Comparing expression level-dependent features in codon usage with protein abundance: an analysis of 'predictive proteomics'

Synonymous codon usage is a commonly used means for estimating gene expression levels of Escherichia coli genes and has also been used for predicting highly expressed genes for a number of prokaryotic genomes. By comparison of expression level-dependent features in codon usage with protein abundance data from two proteome studies of exponentially growing E. coli and Bacillus subtilis cells, we try to evaluate whether the implicit assumption of this approach can be confirmed with experimental data. Log-odds ratio scores are used to model differences in codon usage between highly expressed genes and genomic average. Using these, the strength and significance of expression level-dependent features in codon usage were determined for the genes of the Escherichia coli, Bacillus subtilis and Haemophilus influenzae genomes. The comparison of codon usage features with protein abundance data confirmed a relationship between these to be present, although exceptions to this, possibly related to functional context, were found. For species with expression level-dependent features in their codon usage, the applied methodology could be used to improve in silico simulations of the outcome of two-dimensional gel electrophoretic experiments.     

Cloning and characterization of the gene encoding the highly expressed ribosomal protein l3 of the ciliated protozoan Tetrahymena thermophila. Evidence for differential codon usage in highly expressed genes

We have cloned and characterized the cDNA and the macronuclear genomic copy of the highly conserved ribosomal protein (r-protein) L3 of Tetrahymena thermophila. The r-protein L3 is encoded by a single copy gene interrupted by one intron. The organization of the promoter region exhibits features characteristic of ribosomal protein genes in Tetrahymena. The codon usage of the L3 gene is highly biased. A thorough analysis of codon usage in Tetrahymena genes revealed that genes could be categorized into two classes according to codon usage bias. Class A comprises r-protein genes and a number of other highly expressed genes. Class B comprises weakly expressed genes such as the conjugation induced CnjB and CnjC genes, but surprisingly, this class also contains abundantly expressed genes such as the genes encoding the surface antigens SerH3 and SerH1. Codon usage is slightly more restricted in class A than in class B, but both classes exhibit distinct and different codon usage biases. Class A genes preferentially use C and U in the silent third codon positions, whereas class B genes preferentially use A and U in the silent third codon positions. The analysis suggests that two different strategies have been employed for optimization of codon usage in the A+T-rich genome of Tetrahymena.     

Developmental stage related patterns of codon usage and genomic GC content: searching for evolutionary fingerprints with models of stem cell differentiation

Background  

The usage of synonymous codons shows considerable variation among mammalian genes. How and why this usage is non-random are fundamental biological questions and remain controversial. It is also important to explore whether mammalian genes that are selectively expressed at different developmental stages bear different molecular features.     

Comparative Analysis of Codon Usage Patterns Among Mitochondrion, Chloroplast and Nuclear Genes in Triticum aestivum L.

In many organisms, the difference in codon usage patterns among genes reflects variation in local base compositional biases and the intensity of natural selection. In this study, a comparative analysis was performed to investigate the characteristics of codon bias and factors in shaping the codon usage patterns among mitochondrion, chloroplast and nuclear genes in common wheat （Triticum aestivum L.）. GC contents in nuclear genes were higher than that in mitochondrion and chloroplast genes. The neutrality and correspondence analyses indicated that the codon usage in nuclear genes would be a result of relative strong mutational bias, while the codon usage patterns of mitochondrion and chloroplast genes were more conserved in GC content and influenced by translation level. The Parity Rule 2 （PR2） plot analysis showed that pyrimidines were used more frequently than purines at the third codon position in the three genomes. In addition, using a new alterative strategy, 11, 12, and 24 triplets were defined as preferred codons in the mitochondrion, chloroplast and nuclear genes, respectively. These findings suggested that the mitochondrion, chloroplast and nuclear genes shared particularly different features of codon usage and evolutionary constraints.     

Protein Abundance Prediction Through Machine Learning Methods

Proteins are responsible for most physiological processes, and their abundance provides crucial information for systems biology research. However, absolute protein quantification, as determined by mass spectrometry, still has limitations in capturing the protein pool. Protein abundance is impacted by translation kinetics, which rely on features of codons. In this study, we evaluated the effect of codon usage bias of genes on protein abundance. Notably, we observed differences regarding codon usage patterns between genes coding for highly abundant proteins and genes coding for less abundant proteins. Analysis of synonymous codon usage and evolutionary selection showed a clear split between the two groups. Our machine learning models predicted protein abundances from codon usage metrics with remarkable accuracy, achieving strong correlation with experimental data. Upon integration of the predicted protein abundance in enzyme-constrained genome-scale metabolic models, the simulated phenotypes closely matched experimental data, which demonstrates that our predictive models are valuable tools for systems metabolic engineering approaches.     

Chronic obstructive pulmonary disease: A crosstalk on nucleotide compositional dynamics and codon usage patterns of the genes involved in disease

Chronic obstructive pulmonary disease (COPD), a lung disease, affects a large number of people worldwide, leading to death. Here, we analyzed the compositional features and trends of codon usage of the genes influencing COPD to understand molecular biology, genetics, and evolutionary relationships of these genes as no work was reported yet. Coding sequences of COPD genes were found to be rich in guanine-cytosine (GC) content. A high value (34-60) of the effective number of codons of the genes indicated low codon usage bias (CUB). Correspondence analysis suggested that the COPD genes were distinct in their codon usage patterns. Relative synonymous codon usage values of codons differed between the more preferred codons and the less-preferred ones. Correlation analysis between overall nucleotides and those at third codon position revealed that mutation pressure might influence the CUB of the genes. The high correlation between GC12 and GC3 signified that directional mutation pressure might have operated at all the three codon positions in COPD genes.     

Compositional features are potentially involved in the regulation of gene expression of tumor suppressor genes in human tissues

Different mechanisms regulate the expression level of tissue specific genes in human. Here we report some compositional features such as codon usage bias, amino acid usage bias, codon frequency, and base composition which may be potentially related to mRNA amount of tissue specific tumor suppressor genes. Our findings support the possibility that structural elements in gene and protein may play an important role in the regulation of tumor suppressor genes, development, and tumorigenesis. The data presented here can open broad vistas in the understanding and treatment of a variety of human malignancies.     

Automatic prediction of non-coding RNA genes in prokaryotes based on compositional statistics

Although non-coding RNA (ncRNA) genes do not encode proteins, they play vital roles in cells by producing functionally important RNAs. In this paper, we present a novel method for predicting ncRNA genes based on compositional features extracted directly from gene sequences. Our method consists of two Support Vector Machine (SVM) models--Codon model which uses codon usage features derived from ncRNA genes and protein-coding genes and Kmer model which utilizes features of nucleotide and dinucleotide frequency extracted respectively from ncRNA genes and randomly chosen genome sequences. The 10-fold cross-validation accuracy for the two models is found to be 92% and 91%, respectively. Thus, we could make an automatic prediction of ncRNA genes in one genome without manual filtration of protein-coding genes. After applying our method in Sulfolobus solfataricus genome, 25 prediction results have been generated according to 25 cut-off pairs. We have also applied the approach in E. coli and found our results comparable to those of previous studies. In general, our method enables automatic identification of ncRNA genes in newly sequenced prokaryotic genomes.     

Stress induced MAPK genes show distinct pattern of codon usage in Arabidopsis thaliana,Glycine max and Oryza sativa

Mitogen activated protein kinase (MAPK) genes provide resistance to various biotic and abiotic stresses. Codon usage profiling of the genes reveals the characteristic features of the genes like nucleotide composition, gene expressivity, optimal codons etc. The present study is a comparative analysis of codon usage patterns for different MAPK genes in three organisms, viz. Arabidopsis thaliana, Glycine max (soybean) and Oryza sativa (rice). The study has revealed a high AT content in MAPK genes of Arabidopsis and soybean whereas in rice a balanced AT-GC content at the third synonymous position of codon. The genes show a low bias in codon usage profile as reflected in the higher values (50.83 to 56.55) of effective number of codons (N_c). The prediction of gene expression profile in the MAPK genes revealed that these genes might be under the selective pressure of translational optimization as reflected in the low codon adaptation index (CAI) values ranging from 0.147 to 0.208.     

Di-codon usage for classification of genes

Genes are often classified into biologically related groups so that inferences on their functions can be made. This paper demonstrates that the di-codon usage is a useful feature for gene classification and gives better classification accuracy than the codon usage. Our experiments with different classifiers show that support vector machines performs better than other classifiers in classifying genes by using di-codon usage as features. The method is illustrated on 1841 HLA sequences which are classified into two major classes, HLA-I and HLA-II, and further classified into the subclasses of major classes. By using both codon and di-codon features, we show near perfect accuracies in the classification of HLA molecules into major classes and their sub-classes.     

The Effect of Multiple Evolutionary Selections on Synonymous Codon Usage of Genes in the Mycoplasma bovis Genome

Mycoplasma bovis is a major pathogen causing arthritis, respiratory disease and mastitis in cattle. A better understanding of its genetic features and evolution might represent evidences of surviving host environments. In this study, multiple factors influencing synonymous codon usage patterns in M. bovis (three strains’ genomes) were analyzed. The overall nucleotide content of genes in the M. bovis genome is AT-rich. Although the G and C contents at the third codon position of genes in the leading strand differ from those in the lagging strand (p<0.05), the 59 synonymous codon usage patterns of genes in the leading strand are highly similar to those in the lagging strand. The over-represented codons and the under-represented codons were identified. A comparison of the synonymous codon usage pattern of M. bovis and cattle (susceptible host) indicated the independent formation of synonymous codon usage of M. bovis. Principal component analysis revealed that (i) strand-specific mutational bias fails to affect the synonymous codon usage pattern in the leading and lagging strands, (ii) mutation pressure from nucleotide content plays a role in shaping the overall codon usage, and (iii) the major trend of synonymous codon usage has a significant correlation with the gene expression level that is estimated by the codon adaptation index. The plot of the effective number of codons against the G+C content at the third codon position also reveals that mutation pressure undoubtedly contributes to the synonymous codon usage pattern of M. bovis. Additionally, the formation of the overall codon usage is determined by certain evolutionary selections for gene function classification (30S protein, 50S protein, transposase, membrane protein, and lipoprotein) and translation elongation region of genes in M. bovis. The information could be helpful in further investigations of evolutionary mechanisms of the Mycoplasma family and heterologous expression of its functionally important proteins.     

Studies on codon usage in Entamoeba histolytica

Codon usage bias of Entamoeba histolytica, a protozoan parasite, was investigated using the available DNA sequence data. Entamoeba histolytica having AT rich genome, is expected to have A and/or T at the third position of codons. Overall codon usage data analysis indicates that A and/or T ending codons are strongly biased in the coding region of this organism. However, multivariate statistical analysis suggests that there is a single major trend in codon usage variation among the genes. The genes which are supposed to be highly expressed are clustered at one end, while the majority of the putatively lowly expressed genes are clustered at the other end. The codon usage pattern is distinctly different in these two sets of genes. C ending codons are significantly higher in the putatively highly expressed genes suggesting that C ending codons are translationally optimal in this organism. In the putatively lowly expressed genes A and/or T ending codons are predominant, which suggests that compositional constraints are playing the major role in shaping codon usage variation among the lowly expressed genes. These results suggest that both mutational bias and translational selection are operational in the codon usage variation in this organism.     

Fine structural features of the chloroplast genome: comparison of the sequenced chloroplast genomes.

The entire nucleotide sequences of the rice, tobacco and liverwort chloroplast genomes have been determined. We compared all the chloroplast genes, open reading frames and spacer regions in the plastid genomes of these three species in order to elucidate general structural features of the chloroplast genome. Analyses of homology, GC content and codon usage of the genes enabled us to classify them into two groups: photosynthesis genes and genetic system genes. Based on comparisons of homology, GC content and codon usage, unidentified ORFs can also be assigned to each of these groups such that it is possible to speculate about the functions of products which may be produced by these ORFs. The spacer regions and intron sequences were compared and found to have no obvious homology between rice and liverwort or between tobacco and liverwort.     

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.     

Codon Usage in Plastid Genes Is Correlated with Context, Position Within the Gene, and Amino Acid Content

Highly expressed plastid genes display codon adaptation, which is defined as a bias toward a set of codons which are complementary to abundant tRNAs. This type of adaptation is similar to what is observed in highly expressed Escherichia coli genes and is probably the result of selection to increase translation efficiency. In the current work, the codon adaptation of plastid genes is studied with regard to three specific features that have been observed in E. coli and which may influence translation efficiency. These features are (1) a relatively low codon adaptation at the 5′ end of highly expressed genes, (2) an influence of neighboring codons on codon usage at a particular site (codon context), and (3) a correlation between the level of codon adaptation of a gene and its amino acid content. All three features are found in plastid genes. First, highly expressed plastid genes have a noticeable decrease in codon adaptation over the first 10–20 codons. Second, for the twofold degenerate NNY codon groups, highly expressed genes have an overall bias toward the NNC codon, but this is not observed when the 3′ neighboring base is a G. At these sites highly expressed genes are biased toward NNT instead of NNC. Third, plastid genes that have higher codon adaptations also tend to have an increased usage of amino acids with a high G + C content at the first two codon positions and GNN codons in particular. The correlation between codon adaptation and amino acid content exists separately for both cytosolic and membrane proteins and is not related to any obvious functional property. It is suggested that at certain sites selection discriminates between nonsynonymous codons based on translational, not functional, differences, with the result that the amino acid sequence of highly expressed proteins is partially influenced by selection for increased translation efficiency. Received: 21 July 1999 / Accepted: 5 November 1999     

Relation between mRNA expression and sequence information in Desulfovibrio vulgaris: combinatorial contributions of upstream regulatory motifs and coding sequence features to variations in mRNA abundance

The context-dependent expression of genes is the core for biological activities, and significant attention has been given to identification of various factors contributing to gene expression at genomic scale. However, so far this type of analysis has been focused either on relation between mRNA expression and non-coding sequence features such as upstream regulatory motifs or on correlation between mRNA abundance and non-random features in coding sequences (e.g., codon usage and amino acid usage). In this study multiple regression analyses of the mRNA abundance and all sequence information in Desulfovibrio vulgaris were performed, with the goal to investigate how much coding and non-coding sequence features contribute to the variations in mRNA expression, and in what manner they act together. Using the AlignACE program, 442 over-represented motifs were identified from the upstream 100bp region of 293 genes located in the known regulons. Regression of mRNA expression data against the measures of coding and non-coding sequence features indicated that 54.1% of the variations in mRNA abundance can be explained by the presence of upstream motifs, while coding sequences alone contribute to 29.7% of the variations in mRNA abundance. Interestingly, most of contribution from coding sequences is overlapping with that from upstream motifs; thereby a total of 60.3% of the variations in mRNA abundance can be explained when coding and non-coding information was included. This result demonstrates that upstream regulatory motifs and coding sequence information contribute to the overall mRNA expression in a combinatorial rather than an additive manner.     

Trypanosomatidae codon usage and GC distribution.

A study of Trypanosomatidae GC distribution and codon usage is presented. The codon usage patterns in coincidence with the phylogenetical data are similar in Crithidia and Leishmania, whereas they are more divergent in Trypanosoma brucei and T. cruzi. The analysis of the GC mutational pressure in these organisms reveals that T. brucei, and to a lesser extent T. cruzi, have evolved towards a more balanced use of all bases, whereas Leishmania and Crithidia retain features of a primeval genetic apparatus. Tables with the approximated GC mutational pressure in homologous genes, and codon usage in Trypanosomatidae are presented.     

Synonymous codon usage in Thermosynechococcus elongatus (cyanobacteria) identifies the factors shaping codon usage variation

Analysis of synonymous codon usage pattern in the genome of a thermophilic cyanobacterium, Thermosynechococcus elongatus BP-1 using multivariate statistical analysis revealed a single major explanatory axis accounting for codon usage variation in the organism. This axis is correlated with the GC content at third base of synonymous codons (GC3s) in correspondence analysis taking T. elongatus genes. A negative correlation was observed between effective number of codons i.e. Nc and GC3s. Results suggested a mutational bias as the major factor in shaping codon usage in this cyanobacterium. In comparison to the lowly expressed genes, highly expressed genes of this organism possess significantly higher proportion of pyrimidine-ending codons suggesting that besides, mutational bias, translational selection also influenced codon usage variation in T. elongatus. Correspondence analysis of relative synonymous codon usage (RSCU) with A, T, G, C at third positions (A3s, T3s, G3s, C3s, respectively) also supported this fact and expression levels of genes and gene length also influenced codon usage. A role of translational accuracy was identified in dictating the codon usage variation of this genome. Results indicated that although mutational bias is the major factor in shaping codon usage in T. elongatus, factors like translational selection, translational accuracy and gene expression level also influenced codon usage variation.