY domains of LaWRKY64 have the same origin. The orthologous and paralogous WRKY proteins have different evolutionary rates. Duplicated WRKY genes have gene expression divergence under normal growth conditions in G. max. These results provide insight into understanding WRKY evolution and expression.

Disentangling the Causes for Faster-X Evolution in Aphids

The faster evolution of X chromosomes has been documented in several species, and results from the increased efficiency of selection on recessive alleles in hemizygous males and/or from increased drift due to the smaller effective population size of X chromosomes. Aphids are excellent models for evaluating the importance of selection in faster-X evolution because their peculiar life cycle and unusual inheritance of sex chromosomes should generally lead to equivalent effective population sizes for X and autosomes. Because we lack a high-density genetic map for the pea aphid, whose complete genome has been sequenced, we first assigned its entire genome to the X or autosomes based on ratios of sequencing depth in males (X0) to females (XX). Then, we computed nonsynonymous to synonymous substitutions ratios (dN/dS) for the pea aphid gene set and found faster evolution of X-linked genes. Our analyses of substitution rates, together with polymorphism and expression data, showed that relaxed selection is likely to be the greatest contributor to faster-X because a large fraction of X-linked genes are expressed at low rates and thus escape selection. Yet, a minor role for positive selection is also suggested by the difference between substitution rates for X and autosomes for male-biased genes (but not for asexual female-biased genes) and by lower Tajima’s D for X-linked compared with autosomal genes with highly male-biased expression patterns. This study highlights the relevance of organisms displaying alternative chromosomal inheritance to the understanding of forces shaping genome evolution.

ProteomeVis: a web app for exploration of protein properties from structure to sequence evolution across organisms' proteomes

Motivation

Protein evolution spans time scales and its effects span the length of an organism. A web app named ProteomeVis is developed to provide a comprehensive view of protein evolution in the Saccharomyces cerevisiae and Escherichia coli proteomes. ProteomeVis interactively creates protein chain graphs, where edges between nodes represent structure and sequence similarities within user-defined ranges, to study the long time scale effects of protein structure evolution. The short time scale effects of protein sequence evolution are studied by sequence evolutionary rate (ER) correlation analyses with protein properties that span from the molecular to the organismal level.

Results

We demonstrate the utility and versatility of ProteomeVis by investigating the distribution of edges per node in organismal protein chain universe graphs (oPCUGs) and putative ER determinants. S.cerevisiae and E.coli oPCUGs are scale-free with scaling constants of 1.79 and 1.56, respectively. Both scaling constants can be explained by a previously reported theoretical model describing protein structure evolution. Protein abundance most strongly correlates with ER among properties in ProteomeVis, with Spearman correlations of -0.49 (P-value < 10-10) and -0.46 (P-value < 10-10) for S.cerevisiae and E.coli, respectively. This result is consistent with previous reports that found protein expression to be the most important ER determinant.

Availability and implementation

ProteomeVis is freely accessible at http://proteomevis.chem.harvard.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Patterns of polymorphism and selection in the subgenomes of the allopolyploid Arabidopsis kamchatica

Genome duplication is widespread in wild and crop plants. However, little is known about genome-wide selection in polyploids due to the complexity of duplicated genomes. In polyploids, the patterns of purifying selection and adaptive substitutions may be affected by masking owing to duplicated genes or homeologs as well as effective population size. Here, we resequence 25 accessions of the allotetraploid Arabidopsis kamchatica, which is derived from the diploid species A. halleri and A. lyrata. We observe a reduction in purifying selection compared with the parental species. Interestingly, proportions of adaptive non-synonymous substitutions are significantly positive in contrast to most plant species. A recurrent pattern observed in both frequency and divergence–diversity neutrality tests is that the genome-wide distributions of both subgenomes are similar, but the correlation between homeologous pairs is low. This may increase the opportunity of different evolutionary trajectories such as in the HMA4 gene involved in heavy metal hyperaccumulation.

Despite the prevalence of genome duplication in plants, little is known about the evolutionary patterns of entire subgenomes. Here the authors resequence allopolyploid Arabidopsis kamchatica genome to estimate diversity, linkage disequilibrium and strengths of both positive and purifying selection.

Reduced intrinsic DNA curvature leads to increased mutation rate

BACKGROUND

Mutation rates vary across the genome. Many trans factors that influence mutation rates have been identified, as have specific sequence motifs at the 1-7-bp scale, but cis elements remain poorly characterized. The lack of understanding regarding why different sequences have different mutation rates hampers our ability to identify positive selection in evolution and to identify driver mutations in tumorigenesis.

RESULTS

Here, we use a combination of synthetic genes and sequences of thousands of isolated yeast colonies to show that intrinsic DNA curvature is a major cis determinant of mutation rate. Mutation rate negatively correlates with DNA curvature within genes, and a 10% decrease in curvature results in a 70% increase in mutation rate. Consistently, both yeast and humans accumulate mutations in regions with small curvature. We further show that this effect is due to differences in the intrinsic mutation rate, likely due to differences in mutagen sensitivity and not due to differences in the local activity of DNA repair.

CONCLUSIONS

Our study establishes a framework for understanding the cis properties of DNA sequence in modulating the local mutation rate and identifies a novel causal source of non-uniform mutation rates across the genome.

Protein evolution speed depends on its stability and abundance and on chaperone concentrations

Some biological evolution is slow (millions of years), and some is fast (months to years). The speed at which a protein evolves depends on how stable a protein’s folded structure is, how well it avoids aggregation, and how well-chaperoned it is. What are the mechanisms? We compute fitness landscapes by combining a model of protein-folding equilibria with sequence-change dynamics. We find that adapting to a new environment is fastest for proteins that are least stably folded, because those sit on steep downhill parts of fitness potentials. The modeling shows that cells should adapt to warmer environments faster than to colder ones, explains why increasing a protein’s abundance slows cell evolution, and explains how chaperones accelerate evolution by mitigating this effect.

Proteins evolve at different rates. What drives the speed of protein sequence changes? Two main factors are a protein’s folding stability and aggregation propensity. By combining the hydrophobic–polar (HP) model with the Zwanzig–Szabo–Bagchi rate theory, we find that: (i) Adaptation is strongly accelerated by selection pressure, explaining the broad variation from days to thousands of years over which organisms adapt to new environments. (ii) The proteins that adapt fastest are those that are not very stably folded, because their fitness landscapes are steepest. And because heating destabilizes folded proteins, we predict that cells should adapt faster when put into warmer rather than cooler environments. (iii) Increasing protein abundance slows down evolution (the substitution rate of the sequence) because a typical protein is not perfectly fit, so increasing its number of copies reduces the cell’s fitness. (iv) However, chaperones can mitigate this abundance effect and accelerate evolution (also called evolutionary capacitance) by effectively enhancing protein stability. This model explains key observations about protein evolution rates.

Estimating the protein burden limit of yeast cells by measuring the expression limits of glycolytic proteins

The ultimate overexpression of a protein could cause growth defects, which are known as the protein burden. However, the expression limit at which the protein-burden effect is triggered is still unclear. To estimate this limit, we systematically measured the overexpression limits of glycolytic proteins in Saccharomyces cerevisiae. The limits of some glycolytic proteins were up to 15% of the total cellular protein. These limits were independent of the proteins’ catalytic activities, a finding that was supported by an in silico analysis. Some proteins had low expression limits that were explained by their localization and metabolic perturbations. The codon usage should be highly optimized to trigger the protein-burden effect, even under strong transcriptional induction. The S–S-bond-connected aggregation mediated by the cysteine residues of a protein might affect its expression limit. Theoretically, only non-harmful proteins could be expressed up to the protein-burden limit. Therefore, we established a framework to distinguish proteins that are harmful and non-harmful upon overexpression.

If a cell makes too much of a given protein, it can sometimes cause problems and impair the cell’s growth. Overproducing some proteins may deplete the cell’s limited resources, meaning it does not have enough to make other more essential proteins. This phenomenon is known as the protein burden effect. Theoretically, only harmless proteins can be overproduced up to a level where growth would be impaired in this way. Conversely, if an overproduced protein causes harm before it becomes a burden on resources, scientists must consider other mechanisms to explain the cell’s problems, namely that the protein itself is harmful.

Knowing the ultimate level of protein production that could cause the protein burden effect – the protein burden limit – would allow scientists to distinguish between harmful and non-harmful proteins. However, to date, this limit had not been defined for any cell.

Eguchi et al. have now tried to estimate the protein burden limit for budding yeast – one of the best-studied experimental organisms. The experiments first focused on enzymes involved in alcoholic fermentation because they were expected to be non-harmful. Some of these enzymes were overproduced to the level were the made up 15% of all the cell’s proteins before they started to cause growth defects. The same results were seen with versions of the enzymes that had been mutated to be less active, leading Eguchi et al. to conclude that this level is the protein burden limit.

In other experiments, harmful enzymes could only be overproduced to levels that were far less than this proposed protein burden limit. These enzymes caused problems for the yeast in several ways, including interfering with biochemical reactions and forming large aggregates in the cell. Lastly, Eguchi et al. looked at the yeast’s genetic code and saw that most of its genes seemed to have evolved to specifically limit the production of proteins to a level that would avoid the unwanted protein burden effect.

Together these findings establish a framework to clearly distinguish between harmful and non-harmful proteins. This framework will be useful to understand the different reasons why the overproduction of certain proteins, which is seen in neurodegenerative diseases and cancer cells, can cause problems for cells.

Strong biomechanical relationships bias the tempo and mode of morphological evolution

The influence of biomechanics on the tempo and mode of morphological evolution is unresolved, yet is fundamental to organismal diversification. Across multiple four-bar linkage systems in animals, we discovered that rapid morphological evolution (tempo) is associated with mechanical sensitivity (strong correlation between a mechanical system's output and one or more of its components). Mechanical sensitivity is explained by size: the smallest link(s) are disproportionately affected by length changes and most strongly influence mechanical output. Rate of evolutionary change (tempo) is greatest in the smallest links and trait shifts across phylogeny (mode) occur exclusively via the influential, small links. Our findings illuminate the paradigms of many-to-one mapping, mechanical sensitivity, and constraints: tempo and mode are dominated by strong correlations that exemplify mechanical sensitivity, even in linkage systems known for exhibiting many-to-one mapping. Amidst myriad influences, mechanical sensitivity imparts distinct, predictable footprints on morphological diversity.

On the Origin of Compositional Features of Ribosomes

Ribosomes are highly abundant in cells and comprise, besides RNAs of varying lengths, 55–80 similarly sized, short proteins. This seemingly unusual composition is thought to have resulted from selection for rapid autocatalytic ribosome production. Here, we demonstrate that ribosomal protein-splitting mutations cannot accelerate ribosome production. The autocatalytic explanation is also unnecessary, because protein lengths generally decline with expression levels. Although ribosomal proteins are shorter than expected from their expression levels, they are not outliers among members of large protein complexes in mean protein length or coefficient of variation. These observations are explainable because 1) shortening proteins lowers their synthetic cost and reduces the waste from mistranslation-induced protein dysfunction and degradation, 2) such benefits rise with expression levels, and 3) members of large complexes participate in more protein–protein interactions so are less tolerant to mistranslation. These and other considerations suggest that the compositional features of ribosomes originate from cellular energy economics.

Evolutionary Perspectives of Genotype-Phenotype Factors in Leishmania Metabolism

The sandfly midgut and the human macrophage phagolysosome provide antagonistic metabolic niches for the endoparasite Leishmania to survive and populate. Although these environments fluctuate across developmental stages, the relative changes in both these environments across parasite generations might remain gradual. Such environmental restrictions might endow parasite metabolism with a choice of specific genotypic and phenotypic factors that can constrain enzyme evolution for successful adaptation to the host. With respect to the available cellular information for Leishmania species, for the first time, we measure the relative contribution of eight inter-correlated predictors related to codon usage, GC content, gene expression, gene length, multi-functionality, and flux-coupling potential of an enzyme on the evolutionary rates of singleton metabolic genes and further compare their effects across three Leishmania species. Our analysis reveals that codon adaptation, multi-functionality, and flux-coupling potential of an enzyme are independent contributors of enzyme evolutionary rates, which can together explain a large variation in enzyme evolutionary rates across species. We also hypothesize that a species-specific occurrence of duplicated genes in novel subcellular locations can create new flux routes through certain singleton flux-coupled enzymes, thereby constraining their evolution. A cross-species comparison revealed both common and species-specific genes whose evolutionary divergence was constrained by multiple independent factors. Out of these, previously known pharmacological targets and virulence factors in Leishmania were identified, suggesting their evolutionary reasons for being important survival factors to the parasite. All these results provide a fundamental understanding of the factors underlying adaptive strategies of the parasite, which can be further targeted.

Effect of genetic drift on determinants of protein evolution

A number of previous studies reported that gene expression, tissue specificity, gene essentiality and the number of protein-protein interactions influence the rate of protein evolution. Here we investigated the influence of effective population size (N_e) on these determinants of protein evolution. For this purpose, we compared the ratio of non-synonymous-to-synonymous diversities (π_N/π_S) estimated for protein-coding genes of Mus musculus castaneus and Mus musculus musculus: populations with high and low N_e respectively. Our results revealed that the difference between π_N/π_S estimated for genes with high and low expression levels was significantly smaller for M. m. musculus compared to that observed for M. m. castaneus The difference between the π_N/π_S of broadly expressed and tissue specific genes was much higher for M. m. castaneus compared to that of M. m. musculus. Furthermore, the difference between the π_N/π_S computed for essential and non-essential genes was much smaller for M. m. musculus than M. m. castaneus A similar pattern was observed for genes involved in many protein-protein interactions versus those involved in one. These results suggest that the effects of the determinants on protein evolution were much reduced for the population with small N_e due to increased genetic drift.

Genome-wide maps of ribosomal occupancy provide insights into adaptive evolution and regulatory roles of uORFs during Drosophila development

Upstream open reading frames (uORFs) play important roles in regulating the main coding DNA sequences (CDSs) via translational repression. Despite their prevalence in the genomes, uORFs are overall discriminated against by natural selection. However, it remains unclear why in the genomes there are so many uORFs more conserved than expected under the assumption of neutral evolution. Here, we generated genome-wide maps of translational efficiency (TE) at the codon level throughout the life cycle of Drosophila melanogaster. We identified 35,735 uORFs that were expressed, and 32,224 (90.2%) of them showed evidence of ribosome occupancy during Drosophila development. The ribosome occupancy of uORFs is determined by genomic features, such as optimized sequence contexts around their start codons, a shorter distance to CDSs, and higher coding potentials. Our population genomic analysis suggests the segregating mutations that create or disrupt uORFs are overall deleterious in D. melanogaster. However, we found for the first time that many (68.3% of) newly fixed uORFs that are associated with ribosomes in D. melanogaster are driven by positive Darwinian selection. Our findings also suggest that uORFs play a vital role in controlling the translational program in Drosophila. Moreover, we found that many uORFs are transcribed or translated in a developmental stage-, sex-, or tissue-specific manner, suggesting that selective transcription or translation of uORFs could potentially modulate the TE of the downstream CDSs during Drosophila development.

Upstream open reading frames (uORFs) in the 5′ untranslated regions (UTRs) of messenger RNAs can potentially inhibit translation of the downstream regions that encode proteins by sequestering protein-making machinery the ribosome. Moreover, mutations that destroy existing uORFs or create new ones are known to cause human disease. Although mutations that create new uORFs are generally deleterious and are selected against, many uORFs are evolutionarily conserved across eukaryotic species. To resolve this dilemma, we used extensive mRNA-Seq and ribosome profiling to generate high-resolution genome-wide maps of ribosome occupancy and translational efficiency (TE) during the life cycle of the fruit fly D. melanogaster. This allowed us to identify the sequence features of uORFs that influence their ability to associate with ribosomes. We demonstrate for the first time that the majority of the newly fixed uORFs in D. melanogaster, especially the translated ones, are under positive Darwinian selection. We also show that uORFs exert widespread repressive effects on the translation of the downstream protein-coding region. We find that many uORFs are transcribed or translated in a developmental stage-, sex-, or tissue-specific manner. Our results suggest that during Drosophila development, changes in the TE of uORFs, as well as the inclusion/exclusion of uORFs, are frequently exploited to inversely influence the translation of the downstream protein-coding regions. Our study provides novel insights into the molecular mechanisms and functional consequences of uORF-mediated regulation.

Pathway position constrains the evolution of an ecologically important pathway in aspens (Populus tremula L.)

Many ecological interactions of aspens and their relatives (Populus spp.) are affected by products of the phenylpropanoid pathway synthesizing condensed tannins (CTs), whose production involves trade-offs with other ecologically important compounds and with growth. Genes of this pathway are candidates for investigating the role of selection on ecologically important, polygenic traits. We analysed sequences from 25 genes representing 10 steps of the CT synthesis pathway, which produces CTs used in defence and lignins used for growth, in 12 individuals of European aspen (Populus tremula). We compared these to homologs from P. trichocarpa, to a control set of 77 P. tremula genes, to genome-wide resequencing data and to RNA-seq expression levels, in order to identify signatures of selection distinct from those of demography. In Populus, pathway position exerts a strong influence on the evolution of these genes. Nonsynonymous diversity, divergence and allele frequency shifts (Tajima's D) were much lower than for synonymous measures. Expression levels were higher, and the direction of selection more negative, for upstream genes than for those downstream. Selective constraints act with increasing intensity on upstream genes, despite the presence of multiple paralogs in most gene families. Pleiotropy, expression level, flux control and codon bias appear to interact in determining levels and patterns of variation in genes of this pathway, whose products mediate a wide array of ecological interactions for this widely distributed species.

Patterns of Conservation and Diversification in the Fungal Polarization Network

The combined actions of proteins in networks underlie all fundamental cellular functions. Deeper insights into the dynamics of network composition across species and their functional consequences are crucial to fully understand protein network evolution. Large-scale comparative studies with high phylogenetic resolution are now feasible through the recent rise in available genomic data sets of both model and nonmodel species. Here, we focus on the polarity network, which is universally essential for cell proliferation and studied in great detail in the model organism, Saccharomyces cerevisiae. We examine 42 proteins, directly related to cell polarization, across 298 fungal strains/species to determine the composition of the network and patterns of conservation and diversification. We observe strong protein conservation for a group of 23 core proteins: >95% of all examined strains/species possess at least 14 of these core proteins, albeit in varying compositions, and non of the individual core proteins is 100% conserved. We find high levels of variation in prevalence and sequence identity in the remaining 19 proteins, resulting in distinct lineage-specific compositions of the network in the majority of strains/species. We show that the observed diversification in network composition correlates with lineage, lifestyle, and genetic distance. Yeast, filamentous and basal unicellular fungi, form distinctive groups based on these analyses, with substantial differences to their polarization network. Our study shows that the fungal polarization network is highly dynamic, even between closely related species, and that functional conservation appears to be achieved by varying the specific components of the fungal polarization repertoire.

Amino acid compositions contribute to the proteins' evolution under the influence of their abundances and genomic GC content

Inconsistent results on the association between evolutionary rates and amino acid composition of proteins have been reported in eukaryotes. However, there are few studies of how amino acid composition can influence evolutionary rates in bacteria. Thus, we constructed linear regression models between composition frequencies of amino acids and evolutionary rates for bacteria. Compositions of all amino acids can on average explain 21.5% of the variation in evolutionary rates among 273 investigated bacterial organisms. In five model organisms, amino acid composition contributes more to variation in evolutionary rates than protein abundance, and frequency of optimal codons. The contribution of individual amino acid composition to evolutionary rate varies among organisms. The closer the GC-content of genome to its maximum or minimum, the better the correlation between the amino acid content and the evolutionary rate of proteins would appear in that genome. The types of amino acids that significantly contribute to evolutionary rates can be grouped into GC-rich and AT-rich amino acids. Besides, the amino acid with high composition also contributes more to evolutionary rates than amino acid with low composition in proteome. In summary, amino acid composition significantly contributes to the rate of evolution in bacterial organisms and this in turn is impacted by GC-content.

Further Simulations and Analyses Demonstrate Open Problems of Phylostratigraphy

Phylostratigraphy, originally designed for gene age estimation by BLAST-based protein homology searches of sequenced genomes, has been widely used for studying patterns and inferring mechanisms of gene origination and evolution. We previously showed by computer simulation that phylostratigraphy underestimates gene age for a nonnegligible fraction of genes and that the underestimation is severer for genes with certain properties such as fast evolution and short protein sequences. Consequently, many previously reported age distributions of gene properties may have been methodological artifacts rather than biological realities. Domazet-Lošo and colleagues recently argued that our simulations were flawed and that phylostratigraphic bias does not impact inferences about gene emergence and evolution. Here we discuss conceptual difficulties of phylostratigraphy, identify numerous problems in Domazet-Lošo et al.’s argument, reconfirm phylostratigraphic error using simulations suggested by Domazet-Lošo and colleagues, and demonstrate that a phylostratigraphic trend claimed to be robust to error disappears when genes likely to be error-resistant are analyzed. We conclude that extreme caution is needed in interpreting phylostratigraphic results because of the inherent biases of the method and that reanalysis using genes exhibiting no error in realistic simulations may help reduce spurious findings.

Position Matters: Network Centrality Considerably Impacts Rates of Protein Evolution in the Human Protein-Protein Interaction Network

The proteins of any organism evolve at disparate rates. A long list of factors affecting rates of protein evolution have been identified. However, the relative importance of each factor in determining rates of protein evolution remains unresolved. The prevailing view is that evolutionary rates are dominantly determined by gene expression, and that other factors such as network centrality have only a marginal effect, if any. However, this view is largely based on analyses in yeasts, and accurately measuring the importance of the determinants of rates of protein evolution is complicated by the fact that the different factors are often correlated with each other, and by the relatively poor quality of available functional genomics data sets. Here, we use correlation, partial correlation and principal component regression analyses to measure the contributions of several factors to the variability of the rates of evolution of human proteins. For this purpose, we analyzed the entire human protein–protein interaction data set and the human signal transduction network—a network data set of exceptionally high quality, obtained by manual curation, which is expected to be virtually free from false positives. In contrast with the prevailing view, we observe that network centrality (measured as the number of physical and nonphysical interactions, betweenness, and closeness) has a considerable impact on rates of protein evolution. Surprisingly, the impact of centrality on rates of protein evolution seems to be comparable, or even superior according to some analyses, to that of gene expression. Our observations seem to be independent of potentially confounding factors and from the limitations (biases and errors) of interactomic data sets.

The Mitonuclear Dimension of Neanderthal and Denisovan Ancestry in Modern Human Genomes

Some human populations interbred with Neanderthals and Denisovans, resulting in substantial contributions to modern-human genomes. Therefore, it is now possible to use genomic data to investigate mechanisms that shaped historical gene flow between humans and our closest hominin relatives. More generally, in eukaryotes, mitonuclear interactions have been argued to play a disproportionate role in generating reproductive isolation. There is no evidence of mtDNA introgression into modern human populations, which means that all introgressed nuclear alleles from archaic hominins must function on a modern-human mitochondrial background. Therefore, mitonuclear interactions are also potentially relevant to hominin evolution. We performed a detailed accounting of mtDNA divergence among hominin lineages and used population-genomic data to test the hypothesis that mitonuclear incompatibilities have preferentially restricted the introgression of nuclear genes with mitochondrial functions. We found a small but significant underrepresentation of introgressed Neanderthal alleles at such nuclear loci. Structural analyses of mitochondrial enzyme complexes revealed that these effects are unlikely to be mediated by physically interacting sites in mitochondrial and nuclear gene products. We did not detect any underrepresentation of introgressed Denisovan alleles at mitochondrial-targeted loci, but this may reflect reduced power because locus-specific estimates of Denisovan introgression are more conservative. Overall, we conclude that genes involved in mitochondrial function may have been subject to distinct selection pressures during the history of introgression from archaic hominins but that mitonuclear incompatibilities have had, at most, a small role in shaping genome-wide introgression patterns, perhaps because of limited functional divergence in mtDNA and interacting nuclear genes.

Correlates of evolutionary rates in the murine sperm proteome

Background

Protein-coding genes expressed in sperm evolve at different rates. To gain deeper insight into the factors underlying this heterogeneity we examined the relative importance of a diverse set of previously described rate correlates in determining the evolution of murine sperm proteins.

Results

Using partial rank correlations we detected several major rate indicators: Phyletic gene age, numbers of protein-protein interactions, and survival essentiality emerged as particularly important rate correlates in murine sperm proteins. Tissue specificity, numbers of paralogs, and untranslated region lengths also correlate significantly with sperm genes’ evolutionary rates, albeit to a lesser extent. Multifunctionality, coding sequence or average intron lengths, and mean expression level have insignificant or virtually no independent effects on evolutionary rates in murine sperm genes. Gene ontology enrichment analyses of three equally sized murine sperm protein groups classified based on their evolutionary rates indicate strongest sperm-specific functional specialization in the most quickly evolving gene class.

Conclusions

We propose a model according to which slowly evolving murine sperm proteins tend to be constrained by factors such as survival essentiality, network connectivity, and/or broad expression. In contrast, evolutionary change may arise especially in less constrained sperm proteins, which might, moreover, be prone to specialize to reproduction-related functions. Our results should be taken into account in future studies on rate variations of reproductive genes.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1157-6) contains supplementary material, which is available to authorized users.

Selective Constraints on Coding Sequences of Nervous System Genes Are a Major Determinant of Duplicate Gene Retention in Vertebrates

The evolutionary history of vertebrates is marked by three ancient whole-genome duplications: two successive rounds in the ancestor of vertebrates, and a third one specific to teleost fishes. Biased loss of most duplicates enriched the genome for specific genes, such as slow evolving genes, but this selective retention process is not well understood. To understand what drives the long-term preservation of duplicate genes, we characterized duplicated genes in terms of their expression patterns. We used a new method of expression enrichment analysis, TopAnat, applied to in situ hybridization data from thousands of genes from zebrafish and mouse. We showed that the presence of expression in the nervous system is a good predictor of a higher rate of retention of duplicate genes after whole-genome duplication. Further analyses suggest that purifying selection against the toxic effects of misfolded or misinteracting proteins, which is particularly strong in nonrenewing neural tissues, likely constrains the evolution of coding sequences of nervous system genes, leading indirectly to the preservation of duplicate genes after whole-genome duplication. Whole-genome duplications thus greatly contributed to the expansion of the toolkit of genes available for the evolution of profound novelties of the nervous system at the base of the vertebrate radiation.

Does mRNA structure contain genetic information for regulating co-translational protein folding?

Currently many facets of genetic information are illdefined. In particular, how protein folding is genetically regulated has been a long-standing issue for genetics and protein biology. And a generic mechanistic model with supports of genomic data is still lacking. Recent technological advances have enabled much needed genome-wide experiments. While putting the effect of codon optimality on debate, these studies have supplied mounting evidence suggesting a role of mRNA structure in the regulation of protein folding by modulating translational elongation rate. In conjunctions with previous theories, this mechanistic model of protein folding guided by mRNA structure shall expand our understandings of genetic information and offer new insights into various biomedical puzzles.

Derivative-free neural network for optimizing the scoring functions associated with dynamic programming of pairwise-profile alignment

BACKGROUND

A profile-comparison method with position-specific scoring matrix (PSSM) is among the most accurate alignment methods. Currently, cosine similarity and correlation coefficients are used as scoring functions of dynamic programming to calculate similarity between PSSMs. However, it is unclear whether these functions are optimal for profile alignment methods. By definition, these functions cannot capture nonlinear relationships between profiles. Therefore, we attempted to discover a novel scoring function, which was more suitable for the profile-comparison method than existing functions, using neural networks.

RESULTS

Although neural networks required derivative-of-cost functions, the problem being addressed in this study lacked them. Therefore, we implemented a novel derivative-free neural network by combining a conventional neural network with an evolutionary strategy optimization method used as a solver. Using this novel neural network system, we optimized the scoring function to align remote sequence pairs. Our results showed that the pairwise-profile aligner using the novel scoring function significantly improved both alignment sensitivity and precision relative to aligners using existing functions.

CONCLUSIONS

We developed and implemented a novel derivative-free neural network and aligner (Nepal) for optimizing sequence alignments. Nepal improved alignment quality by adapting to remote sequence alignments and increasing the expressiveness of similarity scores. Additionally, this novel scoring function can be realized using a simple matrix operation and easily incorporated into other aligners. Moreover our scoring function could potentially improve the performance of homology detection and/or multiple-sequence alignment of remote homologous sequences. The goal of the study was to provide a novel scoring function for profile alignment method and develop a novel learning system capable of addressing derivative-free problems. Our system is capable of optimizing the performance of other sophisticated methods and solving problems without derivative-of-cost functions, which do not always exist in practical problems. Our results demonstrated the usefulness of this optimization method for derivative-free problems.

Disulfide Bonds Enable Accelerated Protein Evolution

The different proteins of any proteome evolve at enormously different rates. What factors contribute to this variability, and to what extent, is still a largely open question. We hypothesized that disulfide bonds, by increasing protein stability, should make proteins' structures relatively independent of their amino acid sequences, thus acting as buffers of deleterious mutations and enabling accelerated sequence evolution. In agreement with this hypothesis, we observed that membrane proteins with disulfide bonds evolved 88% faster than those without disulfide bonds, and that extracellular proteins with disulfide bonds evolved 49% faster than those without disulfide bonds. In addition, genes encoding proteins with disulfide bonds exhibit an increased likelihood of showing signatures of positive selection. Multivariate analyses indicate that the trend is independent of a number of potentially confounding factors. The effect, however, is not observed among the longest proteins, which can become stabilized by mechanisms other than disulfide bonds.

Landscape genomics: natural selection drives the evolution of mitogenome in penguins

Background

Mitochondria play a key role in the balance of energy and heat production, and therefore the mitochondrial genome is under natural selection by environmental temperature and food availability, since starvation can generate more efficient coupling of energy production. However, selection over mitochondrial DNA (mtDNA) genes has usually been evaluated at the population level. We sequenced by NGS 12 mitogenomes and with four published genomes, assessed genetic variation in ten penguin species distributed from the equator to Antarctica. Signatures of selection of 13 mitochondrial protein-coding genes were evaluated by comparing among species within and among genera (Spheniscus, Pygoscelis, Eudyptula, Eudyptes and Aptenodytes). The genetic data were correlated with environmental data obtained through remote sensing (sea surface temperature [SST], chlorophyll levels [Chl] and a combination of SST and Chl [COM]) through the distribution of these species.

Results

We identified the complete mtDNA genomes of several penguin species, including ND6 and 8 tRNAs on the light strand and 12 protein coding genes, 14 tRNAs and two rRNAs positioned on the heavy strand. The highest diversity was found in NADH dehydrogenase genes and the lowest in COX genes. The lowest evolutionary divergence among species was between Humboldt (Spheniscus humboldti) and Galapagos (S. mendiculus) penguins (0.004), while the highest was observed between little penguin (Eudyptula minor) and Adélie penguin (Pygoscelis adeliae) (0.097). We identified a signature of purifying selection (Ka/Ks < 1) across the mitochondrial genome, which is consistent with the hypothesis that purifying selection is constraining mitogenome evolution to maintain Oxidative phosphorylation (OXPHOS) proteins and functionality. Pairwise species maximum-likelihood analyses of selection at codon sites suggest positive selection has occurred on ATP8 (Fixed-Effects Likelihood, FEL) and ND4 (Single Likelihood Ancestral Counting, SLAC) in all penguins. In contrast, COX1 had a signature of strong negative selection. ND4 Ka/Ks ratios were highly correlated with SST (Mantel, p-value: 0.0001; GLM, p-value: 0.00001) and thus may be related to climate adaptation throughout penguin speciation.

Conclusions

These results identify mtDNA candidate genes under selection which could be involved in broad-scale adaptations of penguins to their environment. Such knowledge may be particularly useful for developing predictive models of how these species may respond to severe climatic changes in the future.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4424-9) contains supplementary material, which is available to authorized users.

Protein Stability and Avoidance of Toxic Misfolding Do Not Explain the Sequence Constraints of Highly Expressed Proteins

The avoidance of cytotoxic effects associated with protein misfolding has been proposed as a dominant constraint on the sequence evolution and molecular clock of highly expressed proteins. Recently, Leuenberger et al. developed an elegant experimental approach to measure protein thermal stability at the proteome scale. The collected data allow us to rigorously test the predictions of the misfolding avoidance hypothesis that highly expressed proteins have evolved to be more stable, and that maintaining thermodynamic stability significantly constrains their evolution. Notably, reanalysis of the Leuenberger et al. data across four different organisms reveals no substantial correlation between protein stability and protein abundance. Therefore, the key predictions of the misfolding toxicity and related hypotheses are not supported by available empirical data. The data also suggest that, regardless of protein expression, protein stability does not substantially affect the protein molecular clock across organisms.

A new parameter-rich structure-aware mechanistic model for amino acid substitution during evolution

Improvements in the description of amino acid substitution are required to develop better pseudo-energy-based protein structure-aware models for use in phylogenetic studies. These models are used to characterize the probabilities of amino acid substitution and enable better simulation of protein sequences over a phylogeny. A better characterization of amino acid substitution probabilities in turn enables numerous downstream applications, like detecting positive selection, ancestral sequence reconstruction, and evolutionarily-motivated protein engineering. Many existing Markov models for amino acid substitution in molecular evolution disregard molecular structure and describe the amino acid substitution process over longer evolutionary periods poorly. Here, we present a new model upgraded with a site-specific parameterization of pseudo-energy terms in a coarse-grained force field, which describes local heterogeneity in physical constraints on amino acid substitution better than a previous pseudo-energy-based model with minimum cost in runtime. The importance of each weight term parameterization in characterizing underlying features of the site, including contact number, solvent accessibility, and secondary structural elements was evaluated, returning both expected and biologically reasonable relationships between model parameters. This results in the acceptance of proposed amino acid substitutions that more closely resemble those observed site-specific frequencies in gene family alignments. The modular site-specific pseudo-energy function is made available for download through the following website: https://liberles.cst.temple.edu/Software/CASS/index.html.

Most m6A RNA Modifications in Protein-Coding Regions Are Evolutionarily Unconserved and Likely Nonfunctional

Methylation of the adenosine base at the nitrogen-6 position (m6A) is the most prevalent internal posttranscriptional modification of mRNAs in many eukaryotes. Despite the rapid progress in the transcriptome-wide mapping of m6As, identification of proteins responsible for writing, reading, and erasing m6As, and elucidation of m6A functions in splicing, RNA stability, translation, and other processes, it is unknown whether most observed m6A modifications are functional. To address this question, we respectively analyze the evolutionary conservation of yeast and human m6As in protein-coding regions. Relative to comparable unmethylated As, m6As are overall no more conserved in yeasts and only slightly more conserved in mammals. Furthermore, yeast m6As and comparable unmethylated As have no significant difference in single nucleotide polymorphism (SNP) density or SNP site frequency spectrum. The same is true in human. The methylation status of a gene, not necessarily the specific sites methylated in the gene, is subject to purifying selection for no more than ∼20% of m6A-modified genes. These observations suggest that most m6A modifications in protein-coding regions are nonfunctional and nonadaptive, probably resulting from off-target activities of m6A methyltransferases. In addition, our reanalysis invalidates the recent claim of positive selection for newly acquired m6A modifications in human evolution. Regarding the small number of evolutionarily conserved m6As, evidence suggests that a large proportion of them are likely functional; they should be prioritized in future functional characterizations of m6As. Together, these findings have important implications for understanding the biological significance of m6A and other posttranscriptional modifications.

Highly expressed genes evolve under strong epistasis from a proteome-wide scan in E. coli

Epistasis or the non-additivity of mutational effects is a major force in protein evolution, but it has not been systematically quantified at the level of a proteome. Here, we estimated the extent of epistasis for 2,382 genes in E. coli using several hundreds of orthologs for each gene within the class Gammaproteobacteria. We found that the average epistasis is ~41% across genes in the proteome and that epistasis is stronger among highly expressed genes. This trend is quantitatively explained by the prevailing model of sequence evolution based on minimizing the fitness cost of protein unfolding and aggregation. The genes with the highest epistasis are also functionally involved in the maintenance of proteostasis, translation and central metabolism. In contrast, genes evolving with low epistasis mainly encode for membrane proteins and are involved in transport activity. Our results highlight the coupling between selection and epistasis in the long-term evolution of a proteome.

Comprehensive analysis of correlations among codon usage bias, gene expression, and substitution rate in Arachis duranensis and Arachis ipaënsis orthologs

The relationship between evolutionary rates and gene expression in model plant orthologs is well documented. However, little is known about the relationships between gene expression and evolutionary trends in Arachis orthologs. We identified 7,435 one-to-one orthologs, including 925 single-copy and 6,510 multiple-copy sequences in Arachis duranensis and Arachis ipaënsis. Codon usage was stronger for shorter polypeptides, which were encoded by codons with higher GC contents. Highly expressed coding sequences had higher codon usage bias, GC content, and expression breadth. Additionally, expression breadth was positively correlated with polypeptide length, but there was no correlation between gene expression and polypeptide length. Inferred selective pressure was also negatively correlated with both gene expression and expression breadth in all one-to-one orthologs, while positively but non-significantly correlated with gene expression in sequences with signatures of positive selection. Gene expression levels and expression breadth were significantly higher for single-copy genes than for multiple-copy genes. Similarly, the gene expression and expression breadth in sequences with signatures of purifying selection were higher than those of sequences with positive selective signatures. These results indicated that gene expression differed between single-copy and multiple-copy genes as well as sequences with signatures of positive and purifying selection.

Comparative epigenomics in the Brassicaceae reveals two evolutionarily conserved modes of PRC2-mediated gene regulation

Background

Polycomb Repressive Complexes 2 (PRC2) are multi-protein chromatin modifiers that are evolutionarily conserved among eukaryotes and play key roles in the regulation of gene expression, notably through the trimethylation of lysine 27 of histone H3 (H3K27me3). Although PRC2-mediated gene regulation has been studied in many organisms, few studies have explored in depth the evolutionary conservation of PRC2 targets.

Results

Here, we compare the H3K27me3 epigenomic profiles for the two closely related species Arabidopsis thaliana and Arabidopsis lyrata and the more distant species Arabis alpina, three Brassicaceae that diverged from each other within the past 24 million years.

Using a robust set of gene orthologs present in the three species, we identify two classes of evolutionarily conserved PRC2 targets, which are characterized by either developmentally plastic or developmentally constrained H3K27me3 marking across species. Constrained H3K27me3 marking is associated with higher conservation of promoter sequence information content and higher nucleosome occupancy compared to plastic H3K27me3 marking. Moreover, gene orthologs with constrained H3K27me3 marking exhibit a higher degree of tissue specificity and tend to be involved in developmental functions, whereas gene orthologs with plastic H3K27me3 marking preferentially encode proteins associated with metabolism and stress responses. In addition, gene orthologs with constrained H3K27me3 marking are the predominant contributors to higher-order chromosome organization.

Conclusions

Our findings indicate that developmentally plastic and constrained H3K27me3 marking define two evolutionarily conserved modes of PRC2-mediated gene regulation that are associated with distinct selective pressures operating at multiple scales, from DNA sequence to gene function and chromosome architecture.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1333-9) contains supplementary material, which is available to authorized users.

Systematic Analyses and Prediction of Human Drug Side Effect Associated Proteins from the Perspective of Protein Evolution

Identification of various factors involved in adverse drug reactions in target proteins to develop therapeutic drugs with minimal/no side effect is very important. In this context, we have performed a comparative evolutionary rate analyses between the genes exhibiting drug side-effect(s) (SET) and genes showing no side effect (NSET) with an aim to increase the prediction accuracy of SET/NSET proteins using evolutionary rate determinants. We found that SET proteins are more conserved than the NSET proteins. The rates of evolution between SET and NSET protein primarily depend upon their noncomplex (protein complex association number = 0) forming nature, phylogenetic age, multifunctionality, membrane localization, and transmembrane helix content irrespective of their essentiality, total druggability (total number of drugs/target), m-RNA expression level, and tissue expression breadth. We also introduced two novel terms—killer druggability (number of drugs with killing side effect(s)/target), essential druggability (number of drugs targeting essential proteins/target) to explain the evolutionary rate variation between SET and NSET proteins. Interestingly, we noticed that SET proteins are younger than NSET proteins and multifunctional younger SET proteins are candidates of acquiring killing side effects. We provide evidence that higher killer druggability, multifunctionality, and transmembrane helices support the conservation of SET proteins over NSET proteins in spite of their recent origin. By employing all these entities, our Support Vector Machine model predicts human SET/NSET proteins to a high degree of accuracy (∼86%).

Selection on start codons in prokaryotes and potential compensatory nucleotide substitutions

Reconstruction of the evolution of start codons in 36 groups of closely related bacterial and archaeal genomes reveals purifying selection affecting AUG codons. The AUG starts are replaced by GUG and especially UUG significantly less frequently than expected under the neutral expectation derived from the frequencies of the respective nucleotide triplet substitutions in non-coding regions and in 4-fold degenerate sites. Thus, AUG is the optimal start codon that is actively maintained by purifying selection. However, purifying selection on start codons is significantly weaker than the selection on the same codons in coding sequences, although the switches between the codons result in conservative amino acid substitutions. The only exception is the AUG to UUG switch that is strongly selected against among start codons. Selection on start codons is most pronounced in evolutionarily conserved, highly expressed genes. Mutation of the start codon to a sub-optimal form (GUG or UUG) tends to be compensated by mutations in the Shine-Dalgarno sequence towards a stronger translation initiation signal. Together, all these findings indicate that in prokaryotes, translation start signals are subject to weak but significant selection for maximization of initiation rate and, consequently, protein production.

Population Genomics of Paramecium Species

Population-genomic analyses are essential to understanding factors shaping genomic variation and lineage-specific sequence constraints. The dearth of such analyses for unicellular eukaryotes prompted us to assess genomic variation in Paramecium, one of the most well-studied ciliate genera. The Paramecium aurelia complex consists of ∼15 morphologically indistinguishable species that diverged subsequent to two rounds of whole-genome duplications (WGDs, as long as 320 MYA) and possess extremely streamlined genomes. We examine patterns of both nuclear and mitochondrial polymorphism, by sequencing whole genomes of 10-13 worldwide isolates of each of three species belonging to the P. aurelia complex: P. tetraurelia, P. biaurelia, P. sexaurelia, as well as two outgroup species that do not share the WGDs: P. caudatum and P. multimicronucleatum. An apparent absence of global geographic population structure suggests continuous or recent dispersal of Paramecium over long distances. Intergenic regions are highly constrained relative to coding sequences, especially in P. caudatum and P. multimicronucleatum that have shorter intergenic distances. Sequence diversity and divergence are reduced up to ∼100-150 bp both upstream and downstream of genes, suggesting strong constraints imposed by the presence of densely packed regulatory modules. In addition, comparison of sequence variation at non-synonymous and synonymous sites suggests similar recent selective pressures on paralogs within and orthologs across the deeply diverging species. This study presents the first genome-wide population-genomic analysis in ciliates and provides a valuable resource for future studies in evolutionary and functional genetics in Paramecium.

Evolutionary dynamics in the fungal polarization network, a mechanistic perspective

Polarity establishment underlies proper cell cycle completion across virtually all organisms. Much progress has been made in generating an understanding of the structural and functional components of this process, especially in model species. Here we focus on the evolutionary dynamics of the fungal polarization protein network in order to determine general components and mechanistic principles, species- or lineage-specific adaptations and the evolvability of the network. The currently available genomic and proteomic screens in a variety of fungal species have shown three main characteristics: (1) certain proteins, processes and functions are conserved throughout the fungal clade; (2) orthologous functions can never be assumed, as various cases have been observed of homologous loci with dissimilar functions; (3) species have, typically, various species- or lineage-specific proteins incorporated in their polarization network. Further large-scale comparative and experimental studies, including those on non-model species representing the great fungal diversity, are needed to gain a better understanding of the evolutionary dynamics and generalities of the polarization network in fungi.

Constraints and consequences of the emergence of amino acid repeats in eukaryotic proteins

Proteins with amino acid homorepeats have the potential to be detrimental to cells and are often associated with human diseases. Why, then, are homorepeats prevalent in eukaryotic proteomes? In yeast, homorepeats are enriched in proteins that are essential and pleiotropic and that buffer environmental insults. The presence of homorepeats increases the functional versatility of proteins by mediating protein interactions and facilitating spatial organization in a repeat-dependent manner. During evolution, homorepeats are preferentially retained in proteins with stringent proteostasis, which might minimize repeat-associated detrimental effects such as unregulated phase separation and protein aggregation. Their presence facilitates rapid protein divergence through accumulation of amino acid substitutions, which often affect linear motifs and post-translational-modification sites. These substitutions may result in rewiring protein interaction and signaling networks. Thus, homorepeats are distinct modules that are often retained in stringently regulated proteins. Their presence facilitates rapid exploration of the genotype-phenotype landscape of a population, thereby contributing to adaptation and fitness.

Accelerated Evolution of Developmentally Biased Genes in the Tetraphenic Ant Cardiocondyla obscurior

Plastic gene expression underlies phenotypic plasticity and plastically expressed genes evolve under different selection regimes compared with ubiquitously expressed genes. Social insects are well-suited models to elucidate the evolutionary dynamics of plastic genes for their genetically and environmentally induced discrete polymorphisms. Here, we study the evolution of plastically expressed genes in the ant Cardiocondyla obscurior—a species that produces two discrete male morphs in addition to the typical female polymorphism of workers and queens. Based on individual-level gene expression data from 28 early third instar larvae, we test whether the same evolutionary dynamics that pertain to plastically expressed genes in adults also pertain to genes with plastic expression during development. In order to quantify plasticity of gene expression over multiple contrasts, we develop a novel geometric measure. For genes expressed during development, we show that plasticity of expression is positively correlated with evolutionary rates. We furthermore find a strong correlation between expression plasticity and expression variation within morphs, suggesting a close link between active and passive plasticity of gene expression. Our results support the notion of relaxed selection and neutral processes as important drivers in the evolution of adaptive plasticity.

Secreted Proteins Defy the Expression Level-Evolutionary Rate Anticorrelation

The rates of evolution of the proteins of any organism vary across orders of magnitude. A primary factor influencing rates of protein evolution is expression. A strong negative correlation between expression levels and evolutionary rates (the so-called E-R anticorrelation) has been observed in virtually all studied organisms. This effect is currently attributed to the abundance-dependent fitness costs of misfolding and unspecific protein-protein interactions, among other factors. Secreted proteins are folded in the endoplasmic reticulum, a compartment where chaperones, folding catalysts, and stringent quality control mechanisms promote their correct folding and may reduce the fitness costs of misfolding. In addition, confinement of secreted proteins to the extracellular space may reduce misinteractions and their deleterious effects. We hypothesize that each of these factors (the secretory pathway quality control and extracellular location) may reduce the strength of the E-R anticorrelation. Indeed, here we show that among human proteins that are secreted to the extracellular space, rates of evolution do not correlate with protein abundances. This trend is robust to controlling for several potentially confounding factors and is also observed when analyzing protein abundance data for 6 human tissues. In addition, analysis of mRNA abundance data for 32 human tissues shows that the E-R correlation is always less negative, and sometimes nonsignificant, in secreted proteins. Similar observations were made in Caenorhabditis elegans and in Escherichia coli, and to a lesser extent in Drosophila melanogaster, Saccharomyces cerevisiae and Arabidopsis thaliana. Our observations contribute to understand the causes of the E-R anticorrelation.

Structural Biology outside the box-inside the cell

Recent developments in cellular cryo-electron tomography, in-cell single-molecule Förster resonance energy transfer-spectroscopy, nuclear magnetic resonance-spectroscopy and electron paramagnetic resonance-spectroscopy delivered unprecedented insights into the inner workings of cells. Here, we review complementary aspects of these methods and provide an outlook toward joint applications in the future.

Evolutionary Conservation and Emerging Functional Diversity of the Cytosolic Hsp70:J Protein Chaperone Network of Arabidopsis thaliana

Heat shock proteins of 70 kDa (Hsp70s) partner with structurally diverse Hsp40s (J proteins), generating distinct chaperone networks in various cellular compartments that perform myriad housekeeping and stress-associated functions in all organisms. Plants, being sessile, need to constantly maintain their cellular proteostasis in response to external environmental cues. In these situations, the Hsp70:J protein machines may play an important role in fine-tuning cellular protein quality control. Although ubiquitous, the functional specificity and complexity of the plant Hsp70:J protein network has not been studied. Here, we analyzed the J protein network in the cytosol of Arabidopsis thaliana and, using yeast genetics, show that the functional specificities of most plant J proteins in fundamental chaperone functions are conserved across long evolutionary timescales. Detailed phylogenetic and functional analysis revealed that increased number, regulatory differences, and neofunctionalization in J proteins together contribute to the emerging functional diversity and complexity in the Hsp70:J protein network in higher plants. Based on the data presented, we propose that higher plants have orchestrated their "chaperome," especially their J protein complement, according to their specialized cellular and physiological stipulations.

Evidence of Divergent Amino Acid Usage in Comparative Analyses of R5- and X4-Associated HIV-1 Vpr Sequences

Vpr is an HIV-1 accessory protein that plays numerous roles during viral replication, and some of which are cell type dependent. To test the hypothesis that HIV-1 tropism extends beyond the envelope into the vpr gene, studies were performed to identify the associations between coreceptor usage and Vpr variation in HIV-1-infected patients. Colinear HIV-1 Env-V3 and Vpr amino acid sequences were obtained from the LANL HIV-1 sequence database and from well-suppressed patients in the Drexel/Temple Medicine CNS AIDS Research and Eradication Study (CARES) Cohort. Genotypic classification of Env-V3 sequences as X4 (CXCR4-utilizing) or R5 (CCR5-utilizing) was used to group colinear Vpr sequences. To reveal the sequences associated with a specific coreceptor usage genotype, Vpr amino acid sequences were assessed for amino acid diversity and Jensen-Shannon divergence between the two groups. Five amino acid alphabets were used to comprehensively examine the impact of amino acid substitutions involving side chains with similar physiochemical properties. Positions 36, 37, 41, 89, and 96 of Vpr were characterized by statistically significant divergence across multiple alphabets when X4 and R5 sequence groups were compared. In addition, consensus amino acid switches were found at positions 37 and 41 in comparisons of the R5 and X4 sequence populations. These results suggest an evolutionary link between Vpr and gp120 in HIV-1-infected patients.

The Role of Evolutionary Selection in the Dynamics of Protein Structure Evolution

Homology modeling is a powerful tool for predicting a protein's structure. This approach is successful because proteins whose sequences are only 30% identical still adopt the same structure, while structure similarity rapidly deteriorates beyond the 30% threshold. By studying the divergence of protein structure as sequence evolves in real proteins and in evolutionary simulations, we show that this nonlinear sequence-structure relationship emerges as a result of selection for protein folding stability in divergent evolution. Fitness constraints prevent the emergence of unstable protein evolutionary intermediates, thereby enforcing evolutionary paths that preserve protein structure despite broad sequence divergence. However, on longer timescales, evolution is punctuated by rare events where the fitness barriers obstructing structure evolution are overcome and discovery of new structures occurs. We outline biophysical and evolutionary rationale for broad variation in protein family sizes, prevalence of compact structures among ancient proteins, and more rapid structure evolution of proteins with lower packing density.

Gene co-expression network connectivity is an important determinant of selective constraint

While several studies have investigated general properties of the genetic architecture of natural variation in gene expression, few of these have considered natural, outbreeding populations. In parallel, systems biology has established that a general feature of biological networks is that they are scale-free, rendering them buffered against random mutations. To date, few studies have attempted to examine the relationship between the selective processes acting to maintain natural variation of gene expression and the associated co-expression network structure. Here we utilised RNA-Sequencing to assay gene expression in winter buds undergoing bud flush in a natural population of Populus tremula, an outbreeding forest tree species. We performed expression Quantitative Trait Locus (eQTL) mapping and identified 164,290 significant eQTLs associating 6,241 unique genes (eGenes) with 147,419 unique SNPs (eSNPs). We found approximately four times as many local as distant eQTLs, with local eQTLs having significantly higher effect sizes. eQTLs were primarily located in regulatory regions of genes (UTRs or flanking regions), regardless of whether they were local or distant. We used the gene expression data to infer a co-expression network and investigated the relationship between network topology, the genetic architecture of gene expression and signatures of selection. Within the co-expression network, eGenes were underrepresented in network module cores (hubs) and overrepresented in the periphery of the network, with a negative correlation between eQTL effect size and network connectivity. We additionally found that module core genes have experienced stronger selective constraint on coding and non-coding sequence, with connectivity associated with signatures of selection. Our integrated genetics and genomics results suggest that purifying selection is the primary mechanism underlying the genetic architecture of natural variation in gene expression assayed in flushing leaf buds of P. tremula and that connectivity within the co-expression network is linked to the strength of purifying selection.

The Relationship between Selection, Network Connectivity, and Regulatory Variation within a Population of Capsella grandiflora

Interactions between genes can have important consequences for how selection shapes sequence variation at these genes. Specifically, genes that have pleiotropic effects by affecting the expression level of many other genes may be under stronger selective constraint. We used coexpression networks to measure connectivity between genes and investigated the relationship between gene connectivity and selection in a natural population of the plant Capsella grandiflora. We observed that network connectivity was negatively correlated with genetic divergence due to stronger negative selection on highly-connected genes even when controlling for variation in gene expression level. However, the presence of local regulatory variation for a gene's expression level was also associated with reduced negative selection and lower gene connectivity. While it is difficult to disentangle the causal relationships between these factors, our results show that both connectivity and local regulatory variation are important factors for explaining variation in selection between genes.

Biophysical Models of Protein Evolution: Understanding the Patterns of Evolutionary Sequence Divergence

For decades, rates of protein evolution have been interpreted in terms of the vague concept of functional importance. Slowly evolving proteins or sites within proteins were assumed to be more functionally important and thus subject to stronger selection pressure. More recently, biophysical models of protein evolution, which combine evolutionary theory with protein biophysics, have completely revolutionized our view of the forces that shape sequence divergence. Slowly evolving proteins have been found to evolve slowly because of selection against toxic misfolding and misinteractions, linking their rate of evolution primarily to their abundance. Similarly, most slowly evolving sites in proteins are not directly involved in function, but mutating these sites has a large impact on protein structure and stability. In this article, we review the studies in the emerging field of biophysical protein evolution that have shaped our current understanding of sequence divergence patterns. We also propose future research directions to develop this nascent field.

Effects of different kinds of essentiality on sequence evolution of human testis proteins

We asked if essentiality for either fertility or viability differentially affects sequence evolution of human testis proteins. Based on murine knockout data, we classified a set of 965 proteins expressed in human seminiferous tubules into three categories: proteins essential for prepubertal survival (“lethality proteins”), associated with male sub- or infertility (“male sub-/infertility proteins”), and nonessential proteins. In our testis protein dataset, lethality genes evolved significantly slower than nonessential and male sub-/infertility genes, which is in line with other authors’ findings. Using tissue specificity, connectivity in the protein-protein interaction (PPI) network, and multifunctionality as proxies for evolutionary constraints, we found that of the three categories, proteins linked to male sub- or infertility are least constrained. Lethality proteins, on the other hand, are characterized by broad expression, many PPI partners, and high multifunctionality, all of which points to strong evolutionary constraints. We conclude that compared with lethality proteins, those linked to male sub- or infertility are nonetheless indispensable, but evolve under more relaxed constraints. Finally, adaptive evolution in response to postmating sexual selection could further accelerate evolutionary rates of male sub- or infertility proteins expressed in human testis. These findings may become useful for in silico detection of human sub-/infertility genes.

Adaptation of A-to-I RNA editing in Drosophila

Adenosine-to-inosine (A-to-I) editing is hypothesized to facilitate adaptive evolution by expanding proteomic diversity through an epigenetic approach. However, it is challenging to provide evidences to support this hypothesis at the whole editome level. In this study, we systematically characterized 2,114 A-to-I RNA editing sites in female and male brains of D. melanogaster, and nearly half of these sites had events evolutionarily conserved across Drosophila species. We detected strong signatures of positive selection on the nonsynonymous editing sites in Drosophila brains, and the beneficial editing sites were significantly enriched in genes related to chemical and electrical neurotransmission. The signal of adaptation was even more pronounced for the editing sites located in X chromosome or for those commonly observed across Drosophila species. We identified a set of gene candidates (termed "PSEB" genes) that had nonsynonymous editing events favored by natural selection. We presented evidence that editing preferentially increased mutation sequence space of evolutionarily conserved genes, which supported the adaptive evolution hypothesis of editing. We found prevalent nonsynonymous editing sites that were favored by natural selection in female and male adults from five strains of D. melanogaster. We showed that temperature played a more important role than gender effect in shaping the editing levels, although the effect of temperature is relatively weaker compared to that of species effect. We also explored the relevant factors that shape the selective patterns of the global editomes. Altogether we demonstrated that abundant nonsynonymous editing sites in Drosophila brains were adaptive and maintained by natural selection during evolution. Our results shed new light on the evolutionary principles and functional consequences of RNA editing.

Increased rates of protein evolution and asymmetric deceleration after the whole-genome duplication in yeasts

Background

Whole-genome duplication (WGD) events have shaped the genomes of eukaryotic organisms. Relaxed selection after duplication along with inherent functional constraints are thought to determine the fate of the paralogs and, ultimately, the evolution of gene function. Here, we investigated the rate of protein evolution (as measured by dN/dS ratios) before and after the WGD in the hemiascomycete yeasts, and the way in which changes in such rates relate to molecular and biological function.

Results

For most groups of orthologous genes (81%) we observed a change in the rates of evolution after genome duplication. Genes with atypically-low dN/dS ratio before the WGD were prone to increase their rates of evolution after duplication. Importantly, the paralogs were often different in their rates of evolution after the WGD (50% cases), however, this was more consistent with an asymmetric deceleration in the protein-evolution rates, rather than an asymmetric increase of the initial rates. Functional-category analysis showed that regulatory proteins such as protein kinases and transcription factors were enriched in genes that increase their rates of evolution after the WGD. While changes in the rate of protein-sequence evolution were associated to protein abundance, content of disordered regions, and contribution to fitness, these features were an attribute of specific functional classes.

Conclusions

Our results indicate that strong purifying selection in ancestral pre-duplication sequences is a strong predictor of increased rates after the duplication in yeasts and that asymmetry in evolution rate is established during the deceleration phase. In addition, changes in the rates at which paralogous sequences evolve before and after WGD are different for specific protein functions; increased rates of protein evolution after duplication occur preferentially in specific protein functions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-017-0895-1) contains supplementary material, which is available to authorized users.