Selection conflicts, gene expression, and codon usage trends in yeast

Evolution of codon usage in Taenia saginata genomes and its impact on the host

The beef tapeworm, also known as Taenia saginata, is a zoonotic tapeworm from the genus Taenia in the order Cyclophyllidea. Taenia saginata is a food-borne zoonotic parasite with a worldwide distribution. It poses serious health risks to the host and has a considerable negative socioeconomic impact. Previous studies have explained the population structure of T. saginata within the evolutionary time scale and adaptive evolution. However, it is still unknown how synonymous codons are used by T. saginata. In this study, we used 90 T. saginata strains, applying the codon usage bias (CUB). Both base content and relative synonymous codon usage (RSCU) analysis revealed that AT-ended codons were more frequently used in the genome of T. saginata. Further low CUB was observed from the effective number of codons (ENC) value. The neutrality plot analysis suggested that the dominant factor of natural selection was involved in the structuring of CUB in T. saginata. Further analysis showed that T. saginata has adapted host-specific codon usage patterns to sustain successful replication and transmission chains within hosts (Bos taurus and Homo sapiens). Generally, both natural selection and mutational pressure have an impact on the codon usage patterns of the protein-coding genes in T. saginata. This study is important because it characterized the codon usage pattern in the T. saginata genomes and provided the necessary data for a basic evolutionary study on them.

Plastid phylogenomic insights into relationships, divergence, and evolution of Apiales

Members of Apiales are monophyletic and radiated in the Late Cretaceous. Fruit morphologies are critical for Apiales evolution and negative selection and mutation pressure play important roles in environmental adaptation. Apiales include many foods, spices, medicinal, and ornamental plants, but the phylogenetic relationships, origin and divergence, and adaptive evolution remain poorly understood. Here, we reconstructed Apiales phylogeny based on 72 plastid genes from 280 species plastid genomes representing six of seven families of this order. Highly supported phylogenetic relationships were detected, which revealed that each family of Apiales is monophyletic and confirmed that Pennanticeae is a member of Apiales. Genera Centella and Dickinsia are members of Apiaceae, and the genus Hydrocotyle previously classified into Apiaceae is confirmed to belong to Araliaceae. Besides, coalescent phylogenetic analysis and gene trees cluster revealed ten genes that can be used for distinguishing species among families of Apiales. Molecular dating suggested that the Apiales originated during the mid-Cretaceous (109.51 Ma), with the families' radiation occurring in the Late Cretaceous. Apiaceae species exhibit higher differentiation compared to other families. Ancestral trait reconstruction suggested that fruit morphological evolution may be related to shifts in plant types (herbaceous or woody), which in turn is related to the distribution areas and species numbers. Codon bias and positive selection analyses suggest that negative selection and mutation pressure may play important roles in environmental adaptation of Apiales members. Our results improve the phylogenetic framework of Apiales and provide insights into the origin, divergence, and adaptive evolution of this order and its members.

Trait drift in microalgae and applications for strain improvement

Microalgae are increasingly used to generate a wide range of commercial products, and there is growing evidence that microalgae-based products can be produced sustainably. However, industrial production of microalgal biomass is not as developed as other biomanufacturing platform technologies. In addition, results of bench-scale research often fail to translate to large-scale or mass production systems. This disconnect may result from trait drift and evolution occurring, through time, in response to unique drivers in each environment, such as cultivation regimes, weather, and pests. Moreover, outdoor and indoor cultivation of microalgae has the potential to impose negative selection pressures, which makes the maintenance of desired traits a challenge. In this context, this review sheds the light on our current understanding of trait drift and evolution in microalgae. We delineate the basics of phenotype plasticity and evolution, with a focus on how microalgae respond under various conditions. In addition, we review techniques that exploit phenotypic plasticity and evolution for strain improvement in view of industrial commercial applications, highlighting associated advantages and shortcomings. Finally, we suggest future research directions and recommendations to overcome unwanted trait drift and evolution in microalgae cultivation.

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Background

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression.

Results

Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to prevous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding.

Conclusions

Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08635-0).

Massively parallel interrogation of protein fragment secretability using SECRiFY reveals features influencing secretory system transit

While transcriptome- and proteome-wide technologies to assess processes in protein biogenesis are now widely available, we still lack global approaches to assay post-ribosomal biogenesis events, in particular those occurring in the eukaryotic secretory system. We here develop a method, SECRiFY, to simultaneously assess the secretability of >10⁵ protein fragments by two yeast species, S. cerevisiae and P. pastoris, using custom fragment libraries, surface display and a sequencing-based readout. Screening human proteome fragments with a median size of 50-100 amino acids, we generate datasets that enable datamining into protein features underlying secretability, revealing a striking role for intrinsic disorder and chain flexibility. The SECRiFY methodology generates sufficient amounts of annotated data for advanced machine learning methods to deduce secretability patterns. The finding that secretability is indeed a learnable feature of protein sequences provides a solid base for application-focused studies.

Comparative Analysis of Genomic and Transcriptome Sequences Reveals Divergent Patterns of Codon Bias in Wheat and Its Ancestor Species

The synonymous codons usage shows a characteristic pattern of preference in each organism. This codon usage bias is thought to have evolved for efficient protein synthesis. Synonymous codon usage was studied in genes of the hexaploid wheat Triticum aestivum (AABBDD) and its progenitor species, Triticum urartu (AA), Aegilops tauschii (DD), and Triticum turgidum (AABB). Triticum aestivum exhibited stronger usage bias for G/C-ending codons than did the three progenitor species, and this bias was especially higher compared to T. turgidum and Ae. tauschii. High GC content is a primary factor influencing codon usage in T. aestivum. Neutrality analysis showed a significant positive correlation (p<0.001) between GC12 and GC3 in the four species with regression line slopes near zero (0.16–0.20), suggesting that the effect of mutation on codon usage was only 16–20%. The GC3s values of genes were associated with gene length and distribution density within chromosomes. tRNA abundance data indicated that codon preference corresponded to the relative abundance of isoaccepting tRNAs in the four species. Both mutation and selection have affected synonymous codon usage in hexaploid wheat and its progenitor species. GO enrichment showed that GC biased genes were commonly enriched in physiological processes such as photosynthesis and response to acid chemical. In some certain gene families with important functions, the codon usage of small parts of genes has changed during the evolution process of T. aestivum.

Analysis of Codon Usage Patterns in Giardia duodenalis Based on Transcriptome Data from GiardiaDB

Giardia duodenalis, a flagellated parasitic protozoan, the most common cause of parasite-induced diarrheal diseases worldwide. Codon usage bias (CUB) is an important evolutionary character in most species. However, G. duodenalis CUB remains unclear. Thus, this study analyzes codon usage patterns to assess the restriction factors and obtain useful information in shaping G. duodenalis CUB. The neutrality analysis result indicates that G. duodenalis has a wide GC3 distribution, which significantly correlates with GC12. ENC-plot result—suggesting that most genes were close to the expected curve with only a few strayed away points. This indicates that mutational pressure and natural selection played an important role in the development of CUB. The Parity Rule 2 plot (PR2) result demonstrates that the usage of GC and AT was out of proportion. Interestingly, we identified 26 optimal codons in the G. duodenalis genome, ending with G or C. In addition, GC content, gene expression, and protein size also influence G. duodenalis CUB formation. This study systematically analyzes G. duodenalis codon usage pattern and clarifies the mechanisms of G. duodenalis CUB. These results will be very useful to identify new genes, molecular genetic manipulation, and study of G. duodenalis evolution.

Weak selection on synonymous codons substantially inflates dN/dS estimates in bacteria

Synonymous codon substitutions are not always selectively neutral as revealed by several types of analyses, including studies of codon usage patterns among genes. We analyzed codon usage in 13 bacterial genomes sampled from across a large order of bacteria, Enterobacterales, and identified presumptively neutral and selected classes of synonymous substitutions. To estimate substitution rates, given a neutral/selected classification of synonymous substitutions, we developed a flexible [Formula: see text] substitution model that allows multiple classes of synonymous substitutions. Under this multiclass synonymous substitution (MSS) model, the denominator of [Formula: see text] includes only the strictly neutral class of synonymous substitutions. On average, the value of [Formula: see text] under the MSS model was 80% of that under the standard codon model in which all synonymous substitutions are assumed to be neutral. The indication is that conventional [Formula: see text] analyses overestimate these values and thus overestimate the frequency of positive diversifying selection and underestimate the strength of purifying selection. To quantify the strength of selection necessary to explain this reduction, we developed a model of selected compensatory codon substitutions. The reduction in synonymous substitution rate, and thus the contribution that selection makes to codon bias variation among genes, can be adequately explained by very weak selection, with a mean product of population size and selection coefficient, [Formula: see text].

Variation and selection on codon usage bias across an entire subphylum

Variation in synonymous codon usage is abundant across multiple levels of organization: between codons of an amino acid, between genes in a genome, and between genomes of different species. It is now well understood that variation in synonymous codon usage is influenced by mutational bias coupled with both natural selection for translational efficiency and genetic drift, but how these processes shape patterns of codon usage bias across entire lineages remains unexplored. To address this question, we used a rich genomic data set of 327 species that covers nearly one third of the known biodiversity of the budding yeast subphylum Saccharomycotina. We found that, while genome-wide relative synonymous codon usage (RSCU) for all codons was highly correlated with the GC content of the third codon position (GC3), the usage of codons for the amino acids proline, arginine, and glycine was inconsistent with the neutral expectation where mutational bias coupled with genetic drift drive codon usage. Examination between genes' effective numbers of codons and their GC3 contents in individual genomes revealed that nearly a quarter of genes (381,174/1,683,203; 23%), as well as most genomes (308/327; 94%), significantly deviate from the neutral expectation. Finally, by evaluating the imprint of translational selection on codon usage, measured as the degree to which genes' adaptiveness to the tRNA pool were correlated with selective pressure, we show that translational selection is widespread in budding yeast genomes (264/327; 81%). These results suggest that the contribution of translational selection and drift to patterns of synonymous codon usage across budding yeasts varies across codons, genes, and genomes; whereas drift is the primary driver of global codon usage across the subphylum, the codon bias of large numbers of genes in the majority of genomes is influenced by translational selection.

Burkholderia thailandensis strain E555 is a surrogate for the investigation of Burkholderia pseudomallei replication and survival in macrophages

Background

Burkholderia pseudomallei is a human pathogen causing severe infections in tropical and subtropical regions and is classified as a bio-threat agent. B. thailandensis strain E264 has been proposed as less pathogenic surrogate for understanding the interactions of B. pseudomallei with host cells.

Results

We show that, unlike B. thailandensis strain E264, the pattern of growth of B. thailandensis strain E555 in macrophages is similar to that of B. pseudomallei. We have genome sequenced B. thailandensis strain E555 and using the annotated sequence identified genes and proteins up-regulated during infection. Changes in gene expression identified more of the known B. pseudomallei virulence factors than changes in protein levels and used together we identified 16% of the currently known B. pseudomallei virulence factors. These findings demonstrate the utility of B. thailandensis strain E555 to study virulence of B. pseudomallei.

Conclusions

A weakness of studies using B. thailandensis as a surrogate for B. pseudomallei is that the strains used replicate at a slower rate in infected cells. We show that the pattern of growth of B. thailandensis strain E555 in macrophages closely mirrors that of B. pseudomallei. Using this infection model we have shown that virulence factors of B. pseudomallei can be identified as genes or proteins whose expression is elevated on the infection of macrophages. This finding confirms the utility of B. thailandensis strain E555 as a surrogate for B. pseudomallei and this strain should be used for future studies on virulence mechanisms.

Electronic supplementary material

The online version of this article (10.1186/s12866-019-1469-8) contains supplementary material, which is available to authorized users.

Lifestyle modifications: coordinating the tRNA epitranscriptome with codon bias to adapt translation during stress responses

Cells adapt to stress by altering gene expression at multiple levels. Here, we propose a new mechanism regulating stress-dependent gene expression at the level of translation, with coordinated interplay between the tRNA epitranscriptome and biased codon usage in families of stress-response genes. In this model, auxiliary genetic information contained in synonymous codon usage enables regulation of codon-biased and functionally related transcripts by dynamic changes in the tRNA epitranscriptome. This model partly explains the association between synchronous stress-dependent epitranscriptomic marks and significant multi-codon usage skewing in families of translationally regulated transcripts. The model also predicts translational adaptation during viral infections.

DNA compositional dynamics and codon usage patterns of M1 and M2 matrix protein genes in influenza A virus

Influenza A virus subtype H3N2 has been a serious health issue across the globe with approximately 36 thousand annual casualties in the United States of America only. Co-circulation in avian, swine and human hosts has led to frequent mutations in the virus genome, due to which development of successful antivirals against the virus has become a formidable challenge. Recently, focussed research is being carried out targeting the matrix proteins of this strain as vaccine candidates. This study is carried out to unravel the key features of the genes encoding the matrix proteins that manoeuvre the codon usage profile in the H3N2 strains. The findings reveal differential codon choice for both matrix protein 1 and matrix protein 2. The overall codon usage bias is less pronounced in both the datasets which is evident from higher value of effective number of codons (>55). Comparison of the codon usage for both the genes under study with that of humans revealed that the viral codon usage is not fully optimized for the human host conditions. Both the genes enrolled in the study showed variation which was reflected in almost all the indices used for codon usage studies. Neutrality analysis revealed a weak role of mutation pressure while selection was the major contributor towards codon usage.

Accounting for Programmed Ribosomal Frameshifting in the Computation of Codon Usage Bias Indices

Experimental evidence shows that synonymous mutations can have important consequences on genetic fitness. Many organisms display codon usage bias (CUB), where synonymous codons that are translated into the same amino acid appear with distinct frequency. Within genomes, CUB is thought to arise from selection for translational efficiency and accuracy, termed the translational efficiency hypothesis (TEH). Indeed, CUB indices correlate with protein expression levels, which is widely interpreted as evidence for translational selection. However, these tests neglect -1 programmed ribosomal frameshifting (-1 PRF), an important translational disruption effect found across all organisms of the tree of life. Genes that contain -1 PRF signals should cost more to express than genes without. Thus, CUB indices that do not consider -1 PRF may overestimate genes’ true adaptation to translational efficiency and accuracy constraints. Here, we first investigate whether -1 PRF signals do indeed carry such translational cost. We then propose two corrections for CUB indices for genes containing -1 PRF signals. We retest the TEH in Saccharomyces cerevisiae under these corrections. We find that the correlation between corrected CUB index and protein expression remains intact for most levels of uniform -1 PRF efficiencies, and tends to increase when these efficiencies decline with protein expression. We conclude that the TEH is strengthened and that -1 PRF events constitute a promising and useful tool to examine the relationships between CUB and selection for translation efficiency and accuracy.

Ribosome reinitiation can explain length-dependent translation of messenger RNA

Models of mRNA translation usually presume that transcripts are linear; upon reaching the end of a transcript each terminating ribosome returns to the cytoplasmic pool before initiating anew on a different transcript. A consequence of linear models is that faster translation of a given mRNA is unlikely to generate more of the encoded protein, particularly at low ribosome availability. Recent evidence indicates that eukaryotic mRNAs are circularized, potentially allowing terminating ribosomes to preferentially reinitiate on the same transcript. Here we model the effect of ribosome reinitiation on translation and show that, at high levels of reinitiation, protein synthesis rates are dominated by the time required to translate a given transcript. Our model provides a simple mechanistic explanation for many previously enigmatic features of eukaryotic translation, including the negative correlation of both ribosome densities and protein abundance on transcript length, the importance of codon usage in determining protein synthesis rates, and the negative correlation between transcript length and both codon adaptation and 5' mRNA folding energies. In contrast to linear models where translation is largely limited by initiation rates, our model reveals that all three stages of translation-initiation, elongation, and termination/reinitiation-determine protein synthesis rates even at low ribosome availability.

Codon Usage Bias and Determining Forces in Taenia solium Genome

The tapeworm Taenia solium is an important human zoonotic parasite that causes great economic loss and also endangers public health. At present, an effective vaccine that will prevent infection and chemotherapy without any side effect remains to be developed. In this study, codon usage patterns in the T. solium genome were examined through 8,484 protein-coding genes. Neutrality analysis showed that T. solium had a narrow GC distribution, and a significant correlation was observed between GC12 and GC3. Examination of an NC (ENC vs GC3s)-plot showed a few genes on or close to the expected curve, but the majority of points with low-ENC (the effective number of codons) values were detected below the expected curve, suggesting that mutational bias plays a major role in shaping codon usage. The Parity Rule 2 plot (PR2) analysis showed that GC and AT were not used proportionally. We also identified 26 optimal codons in the T. solium genome, all of which ended with either a G or C residue. These optimal codons in the T. solium genome are likely consistent with tRNAs that are highly expressed in the cell, suggesting that mutational and translational selection forces are probably driving factors of codon usage bias in the T. solium genome.

Highly Predictive Reprogramming of tRNA Modifications Is Linked to Selective Expression of Codon-Biased Genes

Cells respond to stress by controlling gene expression at several levels, with little known about the role of translation. Here, we demonstrate a coordinated translational stress response system involving stress-specific reprogramming of tRNA wobble modifications that leads to selective translation of codon-biased mRNAs representing different classes of critical response proteins. In budding yeast exposed to four oxidants and five alkylating agents, tRNA modification patterns accurately distinguished among chemically similar stressors, with 14 modified ribonucleosides forming the basis for a data-driven model that predicts toxicant chemistry with >80% sensitivity and specificity. tRNA modification subpatterns also distinguish S_N1 from S_N2 alkylating agents, with S_N2-induced increases in m³C in tRNA mechanistically linked to selective translation of threonine-rich membrane proteins from genes enriched with ACC and ACT degenerate codons for threonine. These results establish tRNA modifications as predictive biomarkers of exposure and illustrate a novel regulatory mechanism for translational control of cell stress response.

Analysis of codon usage pattern in Taenia saginata based on a transcriptome dataset

BACKGROUND

Codon usage bias is an important evolutionary feature in a genome and has been widely documented in many genomes. Analysis of codon usage bias has significance for mRNA translation, design of transgenes, new gene discovery, and studies of molecular biology and evolution, etc. However, the information about synonymous codon usage pattern of T. saginata genome remains unclear. T. saginata is a food-borne zoonotic cestode which infects approximataely 50 million humans worldwide, and causes significant health problems to the host and considerable socio-economic losses as a consequence. In this study, synonymous codon usage in T. saginata were examined.

METHODS

Total RNA was isolated from T. saginata cysticerci and 91,487 unigenes were generated using Illumina sequencing technology. After filtering, the final sequence collection containing 11,399 CDSs was used for our analysis.

RESULTS

Neutrality analysis showed that the T. saginata had a wide GC3 distribution and a significant correlation was observed between GC12 and GC3. NC-plot showed most of genes on or close to the expected curve, but only a few points with low-ENC values were below it, suggesting that mutational bias plays a major role in shaping codon usage. The Parity Rule 2 plot (PR2) analysis showed that GC and AT were not used proportionally. We also identified twenty-three optimal codons in the T. saginata genome, all of which were ended with a G or C residue. These results suggest that mutational and selection forces are probably driving factors of codon usage bias in T. saginata genome. Meanwhile, other factors such as protein length, gene expression, GC content of genes, the hydropathicity of each protein also influence codon usage.

CONCLUSIONS

Here, we systematically analyzed the codon usage pattern and identified factors shaping in codon usage bias in T. saginata. Currently, no complete nuclear genome is available for codon usage analysis at the genome level in T. saginata. This is the first report to investigate codon biology in T. sagninata. Such information does not only bring about a new perspective for understanding the mechanisms of biased usage of synonymous codons but also provide useful clues for molecular genetic engineering and evolutionary studies.

Enhanced production of recombinant secretory proteins in Pichia pastoris by optimizing Kex2 P1' site

Pichiapastoris is one of the most widely used expression systems for the production of recombinant secretory proteins. Its universal application is, however, somewhat hampered by its unpredictable yields for different heterologous proteins, which is now believed to be caused in part by their varied efficiencies to traffic through the host secretion machinery. The yeast endoprotease Kex2 removes the signal peptides from pre-proteins and releases the mature form of secreted proteins, thus, plays a pivotal role in the yeast secretory pathways. In this study, we found that the yields of many recombinant proteins were greatly influenced by Kex2 P1' site residues and the optimized P1's amino acid residue could largely determine the final amount of secretory proteins synthesized and secreted. A further improvement of secretory yield was achieved by genomic integration of additional Kex2 copies, which again highlighted the importance of Kex2 cleavage to the production of recombinant secretory proteins in Pichia yeast.

Genomic signatures of selection at linked sites: unifying the disparity among species

Population genetics theory supplies powerful predictions about how natural selection interacts with genetic linkage to sculpt the genomic landscape of nucleotide polymorphism. Both the spread of beneficial mutations and the removal of deleterious mutations act to depress polymorphism levels, especially in low-recombination regions. However, empiricists have documented extreme disparities among species. Here we characterize the dominant features that could drive differences in linked selection among species--including roles for selective sweeps being 'hard' or 'soft'--and the concealing effects of demography and confounding genomic variables. We advocate targeted studies of closely related species to unify our understanding of how selection and linkage interact to shape genome evolution.

SHIFT: server for hidden stops analysis in frame-shifted translation

Background

Frameshift is one of the three classes of recoding. Frame-shifts lead to waste of energy, resources and activity of the biosynthetic machinery. In addition, some peptides synthesized after frame-shifts are probably cytotoxic which serve as plausible cause for innumerable number of diseases and disorders such as muscular dystrophies, lysosomal storage disorders, and cancer. Hidden stop codons occur naturally in coding sequences among all organisms. These codons are associated with the early termination of translation for incorrect reading frame selection and help to reduce the metabolic cost related to the frameshift events. Researchers have identified several consequences of hidden stop codons and their association with myriad disorders. However the wealth of information available is speckled and not effortlessly acquiescent to data-mining. To reduce this gap, this work describes an algorithmic web based tool to study hidden stops in frameshifted translation for all the lineages through respective genetic code systems.

Findings

This paper describes SHIFT, an algorithmic web application tool that provides a user-friendly interface for identifying and analyzing hidden stops in frameshifted translation of genomic sequences for all available genetic code systems. We have calculated the correlation between codon usage frequencies and the plausible contribution of codons towards hidden stops in an off-frame context. Markovian chains of various order have been used to model hidden stops in frameshifted peptides and their evolutionary association with naturally occurring hidden stops. In order to obtain reliable and persuasive estimates for the naturally occurring and predicted hidden stops statistical measures have been implemented.

Conclusions

This paper presented SHIFT, an algorithmic tool that allows user-friendly exploration, analysis, and visualization of hidden stop codons in frameshifted translations. It is expected that this web based tool would serve as a useful complement for analyzing hidden stop codons in all available genetic code systems. SHIFT is freely available for academic and research purpose at http://www.nuccore.org/shift/.

A more accurate relationship between 'effective number of codons' and GC3s under assumptions of no selection

The 'effective number of codons' (Nc) introduced by Frank Wright in 1990 is one of the best measures to show the state of codon usage biases in genes and genomes. Although estimate methods of Nc have been improved by several investigators since then, no one noticed that the relationship between Nc and GC3s under assumptions of no selection given by Wright has a little but significant deviation. Since the curve showing such a relationship in Nc-plot is a useful reference line to display the main features of codon usage pattern for a number of genes, its high accuracy is important and necessary. Under ideal and ultimate conditions listed in this text a computational sample of Nc versus GC3s was derived and calculated. By nonlinear regression analysis, the relationship between Nc and GC3s without synonymous codon selection can be approximated by: N(c)=2.5-s+29.5/(s(2)+(1-s)(2)), instead of Wright's: N(c)=2+s+29/(s(2)+(1-s)(2)), where s denotes GC3s. The goodness of fit analysis of both confirmed that the new formula presented in this text is more accurate than the original one. In addition, in the case of using the same estimate method of Nc, the situation in overestimation is decreased to a certain extent by using the new reference line in comparison with Wright's one.

The Correlation between Recombination Rate and Codon Bias in Yeast Mainly Results from Mutational Bias Associated with Recombination Rather than Hill-Robertson Interference

Codon usage has been reported to be correlated with local recombination rate, which can be explained by two proposed models. In the present study, correspondence analysis was used to investigate the major trends in codon usage variation among S. cerevisiae genes. It was found that the first principle source of codon usage variation in yeast is due to the variance of expressional levels, which is consistent with the previous translational selection model. Moreover, recombination rate is also correlated with the codon pattern, which might be a byproduct of mutational bias associated with recombination rather than the consequence of Hill-Robertson interference. A recent study has analysed the genome sequence, but reached opposite conclusions: the positive correlation between recombination rate and codon bias in yeast mainly results from Hill-Robertson interference. In light of this conflicting result, we have discussed the possible reason and found that the previous analysis was undermined by mistaken assumptions that weak selection acting at expression level led to the correlation between recombination and codon bias.

The surprising negative correlation of gene length and optimal codon use--disentangling translational selection from GC-biased gene conversion in yeast

Background

Surprisingly, in several multi-cellular eukaryotes optimal codon use correlates negatively with gene length. This contrasts with the expectation under selection for translational accuracy. While suggested explanations focus on variation in strength and efficiency of translational selection, it has rarely been noticed that the negative correlation is reported only in organisms whose optimal codons are biased towards codons that end with G or C (-GC). This raises the question whether forces that affect base composition - such as GC-biased gene conversion - contribute to the negative correlation between optimal codon use and gene length.

Results

Yeast is a good organism to study this as equal numbers of optimal codons end in -GC and -AT and one may hence compare frequencies of optimal GC- with optimal AT-ending codons to disentangle the forces. Results of this study demonstrate in yeast frequencies of GC-ending (optimal AND non-optimal) codons decrease with gene length and increase with recombination. A decrease of GC-ending codons along genes contributes to the negative correlation with gene length. Correlations with recombination and gene expression differentiate between GC-ending and optimal codons, and also substitution patterns support effects of GC-biased gene conversion.

Conclusion

While the general effect of GC-biased gene conversion is well known, the negative correlation of optimal codon use with gene length has not been considered in this context before. Initiation of gene conversion events in promoter regions and the presence of a gene conversion gradient most likely explain the observed decrease of GC-ending codons with gene length and gene position.

Polymorphism, divergence, and the role of recombination in Saccharomyces cerevisiae genome evolution

A contentious issue in molecular evolution and population genetics concerns the roles of recombination as a facilitator of natural selection and as a potential source of mutational input into genomes. The budding yeast Saccharomyces cerevisiae, in particular, has injected both insights and confusion into this topic, as an early system subject to genomic analysis with subsequent conflicting reports. Here, we revisit the role of recombination in mutation and selection with recent genome-wide maps of population polymorphism and recombination for S. cerevisiae. We confirm that recombination-associated mutation does not leave a genomic signature in yeast and conclude that a previously observed, enigmatic, negative recombination-divergence correlation is largely a consequence of weak selection and other genomic covariates. We also corroborate the presence of biased gene conversion from patterns of polymorphism. Moreover, we identify significant positive relations between recombination and population polymorphism at putatively neutrally evolving sites, independent of other factors and the genomic scale of interrogation. We conclude that widespread natural selection across the yeast genome has left its imprint on segregating genetic variation, but that this signature is much weaker than in Drosophila and Caenorhabditis.

Correlation of mRNA and protein in complex biological samples

The correlation between mRNA and protein abundances in the cell has been reported to be notoriously poor. Recent technological advances in the quantitative analysis of mRNA and protein species in complex samples allow the detailed analysis of this pathway at the center of biological systems. We give an overview of available methods for the identification and quantification of free and ribosome-bound mRNA, protein abundances and individual protein turnover rates. We review available literature on the correlation of mRNA and protein abundances and discuss biological and technical parameters influencing the correlation of these central biological molecules.

The tRNA modification complex elongator regulates the Cdc42-dependent mitogen-activated protein kinase pathway that controls filamentous growth in yeast

Signal transduction pathways control multiple aspects of cellular behavior, including global changes to the cell cycle, cell polarity, and gene expression, which can result in the formation of a new cell type. In the budding yeast Saccharomyces cerevisiae, the mitogen-activated protein kinase (MAPK) pathway that controls filamentous growth induces a dimorphic foraging response under nutrient-limiting conditions. How nutritional cues feed into MAPK activation remains an open question. Here we report a functional connection between the elongator tRNA modification complex (ELP genes) and activity of the filamentous growth pathway. Elongator was required for filamentous growth pathway signaling, and elp mutants were defective for invasive growth, cell polarization, and MAPK-dependent mat formation. Genetic suppression analysis showed that elongator functions at the level of Msb2p, the signaling mucin that operates at the head of the pathway, which led to the finding that elongator regulates the starvation-dependent expression of the MSB2 gene. The Elp complex was not required for activation of related pathways (pheromone response or high osmolarity glycerol response) that share components with the filamentous growth pathway. Because protein translation provides a rough metric of cellular nutritional status, elongator may convey nutritional information to the filamentous growth pathway at the level of MSB2 expression.

Structural determinants of protein evolution are context-sensitive at the residue level

Structural properties of a protein residue's microenvironment have long been implicated as agents of selective constraint. Although these properties are inherently quantitative, structure-based studies of protein evolution tend to rely upon coarse distinctions between "surface" and "buried" residues and between "interfacial" and "noninterfacial" residues. Using homology-mapped yeast protein structures, we explore the relationships between residue evolution and continuous structural properties of the residue microenvironment, including solvent accessibility, density and distribution of residue-residue contacts, and burial depth. We confirm the role of solvent exposure as a major structural determinant of residue evolution and also identify a weak secondary effect arising from packing density. The relationship between solvent exposure and evolutionary rate (d(N)/d(S)) is found to be strong, positive, and linear. This reinforces the notion that residue burial is a continuous property with quantitative fitness implications. Next, we demonstrate systematic variation in residue-level structure-evolution relationships resulting from changes in global physical and biological contexts. We find that increasing protein-core size yields a more rapid relaxation of selective constraint as solvent exposure increases, although solvent-excluded residues remain similarly constrained. Finally, we analyze the selective constraint in protein-protein interfaces, revealing two fundamentally different yet separable components: continuous structural constraint that scales with total residue burial and a more surprising fixed functional constraint that accompanies any degree of interface involvement. These discoveries serve to elucidate and unite structure-evolution relationships at the residue and whole-protein levels.

Evolution of the Caenorhabditis elegans genome

A fundamental problem in genome biology is to elucidate the evolutionary forces responsible for generating nonrandom patterns of genome organization. As the first metazoan to benefit from full-genome sequencing, Caenorhabditis elegans has been at the forefront of research in this area. Studies of genomic patterns, and their evolutionary underpinnings, continue to be augmented by the recent push to obtain additional full-genome sequences of related Caenorhabditis taxa. In the near future, we expect to see major advances with the onset of whole-genome resequencing of multiple wild individuals of the same species. In this review, we synthesize many of the important insights to date in our understanding of genome organization and function that derive from the evolutionary principles made explicit by theoretical population genetics and molecular evolution and highlight fertile areas for future research on unanswered questions in C. elegans genome evolution. We call attention to the need for C. elegans researchers to generate and critically assess nonadaptive hypotheses for genomic and developmental patterns, in addition to adaptive scenarios. We also emphasize the potential importance of evolution in the gonochoristic (female and male) ancestors of the androdioecious (hermaphrodite and male) C. elegans as the source for many of its genomic and developmental patterns.

The impact of the nucleosome code on protein-coding sequence evolution in yeast

Coding sequence evolution was once thought to be the result of selection on optimal protein function alone. Selection can, however, also act at the RNA level, for example, to facilitate rapid translation or ensure correct splicing. Here, we ask whether the way DNA works also imposes constraints on coding sequence evolution. We identify nucleosome positioning as a likely candidate to set up such a DNA-level selective regime and use high-resolution microarray data in yeast to compare the evolution of coding sequence bound to or free from nucleosomes. Controlling for gene expression and intra-gene location, we find a nucleosome-free "linker" sequence to evolve on average 5-6% slower at synonymous sites. A reduced rate of evolution in linker is especially evident at the 5' end of genes, where the effect extends to non-synonymous substitution rates. This is consistent with regular nucleosome architecture in this region being important in the context of gene expression control. As predicted, codons likely to generate a sequence unfavourable to nucleosome formation are enriched in linker sequence. Amino acid content is likewise skewed as a function of nucleosome occupancy. We conclude that selection operating on DNA to maintain correct positioning of nucleosomes impacts codon choice, amino acid choice, and synonymous and non-synonymous rates of evolution in coding sequence. The results support the exclusion model for nucleosome positioning and provide an alternative interpretation for runs of rare codons. As the intimate association of histones and DNA is a universal characteristic of genic sequence in eukaryotes, selection on coding sequence composition imposed by nucleosome positioning should be phylogenetically widespread.

Aminoglycoside resistance genes sgm and kgmB protect bacterial but not yeast small ribosomal subunits in vitro despite high conservation of the rRNA A-site

The aminoglycoside resistance genes sgm from Micromonospora zionensis and kgmB from Streptomyces tenebrarius were cloned into a yeast expression vector to test whether the encoded prokaryotic methylases can modify the 18S rRNA A-site and thus confer resistance to G-418. Despite the detectable presence of mRNAs in yeast cells, neither G-418-resistant yeast transformants nor positive western blot signals were obtained. Neither methylase was capable of methylating 40S subunits despite very high conservation of the antibiotic rRNA binding sites. However, the results provide novel insight into the action of Sgm by showing that it methylates the same site as KgmB, i.e. G1405 in 16S rRNA.

Mutagenesis from meiotic recombination is not a primary driver of sequence divergence between Saccharomyces species

Local rates of recombination positively correlate with DNA sequence diversity in many species. To test whether this relationship stems from mutagenicity of meiotic recombination, studies often look for a similar association between local rates of recombination and sequence "divergence" between species. Because recombination is mutagenic in yeast, I evaluate this assay by testing whether noncoding DNA sequence divergence between Saccharomyces species is related to measures of meiotic double-strand DNA breaks or crossover rates derived from Saccharomyces cerevisiae. Contrary to expectation, I find that sequence divergence is either uncorrelated or negatively correlated with rates of both double-strand break and crossover. Several caveats are mentioned, but these results suggest that mutagenesis from meiotic recombination is not the primary driver of sequence divergence between Saccharomyces species. This study demonstrates that the association between interspecies nucleotide divergence and local recombination rates is not always a reliable indicator of recombination's mutagenicity.

Cut thy neighbor: cyclic birth and death of recombination hotspots via genetic conflict

Most recombination takes place in numerous, localized regions called hotspots. However, empirical evidence indicates that nascent hotspots are susceptible to removal due to biased gene conversion, so it is paradoxical that they should be so widespread. Previous modeling work has shown that hotspots can evolve due to genetic drift overpowering their intrinsic disadvantage. Here we synthesize recent theoretical and empirical results to show how natural selection can favor hotspots. We propose that hotspots are part of a cycle of antagonistic coevolution between two tightly linked chromosomal regions: an inducer region that initiates recombination during meiosis by cutting within a nearby region of DNA and the cut region itself, which can evolve to be resistant to cutting. Antagonistic coevolution between inducers and their cut sites is driven by recurrent episodes of Hill-Robertson interference, genetic hitchhiking, and biased gene conversion.

Conflicting selection pressures on synonymous codon use in yeast suggest selection on mRNA secondary structures

BACKGROUND

Eukaryotic mRNAs often contain secondary structures in their untranslated regions that are involved in expression regulation. Whether secondary structures in the protein coding regions are of functional importance remains unclear: laboratory studies suggest stable secondary structures within the protein coding sequence interfere with translation, while several bioinformatic studies indicate stable mRNA structures are more frequent than expected.

RESULTS

In contrast to several studies testing for unexpected structural stabilities, I directly compare the selective constraint of sites that differ in their structural importance. I.e. for each nucleotide, I identify whether it is paired with another nucleotide, or unpaired, in the predicted secondary structure. I assume paired sites are more important for the predicted secondary structure than unpaired sites. I look at protein coding yeast sequences and use optimal codons and synonymous substitutions to test for structural constraints. As expected under selection for secondary structures, paired sites experience higher constraint than unpaired sites, i.e. significantly lower numbers of conserved optimal codons and consistently lower numbers of synonymous substitutions. This is true for structures predicted by different algorithms.

CONCLUSION

The results of this study are consistent with purifying selection on mRNA secondary structures in yeast protein coding sequences and suggest their biological importance. One should be aware, however, that accuracy of structure prediction is unknown for mRNAs and interrelated selective forces may contribute as well. Note that if selection pressures alternative to translational selection affect synonymous (and optimal) codon use, this may lead to under- or over-estimates of selective strength on optimal codon use depending on strength and direction of translational selection.

Recombination rate and protein evolution in yeast

Background

Theory and artificial selection experiments show that recombination can promote adaptation by enhancing the efficacy of natural selection, but the extent to which recombination affects levels of adaptation across the genome is still an open question. Because patterns of molecular evolution reflect long-term processes of mutation and selection in nature, interactions between recombination rate and genetic differentiation between species can be used to test the benefits of recombination. However, this approach faces a major difficulty: different evolutionary processes (i.e. negative versus positive selection) produce opposing relationships between recombination rate and genetic divergence, and obscure patterns predicted by individual benefits of recombination.

Results

We use a combination of polymorphism and genomic data from the yeast Saccharomyces cerevisiae to infer the relative importance of nearly-neutral (i.e. slightly deleterious) evolution in different gene categories. For genes with high opportunities for slightly deleterious substitution, recombination substantially reduces the rate of molecular evolution, whereas divergence in genes with little opportunity for slightly deleterious substitution is not strongly affected by recombination.

Conclusion

These patterns indicate that adaptation throughout the genome can be strongly influenced by each gene's recombinational environment, and suggest substantial long-term fitness benefits of enhanced purifying selection associated with sexual recombination.

The Hill–Robertson effect: evolutionary consequences of weak selection and linkage in finite populations

The 'Hill-Robertson (HR) effect' describes that linkage between sites under selection will reduce the overall effectiveness of selection in finite populations. Here we discuss the major concepts associated with the HR effect and present results of computer simulations focusing on the linkage effects generated by multiple sites under weak selection. Most models of linkage and selection forecast differences in effectiveness of selection between chromosomes or chromosomal regions involving a number of genes. The abundance and physical clustering of weakly selected mutations across genomes, however, justify the investigation of HR effects at a very local level and we pay particular attention to linkage effects among selected sites of the same gene. Overall, HR effects caused by weakly selected mutations predict differences in effectiveness of selection between genes that differ in exon-intron structures and across genes. Under this scenario, introns might play an advantageous role reducing intragenic HR effects. Finally, we summarize observations that are consistent with local HR effects in Drosophila, discuss potential consequences on population genetic studies and suggest future lines of research.

The effects of differential gene expression on coding sequence features: Analysis by one-way ANOVA

It is well-established that non-random patterns in coding DNA sequence (CDS) features can be partially explained by translational selection. Recent extensions of microarray and proteomic expression data have stimulated many genome-wide investigations of the relationships between gene expression and various CDS features. However, only modest correlations have been found. Here we introduced the one-way ANOVA, a more powerful extension of previous grouping methods, to re-examine these relationships at the whole genome scale for Saccharomyces cerevisiae, where genome-wide protein abundance has been recently quantified. Our results clarify that coding sequence features are inappropriate for use as genome-wide estimators for protein expression levels. This analysis also demonstrates that one-way ANOVA is a powerful and simple method to explore the influence of gene expression on CDS features.

RF-DYMHC: detecting the yeast meiotic recombination hotspots and coldspots by random forest model using gapped dinucleotide composition features

In the yeast, meiotic recombination is initiated by double-strand DNA breaks (DSBs) which occur at relatively high frequencies in some genomic regions (hotspots) and relatively low frequencies in others (coldspots). Although observations concerning individual hot/cold spots have given clues as to the mechanism of recombination initiation, the prediction of hot/cold spots from DNA sequence information is a challenging task. In this article, we introduce a random forest (RF) prediction model to detect recombination hot/cold spots from yeast genome. The out-of-bag (OOB) estimation of the model indicated that the RF classifier achieved high prediction performance with 82.05% total accuracy and 0.638 Mattew's correlation coefficient (MCC) value. Compared with an alternative machine-learning algorithm, support vector machine (SVM), the RF method outperforms it in both sensitivity and specificity. The prediction model is implemented as a web server (RF-DYMHC) and it is freely available at http://www.bioinf.seu.edu.cn/Recombination/rf_dymhc.htm. Given a yeast genome and prediction parameters (RI-value and non-overlapping window scan size), the program reports the predicted hot/cold spots and marks them in color.

Codon-usage bias versus gene conversion in the evolution of yeast duplicate genes

Many Saccharomyces cerevisiae duplicate genes that were derived from an ancient whole-genome duplication (WGD) unexpectedly show a small synonymous divergence (K(S)), a higher sequence similarity to each other than to orthologues in Saccharomyces bayanus, or slow evolution compared with the orthologue in Kluyveromyces waltii, a non-WGD species. This decelerated evolution was attributed to gene conversion between duplicates. Using approximately 300 WGD gene pairs in four species and their orthologues in non-WGD species, we show that codon-usage bias and protein-sequence conservation are two important causes for decelerated evolution of duplicate genes, whereas gene conversion is effective only in the presence of strong codon-usage bias or protein-sequence conservation. Furthermore, we find that change in mutation pattern or in tDNA copy number changed codon-usage bias and increased the K(S) distance between K. waltii and S. cerevisiae. Intriguingly, some proteins showed fast evolution before the radiation of WGD species but little or no sequence divergence between orthologues and paralogues thereafter, indicating that functional conservation after the radiation may also be responsible for decelerated evolution in duplicates.

The evolution of biased codon and amino acid usage in nematode genomes

Despite the degeneracy of the genetic code, whereby different codons encode the same amino acid, alternative codons and amino acids are utilized nonrandomly within and between genomes. Such biases in codon and amino acid usage have been demonstrated extensively in prokaryote genomes and likely reflect a balance between the action of mutation, selection, and genetic drift. Here, we quantify the effects of selection and mutation drift as causes of codon and amino acid-usage bias in a large collection of nematode partial genomes from 37 species spanning approximately 700 Myr of evolution, as inferred from expressed sequence tag (EST) measures of gene expression and from base composition variation. Average G + C content at silent sites among these taxa ranges from 10% to 63%, and EST counts range more than 100-fold, underlying marked differences between the identities of major codons and optimal codons for a given species as well as influencing patterns of amino acid abundance among taxa. Few species in our sample demonstrate a dominant role of selection in shaping intragenomic codon-usage biases, and these are principally free living rather than parasitic nematodes. This suggests that deviations in effective population size among species, with small effective sizes among parasites, are partly responsible for species differences in the extent to which selection shapes patterns of codon usage. Nevertheless, a consensus set of optimal codons emerges that is common to most taxa, indicating that, with some notable exceptions, selection for translational efficiency and accuracy favors similar sets of codons regardless of the major codon-usage trends defined by base compositional properties of individual nematode genomes.

Support vector machine for classification of meiotic recombination hotspots and coldspots in Saccharomyces cerevisiae based on codon composition

Background

Meiotic double-strand breaks occur at relatively high frequencies in some genomic regions (hotspots) and relatively low frequencies in others (coldspots). Hotspots and coldspots are receiving increasing attention in research into the mechanism of meiotic recombination. However, predicting hotspots and coldspots from DNA sequence information is still a challenging task.

Results

We present a novel method for classification of hot and cold ORFs located in hotspots and coldspots respectively in Saccharomyces cerevisiae, using support vector machine (SVM), which relies on codon composition differences. This method has achieved a high classification accuracy of 85.0%. Since codon composition is a fusion of codon usage bias and amino acid composition signals, the ability of these two kinds of sequence attributes to discriminate hot ORFs from cold ORFs was also investigated separately. Our results indicate that neither codon usage bias nor amino acid composition taken separately performed as well as codon composition. Moreover, our SVM based method was applied to the full genome: We predicted the hot/cold ORFs from the yeast genome by using cutoffs of recombination rate. We found that the performance of our method for predicting cold ORFs is not as good as that for predicting hot ORFs. Besides, we also observed a considerable correlation between meiotic recombination rate and amino acid composition of certain residues, which probably reflects the structural and functional dissimilarity between the hot and cold groups.

Conclusion

We have introduced a SVM-based novel method to discriminate hot ORFs from cold ones. Applying codon composition as sequence attributes, we have achieved a high classification accuracy, which suggests that codon composition has strong potential to be used as sequence attributes in the prediction of hot and cold ORFs.

Weak selection and recent mutational changes influence polymorphic synonymous mutations in humans

Recent large-scale genomic and evolutionary studies have revealed the small but detectable signature of weak selection on synonymous mutations during mammalian evolution, likely acting at the level of translational efficacy (i.e., translational selection). To investigate whether weak selection, and translational selection in particular, plays any role in shaping the fate of synonymous mutations that are present today in human populations, we studied genetic variation at the polymorphic level and patterns of evolution in the human lineage after human-chimpanzee separation. We find evidence that neutral mechanisms are influencing the frequency of polymorphic mutations in humans. Our results suggest a recent increase in mutational tendencies toward AT, observed in all isochores, that is responsible for AT mutations segregating at lower frequencies than GC mutations. In all, however, changes in mutational tendencies and other neutral scenarios are not sufficient to explain a difference between synonymous and noncoding mutations or a difference between synonymous mutations potentially advantageous or deleterious under a translational selection model. Furthermore, several estimates of selection intensity on synonymous mutations all suggest a detectable influence of weak selection acting at the level of translational selection. Thus, random genetic drift, recent changes in mutational tendencies, and weak selection influence the fate of synonymous mutations that are present today as polymorphisms. All of these features, neutral and selective, should be taken into account in evolutionary analyses that often assume constancy of mutational tendencies and complete neutrality of synonymous mutations.

Relationships among stop codon usage bias, its context, isochores, and gene expression level in various eukaryotes

It is well known that stop codons play a critical role in the process of protein synthesis. However, little effort has been made to investigate whether stop codon usage exhibits biases, such as widely seen for synonymous codon usage. Here we systematically investigate stop codon usage bias in various eukaryotes as well as its relationships with its context, GC3 content, gene expression level, and secondary structure. The results show that there is a strong bias for stop codon usage in different eukaryotes, i.e., UAA is overrepresented in the lower eukaryotes, UGA is overrepresented in the higher eukaryotes, and UAG is least used in all eukaryotes. Different conserved patterns for each stop codon in different eukaryotic classes are found based on information content and logo analysis. GC3 contents increase with increasing complexity of organisms. Secondary structure prediction revealed that UAA is generally associated with loop structures, whereas UGA is more uniformly present in loop and stem structures, i.e., UGA is less biased toward having a particular structure. The stop codon usage bias, however, shows no significant relationship with GC3 content and gene expression level in individual eukaryotes. The results indicate that genomic complexity and GC3 content might contribute to stop codon usage bias in different eukaryotes. Our results indicate that stop codons, like synonymous codons, exhibit biases in usage. Additional work will be needed to understand the causes of these biases and their relationship to the mechanism of protein termination.

Intragenic spatial patterns of codon usage bias in prokaryotic and eukaryotic genomes

To study the roles of translational accuracy, translational efficiency, and the Hill-Robertson effect in codon usage bias, we studied the intragenic spatial distribution of synonymous codon usage bias in four prokaryotic (Escherichia coli, Bacillus subtilis, Sulfolobus tokodaii, and Thermotoga maritima) and two eukaryotic (Saccharomyces cerevisiae and Drosophila melanogaster) genomes. We generated supersequences at each codon position across genes in a genome and computed the overall bias at each codon position. By quantitatively evaluating the trend of spatial patterns using isotonic regression, we show that in yeast and prokaryotic genomes, codon usage bias increases along translational direction, which is consistent with purifying selection against nonsense errors. Fruit fly genes show a nearly symmetric M-shaped spatial pattern of codon usage bias, with less bias in the middle and both ends. The low codon usage bias in the middle region is best explained by interference (the Hill-Robertson effect) between selections at different codon positions. In both yeast and fruit fly, spatial patterns of codon usage bias are characteristically different from patterns of GC-content variations. Effect of expression level on the strength of codon usage bias is more conspicuous than its effect on the shape of the spatial distribution.

A dissection of volatility in yeast

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

The Ambush Hypothesis: Hidden Stop Codons Prevent Off-Frame Gene Reading

Coding sequences lack stop codons, but many stops appear off-frame. Off-frame stops (stops in -1 and +1 shifted reading frames, termed hidden stops) terminate frame-shifted translation, potentially decreasing energy, and resource waste on nonfunctional proteins. Benefits may include reduced waste elimination costs and avoidance of potentially cytotoxic frame-shifted products. Our "ambush" hypothesis suggests that hidden stops are sometimes selected for. Codons of many amino acids can contribute to hidden stops, depending on the synonymous position state and adjacent codons. In vertebrate mitochondria, 31.75% of all amino acid combinations can form hidden stops. Codons with more potential to form hidden stops have greater usage frequency and bias in their favor among synonymous codons. Among primates, predicted mitochondrial rRNA secondary structure stability correlates negatively with the number of hidden stops in the mitochondrial genome. The taxonomic distribution of genetic codes suggests that +1 frameshifts might be more frequent than -1 frameshifts. This is confirmed by analyses of primate mitochondrial genomes: species with unstable rRNAs have more +1 stops, but the correlation is weak for -1 stops. High hidden stop density seems to be an adaptation in species with slippage prone ribosomes (unstable rRNAs). Hidden stops may thus compensate for reduced efficiency of some parts of the biosynthetic machinery. Some experimental data confirm our hypothesis: gene expression increases with the experimentally manipulated number of stops in the promoter region of a gene, suggesting biotechnological applications.