Synonymous codon usage in Lactococcus lactis: mutational bias versus translational selection

In this study codon usage bias of all experimentally known genes of Lactococcus lactis has been analyzed. Since Lactococcus lactis is an AT rich organism, it is expected to occur A and/or T at the third position of codons and detailed analysis of overall codon usage data indicates that A and/or T ending codons are predominant in this organism. However, multivariate statistical analyses based both on codon count and on relative synonymous codon usage (RSCU) detect a large number of genes, which are supposed to be highly expressed are clustered at one end of the first major axis, while majority of the putatively lowly expressed genes are clustered at the other end of the first major axis. It was observed that in the highly expressed genes C and T ending codons are significantly higher than the lowly expressed genes and also it was observed that C ending codons are predominant in the duets of highly expressed genes, whereas the T endings codons are abundant in the quartets. Abundance of C and T ending codons in the highly expressed genes suggest that, besides, compositional biases, translational selection are also operating in shaping the codon usage variation among the genes in this organism as observed in other compositionally skewed organisms. The second major axis generated by correspondence analysis on simple codon counts differentiates the genes into two distinct groups according to their hydrophobicity values, but the same analysis computed with relative synonymous codon usage values could not discriminate the genes according to the hydropathy values. This suggests that amino acid composition exerts constraints on codon usage in this organism. On the other hand the second major axis produced by correspondence analysis on RSCU values differentiates the genes into two groups according to the synonymous codon usage for cysteine residues (rarest amino acids in this organism), which is nothing but a artifactual effect induced by the RSCU values. Other factors such as length of the genes and the positions of the genes in the leading and lagging strand of replication have practically no influence in the codon usage variation among the genes in this organism.     

A simple program to calculate codon bias index

A computer program (PCBI) was developed to quickly calculate codon bias index (CBI). PCBI can analyze a gene containing introns. The 22 preferred codons defined fromSaccharomyces cerevisiae were used in PCBI as the standard to measure the CBI values. However, users can modify the preferred codons to suit each organism. The data PCBI provides include DNA sequence of open reading frame without introns, amino acid sequence of gene product, a table of amino acid composition, a table of codon usage and (G+C) content, parameters for calculating CBI, and the value of CBI. PCBI runs on DOS or Windows environment, but results can be saved in ASCII text format.     

Quantitative relationship between synonymous codon usage bias and GC composition across unicellular genomes

Background  

Codon usage bias has been widely reported to correlate with GC composition. However, the quantitative relationship between codon usage bias and GC composition across species has not been reported.     

A thermodynamic theory of codon bias in viral genes

The relationship between degeneracy in the genetic code and the occurrence of a strong codon bias is examined, with particular reference to a group of viral genomes. The present paper shows how codon bias may have been imposed by thermodynamic considerations at the time the primitive DNA first formed in the primordial soup. Using a four-state Ising-like model with stacking interactions between successive base pairs, we show how primeval periodic DNA polymers could have arisen the remnants of which are still observed in codon biases today.     

A large-scale analysis of codon usage bias in 4868 bacterial genomes shows association of codon adaptation index with GC content,protein functional domains and bacterial phenotypes

Multiple synonymous codons code for the same amino acid, resulting in the degeneracy of the genetic code and in the preferred used of some codons called codon bias usage (CBU). We performed a large-scale analysis of codon usage bias analysing the distribution of the codon adaptation index (CAI) and the codon relative adaptiveness index (RA) in 4868 bacterial genomes. We found that CAI values differ significantly between protein functional domains and part of the protein outside domains and show how CAI, GC content and preferred usage of polymerase III alpha subunits are related. Additionally, we give evidence of the association between CAI and bacterial phenotypes.     

Synonymous codon bias and functional constraint on GC3-related DNA backbone dynamics in the prokaryotic nucleoid

While mRNA stability has been demonstrated to control rates of translation, generating both global and local synonymous codon biases in many unicellular organisms, this explanation cannot adequately explain why codon bias strongly tracks neighboring intergene GC content; suggesting that structural dynamics of DNA might also influence codon choice. Because minor groove width is highly governed by 3-base periodicity in GC, the existence of triplet-based codons might imply a functional role for the optimization of local DNA molecular dynamics via GC content at synonymous sites (≈GC3). We confirm a strong association between GC3-related intrinsic DNA flexibility and codon bias across 24 different prokaryotic multiple whole-genome alignments. We develop a novel test of natural selection targeting synonymous sites and demonstrate that GC3-related DNA backbone dynamics have been subject to moderate selective pressure, perhaps contributing to our observation that many genes possess extreme DNA backbone dynamics for their given protein space. This dual function of codons may impose universal functional constraints affecting the evolution of synonymous and non-synonymous sites. We propose that synonymous sites may have evolved as an ‘accessory’ during an early expansion of a primordial genetic code, allowing for multiplexed protein coding and structural dynamic information within the same molecular context.     

A note on the bias due to omitted confounders

In observational studies some confounders may be unknown andtherefore omitted from the analysis while others are adjustedfor. Approximations to the functions defining the relationshipbetween the parameters in the full and reduced models are proposedleading to asymptotic bias estimates. Numerical calculationsfor logistic and Poisson regression models show good agreementbetween asymptotic and simulation bias. A data set containingthe relationship between low birth weight and smoking (Hosmer& Lemeshow, 1989) is used as an illustration.     

A cross talk between codon usage bias in human oncogenes

Background: Oncogenes are the genes that have the potential to induce cancer. The extent and origin of codon usage bias is an important indicator of the forces shaping genome evolution in living organisms. Results: We observed moderate correlations between gene expression as measured by CAI and GC content at any codon site. The findings of our results showed that there is a significant positive correlation (Spearman''s r= 0.45, P<0.01) between GC content at first and second codon position with that of third codon position. Further, striking negative correlation (r = -0.771, P < 0.01) between ENC with the GC3s values of each gene and positive correlation (r=0.644, P<0.01) in between CAI and ENC was also observed. Conclusions: The mutation pressure is the major determining factor in shaping the codon usage pattern of oncogenes rather than natural selection since its effects are present at all codon positions. The results revealed that codon usage bias determines the level of oncogene expression in human. Highly expressed oncogenes had rich GC contents with high degree of codon usage bias.     

The bias due to incomplete matching

Observational studies comparing groups of treated and control units are often used to estimate the effects caused by treatments. Matching is a method for sampling a large reservoir of potential controls to produce a control group of modest size that is ostensibly similar to the treated group. In practice, there is a trade-off between the desires to find matches for all treated units and to obtain matched treated-control pairs that are extremely similar to each other. We derive expressions for the bias in the average matched pair difference due to the failure to match all treated units--incomplete matching, and the failure to obtain exact matches--inexact matching. A practical example shows that the bias due to incomplete matching can be severe, and moreover, can be avoided entirely by using an appropriate multivariate nearest available matching algorithm, which, in the example, leaves only a small residual bias due to inexact matching.     

Dissecting the contributions of GC content and codon usage to gene expression in the model alga Chlamydomonas reinhardtii

The efficiency of gene expression in all organisms depends on the nucleotide composition of the coding region. GC content and codon usage are the two key sequence features known to influence gene expression, but the underlying molecular mechanisms are not entirely clear. Here we have determined the relative contributions of GC content and codon usage to the efficiency of nuclear gene expression in the unicellular green alga Chlamydomonas reinhardtii. By comparing gene variants that encode an identical amino acid sequence but differ in their GC content and/or codon usage, we show that codon usage is the key factor determining translational efficiency and, surprisingly, also mRNA stability. By contrast, unfavorable GC content affects gene expression at the level of the chromatin structure by triggering heterochromatinization. We further show that mutant algal strains that permit high‐level transgene expression are less susceptible to epigenetic transgene suppression and do not establish a repressive chromatin structure at the transgenic locus. Our data disentangle the relationship between GC content and codon usage, and suggest simple strategies to overcome the transgene expression problem in Chlamydomonas.     

Analysis of synonymous codon usage bias in Chlamydia

Chlamydiae are obligate intracellular bacterial pathogens that cause ocular and sexuallytransmitted diseases,and are associated with cardiovascular diseases.The analysis of codon usage mayimprove our understanding of the evolution and pathogenesis of Chlamydia and allow reengineering of targetgenes to improve their expression for gene therapy.Here,we analyzed the codon usage of C.muridarum,C.trachomatis(here indicating biovar trachoma and LGV),C.pneumoniae,and C.psittaci using the codonusage database and the CUSP(Create a codon usage table)program of EMBOSS(The European MolecularBiology Open Software Suite).The results show that the four genomes have similar codon usage patterns,with a strong bias towards the codons with A and T at the third codon position.Compared with Homosapiens,the four chlamydial species show discordant seven or eight preferred codons.The ENC(effectivenumber of codons used in a gene)-plot reveals that the genetic heterogeneity in Chlamydia is constrained bythe G+C content,while translational selection and gene length exert relatively weaker influences.Moreover,mutational pressure appears to be the major determinant of the codon usage variation among the chlamydialgenes.In addition,we compared the codon preferences of C.trachomatis with those of E.coli,yeast,adenovirus and Homo sapiens.There are 23 codons showing distinct usage differences between C.trachomatisand E.coli,24 between C.trachomatis and adenovirus,21 between C.trachomatis and Homo sapiens,butonly six codons between C.trachomatis and yeast.Therefore,the yeast system may be more suitable for theexpression of chlamydial genes.Finally,we compared the codon preferences of C.trachomatis with those ofsix eukaryotes,eight prokaryotes and 23 viruses.There is a strong positive correlation between the differ-ences in coding GC content and the variations in codon bias(r=0.905,P<0,001).We conclude that thevariation of codon bias between C.trachomatis and other organisms is much less influenced by phylogeneticlineage and primarily determined by the extent of disparities in GC content.     

Regularities of context-dependent codon bias in eukaryotic genes

Nucleotides surrounding a codon influence the choice of this particular codon from among the group of possible synonymous codons. The strongest influence on codon usage arises from the nucleotide immediately following the codon and is known as the N₁ context. We studied the relative abundance of codons with N₁ contexts in genes from four eukaryotes for which the entire genomes have been sequenced: Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans and Arabidopsis thaliana. For all the studied organisms it was found that 90% of the codons have a statistically significant N₁ context-dependent codon bias. The relative abundance of each codon with an N₁ context was compared with the relative abundance of the same 4mer oligonucleotide in the whole genome. This comparison showed that in about half of all cases the context-dependent codon bias could not be explained by the sequence composition of the genome. Ranking statistics were applied to compare context-dependent codon biases for codons from different synonymous groups. We found regularities in N₁ context-dependent codon bias with respect to the codon nucleotide composition. Codons with the same nucleotides in the second and third positions and the same N₁ context have a statistically significant correlation of their relative abundances.     

A method for measuring the non-random bias of a codon usage table

We describe a new statistical method for measuring bias in the codon usage table of a gene. The test is based on the multinomial and Poisson distributions. The method is used to scan DNA sequences and measure the strength of codon preference. For E. Coli we show that the strength of codon preference is related to levels of gene expression. The method can also be used to compare base triplet frequencies with those expected from the base composition. This second type of codon bias test is useful for distinguishing coding from non-coding regions.     

Role of mutational bias and natural selection on genome-wide nucleotide bias in prokaryotic organisms

Correlations between genomic GC contents and amino acid frequencies were studied in the homologous sequences of 12 eubacterial genomes. Results show that amino acids encoded by GC-rich codons increases significantly with genomic GC contents, whereas opposite trend was observed in case of amino acids encoded by GC-poor codons. Further studies show all the amino acids do not change in the predicted direction according to their genomic GC pressure, suggesting that protein evolution is not entirely dictated by their nucleotide frequencies. Amino acid substitution matrix calculated among hydrophobic, amphipathic and hydrophilic amino acid groups' shows that amphipathic and hydrophilic amino acids are more frequently substituted by hydrophobic amino acids than from hydrophobic to hydrophilic or amphipathic amino acids. This indicates that nucleotide bias induces a directional changes in proteome composition in such a way that underwent strong changes in hydropathy values. In fact, significant increases in hydrophobicity values have also been observed with the increase of genomic GC contents. Correlations between GC contents and amino acid compositions in three different predicted protein secondary structures show that hydropathy values increases significantly with GC contents in aperiodic and helix structures whereas strand structure remains insensitive with the genomic GC levels. The relative importance of mutation and selection on the evolution of proteins have been discussed on the basis of these results.     

A combined empirical and mechanistic codon model

The evolutionary selection forces acting on a protein are commonly inferred using evolutionary codon models by contrasting the rate of synonymous to nonsynonymous substitutions. Most widely used models are based on theoretical assumptions and ignore the empirical observation that distinct amino acids differ in their replacement rates. In this paper, we develop a general method that allows assimilation of empirical amino acid replacement probabilities into a codon-substitution matrix. In this way, the resulting codon model takes into account not only the transition-transversion bias and the nonsynonymous/synonymous ratio, but also the different amino acid replacement probabilities as specified in empirical amino acid matrices. Different empirical amino acid replacement matrices, such as secondary structure-specific matrices or organelle-specific matrices (e.g., mitochondria and chloroplasts), can be incorporated into the model, making it context dependent. Using a diverse set of coding DNA sequences, we show that the novel model better fits biological data as compared with either mechanistic or empirical codon models. Using the suggested model, we further analyze human immunodeficiency virus type 1 protease sequences obtained from drug-treated patients and reveal positive selection in sites that are known to confer drug resistance to the virus.     

Analysis of phylogeny and codon usage bias and relationship of GC content,amino acid composition with expression of the structural nif genes

Bacteria and archaea have evolved with the ability to fix atmospheric dinitrogen in the form of ammonia, catalyzed by the nitrogenase enzyme complex which comprises three structural genes nifK, nifD and nifH. The nifK and nifD encodes for the beta and alpha subunits, respectively, of component 1, while nifH encodes for component 2 of nitrogenase. Phylogeny based on nifDHK have indicated that Cyanobacteria is closer to Proteobacteria alpha and gamma but not supported by the tree based on 16SrRNA. The evolutionary ancestor for the different trees was also different. The GC1 and GC2% analysis showed more consistency than GC3% which appeared to below for Firmicutes, Cyanobacteria and Euarchaeota while highest in Proteobacteria beta and clearly showed the proportional effect on the codon usage with a few exceptions. Few genes from Firmicutes, Euryarchaeota, Proteobacteria alpha and delta were found under mutational pressure. These nif genes with low and high GC3% from different classes of organisms showed similar expected number of codons. Distribution of the genes and codons, based on codon usage demonstrated opposite pattern for different orientation of mirror plane when compared with each other. Overall our results provide a comprehensive analysis on the evolutionary relationship of the three structural nif genes, nifK, nifD and nifH, respectively, in the context of codon usage bias, GC content relationship and amino acid composition of the encoded proteins and exploration of crucial statistical method for the analysis of positive data with non-constant variance to identify the shape factors of codon adaptation index.     

Combination of hydrophobicity and codon usage bias determines sorting of model K+ channel protein to either mitochondria or endoplasmic reticulum

When the K⁺ channel-like protein Kesv from Ectocarpus siliculosus virus 1 is heterologously expressed in mammalian cells, it is sorted to the mitochondria. This targeting can be redirected to the endoplasmic reticulum (ER) by altering the codon usage in distinct regions of the gene or by inserting a triplet of hydrophobic amino acids (AAs) into the protein's C-terminal transmembrane domain (ct-TMD). Systematic variations in the flavor of the inserted AAs and/or its codon usage show that a positive charge in the inserted AA triplet alone serves as strong signal for mitochondria sorting. In cases of neutral AA triplets, mitochondria sorting are favored by a combination of hydrophilic AAs and rarely used codons; sorting to the ER exhibits the inverse dependency. This propensity for ER sorting is particularly high when a common codon follows a rarer one in the AA triplet; mitochondria sorting in contrast is supported by codon uniformity. Since parameters like positive charge, hydrophobic AAs, and common codons are known to facilitate elongation of nascent proteins in the ribosome the data suggest a mechanism in which local changes in elongation velocity and co-translational folding in the ct-TMD influence intracellular protein sorting.     

Optimality of codon usage in Escherichia coli due to load minimization

The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, an ability which in term is designated "load minimization". One parameter involved in calculating the load minimizing property of the genetic code is codon usage. In most bacteria, synonymous codons are not used with equal frequencies. Different factors have been proposed to contribute to codon usage preference. It has been shown that the codon preference is correlated with the composition of the tRNA pool. Selection for translational efficiency and translational accuracy both result in such a correlation. In this work, it is shown that codon usage bias in Escherichia coli works so as to minimize the consequences of translational errors, i.e. optimized for load minimization.