Codon usage in Kluyveromyces lactis and in yeast cytochrome c-encoding genes

GenRCA: a user-friendly rare codon analysis tool for comprehensive evaluation of codon usage preferences based on coding sequences in genomes

BACKGROUND

The study of codon usage bias is important for understanding gene expression, evolution and gene design, providing critical insights into the molecular processes that govern the function and regulation of genes. Codon Usage Bias (CUB) indices are valuable metrics for understanding codon usage patterns across different organisms without extensive experiments. Considering that there is no one-fits-all index for all species, a comprehensive platform supporting the calculation and analysis of multiple CUB indices for codon optimization is greatly needed.

RESULTS

Here, we release GenRCA, an updated version of our previous Rare Codon Analysis Tool, as a free and user-friendly website for all-inclusive evaluation of codon usage preferences of coding sequences. In this study, we manually reviewed and implemented up to 31 codon preference indices, with 65 expression host organisms covered and batch processing of multiple gene sequences supported, aiming to improve the user experience and provide more comprehensive and efficient analysis.

CONCLUSIONS

Our website fills a gap in the availability of comprehensive tools for species-specific CUB calculations, enabling researchers to thoroughly assess the protein expression level based on a comprehensive list of 31 indices and further guide the codon optimization.

Composition and Codon Usage Pattern Results in Divergence of the Zinc Binuclear Cluster (Zn(II)2Cys6) Sequences among Ascomycetes Plant Pathogenic Fungi

Zinc binuclear cluster proteins (ZBC; Zn(II)2Cys6) are unique to the fungi kingdom and associated with a series of functions, viz., the utilization of macromolecules, stress tolerance, and most importantly, host-pathogen interactions by imparting virulence to the pathogen. Codon usage bias (CUB) is the phenomenon of using synonymous codons in a non-uniform fashion during the translation event, which has arisen because of interactions among evolutionary forces. The Zn(II)2Cys6 coding sequences from nine Ascomycetes plant pathogenic species and model system yeast were analysed for compositional and codon usage bias patterns. The clustering analysis diverged the Ascomycetes fungi into two clusters. The nucleotide compositional and relative synonymous codon usage (RSCU) analysis indicated GC biasness toward Ascomycetes fungi compared with the model system S. cerevisiae, which tends to be AT-rich. Further, plant pathogenic Ascomycetes fungi belonging to cluster-2 showed a higher number of GC-rich high-frequency codons than cluster-1 and was exclusively AT-rich in S. cerevisiae. The current investigation also showed the mutual effect of the two evolutionary forces, viz. natural selection and compositional constraints, on the CUB of Zn(II)2Cys6 genes. The perseverance of GC-rich codons of Zn(II)2Cys6 in Ascomycetes could facilitate the invasion process. The findings of the current investigation show the role of CUB and nucleotide composition in the evolutionary divergence of Ascomycetes plant pathogens and paves the way to target specific codons and sequences to modulate host-pathogen interactions through genome editing and functional genomics tools.

Analysis of evolutionary and genetic patterns in structural genes of primate lentiviruses

Background

Primate lentiviruses (HIV1, HIV2, and Simian immunodeficiency virus [SIV]) cause immune deficiency, encephalitis, and infectious anemia in mammals such as cattle, cat, goat, sheep, horse, and puma.

Objective

This study was designed and conducted with the main purpose of confirming the overall codon usage pattern of primate lentiviruses and exploring the evolutionary and genetic characteristics commonly or specifically expressed in HIV1, HIV2, and SIV.

Methods

The gag, pol, and env gene sequences of HIV1, HIV2, and SIV were analyzed to determine their evolutionary relationships, nucleotide compositions, codon usage patterns, neutrality, selection pressure (influence of mutational pressure and natural selection), and viral adaptation to human codon usage.

Results

A strong ‘A’ bias was confirmed in all three structural genes, consistent with previous findings regarding HIV. Notably, the ENC-GC3s plot and neutral evolution analysis showed that all primate lentiviruses were more affected by selection pressure than by mutation caused by the GC composition of the gene, consistent with prior reports regarding HIV1. The overall codon usage bias of pol was highest among the structural genes, while the codon usage bias of env was lowest. The virus groups showing high codon bias in all three genes were HIV1 and SIVcolobus. The codon adaptation index (CAI) and similarity D(A, B) values indicated that although there was a high degree of similarity to human codon usage in all three structural genes of HIV, this similarity was not caused by translation pressure. In addition, compared with HIV1, the codon usage of HIV2 is more similar to the human codon usage, but the overall codon usage bias is lower.

Conclusion

The origin viruses of HIV (SIVcpz_gor and SIVsmm) exhibit greater similarity to human codon usage in the gag gene, confirming their robust adaptability to human codon usage. Therefore, HIV1 and HIV2 may have evolved to avoid human codon usage by selection pressure in the gag gene after interspecies transmission from SIV hosts to humans. By overcoming safety and stability issues, information from codon usage analysis will be useful for attenuated HIV1 vaccine development. A recoded HIV1 variant can be used as a vaccine vector or in immunotherapy to induce specific innate immune responses. Further research regarding HIV1 dinucleotide usage and codon pair usage will facilitate new approaches to the treatment of AIDS.

Strong Selectional Forces Fine-Tune CpG Content in Genes Involved in Neurological Disorders as Revealed by Codon Usage Patterns

Neurodegenerative disorders cause irreversible damage to the neurons and adversely affect the quality of life. Protein misfolding and their aggregation in specific parts of the brain, mitochondrial dysfunction, calcium load, proteolytic stress, and oxidative stress are among the causes of neurodegenerative disorders. In addition, altered metabolism has been associated with neurodegeneration as evidenced by reductions in glutamine and alanine in transient global amnesia patients, higher homocysteine-cysteine disulfide, and lower methionine decline in serum urea have been observed in Alzheimer's disease patients. Neurodegeneration thus appears to be a culmination of altered metabolism. The study's objective is to analyze various attributes like composition, physical properties of the protein, and factors like selectional and mutational forces, influencing codon usage preferences in a panel of genes involved directly or indirectly in metabolism and contributing to neurodegeneration. Various parameters, including gene composition, dinucleotide analysis, Relative synonymous codon usage (RSCU), Codon adaptation index (CAI), neutrality and parity plots, and different protein indices, were computed and analyzed to determine the codon usage pattern and factors affecting it. The correlation of intrinsic protein properties such as the grand average of hydropathicity index (GRAVY), isoelectric point, hydrophobicity, and acidic, basic, and neutral amino acid content has been found to influence codon usage. In genes up to 800 amino acids long, the GC3 content was highly variable, while GC12 content was relatively constant. An optimum CpG content is present in genes to maintain a high expression level as required for genes involved in metabolism. Also observed was a low codon usage bias with a higher protein expression level. Compositional parameters and nucleotides at the second position of codons played essential roles in explaining the extent of bias. Overall analysis indicated that the dominance of selection pressure and compositional constraints and mutational forces shape codon usage.

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

Codon-based indices for modeling gene expression and transcript evolution

Codon usage bias (CUB) refers to the phenomena that synonymous codons are used in different frequencies in most genes and organisms. The general assumption is that codon biases reflect a balance between mutational biases and natural selection. Today we understand that the codon content is related and can affect all gene expression steps. Starting from the 1980s, codon-based indices have been used for answering different questions in all biomedical fields, including systems biology, agriculture, medicine, and biotechnology. In general, codon usage bias indices weigh each codon or a small set of codons to estimate the fitting of a certain coding sequence to a certain phenomenon (e.g., bias in codons, adaptation to the tRNA pool, frequencies of certain codons, transcription elongation speed, etc.) and are usually easy to implement. Today there are dozens of such indices; thus, this paper aims to review and compare the different codon usage bias indices, their applications, and advantages. In addition, we perform analysis that demonstrates that most indices tend to correlate even though they aim to capture different aspects. Due to the centrality of codon usage bias on different gene expression steps, it is important to keep developing new indices that can capture additional aspects that are not modeled with the current indices.

COUSIN (COdon Usage Similarity INdex): A Normalized Measure of Codon Usage Preferences

Codon Usage Preferences (CUPrefs) describe the unequal usage of synonymous codons at the gene, chromosome, or genome levels. Numerous indices have been developed to evaluate CUPrefs, either in absolute terms or with respect to a reference. We introduce the normalized index COUSIN (for COdon Usage Similarity INdex), that compares the CUPrefs of a query against those of a reference and normalizes the output over a Null Hypothesis of random codon usage. The added value of COUSIN is to be easily interpreted, both quantitatively and qualitatively. An eponymous software written in Python3 is available for local or online use (http://cousin.ird.fr). This software allows for an easy and complete analysis of CUPrefs via COUSIN, includes seven other indices, and provides additional features such as statistical analyses, clustering, and CUPrefs optimization for gene expression. We illustrate the flexibility of COUSIN and highlight its advantages by analyzing the complete coding sequences of eight divergent genomes. Strikingly, COUSIN captures a bimodal distribution in the CUPrefs of human and chicken genes hitherto unreported with such precision. COUSIN opens new perspectives to uncover CUPrefs specificities in genomes in a practical, informative, and user-friendly way.

Compositional properties and codon usage of TP73 gene family

The TP73 gene is considered as one of the members of TP53 gene family and shows much homology to p53 gene. TP73 gene plays a pivotal role in cancer studies in addition to other biological functions. Codon usage bias (CUB) is the phenomenon of unequal usage of synonymous codons for an amino acid wherein some codons are more frequently used than others and it reveals the evolutionary relationship of a gene. Here, we report the pattern of codon usage in TP73 gene using various bioinformatic tools as no work was reported yet. Nucleotide composition analysis suggested that the mean nucleobase C was the highest, followed by G and the gene was GC rich. Correlation analysis between codon usage and GC3 suggested that most of the GC-ending codons showed positive correlation while most of the AT-ending codons showed negative correlation with GC3 in the coding sequences of TP73 gene variants in human. The CUB is moderate in human TP73 gene as evident from intrinsic codon deviation index (ICDI) analysis. Nature selected against two codons namely ATA (isoleucine) and AGA (arginine) in the coding sequences of TP73 gene during the course of evolution. A significant correlation (p < 0.05) was found between overall nucleotide composition and its composition at the 3rd codon position, indicating that both mutation pressure and natural selection might influence the CUB. The correlation analysis between ICDI and biochemical properties of protein suggested that variation of CUB was associated with degree of hydrophobicity and length of protein.

Gene expression, nucleotide composition and codon usage bias of genes associated with human Y chromosome

Analysis of codon usage pattern is important to understand the genetic and evolutionary characteristics of genomes. We have used bioinformatic approaches to analyze the codon usage bias (CUB) of the genes located in human Y chromosome. Codon bias index (CBI) indicated that the overall extent of codon usage bias was low. The relative synonymous codon usage (RSCU) analysis suggested that approximately half of the codons out of 59 synonymous codons were most frequently used, and possessed a T or G at the third codon position. The codon usage pattern was different in different genes as revealed from correspondence analysis (COA). A significant correlation between effective number of codons (ENC) and various GC contents suggests that both mutation pressure and natural selection affect the codon usage pattern of genes located in human Y chromosome. In addition, Y-linked genes have significant difference in GC contents at the second and third codon positions, expression level, and codon usage pattern of some codons like the SPANX genes in X chromosome.

Analysis of codon usage patterns in Ginkgo biloba reveals codon usage tendency from A/U-ending to G/C-ending

As one of the most ancient tree species, the codon usage pattern analysis of Ginkgo biloba is a useful way to understand its evolutionary and genetic mechanisms. Several studies have been conducted on angiosperms, but seldom on gymnosperms. Based on RNA-Seq data of the G. biloba transcriptome, amount to 17,579 unigenes longer than 300 bp were selected and analyzed from 68,547 candidates. The codon usage pattern tended towards more frequently use of A/U-ending codons, which showed an obvious gradient progressing from gymnosperms to dicots to monocots. Meanwhile, analysis of high/low-expression unigenes revealed that high-expression unigenes tended to use G/C-ending codons together with more codon usage bias. Variation of unigenes with different functions suggested that unigenes involving in environment adaptation use G/C-ending codons more frequently with more usage bias, and these results were consistent with the conclusion that the formation of G. biloba codon usage bias was dominated by natural selection.

Promoter-Terminator Gene Loops Affect Alternative 3'-End Processing in Yeast

Many eukaryotic genes undergo alternative 3'-end poly(A)-site selection producing transcript isoforms with 3'-UTRs of different lengths and post-transcriptional fates. Gene loops are dynamic structures that juxtapose the 3'-ends of genes with their promoters. Several functions have been attributed to looping, including memory of recent transcriptional activity and polarity of transcription initiation. In this study, we investigated the relationship between gene loops and alternative poly(A)-site. Using the KlCYC1 gene of the yeast Kluyveromyces lactis, which includes a single promoter and two poly(A) sites separated by 394 nucleotides, we demonstrate in two yeast species the formation of alternative gene loops (L1 and L2) that juxtapose the KlCYC1 promoter with either proximal or distal 3'-end processing sites, resulting in the synthesis of short and long forms of KlCYC1 mRNA. Furthermore, synthesis of short and long mRNAs and formation of the L1 and L2 loops are growth phase-dependent. Chromatin immunoprecipitation experiments revealed that the Ssu72 RNA polymerase II carboxyl-terminal domain phosphatase, a critical determinant of looping, peaks in early log phase at the proximal poly(A) site, but as growth phase advances, it extends to the distal site. These results define a cause-and-effect relationship between gene loops and alternative poly(A) site selection that responds to different physiological signals manifested by RNA polymerase II carboxyl-terminal domain phosphorylation status.

Identifying cis-regulatory changes involved in the evolution of aerobic fermentation in yeasts

Gene regulation change has long been recognized as an important mechanism for phenotypic evolution. We used the evolution of yeast aerobic fermentation as a model to explore how gene regulation has evolved and how this process has contributed to phenotypic evolution and adaptation. Most eukaryotes fully oxidize glucose to CO₂ and H₂O in mitochondria to maximize energy yield, whereas some yeasts, such as Saccharomyces cerevisiae and its relatives, predominantly ferment glucose into ethanol even in the presence of oxygen, a phenomenon known as aerobic fermentation. We examined the genome-wide gene expression levels among 12 different yeasts and found that a group of genes involved in the mitochondrial respiration process showed the largest reduction in gene expression level during the evolution of aerobic fermentation. Our analysis revealed that the downregulation of these genes was significantly associated with massive loss of binding motifs of Cbf1p in the fermentative yeasts. Our experimental assays confirmed the binding of Cbf1p to the predicted motif and the activator role of Cbf1p. In summary, our study laid a foundation to unravel the long-time mystery about the genetic basis of evolution of aerobic fermentation, providing new insights into understanding the role of cis-regulatory changes in phenotypic evolution.

Role of genomic and proteomic tools in the study of host-virus interactions and virus evolution

Viruses have short replication cycles and produce genomic variants within a host, a process that seems to adapt to their specific host and also enable them to infect new hosts. The recent emergence of viral genomic variants from the circulating pool within the host population and re-emergence of the old ones are posing serious threat to agriculture, animal husbandry and humanity as a whole. This review assesses the potential role of genomic and proteomic tools that can monitor not only the course of infection and pathogenesis, but also predict the pandemic or zoonotic epidemic potential of a virus in a previously exposed or immunologically naive biological population.

Analysis of codon use features of stearoyl-acyl carrier protein desaturase gene in Camellia sinensis

The stearoyl-acyl carrier protein desaturase (SAD) gene widely exists in all kinds of plants. In this paper, the Camellia sinensis SAD gene (CsSAD) sequence was firstly analyzed by Codon W, CHIPS, and CUSP programs online, and then compared with genomes of the tea plant, other species and SAD genes from 11 plant species. The results show that the CsSAD gene and the selected 73 of C. sinensis genes have similar codon usage bias. The CsSAD gene has a bias toward the synonymous codons with A and T at the third codon position, the same as the 73 of C. sinensis genes. Compared with monocotyledons such as Triticum aestivum and Zea mays, the differences in codon usage frequency between the CsSAD gene and dicotyledons such as Arabidopsis thaliana and Nicotiana tobacum are less. Therefore, A. thaliana and N. tobacum expression systems may be more suitable for the expression of the CsSAD gene. The analysis result of SAD genes from 12 plant species also shows that most of the SAD genes are biased toward the synonymous codons with G and C at the third codon position. We believe that the codon usage bias analysis presented in this study will be essential for providing a theoretical basis for discussing the structure and function of the CsSAD gene.

Insight into pattern of codon biasness and nucleotide base usage in serotonin receptor gene family from different mammalian species

5-HT (5-Hydroxy-tryptamine) or serotonin receptors are found both in central and peripheral nervous system as well as in non-neuronal tissues. In the animal and human nervous system, serotonin produces various functional effects through a variety of membrane bound receptors. In this study, we focus on 5-HT receptor family from different mammals and examined the factors that account for codon and nucleotide usage variation. A total of 110 homologous coding sequences from 11 different mammalian species were analyzed using relative synonymous codon usage (RSCU), correspondence analysis (COA) and hierarchical cluster analysis together with nucleotide base usage frequency of chemically similar amino acid codons. The mean effective number of codon (ENc) value of 37.06 for 5-HT(6) shows very high codon bias within the family and may be due to high selective translational efficiency. The COA and Spearman's rank correlation reveals that the nucleotide compositional mutation bias as the major factors influencing the codon usage in serotonin receptor genes. The hierarchical cluster analysis suggests that gene function is another dominant factor that affects the codon usage bias, while species is a minor factor. Nucleotide base usage was reported using Goldman, Engelman, Stietz (GES) scale reveals the presence of high uracil (>45%) content at functionally important hydrophobic regions. Our in silico approach will certainly help for further investigations on critical inference on evolution, structure, function and gene expression aspects of 5-HT receptors family which are potential antipsychotic drug targets.

Gene expression profile of the cynobacterium synechocystis genome

The expression of functional proteins plays a crucial role in modern biotechnology. The free-living cynobacterium Synechocystis PCC 6803 is an interesting model organism to study oxygenic photosynthesis as well as other metabolic processes. Here we analyze a gene expression profiling methodology, RCBS (the scores of relative codon usage bias) to elucidate expression patterns of genes in the Synechocystis genome. To assess the predictive performance of the methodology, we propose a simple algorithm to calculate the threshold score to identify the highly expressed genes in a genome. Analysis of differential expression of the genes of this genome reveals that most of the genes in photosynthesis and respiration belong to the highly expressed category. The other genes with the higher predicted expression level include ribosomal proteins, translation processing factors and many hypothetical proteins. Only 9.5% genes are identified as highly expressed genes and we observe that highly expressed genes in Synechocystis genome often have strong compositional bias in terms of codon usage. An important application concerns the automatic detection of a set of impact codons and genes that are highly expressed tend to use this narrow set of preferred codons and display high codon bias .We further observe a strong correlation between RCBS and protein length indicating natural selection in favor of shorter genes to be expressed at higher level. The better correlations of RCBS with 2D electrophoresis and microarray data for heat shock proteins compared to the expression measure based on codon usage difference, E(g) and codon adaptive index, CAI indicate that the genomic expression profile available in our method can be applied in a meaningful way to study the mRNA expression patterns, which are by themselves necessary for the quantitative description of the biological states.

Genes optimized by evolution for accurate and fast translation encode in Archaea and Bacteria a broad and characteristic spectrum of protein functions

Background

In many microbial genomes, a strong preference for a small number of codons can be observed in genes whose products are needed by the cell in large quantities. This codon usage bias (CUB) improves translational accuracy and speed and is one of several factors optimizing cell growth. Whereas CUB and the overrepresentation of individual proteins have been studied in detail, it is still unclear which high-level metabolic categories are subject to translational optimization in different habitats.

Results

In a systematic study of 388 microbial species, we have identified for each genome a specific subset of genes characterized by a marked CUB, which we named the effectome. As expected, gene products related to protein synthesis are abundant in both archaeal and bacterial effectomes. In addition, enzymes contributing to energy production and gene products involved in protein folding and stabilization are overrepresented. The comparison of genomes from eleven habitats shows that the environment has only a minor effect on the composition of the effectomes. As a paradigmatic example, we detailed the effectome content of 37 bacterial genomes that are most likely exposed to strongest selective pressure towards translational optimization. These effectomes accommodate a broad range of protein functions like enzymes related to glycolysis/gluconeogenesis and the TCA cycle, ATP synthases, aminoacyl-tRNA synthetases, chaperones, proteases that degrade misfolded proteins, protectants against oxidative damage, as well as cold shock and outer membrane proteins.

Conclusions

We made clear that effectomes consist of specific subsets of the proteome being involved in several cellular functions. As expected, some functions are related to cell growth and affect speed and quality of protein synthesis. Additionally, the effectomes contain enzymes of central metabolic pathways and cellular functions sustaining microbial life under stress situations. These findings indicate that cell growth is an important but not the only factor modulating translational accuracy and speed by means of CUB.

Automated isolation of translational efficiency bias that resists the confounding effect of GC(AT)-content

Genomic sequencing projects are an abundant source of information for biological studies ranging from the molecular to the ecological in scale; however, much of the information present may yet be hidden from casual analysis. One such information domain, trends in codon usage, can provide a wealth of information about an organism's genes and their expression. Degeneracy in the genetic code allows more than one triplet codon to code for the same amino acid, and usage of these codons is often biased such that one or more of these synonymous codons are preferred. Detection of this bias is an important tool in the analysis of genomic data, particularly as a predictor of gene expressivity. Methods for identifying codon usage bias in genomic data that rely solely on genomic sequence data are susceptible to being confounded by the presence of several factors simultaneously influencing codon selection. Presented here is a new technique for removing the effects of one of the more common confounding factors, GC(AT)-content, and of visualizing the search-space for codon usage bias through the use of a solution landscape. This technique successfully isolates expressivity-related codon usage trends, using only genomic sequence information, where other techniques fail due to the presence of GC(AT)-content confounding influences.

Theoretical methods for identifying important functional genes in bacterial genomes

Some functional genes, such as essential genes, highly expressed genes and horizontally transferred genes, play important roles in the survival and pathogenicity of bacteria. This review attempts to summarize current computational methods in identifying the above functional genes from bacterial genomes, which is of significant importance in exploring the bacterial genomes.

Analyzing gene expression from relative codon usage bias in Yeast genome: a statistical significance and biological relevance

Based on the hypothesis that highly expressed genes are often characterized by strong compositional bias in terms of codon usage, there are a number of measures currently in use that quantify codon usage bias in genes, and hence provide numerical indices to predict the expression levels of genes. With the recent advent of expression measure from the score of the relative codon usage bias (RCBS), we have explicitly tested the performance of this numerical measure to predict the gene expression level and illustrate this with an analysis of Yeast genomes. In contradiction with previous other studies, we observe a weak correlations between GC content and RCBS, but a selective pressure on the codon preferences in highly expressed genes. The assertion that the expression of a given gene depends on the score of relative codon usage bias (RCBS) is supported by the data. We further observe a strong correlation between RCBS and protein length indicating natural selection in favour of shorter genes to be expressed at higher level. We also attempt a statistical analysis to assess the strength of relative codon bias in genes as a guide to their likely expression level, suggesting a decrease of the informational entropy in the highly expressed genes.

Predicting gene expression level from relative codon usage bias: an application to Escherichia coli genome

We present an expression measure of a gene, devised to predict the level of gene expression from relative codon bias (RCB). There are a number of measures currently in use that quantify codon usage in genes. Based on the hypothesis that gene expressivity and codon composition is strongly correlated, RCB has been defined to provide an intuitively meaningful measure of an extent of the codon preference in a gene. We outline a simple approach to assess the strength of RCB (RCBS) in genes as a guide to their likely expression levels and illustrate this with an analysis of Escherichia coli (E. coli) genome. Our efforts to quantitatively predict gene expression levels in E. coli met with a high level of success. Surprisingly, we observe a strong correlation between RCBS and protein length indicating natural selection in favour of the shorter genes to be expressed at higher level. The agreement of our result with high protein abundances, microarray data and radioactive data demonstrates that the genomic expression profile available in our method can be applied in a meaningful way to the study of cell physiology and also for more detailed studies of particular genes of interest.

Gene classification using codon usage and support vector machines

A novel approach for gene classification, which adopts codon usage bias as input feature vector for classification by support vector machines (SVM) is proposed. The DNA sequence is first converted to a 59-dimensional feature vector where each element corresponds to the relative synonymous usage frequency of a codon. As the input to the classifier is independent of sequence length and variance, our approach is useful when the sequences to be classified are of different lengths, a condition that homology-based methods tend to fail. The method is demonstrated by using 1,841 Human Leukocyte Antigen (HLA) sequences which are classified into two major classes: HLA-I and HLA-II; each major class is further subdivided into sub-groups of HLA-I and HLA-II molecules. Using codon usage frequencies, binary SVM achieved accuracy rate of 99.3% for HLA major class classification and multi-class SVM achieved accuracy rates of 99.73% and 98.38% for sub-class classification of HLA-I and HLA-II molecules, respectively. The results show that gene classification based on codon usage bias is consistent with the molecular structures and biological functions of HLA molecules.

Evolution of the G+C Content Frontier in the Rat Cytomegalovirus Genome

Within the 230138 bp of the rat cytomegalovirus (RCMV) genome, the G+C content changes abruptly at position 142644, constituting a G+C content frontier. To the left of this point, overall G+C content is 69.2%, and to the right it is only 47.6%. A region of extremely low G+C content (33.8%) is found in the 5 kb immediately to the right of the frontier, in which there are no predicted coding sequences. To the right of position 147501, the G+C content rises and predicted coding sequences reappear. However, these genes are much shorter (average 848 bp, 50% G+C) than those in the left two-thirds of the genome (average 1462 bp, 70% G+C). Whole genome alignment of several viruses indicates that the initial ultra-low G+C region appeared in the common ancestor of the genera Cytomegalovirus and Muromegalovirus, and that the lowering of G+C in the right third has been a subsequent process in the lineage leading to RCMV. The left two-thirds of RCMV has stop codon occurrences at 67.5% of their expected level, based on a modified Markov chain model of stop codon distribution, and the corresponding figure for the right third is 78%. Therefore, despite heavy mutation pressure, selective constraint has operated in the right third of the RCMV genome to maintain a degree of gene length unusual for such low G+C sequences.

Can RNA selection pressure distort the measurement of Ka/Ks?

Recently, an interesting question has emerged in the evolutionary interpretation of sequence substitution data as evidence of amino acid selection pressure. Specifically, the Ka/Ks metric was designed to measure selection pressure on amino acid substitutions, assuming that the synonymous substitution rate Ks reflects the neutral nucleotide substitution rate. However, there is increasing evidence for selection pressure at silent sites due to constraints of RNA splicing. Is Ka/Ks an appropriate metric for selection pressure on amino acid substitutions, in the presence of other selection pressures acting only at the RNA level (such as selection for exonic splicing enhancers)? Or can the resulting decreases in Ks from such selection pressures introduce bias into the Ka/Ks metric, so that it no longer gives an accurate measure of amino acid level selection pressure? In this review, we present both mathematical models and empirical evidence for these divergent points of view.

Effects of splitting alternative KlCYC1 3'-UTR regions on processing: metabolic consequences and biotechnological applications

To analyze the functionality of alternative 3'-UTR processing in the yeast Kluyveromyces lactis, recombinant forms of the KlCYC1 gene containing the proximal (1-713) or the distal (699-1194) 3'-UTR region (positions related to the TAA stop codon) were obtained. The cells expressing the gene with proximal 3'-UTR showed the same growth phenotype as the wild type. When the gene expressed only the distal region, a single transcript was generated and its expression was increased in late-growth phases. Cells expressing the alternative distal 3'-UTR region showed differences in their levels of cytochrome c biomass and ethanol production with respect to the wild type. The split 3'-UTR regions were also functional as separate processing units in Saccharomyces cerevisiae. The importance of our results in recombinant gene expression applications will be discussed.

Comparison of codon usage measures and their applicability in prediction of microbial gene expressivity

Background

There are a number of methods (also called: measures) currently in use that quantify codon usage in genes. These measures are often influenced by other sequence properties, such as length. This can introduce strong methodological bias into measurements; therefore we attempted to develop a method free from such dependencies. One of the common applications of codon usage analyses is to quantitatively predict gene expressivity.

Results

We compared the performance of several commonly used measures and a novel method we introduce in this paper – Measure Independent of Length and Composition (MILC). Large, randomly generated sequence sets were used to test for dependence on (i) sequence length, (ii) overall amount of codon bias and (iii) codon bias discrepancy in the sequences. A derivative of the method, named MELP (MILC-based Expression Level Predictor) can be used to quantitatively predict gene expression levels from genomic data. It was compared to other similar predictors by examining their correlation with actual, experimentally obtained mRNA or protein abundances.

Conclusion

We have established that MILC is a generally applicable measure, being resistant to changes in gene length and overall nucleotide composition, and introducing little noise into measurements. Other methods, however, may also be appropriate in certain applications. Our efforts to quantitatively predict gene expression levels in several prokaryotes and unicellular eukaryotes met with varying levels of success, depending on the experimental dataset and predictor used. Out of all methods, MELP and Rainer Merkl's GCB method had the most consistent behaviour. A 'reference set' containing known ribosomal protein genes appears to be a valid starting point for a codon usage-based expressivity prediction.

A Comprehensive Software Suite for the Analysis of cDNAs

We have developed a comprehensive software suite for bioinformatics research of cDNAs; it is aimed at rapid characterization of the features of genes and the proteins they code. Methods implemented include the detection of translation initiation and termination signals, statistical analysis of codon usage, comparative study of amino acid composition, comparative modeling of the structures of product proteins, prediction of alternative splice forms, and metabolic pathway reconstruction. The software package is freely available under the GNU General Public License at http://www.g-language.org/data/cdna/.

Characterization of a gene similar to BIK1 in the yeast Kluyveromyces lactis

In Saccharomyces cerevisiae, Bik1p is a microtubule plus-end-tracking protein that plays several roles in mitosis and ploidy. KlBik1p (from Kluyveromyces lactis) maintains the same structural-domain organization as does S. cerevisiae Bik1p. As part of its characterization, we constructed a stable klbik1 mutant which is sensitive to benomyl only at 14 degrees C and has a higher frequency of crescent-shaped nuclei than S. cerevisiae bik1 mutants. This phenotype is partially rescued by S. cerevisiae BIK1. Other phenotypes associated with bik1 are not present in the K. lactis mutant. By fusion to GFP we were able to show the functionality of the KlBik1p CAP-Gly domain and found that the fusion protein changes its cellular location during the cell cycle.

A survey of codon and amino acid frequency bias in microbial genomes focusing on translational efficiency

Unequal use of synonymous codons has been found in several prokaryotic and eukaryotic genomes. This bias has been associated with translational efficiency. The prevalence of this bias across lineages is currently unknown. Here, a new method (GCB) to measure codon usage bias is presented. It uses an iterative approach for the determination of codon scores and allows the computation of an index of codon bias suitable for interspecies comparison. A server to calculate GCB-values of individual genes as well as a list of compiled results are available at www.g21.bio.uni-goettingen.de. The method was applied to complete bacterial genomes. The relation of codon usage bias with amino acid composition and the choice of stop codons were determined and discussed.

Analysis of codon usage in beta-tubulin sequences of helminths

Codon usage bias has been shown to be correlated with gene expression levels in many organisms, including the nematode Caenorhabditis elegans. Here, the codon usage (cu) characteristics for a set of currently available beta-tubulin coding sequences of helminths were assessed by calculating several indices, including the effective codon number (Nc), the intrinsic codon deviation index (ICDI), the P2 value and the mutational response index (MRI). The P2 value gives a measure of translational pressure, which has been shown to be correlated to high gene expression levels in some organisms, but it has not yet been analysed in that respect in helminths. For all but two of the C. elegans beta-tubulin coding sequences investigated, the P2 value was the only index that indicated the presence of codon usage bias. Therefore, we propose that in general the helminth beta-tubulin sequences investigated here are not expressed at high levels. Furthermore, we calculated the correlation coefficients for the cu patterns of the helminth beta-tubulin sequences compared with those of highly expressed genes in organisms such as Escherichia coli and C. elegans. It was found that beta-tubulin cu patterns for all sequences of members of the Strongylida were significantly correlated to those for highly expressed C. elegans genes. This approach provides a new measure for comparing the adaptation of cu of a particular coding sequence with that of highly expressed genes in possible expression systems.Finally, using the cu patterns of the sequences studied, a phylogenetic tree was constructed. The topology of this tree was very much in concordance with that of a phylogeny based on small subunit ribosomal DNA sequence alignments.

HGT-DB: a database of putative horizontally transferred genes in prokaryotic complete genomes

The Horizontal Gene Transfer DataBase (HGT-DB) is a genomic database that includes statistical parameters such as G+C content, codon and amino-acid usage, as well as information about which genes deviate in these parameters for prokaryotic complete genomes. Under the hypothesis that genes from distantly related species have different nucleotide compositions, these deviated genes may have been acquired by horizontal gene transfer. The current version of the database contains 88 bacterial and archaeal complete genomes, including multiple chromosomes and strains. For each genome, the database provides statistical parameters for all the genes, as well as averages and standard deviations of G+C content, codon usage, relative synonymous codon usage and amino-acid content. It also provides information about correspondence analyses of the codon usage, plus lists of extraneous group of genes in terms of G+C content and lists of putatively acquired genes. With this information, researchers can explore the G+C content and codon usage of a gene when they find incongruities in sequence-based phylogenetic trees. A search engine that allows searches for gene names or keywords for a specific organism is also available. HGT-DB is freely accessible at http://www.fut.es/~debb/HGT.

Cluster analysis of the codon use frequency of MHC genes from different species

The relative synonymous codon use frequency of 135 MHC genes from four mammal species (Homo sapiens, Pan troglodyte, Macaca mulanta and Rattus norvegicus) is analyzed using a hierarchical cluster method. The result suggests that gene function is the dominant factor that determines codon usage bias, while species is a minor factor that determines further difference in codon usage bias for genes with similar functions. The conclusion may be useful in gene classification and gene function prediction.

The KlCYC1 gene, a downstream region for two differentially regulated transcripts

KlCYC1 encodes for cytochrome c in the yeast Kluyveromyces lactis and is transcribed in two mRNAs with different 3'-processing points. This is an uncommon transcription mechanism in yeast mRNAs. The 3' sequence encompassing the whole region that is needed to produce both mRNAs is analysed. We have determined identical processing points in K.lactis and in Saccharomyces cerevisiae cells transformed with KlCYC1; positions 698 and 1092 (with respect to the TAA) are the major polyadenylation points. This shows that the cis-elements present in the KlCYC1 3'-untranslated region (3'-UTR) direct a processing mechanism that has been conserved in yeast. In K. lactis there is a high predominance of the shorter transcript (1.14 kb) only at the initial logarithmic growth phase. Interestingly, this growth phase-dependent regulation of 3'-UTR processing is lost when the gene is expressed in S. cerevisiae.

Respirofermentative metabolism in Kluyveromyces lactis: Insights and perspectives

Yeasts do not form a homogeneous group as far as energy-yielding metabolism is concerned and the fate of pyruvate, a glycolytic intermediate, determines the type of energy metabolism. Kluyveromyces lactis has become an alternative to the traditional yeast Saccharomyces cerevisiae owing to its industrial applications as well as to studies on mitochondrial respiration. In this review we summarize the current knowdeledge about the K. lactis respirofermentative metabolism, taking into account the respiratory capacity of this yeast and the molecular mechanisms controlling its regulation, giving an up-to-date picture.

Codon indices as a predictor of gene functionality in aFrankiaoperon

The mutational response index and measurements of codon bias were determined in eight potential open reading frames in a Frankia operon that encodes genes for nitrogen fixation. The functionality of the different open reading frames is assessed in light of these results and compared with previously published results, as is the applicability of these techniques to the assessment of translational function of putative open reading frames.Key words: Frankia, codon usage, codon bias, open reading frames, mutation pressure.

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 from Saccharomyces 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 a DOS or Windows environment, but results can be saved in ASCII text format.

Codon usage and gene function are related in sequences of Arabidopsis thaliana

In this paper, the relationship between codon usage and the physiological pattern of expression of a gene is investigated while considering a dataset of 815 nuclear genes of Arabidopsis thaliana. Factorial Correspondence Analysis, a commonly used multivariate statistical approach in codon usage analysis, was used in order to analyse codon usage bias gene by gene. The analysis reveals a single major trend in codon usage among genes in Arabidopsis. At one end of the trend lie genes with a highly G/C biased codon usage. This group contains mainly photosynthetic and housekeeping genes which are known to encode the most abundant proteins of the vegetal cell. At the other extreme lie genes with a weaker A/T-biased codon usage. This group contain genes with various functions which exhibits most of the time a strong tissue-specific pattern of expression in relation, for example, to stress conditions. These observations were confirmed by the detailed analysis of codon usage in the multigene family of tubulins and appear to be general in plant species, even as distant from Arabidopsis thaliana as a monocotyledonous plant such as maize.

Isolation and characterization of the KlHEM1 gene in Kluyveromyces lactis

The KlHEM1 gene from Kluyveromyces lactis encodes a functional 5-aminolevulinate synthase (deltaALA synthase), as confirmed by complementation of a hem1 mutant Saccharomyces cerevisiae strain, homology search, and detection of a 2.3 kb transcript. The gene is highly homologous to the ScHEM1 gene, and the sequence of the promoter region contains a complex combination of putative regulatory signals. Some of them are related to phospholipid biosynthesis, glycolytic metabolism, and regulation by carbon source. Transcription of KlHEM1 increased significantly in response to limited oxygen, and only slightly with the change from repressed (glucose) to derepressed conditions (glycerol). The deltaALA synthase from K. lactis contains, in the amino-terminal region, two heme-responsive elements that are not present in the protein from Saccharomyces cerevisiae.

PICDI, a simple program for codon bias calculation

PICDI is a very simple program designed to calculate the Intrinsic Codon Deviation Index (ICDI). The program is available in Macintosh as well a PC format. Requirements for correct input of the sequences have been kept to a minimum and the analysis of sequences up to 2000 codons is very quick. The ICDI is very useful for estimation of codon bias of genes from species in which optimal codons are not known. The availability of a computer program for its calculation will increase its usefulness in the fields of Molecular Biology and Biotechnology.

Reoxidation of the NADPH produced by the pentose phosphate pathway is necessary for the utilization of glucose by Kluyveromyces lactis rag2 mutants

Kluyveromyces lactis mutants defective in the glycolytic enzyme phosphoglucose isomerase are able to grow in glucose media and to produce ethanol, but they depend on a functional respiratory chain and do not grow in glucose-antimycin media. We postulate that this is due to the necessity of reoxidizing, in the mitochondria, the NADPH produced by the pentose phosphate pathway, which may be highly active in these mutants in order to bypass the blockade in the phosphoglucose isomerase step. This oxidation would be mediated by a cytoplasmic-side mitochondrial NAD(P)H dehydrogenase that would pass the electrons to ubiquinone. Data supporting this hypothesis are provided.

DNA sequence evolution: the sounds of silence

Silent sites (positions that can undergo synonymous substitutions) in protein-coding genes can illuminate two evolutionary processes. First, despite being silent, they may be subject to natural selection. Among eukaryotes this is exemplified by yeast, where synonymous codon usage patterns are shaped by selection for particular codons that are more efficiently and/or accurately translated by the most abundant tRNAs; codon usage across the genome, and the abundance of different tRNA species, are highly co-adapted. Second, in the absence of selection, silent sites reveal underlying mutational patterns. Codon usage varies enormously among human genes, and yet silent sites do not appear to be influenced by natural selection, suggesting that mutation patterns vary among regions of the genome. At first, the yeast and human genomes were thought to reflect a dichotomy between unicellular and multicellular organisms. However, it now appears that natural selection shapes codon usage in some multicellular species (e.g. Drosophila and Caenorhabditis), and that regional variations in mutation biases occur in yeast. Silent sites (in serine codons) also provide evidence for mutational events changing adjacent nucleotides simultaneously.

Isolation and characterization of the gene encoding xylose reductase from Kluyveromyces lactis

The identification of a xylose reductase (XR)-encoding gene (XYL1) from the xylose-assimilating yeast Kluyveromyces lactis (Kl) is described. XYL1 was isolated as a highly expressed fusion clone from a 'lacZ translational fusion library. DNA sequence analysis revealed an open reading frame (ORF) of 987 bp capable of encoding a polypeptide of 329 amino acids (aa). The deduced aa sequence displays a 62% overall identity to that of XR from Pichia stipitis. Gene disruption studies indicate that XYL1 exists as a single copy in the yeast genome and is essential for growth on xylose. Northern blot analysis of the XYL1 transcript and measurement of the XR enzymatic activities show, in contrast to other known XR-encoding genes, a constitutive expression of Kl XYL1.

Regulation of cytochrome c expression in the aerobic respiratory yeast Kluyveromyces lactis

Transcriptional regulation of the KlCYC1 gene from the aerobic respiratory yeast Kluyveromyces lactis has been studied. The KlCYC1 gene produces two transcripts of different sizes, in contrast with the single transcripts found for CYC1 and CYC7 from Saccharomyces cerevisiae, and for the CYC gene from Schwanniomyces occidentalis. Both KlCYC1 transcripts respond in the same way to the regulatory signals studied here. The transcription of KlCYC1 is regulated by oxygen and this control is mediated by heme. The KlCYC1 gene is also subject to catabolite repression. Heterologous expression in S. cerevisiae mutants reveals that the factors HAP1 and HAP2 take part in the regulatory mechanism.

Codon usage and genome evolution

The rates and patterns of evolution at silent sites in codons reveal much about the basic features of molecular evolution. Recent increases in the amount of sequence data available for various species and more precise knowledge of the chromosomal locations of those sequences, coming in particular from genome projects, reveal that some features of molecular evolution vary around the genome.