Translational selection and yeast proteome evolution

Complete mitogenome and intra-family comparative mitogenomics showed distinct position of Pama Croaker Otolithoides pama

The Pama Croaker, Otolithoides pama, is an economically important fish species in Bangladesh. Intra-family similarities in morphology and typical barcode sequences of cox1 create ambiguities in its identification. Therefore, morphology and the complete mitochondrial genome of O. pama, and comparative mitogenomics within the family Sciaenidae have been studied. Extracted genomic DNA was subjected to Illumina-based short read sequencing for De-Novo mitogenome assembly. The complete mitogenome of O. pama (Accession: OQ784575.1) was 16,513 bp, with strong AC biasness and strand asymmetry. Relative synonymous codon usage (RSCU) among 13 protein-coding genes (PCGs) of O. pama was also analyzed. The studied mitogenomes including O. pama exhibited consistent sizes and gene orders, except for the genus Johnius which possessed notably longer mitogenomes with unique gene rearrangements. Different genetic distance metrics across 30 species of Sciaenidae family demonstrated 12S rRNA and the control region (CR) as the most conserved and variable regions, respectively, while most of the PCGs undergone a purifying selection. Different phylogenetic trees were congruent with one another, where O. pama was distinctly placed. This study would contribute to distinguishing closely related fish species of Sciaenidae family and can be instrumental in conserving the genetic diversity of O. pama.

Characterization of the Complete Mitochondrial Genome of the Elongate Loach and Its Phylogenetic Implications in Cobitidae

The elongate loach is an endemic fish in China. Previous studies have provided some insights into the mitochondrial genome composition and the phylogenetic relationships of the elongate loach inferred using protein-coding genes (PCGs), yet detailed information about it remains limited. Therefore, in this study we sequenced the complete mitochondrial genome of the elongate loach and analyzed its structural characteristics. The PCGs and mitochondrial genome were used for selective stress analysis and genomic comparative analysis. The complete mitochondrial genome of the elongate loach, together with those of 35 Cyprinidae species, was used to infer the phylogenetic relationships of the Cobitidae family through maximum likelihood (ML) reconstruction. The results showed that the genome sequence has a full length of 16,591 bp, which includes 13 PCGs, 22 transfer RNA genes (tRNA), 2 ribosomal RNA genes (rRNA), and 2 non-coding regions (CR D-loop and light chain sub-chain replication origin OL). Overall, the elongate loach shared the same gene arrangement and composition of the mitochondrial genes with other teleost fishes. The Ka/Ks ratios of all mitochondrial PCGs were less than 1, indicating that all of the PCGs were evolving under purifying selection. Genome comparison analyses showed a significant sequence homology of species of Leptobotia. A significant identity between L. elongata and the other five Leptobotia species was observed in the visualization result, except for L. mantschurica, which lacked the tRNA-Arg gene and had a shorter tRNA-Asp gene. The phylogenetic tree revealed that the Cobitidae species examined here can be grouped into two clades, with the elongate loach forming a sister relationship with L. microphthalma. This study could provide additional inferences for a better understanding of the phylogenetic relationships among Cobitidae species.

A Dynamic rRNA Ribomethylome Drives Stemness in Acute Myeloid Leukemia

The development and regulation of malignant self-renewal remain unresolved issues. Here, we provide biochemical, genetic, and functional evidence that dynamics in ribosomal RNA (rRNA) 2'-O-methylation regulate leukemia stem cell (LSC) activity in vivo. A comprehensive analysis of the rRNA 2'-O-methylation landscape of 94 patients with acute myeloid leukemia (AML) revealed dynamic 2'-O-methylation specifically at exterior sites of ribosomes. The rRNA 2'-O-methylation pattern is closely associated with AML development stage and LSC gene expression signature. Forced expression of the 2'-O-methyltransferase fibrillarin (FBL) induced an AML stem cell phenotype and enabled engraftment of non-LSC leukemia cells in NSG mice. Enhanced 2'-O-methylation redirected the ribosome translation program toward amino acid transporter mRNAs enriched in optimal codons and subsequently increased intracellular amino acid levels. Methylation at the single site 18S-guanosine 1447 was instrumental for LSC activity. Collectively, our work demonstrates that dynamic 2'-O-methylation at specific sites on rRNAs shifts translational preferences and controls AML LSC self-renewal.

SIGNIFICANCE

We establish the complete rRNA 2'-O-methylation landscape in human AML. Plasticity of rRNA 2'-O-methylation shifts protein translation toward an LSC phenotype. This dynamic process constitutes a novel concept of how cancers reprogram cell fate and function. This article is highlighted in the In This Issue feature, p. 247.

Determinants of associations between codon and amino acid usage patterns of microbial communities and the environment inferred based on a cross-biome metagenomic analysis

Codon and amino acid usage were associated with almost every aspect of microbial life. However, how the environment may impact the codon and amino acid choice of microbial communities at the habitat level is not clearly understood. Therefore, in this study, we analyzed codon and amino acid usage patterns of a large number of environmental samples collected from diverse ecological niches. Our results suggested that samples derived from similar environmental niches, in general, show overall similar codon and amino acid distribution as compared to samples from other habitats. To substantiate the relative impact of the environment, we considered several factors, such as their similarity in GC content, or in functional or taxonomic abundance. Our analysis demonstrated that none of these factors can fully explain the trends that we observed at the codon or amino acid level implying a direct environmental influence on them. Further, our analysis demonstrated different levels of selection on codon bias in different microbial communities with the highest bias in host-associated environments such as the digestive system or oral samples and the lowest level of selection in soil and water samples. Considering a large number of metagenomic samples here we showed that microorganisms collected from similar environmental backgrounds exhibit similar patterns of codon and amino acid usage irrespective of the location or time from where the samples were collected. Thus our study suggested a direct impact of the environment on codon and amino usage of microorganisms that cannot be explained considering the influence of other factors.

Characterization of mitochondrial genome of Indian Ocean blue-spotted maskray, Neotrygon indica and its phylogenetic relationship within Dasyatidae Family

The present study characterized complete mitochondrial genome of Blue-spotted maskray, Neotrygon indica and studied the evolutionary relationship of the species within the Dasyatidae family. The total length of the mitogenome was 17,974 bp including 37 genes and a non-coding control region. The average frequency of nucleotides in protein-coding genes was A: 29.1 %, T: 30.2 %, G: 13.0 % and C: 27.7 % with AT content of 59.3 %. The values of AT and GC skewness were -0.018 and -0.338, respectively. Comparative analyses showed a large number of average synonymous substitutions per synonymous site (Ks) in gene NADH4 (5.07) followed by NADH5 (4.72). High values of average number of non-synonymous substitutions per non-synonymous site (Ka) were observed in genes ATPase8 (0.54) and NADH2 (0.44). Genes NADH4L and NADH2 showed high interspecific genetic distance values of 0.224 ± 0.001 and 0.213 ± 0.002, respectively. Heat map analysis showed variation in codon usage among different species of the Dasyatidae family. The phylogenetic tree showed a sister relationship between the Dasyatinae and the Neotrygoninae subfamilies. Neotrygon indica formed as a sister species to the clade consisting of N. varidens and N. orientalis. Based on the present results, Neotrygon indica could have diverged from the common ancestor of the two latter in the Plio-Pleistocene. The present study showed distinct characteristics of N. indica from its congeners through comparative mitogenomics.

Purifying selection enduringly acts on the sequence evolution of highly expressed proteins in Escherichia coli

The evolutionary speed of a protein sequence is constrained by its expression level, with highly expressed proteins evolving relatively slowly. This negative correlation between expression levels and evolutionary rates (known as the E–R anticorrelation) has already been widely observed in past macroevolution between species from bacteria to animals. However, it remains unclear whether this seemingly general law also governs recent evolution, including past and de novo, within a species. However, the advent of genomic sequencing and high-throughput phenotyping, particularly for bacteria, has revealed fundamental gaps between the 2 evolutionary processes and has provided empirical data opposing the possible underlying mechanisms which are widely believed. These conflicts raise questions about the generalization of the E–R anticorrelation and the relevance of plausible mechanisms. To explore the ubiquitous impact of expression levels on molecular evolution and test the relevance of the possible underlying mechanisms, we analyzed the genome sequences of 99 strains of Escherichia coli for evolution within species in nature. We also analyzed genomic mutations accumulated under laboratory conditions as a model of de novo evolution within species. Here, we show that E–R anticorrelation is significant in both past and de novo evolution within species in E. coli. Our data also confirmed ongoing purifying selection on highly expressed genes. Ongoing selection included codon-level purifying selection, supporting the relevance of the underlying mechanisms. However, the impact of codon-level purifying selection on the constraints in evolution within species might be smaller than previously expected from evolution between species.

Variables Influencing Differences in Sequence Conservation in the Fission Yeast Schizosaccharomyces pombe

Which variables determine the constraints on gene sequence evolution is one of the most central questions in molecular evolution. In the fission yeast Schizosaccharomyces pombe, an important model organism, the variables influencing the rate of sequence evolution have yet to be determined. Previous studies in other single celled organisms have generally found gene expression levels to be most significant, with numerous other variables such as gene length and functional importance identified as having a smaller impact. Using publicly available data, we used partial least squares regression, principal components regression, and partial correlations to determine the variables most strongly associated with sequence evolution constraints. We identify centrality in the protein–protein interactions network, amino acid composition, and cellular location as the most important determinants of sequence conservation. However, each factor only explains a small amount of variance, and there are numerous variables having a significant or heterogeneous influence. Our models explain more than half of the variance in dN, raising the possibility that future refined models could quantify the role of stochastics in evolutionary rate variation.

The impact of codon choice on translation process in Saccharomyces cerevisiae: folding class, protein function and secondary structure

The genetic code consists in a set of rules used by living organisms to translate genomic information, contained in genes, into proteins; every amino acid is coded by a set of nucleotide triplets or codons. We refer to codon choice as the choice of a given codon, among the synonymous available ones, to code a given amino acid occurrence. The aim of this work is to shed light on the pivotal role that codon choice plays in regulating the timing of translation process, through patterns of low and high translation efficiency codons. A translation efficiency value, namely codon score, was associated to each codon through a formula based on the number of tRNAs gene copies able to translate the given codon. By using codon scores, those k-mers of the proteome of Saccharomyces cerevisiae, showing low and high average scores associated to the correspondent codons, were computed. The analysis of distribution of both low and high average score k-mers clearly showed that, in particular for higher k-mer size, they occur much more than expected, strongly suggesting a functional role. Moreover performed analysis highlighted that significant k-mers preferentially occur in some protein folding classes, such as those containing alpha helices, and in some functional classes mainly involved in transcription process while codon choice seems to have a very low impact in proteins associated to energy production and metabolism. The relationship between secondary structures and significant k-mers was investigated, revealing that low score k-mers tend to preferentially occur in coil or close to coil regions and almost never in beta sheets, while high score k-mers preferentially occur in alpha helices, avoiding beta sheets, and close to coil regions for high k-mer sizes. Finally the analysis of distribution of significant codon patterns along the proteins highlighted a relevant enrichment of low average score k-mers at the 5' end of protein-coding sequences in the region from 5th to 25th amino acid.

The Adenine/Thymine Deleterious Selection Model for GC Content Evolution at the Third Codon Position of the Histone Genes in Drosophila

The evolution of the GC (guanine cytosine) content at the third codon position of the histone genes (H1, H2A, H2B, H3, H4, H2AvD, H3.3A, H3.3B, and H4r) in 12 or more Drosophila species is reviewed. For explaining the evolution of the GC content at the third codon position of the genes, a model assuming selection with a deleterious effect for adenine/thymine and a size effect is presented. The applicability of the model to whole-genome genes is also discussed.

Abundance Imparts Evolutionary Constraints of Similar Magnitude on the Buried, Surface, and Disordered Regions of Proteins

An understanding of the forces shaping protein conservation is key, both for the fundamental knowledge it represents and to allow for optimal use of evolutionary information in practical applications. Sequence conservation is typically examined at one of two levels. The first is a residue-level, where intra-protein differences are analyzed and the second is a protein-level, where inter-protein differences are studied. At a residue level, we know that solvent-accessibility is a prime determinant of conservation. By inverting this logic, we inferred that disordered regions are slightly more solvent-accessible on average than the most exposed surface residues in domains. By integrating abundance information with evolutionary data within and across proteins, we confirmed a previously reported strong surface-core association in the evolution of structured regions, but we found a comparatively weak association between disordered and structured regions. The facts that disordered and structured regions experience different structural constraints and evolve independently provide a unique setup to examine an outstanding question: why is a protein’s abundance the main determinant of its sequence conservation? Indeed, any structural or biophysical property linked to the abundance-conservation relationship should increase the relative conservation of regions concerned with that property (e.g., disordered residues with mis-interactions, domain residues with misfolding). Surprisingly, however, we found the conservation of disordered and structured regions to increase in equal proportion with abundance. This observation implies that either abundance-related constraints are structure-independent, or multiple constraints apply to different regions and perfectly balance each other.

Some theoretical aspects of reprogramming the standard genetic code

Reprogramming of the standard genetic code to include non-canonical amino acids (ncAAs) opens new prospects for medicine, industry, and biotechnology. There are several methods of code engineering, which allow us for storing new genetic information in DNA sequences and producing proteins with new properties. Here, we provided a theoretical background for the optimal genetic code expansion, which may find application in the experimental design of the genetic code. We assumed that the expanded genetic code includes both canonical and non-canonical information stored in 64 classical codons. What is more, the new coding system is robust to point mutations and minimizes the possibility of reversion from the new to old information. In order to find such codes, we applied graph theory to analyze the properties of optimal codon sets. We presented the formal procedure in finding the optimal codes with various number of vacant codons that could be assigned to new amino acids. Finally, we discussed the optimal number of the newly incorporated ncAAs and also the optimal size of codon groups that can be assigned to ncAAs.

Molecular features similarities between SARS-CoV-2, SARS, MERS and key human genes could favour the viral infections and trigger collateral effects

In December 2019, rising pneumonia cases caused by a novel β-coronavirus (SARS-CoV-2) occurred in Wuhan, China, which has rapidly spread worldwide, causing thousands of deaths. The WHO declared the SARS-CoV-2 outbreak as a public health emergency of international concern, since then several scientists are dedicated to its study. It has been observed that many human viruses have codon usage biases that match highly expressed proteins in the tissues they infect and depend on the host cell machinery for the replication and co-evolution. In this work, we analysed 91 molecular features and codon usage patterns for 339 viral genes and 463 human genes that consisted of 677,873 codon positions. Hereby, we selected the highly expressed genes from human lung tissue to perform computational studies that permit to compare their molecular features with those of SARS, SARS-CoV-2 and MERS genes. The integrated analysis of all the features revealed that certain viral genes and overexpressed human genes have similar codon usage patterns. The main pattern was the A/T bias that together with other features could propitiate the viral infection, enhanced by a host dependant specialization of the translation machinery of only some of the overexpressed genes. The envelope protein E, the membrane glycoprotein M and ORF7 could be further benefited. This could be the key for a facilitated translation and viral replication conducting to different comorbidities depending on the genetic variability of population due to the host translation machinery. This is the first codon usage approach that reveals which human genes could be potentially deregulated due to the codon usage similarities between the host and the viral genes when the virus is already inside the human cells of the lung tissues. Our work leaded to the identification of additional highly expressed human genes which are not the usual suspects but might play a role in the viral infection and settle the basis for further research in the field of human genetics associated with new viral infections. To identify the genes that could be deregulated under a viral infection is important to predict the collateral effects and determine which individuals would be more susceptible based on their genetic features and comorbidities associated.

The regulatory genome constrains protein sequence evolution: implications for the search for disease-associated genes

The development of explanatory models of protein sequence evolution has broad implications for our understanding of cellular biology, population history, and disease etiology. Here we analyze the GTEx transcriptome resource to quantify the effect of the transcriptome on protein sequence evolution in a multi-tissue framework. We find substantial variation among the central nervous system tissues in the effect of expression variance on evolutionary rate, with highly variable genes in the cortex showing significantly greater purifying selection than highly variable genes in subcortical regions (Mann-Whitney U p = 1.4 × 10^-4). The remaining tissues cluster in observed expression correlation with evolutionary rate, enabling evolutionary analysis of genes in diverse physiological systems, including digestive, reproductive, and immune systems. Importantly, the tissue in which a gene attains its maximum expression variance significantly varies (p = 5.55 × 10^-284) with evolutionary rate, suggesting a tissue-anchored model of protein sequence evolution. Using a large-scale reference resource, we show that the tissue-anchored model provides a transcriptome-based approach to predicting the primary affected tissue of developmental disorders. Using gradient boosted regression trees to model evolutionary rate under a range of model parameters, selected features explain up to 62% of the variation in evolutionary rate and provide additional support for the tissue model. Finally, we investigate several methodological implications, including the importance of evolutionary-rate-aware gene expression imputation models using genetic data for improved search for disease-associated genes in transcriptome-wide association studies. Collectively, this study presents a comprehensive transcriptome-based analysis of a range of factors that may constrain molecular evolution and proposes a novel framework for the study of gene function and disease mechanism.

Survival of the cheapest: how proteome cost minimization drives evolution

Darwin's theory of evolution emphasized that positive selection of functional proficiency provides the fitness that ultimately determines the structure of life, a view that has dominated biochemical thinking of enzymes as perfectly optimized for their specific functions. The 20th-century modern synthesis, structural biology, and the central dogma explained the machinery of evolution, and nearly neutral theory explained how selection competes with random fixation dynamics that produce molecular clocks essential e.g. for dating evolutionary histories. However, quantitative proteomics revealed that selection pressures not relating to optimal function play much larger roles than previously thought, acting perhaps most importantly via protein expression levels. This paper first summarizes recent progress in the 21st century toward recovering this universal selection pressure. Then, the paper argues that proteome cost minimization is the dominant, underlying 'non-function' selection pressure controlling most of the evolution of already functionally adapted living systems. A theory of proteome cost minimization is described and argued to have consequences for understanding evolutionary trade-offs, aging, cancer, and neurodegenerative protein-misfolding diseases.

The Impact of Protein Architecture on Adaptive Evolution

Adaptive mutations play an important role in molecular evolution. However, the frequency and nature of these mutations at the intramolecular level are poorly understood. To address this, we analyzed the impact of protein architecture on the rate of adaptive substitutions, aiming to understand how protein biophysics influences fitness and adaptation. Using Drosophila melanogaster and Arabidopsis thaliana population genomics data, we fitted models of distribution of fitness effects and estimated the rate of adaptive amino-acid substitutions both at the protein and amino-acid residue level. We performed a comprehensive analysis covering genome, gene, and protein structure, by exploring a multitude of factors with a plausible impact on the rate of adaptive evolution, such as intron number, protein length, secondary structure, relative solvent accessibility, intrinsic protein disorder, chaperone affinity, gene expression, protein function, and protein-protein interactions. We found that the relative solvent accessibility is a major determinant of adaptive evolution, with most adaptive mutations occurring at the surface of proteins. Moreover, we observe that the rate of adaptive substitutions differs between protein functional classes, with genes encoding for protein biosynthesis and degradation signaling exhibiting the fastest rates of protein adaptation. Overall, our results suggest that adaptive evolution in proteins is mainly driven by intermolecular interactions, with host-pathogen coevolution likely playing a major role.

Characterization of bovine (Bos taurus) imprinted genes from genomic to amino acid attributes by data mining approaches

Genomic imprinting results in monoallelic expression of genes in mammals and flowering plants. Understanding the function of imprinted genes improves our knowledge of the regulatory processes in the genome. In this study, we have employed classification and clustering algorithms with attribute weighting to specify the unique attributes of both imprinted (monoallelic) and biallelic expressed genes. We have obtained characteristics of 22 known monoallelically expressed (imprinted) and 8 biallelic expressed genes that have been experimentally validated alongside 208 randomly selected genes in bovine (Bos taurus). Attribute weighting methods and various supervised and unsupervised algorithms in machine learning were applied. Unique characteristics were discovered and used to distinguish mono and biallelic expressed genes from each other in bovine. To obtain the accuracy of classification, 10-fold cross-validation with concerning each combination of attribute weighting (feature selection) and machine learning algorithms, was used. Our approach was able to accurately predict mono and biallelic genes using the genomics and proteomics attributes.

Molecular evolutionary engineering of xylose isomerase to improve its catalytic activity and performance of micro-aerobic glucose/xylose co-fermentation in Saccharomyces cerevisiae

BACKGROUND

Expression of d-xylose isomerase having high catalytic activity in Saccharomyces cerevisiae (S. cerevisiae) is a prerequisite for efficient and economical production of bioethanol from cellulosic biomass. Although previous studies demonstrated functional expression of several xylose isomerases (XI) in S. cerevisiae, identification of XIs having higher catalytic activity is needed. Here, we report a new strategy to improve xylose fermentation in the S. cerevisiae strain IR-2 that involves an evolutionary engineering to select top-performing XIs from eight previously reported XIs derived from various species.

RESULTS

Eight XI genes shown to have good expression in S. cerevisiae were introduced into the strain IR-2 having a deletion of GRE3 and XKS1 overexpression that allows use of d-xylose as a carbon source. Each transformant was evaluated under aerobic and micro-aerobic culture conditions. The strain expressing XI from Lachnoclostridium phytofermentans ISDg (LpXI) had the highest d-xylose consumption rate after 72 h of micro-aerobic fermentation on d-glucose and d-xylose mixed medium. To enhance LpXI catalytic activity, we performed random mutagenesis using error-prone polymerase chain reaction (PCR), which yielded two LpXI candidates, SS82 and SS92, that showed markedly improved fermentation performance. The LpXI genes in these clones carried either T63I or V162A/N303T point mutations. The SS120 strain expressing LpXI with the double mutation of T63I/V162A assimilated nearly 85 g/L d-glucose and 35 g/L d-xylose to produce 53.3 g/L ethanol in 72 h with an ethanol yield of approximately 0.44 (g/g-input sugars). An in vitro enzyme assay showed that, compared to wild-type, the LpXI double mutant in SS120 had a considerably higher V _max (0.107 µmol/mg protein/min) and lower K _m (37.1 mM).

CONCLUSIONS

This study demonstrated that LpXI has the highest d-xylose consumption rate among the XIs expressed in IR-2 under micro-aerobic co-fermentation conditions. A combination of novel mutations (T63I and V162A) significantly improved the enzymatic activity of LpXI, indicating that LpXI-T63I/V162A would be a potential construct for highly efficient production of cellulosic ethanol.

Genome-Wide Patterns of Sequence Divergence of Protein-Coding Genes Between Drosophila buzzatii and D. mojavensis

Evolutionary rates for protein-coding genes are determined not only by natural selection but also by multiple genomic factors including mutation rates, recombination, gene expression levels, and chromosomal location. To investigate the joint effects of different genomic determinants on protein evolution, we compared the coding sequences of 9017 single-copy orthologs between 2 cactophilic species from the Drosophila subgenus, Drosophila mojavensis and D. buzzatii, whose genomes have been previously sequenced. We assessed the impact of 7 genomic determinants, that is, chromosome type, recombination, chromosomal inversions, expression breadth, expression level, gene length, and the number of exons, on divergence rates of protein-coding genes to understand patterns of evolutionary variation. Integrative analysis of these factors revealed that 1) X-linked and autosomal genes evolve at significantly different rates in agreement with the faster-X hypothesis, 2) genes located on the dot chromosome and pericentromeric regions have higher divergence rates, 3) genes located at chromosomes with more fixed inversions have higher pairwise divergence than those located at nearly collinear chromosomes, and 4) gene expression patterns can be considered the strongest determinant of protein evolution. In addition, the number of exons and protein length had a significant effect on pairwise divergence at synonymous sites. All in all, our results show the relative importance of each genomic factor on the rates of protein evolution and functional constraint in these 2 cactophilic Drosophila species.

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.

Codon usage of highly expressed genes affects proteome-wide translation efficiency

Although the genetic code is redundant, synonymous codons for the same amino acid are not used with equal frequencies in genomes, a phenomenon termed "codon usage bias." Previous studies have demonstrated that synonymous changes in a coding sequence can exert significant cis effects on the gene's expression level. However, whether the codon composition of a gene can also affect the translation efficiency of other genes has not been thoroughly explored. To study how codon usage bias influences the cellular economy of translation, we massively converted abundant codons to their rare synonymous counterpart in several highly expressed genes in Escherichia coli This perturbation reduces both the cellular fitness and the translation efficiency of genes that have high initiation rates and are naturally enriched with the manipulated codon, in agreement with theoretical predictions. Interestingly, we could alleviate the observed phenotypes by increasing the supply of the tRNA for the highly demanded codon, thus demonstrating that the codon usage of highly expressed genes was selected in evolution to maintain the efficiency of global protein translation.

Promoter architecture determines cotranslational regulation of mRNA

Information that regulates gene expression is encoded throughout each gene but if different regulatory regions can be understood in isolation, or if they interact, is unknown. Here we measure mRNA levels for 10,000 open reading frames (ORFs) transcribed from either an inducible or constitutive promoter. We find that the strength of cotranslational regulation on mRNA levels is determined by promoter architecture. By using a novel computational genetic screen of 6402 RNA-seq experiments, we identify the RNA helicase Dbp2 as the mechanism by which cotranslational regulation is reduced specifically for inducible promoters. Finally, we find that for constitutive genes, but not inducible genes, most of the information encoding regulation of mRNA levels in response to changes in growth rate is encoded in the ORF and not in the promoter. Thus, the ORF sequence is a major regulator of gene expression, and a nonlinear interaction between promoters and ORFs determines mRNA levels.

Dissimilar substitution rates between two strands of DNA influence codon usage pattern in some human genes

We illustrated the descriptive aspects of codon usage of some important human genes and their expression potential in E. coli. By comparing the results of various codon usage parameters, effects that are due to selection and mutational pressures have been deciphered. The variation in GC3s explains a significant proportion of the variation in codon usage patterns. The codons CGC, CGG, CTG and GCG showed strong positive correlation with GC3, which suggested that codon usage had been influenced by GC bias. We also found that ACC (Thr, RSCU-1.77), GCC (Ala, RSCU-1.67), CCC (Pro, RSCU-1.54), TCC (Ser, RSCU-1.47) were frequently used which signified that C was common at 2nd and 3rd codon positions. Correspondence analysis revealed that F1 axis had significant correlation with various GC contents suggesting that compositional properties under mutation pressure might affect codon usage bias. Nc-GC3 plot analysis suggested that both mutation pressure and natural selection might affect the codon usage bias which is also supported by neutrality plot analysis. The dinucleotide CT, TG and AG were significantly over-represented and CG, TA, AT, TT, and GT were underrepresented due to high rate of spontaneous mutation resulting from cytosine deamination.

Diminishing Returns on Intragenic Repeat Number Expansion in the Production of Signaling Peptides

Signaling peptides enable communication between cells, both within and between individuals, and are therefore key to the control of complex physiological and behavioral responses. Since their small sizes prevent direct transmission to secretory pathways, these peptides are often produced as part of a larger polyprotein comprising precursors for multiple related or identical peptides; the physiological and behavioral consequences of this unusual gene structure are not understood. Here, we show that the number of mature-pheromone-encoding repeats in the yeast α-mating-factor gene MFα1 varies considerably between closely related isolates of both Saccharomyces cerevisiae and its sister species Saccharomyces paradoxus. Variation in repeat number has important phenotypic consequences: Increasing repeat number caused higher pheromone production and greater competitive mating success. However, the magnitude of the improvement decreased with increasing repeat number such that repeat amplification beyond that observed in natural isolates failed to generate more pheromone, and could actually reduce sexual fitness. We investigate multiple explanations for this pattern of diminishing returns and find that our results are most consistent with a translational trade-off: Increasing the number of encoded repeats results in more mature pheromone per translation event, but also generates longer transcripts thereby reducing the rate of translation—a phenomenon known as length-dependent translation. Length-dependent translation may be a powerful constraint on the evolution of genes encoding repetitive or modular proteins, with important physiological and behavioral consequences across eukaryotes.

Codon usage and codon pair patterns in non-grass monocot genomes

BACKGROUND AND AIMS

Studies on codon usage in monocots have focused on grasses, and observed patterns of this taxon were generalized to all monocot species. Here, non-grass monocot species were analysed to investigate the differences between grass and non-grass monocots.

METHODS

First, studies of codon usage in monocots were reviewed. The current information was then extended regarding codon usage, as well as codon-pair context bias, using four completely sequenced non-grass monocot genomes (Musa acuminata, Musa balbisiana, Phoenix dactylifera and Spirodela polyrhiza) for which comparable transcriptome datasets are available. Measurements were taken regarding relative synonymous codon usage, effective number of codons, derived optimal codon and GC content and then the relationships investigated to infer the underlying evolutionary forces.

KEY RESULTS

The research identified optimal codons, rare codons and preferred codon-pair context in the non-grass monocot species studied. In contrast to the bimodal distribution of GC3 (GC content in third codon position) in grasses, non-grass monocots showed a unimodal distribution. Disproportionate use of G and C (and of A and T) in two- and four-codon amino acids detected in the analysis rules out the mutational bias hypothesis as an explanation of genomic variation in GC content. There was found to be a positive relationship between CAI (codon adaptation index; predicts the level of expression of a gene) and GC3. In addition, a strong correlation was observed between coding and genomic GC content and negative correlation of GC3 with gene length, indicating a strong impact of GC-biased gene conversion (gBGC) in shaping codon usage and nucleotide composition in non-grass monocots.

CONCLUSION

Optimal codons in these non-grass monocots show a preference for G/C in the third codon position. These results support the concept that codon usage and nucleotide composition in non-grass monocots are mainly driven by gBGC.

Identification of Conflicting Selective Effects on Highly Expressed Genes

Many different selective effects on DNA and proteins influence the frequency of codons and amino acids in coding sequences. Selection is often stronger on highly expressed genes. Hence, by comparing high- and low-expression genes it is possible to distinguish the factors that are selected by evolution. It has been proposed that highly expressed genes should (i) preferentially use codons matching abundant tRNAs (translational efficiency), (ii) preferentially use amino acids with low cost of synthesis, (iii) be under stronger selection to maintain the required amino acid content, and (iv) be selected for translational robustness. These effects act simultaneously and can be contradictory. We develop a model that combines these factors, and use Akaike's Information Criterion for model selection. We consider pairs of paralogues that arose by whole-genome duplication in Saccharmyces cerevisiae. A codon-based model is used that includes asymmetric effects due to selection on highly expressed genes. The largest effect is translational efficiency, which is found to strongly influence synonymous, but not non-synonymous rates. Minimization of the cost of amino acid synthesis is implicated. However, when a more general measure of selection for amino acid usage is used, the cost minimization effect becomes redundant. Small effects that we attribute to selection for translational robustness can be identified as an improvement in the model fit on top of the effects of translational efficiency and amino acid usage.

Deep learning of the regulatory grammar of yeast 5' untranslated regions from 500,000 random sequences

Our ability to predict protein expression from DNA sequence alone remains poor, reflecting our limited understanding of cis-regulatory grammar and hampering the design of engineered genes for synthetic biology applications. Here, we generate a model that predicts the protein expression of the 5′ untranslated region (UTR) of mRNAs in the yeast Saccharomyces cerevisiae. We constructed a library of half a million 50-nucleotide-long random 5′ UTRs and assayed their activity in a massively parallel growth selection experiment. The resulting data allow us to quantify the impact on protein expression of Kozak sequence composition, upstream open reading frames (uORFs), and secondary structure. We trained a convolutional neural network (CNN) on the random library and showed that it performs well at predicting the protein expression of both a held-out set of the random 5′ UTRs as well as native S. cerevisiae 5′ UTRs. The model additionally was used to computationally evolve highly active 5′ UTRs. We confirmed experimentally that the great majority of the evolved sequences led to higher protein expression rates than the starting sequences, demonstrating the predictive power of this model.

Codon optimality, bias and usage in translation and mRNA decay

The advent of ribosome profiling and other tools to probe mRNA translation has revealed that codon bias - the uneven use of synonymous codons in the transcriptome - serves as a secondary genetic code: a code that guides the efficiency of protein production, the fidelity of translation and the metabolism of mRNAs. Recent advancements in our understanding of mRNA decay have revealed a tight coupling between ribosome dynamics and the stability of mRNA transcripts; this coupling integrates codon bias into the concept of codon optimality, or the effects that specific codons and tRNA concentrations have on the efficiency and fidelity of the translation machinery. In this Review, we first discuss the evidence for codon-dependent effects on translation, beginning with the basic mechanisms through which translation perturbation can affect translation efficiency, protein folding and transcript stability. We then discuss how codon effects are leveraged by the cell to tailor the proteome to maintain homeostasis, execute specific gene expression programmes of growth or differentiation and optimize the efficiency of protein production.

Microbial taxonomy in the era of OMICS: application of DNA sequences, computational tools and techniques

The current prokaryotic taxonomy classifies phenotypically and genotypically diverse microorganisms using a polyphasic approach. With advances in the next-generation sequencing technologies and computational tools for analysis of genomes, the traditional polyphasic method is complemented with genomic data to delineate and classify bacterial genera and species as an alternative to cumbersome and error-prone laboratory tests. This review discusses the applications of sequence-based tools and techniques for bacterial classification and provides a scheme for more robust and reproducible bacterial classification based on genomic data. The present review highlights promising tools and techniques such as ortho-Average Nucleotide Identity, Genome to Genome Distance Calculator and Multi Locus Sequence Analysis, which can be validly employed for characterizing novel microorganisms and assessing phylogenetic relationships. In addition, the review discusses the possibility of employing metagenomic data to assess the phylogenetic associations of uncultured microorganisms. Through this article, we present a review of genomic approaches that can be included in the scheme of taxonomy of bacteria and archaea based on computational and in silico advances to boost the credibility of taxonomic classification in this genomic era.

Genetic Code Optimization for Cotranslational Protein Folding: Codon Directional Asymmetry Correlates with Antiparallel Betasheets, tRNA Synthetase Classes

A new codon property, codon directional asymmetry in nucleotide content (CDA), reveals a biologically meaningful genetic code dimension: palindromic codons (first and last nucleotides identical, codon structure XZX) are symmetric (CDA = 0), codons with structures ZXX/XXZ are 5'/3' asymmetric (CDA = - 1/1; CDA = - 0.5/0.5 if Z and X are both purines or both pyrimidines, assigning negative/positive (-/+) signs is an arbitrary convention). Negative/positive CDAs associate with (a) Fujimoto's tetrahedral codon stereo-table; (b) tRNA synthetase class I/II (aminoacylate the 2'/3' hydroxyl group of the tRNA's last ribose, respectively); and (c) high/low antiparallel (not parallel) betasheet conformation parameters. Preliminary results suggest CDA-whole organism associations (body temperature, developmental stability, lifespan). Presumably, CDA impacts spatial kinetics of codon-anticodon interactions, affecting cotranslational protein folding. Some synonymous codons have opposite CDA sign (alanine, leucine, serine, and valine), putatively explaining how synonymous mutations sometimes affect protein function. Correlations between CDA and tRNA synthetase classes are weaker than between CDA and antiparallel betasheet conformation parameters. This effect is stronger for mitochondrial genetic codes, and potentially drives mitochondrial codon-amino acid reassignments. CDA reveals information ruling nucleotide-protein relations embedded in reversed (not reverse-complement) sequences (5'-ZXX-3'/5'-XXZ-3').

Rapid Evolution of Ovarian-Biased Genes in the Yellow Fever Mosquito (Aedes aegypti)

Males and females exhibit highly dimorphic phenotypes, particularly in their gonads, which is believed to be driven largely by differential gene expression. Typically, the protein sequences of genes upregulated in males, or male-biased genes, evolve rapidly as compared to female-biased and unbiased genes. To date, the specific study of gonad-biased genes remains uncommon in metazoans. Here, we identified and studied a total of 2927, 2013, and 4449 coding sequences (CDS) with ovary-biased, testis-biased, and unbiased expression, respectively, in the yellow fever mosquito Aedes aegypti The results showed that ovary-biased and unbiased CDS had higher nonsynonymous to synonymous substitution rates (dN/dS) and lower optimal codon usage (those codons that promote efficient translation) than testis-biased genes. Further, we observed higher dN/dS in ovary-biased genes than in testis-biased genes, even for genes coexpressed in nonsexual (embryo) tissues. Ovary-specific genes evolved exceptionally fast, as compared to testis- or embryo-specific genes, and exhibited higher frequency of positive selection. Genes with ovary expression were preferentially involved in olfactory binding and reception. We hypothesize that at least two potential mechanisms could explain rapid evolution of ovary-biased genes in this mosquito: (1) the evolutionary rate of ovary-biased genes may be accelerated by sexual selection (including female-female competition or male-mate choice) affecting olfactory genes during female swarming by males, and/or by adaptive evolution of olfactory signaling within the female reproductive system (e.g., sperm-ovary signaling); and/or (2) testis-biased genes may exhibit decelerated evolutionary rates due to the formation of mating plugs in the female after copulation, which limits male-male sperm competition.

The Impact of Selection at the Amino Acid Level on the Usage of Synonymous Codons

There are two main forces that affect usage of synonymous codons: directional mutational pressure and selection. The effectiveness of protein translation is usually considered as the main selectional factor. However, biased codon usage can also be a byproduct of a general selection at the amino acid level interacting with nucleotide replacements. To evaluate the validity and strength of such an effect, we superimposed >3.5 billion unrestricted mutational processes on the selection of nonsynonymous substitutions based on the differences in physicochemical properties of the coded amino acids. Using a modified evolutionary optimization algorithm, we determined the conditions in which the effect on the relative codon usage is maximized. We found that the effect is enhanced by mutational processes generating more adenine and thymine than guanine and cytosine, as well as more purines than pyrimidines. Interestingly, this effect is observed only under an unrestricted model of nucleotide substitution, and disappears when the mutational process is time-reversible. Comparison of the simulation results with data for real protein coding sequences indicates that the impact of selection at the amino acid level on synonymous codon usage cannot be neglected. Furthermore, it can considerably interfere, especially in AT-rich genomes, with other selections on codon usage, e.g., translational efficiency. It may also lead to difficulties in the recognition of other effects influencing codon bias, and an overestimation of protein coding sequences whose codon usage is subjected to adaptational selection.

The Information Content of Glutamine-Rich Sequences Define Protein Functional Characteristics

The presence of abnormally expanded glutamine (Q) repeats within specific proteins (e.g., huntingtin) are the well-established cause of several neurogenerative diseases, including Huntington disease and spinocerebellar ataxias. However, the impact of "expanded Q" stretches on the protein function is not well-understood, mostly due to lack of knowledge about the physiological role of Q repeats and the mechanism by which these repeats achieve functional-specificity. Indeed, is intriguing that regions with such low complexity (low information content) can display exquisite functional specificity. Prompting the question: where is this information stored? Applying biochemical/structural constraints and statistical analysis of protein composition we identified Q-rich (Q_R) regions present in coiled coils of yeast transcription factors and endocytic proteins. Our analysis indicated the existence of non-Q amino-acids differentially enriched or excluded from Q_R regions in one protein group versus the other. Importantly, when the non-Q amino-acids from an endocytic protein were exchanged by the ones enriched in Q_R from transcription factors, the resulting protein was unable to localize to the plasma membrane and was instead found in the nucleus. These results indicate that while Q_R repeats can efficiently engage in binding, the non-Q amino-acids provide essential specificity information. We speculate that coupling low complexity regions with information-intensive determinants might be a strategy used in many protein systems involved in different biological processes.

Natural gene expression variation studies in yeast

The rise of sequence information across different yeast species and strains is driving an increasing number of studies in the emerging field of genomics to associate polymorphic variants, mRNA abundance and phenotypic differences between individuals. Here, we gathered evidence from recent studies covering several layers that define the genotype-phenotype gap, such as mRNA abundance, allele-specific expression and translation efficiency to demonstrate how genetic variants co-evolve and define an individual's genome. Moreover, we exposed several antecedents where inter- and intra-specific studies led to opposite conclusions, probably owing to genetic divergence. Future studies in this area will benefit from the access to a massive array of well-annotated genomes and new sequencing technologies, which will allow the fine breakdown of the complex layers that delineate the genotype-phenotype map. Copyright © 2016 John Wiley & Sons, Ltd.

Genome-wide comparative analysis of codon usage bias and codon context patterns among cyanobacterial genomes

With the increasing accumulation of genomic sequence information of prokaryotes, the study of codon usage bias has gained renewed attention. The purpose of this study was to examine codon selection pattern within and across cyanobacterial species belonging to diverse taxonomic orders and habitats. We performed detailed comparative analysis of cyanobacterial genomes with respect to codon bias. Our analysis reflects that in cyanobacterial genomes, A- and/or T-ending codons were used predominantly in the genes whereas G- and/or C-ending codons were largely avoided. Variation in the codon context usage of cyanobacterial genes corresponded to the clustering of cyanobacteria as per their GC content. Analysis of codon adaptation index (CAI) and synonymous codon usage order (SCUO) revealed that majority of genes are associated with low codon bias. Codon selection pattern in cyanobacterial genomes reflected compositional constraints as major influencing factor. It is also identified that although, mutational constraint may play some role in affecting codon usage bias in cyanobacteria, compositional constraint in terms of genomic GC composition coupled with environmental factors affected codon selection pattern in cyanobacterial genomes.

Backmasking in the yeast genome: encoding overlapping information for protein-coding and RNA degradation

Backmasking is a recording technique used to hide a sound or message in a music track in reverse, meaning that it is only audible when the record is played backwards. Analogously, the compact yeast genome encodes for diverse sources of information such as overlapping coding and non-coding transcripts, and protein-binding sites on the two complementary DNA strands. Examples are the consensus binding site sequences of the RNA-binding proteins Nrd1 and Nab3 that target non-coding transcripts for degradation. Here, by examining the overlap of stable (SUTs, stable unannotated transcripts) and unstable (CUTs, cryptic unstable transcripts) transcripts with protein-coding genes, we show that the predicted Nrd1 and Nab3-binding site sequences occur at differing frequencies. They are always depleted in the sense direction of protein-coding genes, thus avoiding degradation of the transcript. However in the antisense direction, predicted binding sites occur at high frequencies in genes with overlapping unstable ncRNAs (CUTs), so limiting the availability of non-functional transcripts. In contrast they are depleted in genes with overlapping stable ncRNAs (SUTs), presumably to avoid degrading the non-coding transcript. The protein-coding genes maintain similar amino-acid contents, but they display distinct codon usages so that Nrd1 and Nab3-binding sites can arise at differing frequencies in antisense depending on the overlapping transcript type. Our study demonstrates how yeast has evolved to encode multiple layers of information-protein-coding genes in one strand and the relative chance of degrading antisense RNA in the other strand-in the same regions of a compact genome.

Expression-Linked Patterns of Codon Usage, Amino Acid Frequency, and Protein Length in the Basally Branching Arthropod Parasteatoda tepidariorum

Spiders belong to the Chelicerata, the most basally branching arthropod subphylum. The common house spider, Parasteatoda tepidariorum, is an emerging model and provides a valuable system to address key questions in molecular evolution in an arthropod system that is distinct from traditionally studied insects. Here, we provide evidence suggesting that codon usage, amino acid frequency, and protein lengths are each influenced by expression-mediated selection in P. tepidariorum. First, highly expressed genes exhibited preferential usage of T3 codons in this spider, suggestive of selection. Second, genes with elevated transcription favored amino acids with low or intermediate size/complexity (S/C) scores (glycine and alanine) and disfavored those with large S/C scores (such as cysteine), consistent with the minimization of biosynthesis costs of abundant proteins. Third, we observed a negative correlation between expression level and coding sequence length. Together, we conclude that protein-coding genes exhibit signals of expression-related selection in this emerging, noninsect, arthropod model.

Resource Availability Modulates the Cooperative and Competitive Nature of a Microbial Cross-Feeding Mutualism

Mutualisms between species play an important role in ecosystem function and stability. However, in some environments, the competitive aspects of an interaction may dominate the mutualistic aspects. Although these transitions could have far-reaching implications, it has been difficult to study the causes and consequences of this mutualistic–competitive transition in experimentally tractable systems. Here, we study a microbial cross-feeding mutualism in which each yeast strain supplies an essential amino acid for its partner strain. We find that, depending upon the amount of freely available amino acid in the environment, this pair of strains can exhibit an obligatory mutualism, facultative mutualism, competition, parasitism, competitive exclusion, or failed mutualism leading to extinction of the population. A simple model capturing the essential features of this interaction explains how resource availability modulates the interaction and predicts that changes in the dynamics of the mutualism in deteriorating environments can provide advance warning that collapse of the mutualism is imminent. We confirm this prediction experimentally by showing that, in the high nutrient competitive regime, the strains rapidly reach a common carrying capacity before slowly reaching the equilibrium ratio between the strains. However, in the low nutrient regime, before collapse of the obligate mutualism, we find that the ratio rapidly reaches its equilibrium and it is the total abundance that is slow to reach equilibrium. Our results provide a general framework for how mutualisms may transition between qualitatively different regimes of interaction in response to changes in nutrient availability in the environment.

A combination of computational modeling and experiments reveals the striking effects of changing resource availability on the population dynamics observed between two cross-feeding yeast strains.

Species often engage in mutualistic interactions that are beneficial for both partners. However, there is also a cost associated with cooperation, for example, in the form of energy required to make nutrients for a partner. When environments change, the costs and benefits of cooperating can change as well, and this can cause the mutualistic interaction to break down into other interaction types, such as parasitism. In this study, we varied nutrient availability to examine how changing environments can affect the interaction between two cross-feeding yeast strains. Lower nutrient concentrations made each strain more dependent on the nutrients provided by its partner strain and thus favored cooperation. Using both experiments and mathematic models, we found that in different environments, these yeast strains can interact in at least seven different qualitatively different ways, including obligate mutualism, facultative mutualism, parasitism, and competition. We also found that the dynamics of how the two strains influence each other change drastically in different nutrient concentrations. Examining the population dynamics could therefore potentially be used to predict the stability or collapse of a community.

Codon identity regulates mRNA stability and translation efficiency during the maternal-to-zygotic transition

Cellular transitions require dramatic changes in gene expression that are supported by regulated mRNA decay and new transcription. The maternal-to-zygotic transition is a conserved developmental progression during which thousands of maternal mRNAs are cleared by post-transcriptional mechanisms. Although some maternal mRNAs are targeted for degradation by microRNAs, this pathway does not fully explain mRNA clearance. We investigated how codon identity and translation affect mRNA stability during development and homeostasis. We show that the codon triplet contains translation-dependent regulatory information that influences transcript decay. Codon composition shapes maternal mRNA clearance during the maternal-to-zygotic transition in zebrafish, Xenopus, mouse, and Drosophila, and gene expression during homeostasis across human tissues. Some synonymous codons show consistent stabilizing or destabilizing effects, suggesting that amino acid composition influences mRNA stability. Codon composition affects both polyadenylation status and translation efficiency. Thus, the ribosome interprets two codes within the mRNA: the genetic code which specifies the amino acid sequence and a conserved "codon optimality code" that shapes mRNA stability and translation efficiency across vertebrates.

Discrepancy among the synonymous codons with respect to their selection as optimal codon in bacteria

The different triplets encoding the same amino acid, termed as synonymous codons, are not equally abundant in a genome. Factors such as G + C% and tRNA are known to influence their abundance in a genome. However, the order of the nucleotide in each codon per se might also be another factor impacting on its abundance values. Of the synonymous codons for specific amino acids, some are preferentially used in the high expression genes that are referred to as the 'optimal codons' (OCs). In this study, we compared OCs of the 18 amino acids in 221 species of bacteria. It is observed that there is amino acid specific influence for the selection of OCs. There is also influence of phylogeny in the choice of OCs for some amino acids such as Glu, Gln, Lys and Leu. The phenomenon of codon bias is also supported by the comparative studies of the abundance values of the synonymous codons with same G + C. It is likely that the order of the nucleotides in the triplet codon is also perhaps involved in the phenomenon of codon usage bias in organisms.

Coevolution between Stop Codon Usage and Release Factors in Bacterial Species

Three stop codons in bacteria represent different translation termination signals, and their usage is expected to depend on their differences in translation termination efficiency, mutation bias, and relative abundance of release factors (RF1 decoding UAA and UAG, and RF2 decoding UAA and UGA). In 14 bacterial species (covering Proteobacteria, Firmicutes, Cyanobacteria, Actinobacteria and Spirochetes) with cellular RF1 and RF2 quantified, UAA is consistently over-represented in highly expressed genes (HEGs) relative to lowly expressed genes (LEGs), whereas UGA usage is the opposite even in species where RF2 is far more abundant than RF1. UGA usage relative to UAG increases significantly with P_RF2 [=RF2/(RF1 + RF2)] as expected from adaptation between stop codons and their decoders. P_RF2 is > 0.5 over a wide range of AT content (measured by P_AT3 as the proportion of AT at third codon sites), but decreases rapidly toward zero at the high range of P_AT3. This explains why bacterial lineages with high P_AT3 often have UGA reassigned because of low RF2. There is no indication that UAG is a minor stop codon in bacteria as claimed in a recent publication. The claim is invalid because of the failure to apply the two key criteria in identifying a minor codon: (1) it is least preferred by HEGs (or most preferred by LEGs) and (2) it corresponds to the least abundant decoder. Our results suggest a more plausible explanation for why UAA usage increases, and UGA usage decreases, with P_AT3, but UAG usage remains low over the entire P_AT3 range.

Old genes experience stronger translational selection than young genes

Selection on synonymous codon usage for translation efficiency and/or accuracy has been identified as a widespread mechanism in many living organisms. However, it remains unknown whether translational selection associates closely with gene age and acts differentially on genes with different evolutionary ages. To address this issue, here we investigate the strength of translational selection acting on different aged genes in human. Our results show that old genes present stronger translational selection than young genes, demonstrating that translational selection correlates positively with gene age. We further explore the difference of translational selection in duplicates vs. singletons and in housekeeping vs. tissue-specific genes. We find that translational selection acts comparably in old singletons and old duplicates and stronger translational selection in old genes is contributed primarily by housekeeping genes. For young genes, contrastingly, singletons experience stronger translational selection than duplicates, presumably due to redundant function of duplicated genes during their early evolutionary stage. Taken together, our results indicate that translational selection acting on a gene would not be constant during all stages of evolution, associating closely with gene age.

Molecular evolution of anthocyanin pigmentation genes following losses of flower color

Background

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

Results

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

Conclusions

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

Electronic supplementary material

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

The Roles of Compensatory Evolution and Constraint in Aminoacyl tRNA Synthetase Evolution

Mitochondrial protein translation requires interactions between transfer RNAs encoded by the mitochondrial genome (mt-tRNAs) and mitochondrial aminoacyl tRNA synthetase proteins (mt-aaRS) encoded by the nuclear genome. It has been argued that animal mt-tRNAs have higher deleterious substitution rates relative to their nuclear-encoded counterparts, the cytoplasmic tRNAs (cyt-tRNAs). This dynamic predicts elevated rates of compensatory evolution of mt-aaRS that interact with mt-tRNAs, relative to aaRS that interact with cyt-tRNAs (cyt-aaRS). We find that mt-aaRS do evolve at significantly higher rates (exemplified by higher d_N and d_N/d_S) relative to cyt-aaRS, across mammals, birds, and Drosophila. While this pattern supports a model of compensatory evolution, the level at which a gene is expressed is a more general predictor of protein evolutionary rate. We find that gene expression level explains 10–56% of the variance in aaRS d_N/d_S, and that cyt-aaRS are more highly expressed in addition to having lower d_N/d_S values relative to mt-aaRS, consistent with more highly expressed genes being more evolutionarily constrained. Furthermore, we find no evidence of positive selection acting on either class of aaRS protein, as would be expected under a model of compensatory evolution. Nevertheless, the signature of faster mt-aaRS evolution persists in mammalian, but not bird or Drosophila, lineages after controlling for gene expression, suggesting some additional effect of compensatory evolution for mammalian mt-aaRS. We conclude that gene expression is the strongest factor governing differential amino acid substitution rates in proteins interacting with mitochondrial versus cytoplasmic factors, with important differences in mt-aaRS molecular evolution among taxonomic groups.

Codon and Amino Acid Usage Are Shaped by Selection Across Divergent Model Organisms of the Pancrustacea

In protein-coding genes, synonymous codon usage and amino acid composition correlate to expression in some eukaryotes, and may result from translational selection. Here, we studied large-scale RNA-seq data from three divergent arthropod models, including cricket (Gryllus bimaculatus), milkweed bug (Oncopeltus fasciatus), and the amphipod crustacean Parhyale hawaiensis, and tested for optimization of codon and amino acid usage relative to expression level. We report strong signals of AT3 optimal codons (those favored in highly expressed genes) in G. bimaculatus and O. fasciatus, whereas weaker signs of GC3 optimal codons were found in P. hawaiensis, suggesting selection on codon usage in all three organisms. Further, in G. bimaculatus and O. fasciatus, high expression was associated with lowered frequency of amino acids with large size/complexity (S/C) scores in favor of those with intermediate S/C values; thus, selection may favor smaller amino acids while retaining those of moderate size for protein stability or conformation. In P. hawaiensis, highly transcribed genes had elevated frequency of amino acids with large and small S/C scores, suggesting a complex dynamic in this crustacean. In all species, the highly transcribed genes appeared to favor short proteins, high optimal codon usage, specific amino acids, and were preferentially involved in cell-cycling and protein synthesis. Together, based on examination of 1,680,067, 1,667,783, and 1,326,896 codon sites in G. bimaculatus, O. fasciatus, and P. hawaiensis, respectively, we conclude that translational selection shapes codon and amino acid usage in these three Pancrustacean arthropods.

Genome-wide identification of Calcineurin B-Like (CBL) gene family of plants reveals novel conserved motifs and evolutionary aspects in calcium signaling events

BACKGROUND

Calcium ions, the most versatile secondary messenger found in plants, are involved in the regulation of diverse arrays of plant growth and development, as well as biotic and abiotic stress responses. The calcineurin B-like proteins are one of the most important genes that act as calcium sensors.

RESULTS

In this study, we identified calcineurin B-like gene family members from 38 different plant species and assigned a unique nomenclature to each of them. Sequence analysis showed that, the CBL proteins contain three calcium binding EF-hand domain that contains several conserved Asp and Glu amino acid residues. The third EF-hand of the CBL protein was found to posses the D/E-x-D calcium binding sensor motif. Phylogenetic analysis showed that, the CBL genes fall into six different groups. Additionally, except group B CBLs, all the CBL proteins were found to contain N-terminal palmitoylation and myristoylation sites. An evolutionary study showed that, CBL genes are evolved from a common ancestor and subsequently diverged during the course of evolution of land plants. Tajima's neutrality test showed that, CBL genes are highly polymorphic and evolved via decreasing population size due to balanced selection. Differential expression analysis with cold and heat stress treatment led to differential modulation of OsCBL genes.

CONCLUSIONS

The basic architecture of plant CBL genes is conserved throughout the plant kingdom. Evolutionary analysis showed that, these genes are evolved from a common ancestor of lower eukaryotic plant lineage and led to broadening of the calcium signaling events in higher eukaryotic organisms.