Universal function-specificity of codon usage

Dynamic Landscapes of tRNA Transcriptomes and Translatomes in Diverse Mouse Tissues

Although the function of tRNAs in the translational process is well established, it remains controversial whether tRNA abundance is tightly associated with translational efficiency (TE) in mammals. Moreover, how critically the expression of tRNAs contributes to the establishment of tissue-specific proteomes in mammals has not been well addressed. Here, we measured both tRNA expression using demethylase-tRNA sequencing (DM-tRNA-seq) and TE of mRNAs using ribosome-tagging sequencing (RiboTag-seq) in the brain, heart, and testis of mice. Remarkable variation in the expression of tRNA isodecoders was observed among different tissues. When the statistical effect of isodecoder-grouping on reducing variations is considered through permutating the anticodons, we observed an expected reduction in the variation of anticodon expression across all samples, an unexpected smaller variation of anticodon usage bias, and an unexpected larger variation of tRNA isotype expression at amino acid level. Regardless of whether or not they share the same anticodons, the isodecoders encoding the same amino acids are co-expressed across different tissues. Based on the expression of tRNAs and the TE of mRNAs, we find that the tRNA adaptation index (tAI) and TE are significantly correlated in the same tissues but not between tissues; and tRNA expression and the amino acid composition of translating peptides are positively correlated in the same tissues but not between tissues. We therefore hypothesize that the tissue-specific expression of tRNAs might be due to post-transcriptional mechanisms. This study provides a resource for tRNA and translation studies, as well as novel insights into the dynamics of tRNAs and their roles in translational regulation.

Genes enriched in A/T-ending codons are co-regulated and conserved across mammals

Codon usage influences gene expression distinctly depending on the cell context. Yet, the importance of codon bias in the simultaneous turnover of specific groups of protein-coding genes remains to be investigated. Here, we find that genes enriched in A/T-ending codons are expressed more coordinately in general and across tissues and development than those enriched in G/C-ending codons. tRNA abundance measurements indicate that this coordination is linked to the expression changes of tRNA isoacceptors reading A/T-ending codons. Genes with similar codon composition are more likely to be part of the same protein complex, especially for genes with A/T-ending codons. The codon preferences of genes with A/T-ending codons are conserved among mammals and other vertebrates. We suggest that this orchestration contributes to tissue-specific and ontogenetic-specific expression, which can facilitate, for instance, timely protein complex formation.

A Dynamic rRNA Ribomethylome Drives Stemness in Acute Myeloid Leukemia

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

SIGNIFICANCE

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

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

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

Codon optimality in cancer

A key characteristic of cancer cells is their increased proliferative capacity, which requires elevated levels of protein synthesis. The process of protein synthesis involves the translation of codons within the mRNA coding sequence into a string of amino acids to form a polypeptide chain. As most amino acids are encoded by multiple codons, the nucleotide sequence of a coding region can vary dramatically without altering the polypeptide sequence of the encoded protein. Although mutations that do not alter the final amino acid sequence are often thought of as silent/synonymous, these can still have dramatic effects on protein output. Because each codon has a distinct translation elongation rate and can differentially impact mRNA stability, each codon has a different degree of 'optimality' for protein synthesis. Recent data demonstrates that the codon preference of a transcriptome matches the abundance of tRNAs within the cell and that this supply and demand between tRNAs and mRNAs varies between different cell types. The largest observed distinction is between mRNAs encoding proteins associated with proliferation or differentiation. Nevertheless, precisely how codon optimality and tRNA expression levels regulate cell fate decisions and their role in malignancy is not fully understood. This review describes the current mechanistic understanding on codon optimality, its role in malignancy and discusses the potential to target codon optimality therapeutically in the context of cancer.

Co-evolution between codon usage and protein-protein interaction in bacteria

We study the correlation between the codon usage bias of genetic sequences and the network features of protein-protein interaction (PPI) in bacterial species. We use PCA techniques in the space of codon bias indices to show that genes with similar patterns of codon usage have a significantly higher probability that their encoded proteins are functionally connected and interacting. Importantly, this signal emerges when multiple aspects of codon bias are taken into account at the same time. The present study extends our previous observations on E. coli over a wide set of 34 bacteria. These findings could allow for future investigations on the possible effects of codon bias on the topology of the PPI network, with the aim of improving existing bioinformatics methods for predicting protein interactions.

Translational efficiency across healthy and tumor tissues is proliferation-related

Different tissues express genes with particular codon usage and anticodon tRNA repertoires. However, the codon-anticodon co-adaptation in humans is not completely understood, nor is its effect on tissue-specific protein levels. Here, we first validated the accuracy of small RNA-seq for tRNA quantification across five human cell lines. We then analyzed the tRNA abundance of more than 8,000 tumor samples from TCGA, together with their paired mRNA-seq and proteomics data, to determine the Supply-to-Demand Adaptation. We thereby elucidate that the dynamic adaptation of the tRNA pool is largely related to the proliferative state across tissues. The distribution of such tRNA pools over the whole cellular translatome affects the subsequent translational efficiency, which functionally determines a condition-specific expression program both in healthy and tumor states. Furthermore, the aberrant translational efficiency of some codons in cancer, exemplified by ProCCA and GlyGGT, is associated with poor patient survival. The regulation of these tRNA profiles is partly explained by the tRNA gene copy numbers and their promoter DNA methylation.

TissueCoCoPUTs: Novel Human Tissue-Specific Codon and Codon-Pair Usage Tables Based on Differential Tissue Gene Expression

Protein expression in multicellular organisms varies widely across tissues. Codon usage in the transcriptome of each tissue is derived from genomic codon usage and the relative expression level of each gene. We created a comprehensive computational resource that houses tissue-specific codon, codon-pair, and dinucleotide usage data for 51 Homo sapiens tissues (TissueCoCoPUTs: https://hive.biochemistry.gwu.edu/review/tissue_codon), using transcriptome data from the Broad Institute Genotype-Tissue Expression (GTEx) portal. Distances between tissue-specific codon and codon-pair frequencies were used to generate a dendrogram based on the unique patterns of codon and codon-pair usage in each tissue that are clearly distinct from the genomic distribution. This novel resource may be useful in unraveling the relationship between codon usage and tRNA abundance, which could be critical in determining translation kinetics and efficiency across tissues. Areas of investigation such as biotherapeutic development, tissue-specific genetic engineering, and genetic disease prediction will greatly benefit from this resource.

Translational control plays an important role in the adaptive heat-shock response of Streptomyces coelicolor

Stress-induced adaptations require multiple levels of regulation in all organisms to repair cellular damage. In the present study we evaluated the genome-wide transcriptional and translational changes following heat stress exposure in the soil-dwelling model actinomycete bacterium, Streptomyces coelicolor. The combined analysis revealed an unprecedented level of translational control of gene expression, deduced through polysome profiling, in addition to transcriptional changes. Our data show little correlation between the transcriptome and ‘translatome’; while an obvious downward trend in genome wide transcription was observed, polysome associated transcripts following heat-shock showed an opposite upward trend. A handful of key protein players, including the major molecular chaperones and proteases were highly induced at both the transcriptional and translational level following heat-shock, a phenomenon known as ‘potentiation’. Many other transcripts encoding cold-shock proteins, ABC-transporter systems, multiple transcription factors were more highly polysome-associated following heat stress; interestingly, these protein families were not induced at the transcriptional level and therefore were not previously identified as part of the stress response. Thus, stress coping mechanisms at the level of gene expression in this bacterium go well beyond the induction of a relatively small number of molecular chaperones and proteases in order to ensure cellular survival at non-physiological temperatures.

Codon Usage in Trypanosomatids: The Bias of Expression

Translation and RNA decay, two processes in which all mRNAs are engaged, are intimately related processes. Two new studies demonstrate that, in trypanosomatids, codon usage largely shapes mRNA abundance in a translation-dependent manner. The findings indicate that mRNA decay control by codon choice is an ancient and conserved mechanism.

Hybrid, randomized and high capacity conservative mutations DNA-based steganography for large sized data

In this paper, a well secured, high capacity, preserved algorithm is proposed through integrating the cryptography and steganography concepts with the molecular biology concepts. We achieved this by first encrypting the confidential data using the DNA Playfair cipher to avoid extra information sent to the receiver and it consequently acts as a trap for an attacker. Second, it achieves a randomized steganography process by exploiting the DNA conservative mutations. The DNA conservative mutations are utilized in a way that allows a DNA base to be substituted by another base to allow carrying two bits. Consequently, a high capacity feature is obtained with no payload for the used sequence. There are three main achieved contributions in this work. First, is hiding high capacity of data within DNA by exploiting each codon to hide two bits whilst preserving the sequence properties of protein after the steganography process, which is a trade off in the field. Secondly, using the conservative mutation with all its valid biological permutations, leads to the lowest cracking probability achieved and published till now, as proven in the security analysis section. Finally, a comparison is conducted between the proposed algorithm and five recent substitution based algorithms using large sized data up to three megabytes, to prove the algorithm's scalability.

Charting the "unknown unknowns" of cancer progression

Integrated computational and experimental strategies reveal previously unknown regulatory programs underlying metastatic disease.

Codon optimality, bias and usage in translation and mRNA decay

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

Integrated analysis of individual codon contribution to protein biosynthesis reveals a new approach to improving the basis of rational gene design

Gene codon optimization may be impaired by the misinterpretation of frequency and optimality of codons. Although recent studies have revealed the effects of codon usage bias (CUB) on protein biosynthesis, an integrated perspective of the biological role of individual codons remains unknown. Unlike other previous studies, we show, through an integrated framework that attributes of codons such as frequency, optimality and positional dependency should be combined to unveil individual codon contribution for protein biosynthesis. We designed a codon quantification method for assessing CUB as a function of position within genes with a novel constraint: the relativity of position-dependent codon usage shaped by coding sequence length. Thus, we propose a new way of identifying the enrichment, depletion and non-uniform positional distribution of codons in different regions of yeast genes. We clustered codons that shared attributes of frequency and optimality. The cluster of non-optimal codons with rare occurrence displayed two remarkable characteristics: higher codon decoding time than frequent-non-optimal cluster and enrichment at the 5'-end region, where optimal codons with the highest frequency are depleted. Interestingly, frequent codons with non-optimal adaptation to tRNAs are uniformly distributed in the Saccharomyces cerevisiae genes, suggesting their determinant role as a speed regulator in protein elongation.

Analysis of codon usage patterns in Morus notabilis based on genome and transcriptome data

Codons play important roles in regulating gene expression levels and mRNA half-lives. However, codon usage and related studies in multicellular organisms still lag far behind those in unicellular organisms. In this study, we describe for the first time genome-wide patterns of codon bias in Morus notabilis (mulberry tree), and analyze genome-wide codon usage in 12 other species within the order Rosales. The codon usage of M. notabilis was affected by nucleotide composition, mutation pressure, nature selection, and gene expression level. Translational selection optimal codons were identified and highly expressed genes of M. notabilis tended to use the optimal codons. Genes with higher expression levels have shorter coding region and lower amino acid complexity. Housekeeping genes showed stronger translational selection, which, notably, was not caused by the large differences between the expression level of housekeeping genes and other genes.

Selective forces and mutational biases drive stop codon usage in the human genome: a comparison with sense codon usage

BACKGROUND

The three stop codons UAA, UAG, and UGA signal the termination of mRNA translation. As a result of a mechanism that is not adequately understood, they are normally used with unequal frequencies.

RESULTS

In this work, we showed that selective forces and mutational biases drive stop codon usage in the human genome. We found that, in respect to sense codons, stop codon usage was affected by stronger selective forces but was less influenced by neutral mutational biases. UGA is the most frequent termination codon in human genome. However, UAA was the preferred stop codon in genes with high breadth of expression, high level of expression, AT-rich coding sequences, housekeeping functions, and in gene ontology categories with the largest deviation from expected stop codon usage. Selective forces associated with the breadth and the level of expression favoured AT-rich sequences in the mRNA region including the stop site and its proximal 3'-UTR, but acted with scarce effects on sense codons, generating two regions, upstream and downstream of the stop codon, with strongly different base composition. By favouring low levels of GC-content, selection promoted labile local secondary structures at the stop site and its proximal 3'-UTR. The compositional and structural context favoured by selection was surprisingly emphasized in the class of ribosomal proteins and was consistent with sequence elements that increase the efficiency of translational termination. Stop codons were also heterogeneously distributed among chromosomes by a mechanism that was strongly correlated with the GC-content of coding sequences.

CONCLUSIONS

In human genome, the nucleotide composition and the thermodynamic stability of stop codon site and its proximal 3'-UTR are correlated with the GC-content of coding sequences and with the breadth and the level of gene expression. In highly expressed genes stop codon usage is compositionally and structurally consistent with highly efficient translation termination signals.

New insights into the interplay between codon bias determinants in plants

Codon bias is the non-random use of synonymous codons, a phenomenon that has been observed in species as diverse as bacteria, plants and mammals. The preferential use of particular synonymous codons may reflect neutral mechanisms (e.g. mutational bias, G|C-biased gene conversion, genetic drift) and/or selection for mRNA stability, translational efficiency and accuracy. The extent to which these different factors influence codon usage is unknown, so we dissected the contribution of mutational bias and selection towards codon bias in genes from 15 eudicots, 4 monocots and 2 mosses. We analysed the frequency of mononucleotides, dinucleotides and trinucleotides and investigated whether the compositional genomic background could account for the observed codon usage profiles. Neutral forces such as mutational pressure and G|C-biased gene conversion appeared to underlie most of the observed codon bias, although there was also evidence for the selection of optimal translational efficiency and mRNA folding. Our data confirmed the compositional differences between monocots and dicots, with the former featuring in general a lower background compositional bias but a higher overall codon bias.

The Code of Silence: Widespread Associations Between Synonymous Codon Biases and Gene Function

Some mutations in gene coding regions exchange one synonymous codon for another, and thus do not alter the amino acid sequence of the encoded protein. Even though they are often called 'silent,' these mutations may exhibit a plethora of effects on the living cell. Therefore, they are often selected during evolution, causing synonymous codon usage biases in genomes. Comparative analyses of bacterial, archaeal, fungal, and human cancer genomes have found many links between a gene's biological role and the accrual of synonymous mutations during evolution. In particular, highly expressed genes in certain functional categories are enriched with optimal codons, which are decoded by the abundant tRNAs, thus enhancing the speed and accuracy of the translating ribosome. The set of genes exhibiting codon adaptation differs between genomes, and these differences show robust associations to organismal phenotypes. In addition to selection for translation efficiency, other distinct codon bias patterns have been found in: amino acid starvation genes, cyclically expressed genes, tissue-specific genes in animals and plants, oxidative stress response genes, cellular differentiation genes, and oncogenes. In addition, genomes of organisms harboring tRNA modifications exhibit particular codon preferences. The evolutionary trace of codon bias patterns across orthologous genes may be examined to learn about a gene's relevance to various phenotypes, or, more generally, its function in the cell.

Protein-protein interaction prediction by combined analysis of genomic and conservation information

Protein-protein interactions (PPIs) are highly important because of their main role in cellular processes and biochemical pathways; therefore, PPI can be very useful in the prediction of protein functions. Experimental techniques of PPI detection have certain drawbacks; hence computational methods can be used to complement wet lab techniques. Such methods can be applied to PPI prediction as well as validation of experimental results. Computational algorithms can lead to many false PPI predictions, which in turn result in non-adequate performance. We have developed a novel method based on combined analysis, entitled PPIccc. Three different descriptors for PPIccc included gene co-expression values, codon usage similarity and conservation of surface residues between protein products of a gene pair, which combined to predict PPI. Validation of results based on Human Protein Reference Database (HPRD) indicated improvement of performance in our proposed method. The results also revealed that conservation of surface residues between proteins in combination with codon usage similarity of their related genes increase the performance of PPI prediction. This means that codon usage similarity and surface residues between proteins (only sequence-based features) can predict PPIs as good as PPIccc.

Trade-offs between tRNA abundance and mRNA secondary structure support smoothing of translation elongation rate

Translation of protein from mRNA is a complex multi-step process that occurs at a non-uniform rate. Variability in ribosome speed along an mRNA enables refinement of the proteome and plays a critical role in protein biogenesis. Detailed single protein studies have found both tRNA abundance and mRNA secondary structure as key modulators of translation elongation rate, but recent genome-wide ribosome profiling experiments have not observed significant influence of either on translation efficiency. Here we provide evidence that this results from an inherent trade-off between these factors. We find codons pairing to high-abundance tRNAs are preferentially used in regions of high secondary structure content, while codons read by significantly less abundant tRNAs are located in lowly structured regions. By considering long stretches of high and low mRNA secondary structure in Saccharomyces cerevisiae and Escherichia coli and comparing them to randomized-gene models and experimental expression data, we were able to distinguish clear selective pressures and increased protein expression for specific codon choices. The trade-off between secondary structure and tRNA-concentration based codon choice allows for compensation of their independent effects on translation, helping to smooth overall translational speed and reducing the chance of potentially detrimental points of excessively slow or fast ribosome movement.

Codon usage and protein sequence pattern dependency in different organisms: A Bioinformatics approach

Although it is known that synonymous codons are not chosen randomly, the role of the codon usage in gene regulation is not clearly understood, yet. Researchers have investigated the relation between the codon usage and various properties, such as gene regulation, translation rate, translation efficiency, mRNA stability, splicing, and protein domains. Recently, a universal codon usage based mechanism for gene regulation is proposed. We studied the role of protein sequence patterns on the codons usage by related genes. Considering a subsequence of a protein that matches to a pattern or motif, we showed that, parts of the genes, which are translated to this subsequence, use specific ratios of synonymous codons. Also, we built a multinomial logistic regression statistical model for codon usage, which considers the effect of patterns on codon usage. This model justifies the observed codon usage preference better than the classic organism dependent codon usage. Our results showed that the codon usage plays a role in controlling protein levels, for genes that participate in a specific biological function. This is the first time that this phenomenon is reported.

LocFuse: human protein-protein interaction prediction via classifier fusion using protein localization information

Protein-protein interaction (PPI) detection is one of the central goals of functional genomics and systems biology. Knowledge about the nature of PPIs can help fill the widening gap between sequence information and functional annotations. Although experimental methods have produced valuable PPI data, they also suffer from significant limitations. Computational PPI prediction methods have attracted tremendous attentions. Despite considerable efforts, PPI prediction is still in its infancy in complex multicellular organisms such as humans. Here, we propose a novel ensemble learning method, LocFuse, which is useful in human PPI prediction. This method uses eight different genomic and proteomic features along with four types of different classifiers. The prediction performance of this classifier selection method was found to be considerably better than methods employed hitherto. This confirms the complex nature of the PPI prediction problem and also the necessity of using biological information for classifier fusion. The LocFuse is available at: http://lbb.ut.ac.ir/Download/LBBsoft/LocFuse.

BIOLOGICAL SIGNIFICANCE

The results revealed that if we divide proteome space according to the cellular localization of proteins, then the utility of some classifiers in PPI prediction can be improved. Therefore, to predict the interaction for any given protein pair, we can select the most accurate classifier with regard to the cellular localization information. Based on the results, we can say that the importance of different features for PPI prediction varies between differently localized proteins; however in general, our novel features, which were extracted from position-specific scoring matrices (PSSMs), are the most important ones and the Random Forest (RF) classifier performs best in most cases. LocFuse was developed with a user-friendly graphic interface and it is freely available for Linux, Mac OSX and MS Windows operating systems.

Refining the balance of attenuation and immunogenicity of respiratory syncytial virus by targeted codon deoptimization of virulence genes

Respiratory syncytial virus (RSV) is the most important pathogen for lower respiratory tract illness in children for which there is no licensed vaccine. Live-attenuated RSV vaccines are the most clinically advanced in children, but achieving an optimal balance of attenuation and immunogenicity is challenging. One way to potentially retain or enhance immunogenicity of attenuated virus is to mutate virulence genes that suppress host immune responses. The NS1 and NS2 virulence genes of the RSV A2 strain were codon deoptimized according to either human or virus codon usage bias, and the resulting recombinant viruses (dNSh and dNSv, respectively) were rescued by reverse genetics. RSV dNSh exhibited the desired phenotype of reduced NS1 and NS2 expression. RSV dNSh was attenuated in BEAS-2B and primary differentiated airway epithelial cells but not in HEp-2 or Vero cells. In BALB/c mice, RSV dNSh exhibited a lower viral load than did A2, and yet it induced slightly higher levels of RSV-neutralizing antibodies than did A2. RSV A2 and RSV dNSh induced equivalent protection against challenge strains A/1997/12-35 and A2-line19F. RSV dNSh caused less STAT2 degradation and less NF-κB activation than did A2 in vitro. Serial passage of RSV dNSh in BEAS-2B cells did not result in mutations in the deoptimized sequences. Taken together, RSV dNSh was moderately attenuated, more immunogenic, and equally protective compared to wild-type RSV and genetically stable.

Respiratory syncytial virus (RSV) is the leading cause of infant viral death in the United States and worldwide, and no vaccine is available. Live-attenuated RSV vaccines are the most studied in children but have suffered from genetic instability and low immunogenicity. In order to address both obstacles, we selectively changed the codon usage of the RSV nonstructural (NS) virulence genes NS1 and NS2 to the least-used codons in the human genome (deoptimization). Compared to parental RSV, the codon-deoptimized NS1/NS2 RSV was attenuated in vitro and in mice but induced higher levels of neutralizing antibodies and equivalent protection against challenge. We identified a new attenuating module that retains immunogenicity and is genetically stable, achieved through specific targeting of nonessential virulence genes by codon usage deoptimization.

Translational selection in human: more pronounced in housekeeping genes

BACKGROUND

Translational selection is a ubiquitous and significant mechanism to regulate protein expression in prokaryotes and unicellular eukaryotes. Recent evidence has shown that translational selection is weakly operative in highly expressed genes in human and other vertebrates. However, it remains unclear whether translational selection acts differentially on human genes depending on their expression patterns.

RESULTS

Here we report that human housekeeping (HK) genes that are strictly defined as genes that are expressed ubiquitously and consistently in most or all tissues, are under stronger translational selection.

CONCLUSIONS

These observations clearly show that translational selection is also closely associated with expression pattern. Our results suggest that human HK genes are more efficiently and/or accurately translated into proteins, which will inevitably open up a new understanding of HK genes and the regulation of gene expression.

REVIEWERS

This article was reviewed by Yuan Yuan, Baylor College of Medicine; Han Liang, University of Texas MD Anderson Cancer Center (nominated by Dr Laura Landweber) Eugene Koonin, NCBI, NLM, NIH, United States of America Sandor Pongor, International Centre for Genetic Engineering and biotechnology (ICGEB), Italy.

Bicluster pattern of codon context usages between flavivirus and vector mosquito Aedes aegypti: relevance to infection and transcriptional response of mosquito genes

The mosquito Aedes aegypti is the primary vector of dengue virus (DENV) infection in most of the subtropical and tropical countries. Besides DENV, yellow fever virus (YFV) is also transmitted by A. aegypti. Susceptibility of A. aegypti to West Nile virus (WNV) has also been confirmed. Although studies have indicated correlation of codon bias between flaviviridae and their animal/insect hosts, it is not clear if codon sequences have any relation to susceptibility of A. aegypti to DENV, YFV and WNV. In the current study, usages of codon context sequences (codon pairs for neighboring amino acids) of the vector (A. aegypti) genome as well as the flaviviral genomes are investigated. We used bioinformatics methods to quantify codon context bias in a genome-wide manner of A. aegypti as well as DENV, WNV and YFV sequences. Mutual information statistics was applied to perform bicluster analysis of codon context bias between vector and flaviviral sequences. Functional relevance of the bicluster pattern was inferred from published microarray data. Our study shows that codon context bias of DENV, WNV and YFV sequences varies in a bicluster manner with that of specific sets of genes of A. aegypti. Many of these mosquito genes are known to be differentially expressed in response to flaviviral infection suggesting that codon context sequences of A. aegypti and the flaviviruses may play a role in the susceptible interaction between flaviviruses and this mosquito. The bias in usages of codon context sequences likely has a functional association with susceptibility of A. aegypti to flaviviral infection. The results from this study will allow us to conduct hypothesis-driven tests to examine the role of codon context bias in evolution of vector-virus interactions at the molecular level.

A comparative analysis of synonymous codon usage bias pattern in human albumin superfamily

Synonymous codon usage bias is an inevitable phenomenon in organismic taxa across the three domains of life. Though the frequency of codon usage is not equal across species and within genome in the same species, the phenomenon is non random and is tissue-specific. Several factors such as GC content, nucleotide distribution, protein hydropathy, protein secondary structure, and translational selection are reported to contribute to codon usage preference. The synonymous codon usage patterns can be helpful in revealing the expression pattern of genes as well as the evolutionary relationship between the sequences. In this study, synonymous codon usage bias patterns were determined for the evolutionarily close proteins of albumin superfamily, namely, albumin, α-fetoprotein, afamin, and vitamin D-binding protein. Our study demonstrated that the genes of the four albumin superfamily members have low GC content and high values of effective number of codons (ENC) suggesting high expressivity of these genes and less bias in codon usage preferences. This study also provided evidence that the albumin superfamily members are not subjected to mutational selection pressure.

Dependency of codon usage on protein sequence patterns: a statistical study

BACKGROUND

Codon degeneracy and codon usage by organisms is an interesting and challenging problem. Researchers demonstrated the relation between codon usage and various functions or properties of genes and proteins, such as gene regulation, translation rate, translation efficiency, mRNA stability, splicing, and protein domains. Researchers usually represent segments of proteins responsible for specific functions or structures in a family of proteins as sequence patterns or motifs. We asked the question if organisms use the same codons in pattern segments as compared to the rest of the sequence.

METHODS

We used the likelihood ratio test, Pearson's chi-squared test, and mutual information to compare these two codon usages.

RESULTS

We showed that codon usage, in segments of genes that code for a given pattern or motif in a group of proteins, varied from the rest of the gene. The codon usage in these segments was not random. Amino acids with larger number of codons used more specific codon ratios in these segments. We studied the number of amino acids in the pattern (pattern length). As patterns got longer, there was a slight decrease in the fraction of patterns with significant different codon usage in the pattern region as compared to codon usage in the gene region. We defined a measure of specificity of protein patterns, and studied its relation to the codon usage. The difference in the codon usage between pattern region and gene region, was less for the patterns with higher specificity.

CONCLUSIONS

We provided a hypothesis that there are segments on genes that affect the codon usage and thus influence protein translation speed, and these regions are the regions that code protein pattern regions.

ATTED-II in 2014: evaluation of gene coexpression in agriculturally important plants

ATTED-II (http://atted.jp) is a database of coexpressed genes that was originally developed to identify functionally related genes in Arabidopsis and rice. Herein, we describe an updated version of ATTED-II, which expands this resource to include additional agriculturally important plants. To improve the quality of the coexpression data for Arabidopsis and rice, we included more gene expression data from microarray and RNA sequencing studies. The RNA sequencing-based coexpression data now cover 94% of the Arabidopsis protein-encoding genes, representing a substantial increase from previously available microarray-based coexpression data (76% coverage). We also generated coexpression data for four dicots (soybean, poplar, grape and alfalfa) and one monocot (maize). As both the quantity and quality of expression data for the non-model species are generally poorer than for the model species, we verified coexpression data associated with these new species using multiple methods. First, the overall performance of the coexpression data was evaluated using gene ontology annotations and the coincidence of a genomic feature. Secondly, the reliability of each guide gene was determined by comparing coexpressed gene lists between platforms. With the expanded and newly evaluated coexpression data, ATTED-II represents an important resource for identifying functionally related genes in agriculturally important plants.

Translational sensitivity of the Escherichia coli genome to fluctuating tRNA availability

The synthesis of protein from messenger RNA during translation is a highly dynamic process that plays a key role in controlling the efficiency and fidelity of genome-wide protein expression. The availability of aminoacylated transfer RNA (tRNA) is a major factor influencing the speed of ribosomal movement, which depending on codon choices, varies considerably along a transcript. Furthermore, it has been shown experimentally that tRNA availability can vary significantly under different growth and stress conditions, offering the cell a way to adapt translational dynamics across the genome. Existing models of translation have neglected fluctuations of tRNA pools, instead assuming fixed tRNA availabilities over time. This has lead to an incomplete understanding of this process. Here, we show for the entire Escherichia coli genome how and to what extent translational speed profiles, which capture local aspects of translational elongation, respond to measured shifts in tRNA availability. We find that translational profiles across the genome are affected to differing degrees, with genes that are essential or related to fundamental processes such as translation, being more robust than those linked to regulation. Furthermore, we reveal how fluctuating tRNA availability influences profiles of specific sequences known to play a significant role in translational control of gene expression.

Sounds of silence: synonymous nucleotides as a key to biological regulation and complexity

Messenger RNA is a key component of an intricate regulatory network of its own. It accommodates numerous nucleotide signals that overlap protein coding sequences and are responsible for multiple levels of regulation and generation of biological complexity. A wealth of structural and regulatory information, which mRNA carries in addition to the encoded amino acid sequence, raises the question of how these signals and overlapping codes are delineated along non-synonymous and synonymous positions in protein coding regions, especially in eukaryotes. Silent or synonymous codon positions, which do not determine amino acid sequences of the encoded proteins, define mRNA secondary structure and stability and affect the rate of translation, folding and post-translational modifications of nascent polypeptides. The RNA level selection is acting on synonymous sites in both prokaryotes and eukaryotes and is more common than previously thought. Selection pressure on the coding gene regions follows three-nucleotide periodic pattern of nucleotide base-pairing in mRNA, which is imposed by the genetic code. Synonymous positions of the coding regions have a higher level of hybridization potential relative to non-synonymous positions, and are multifunctional in their regulatory and structural roles. Recent experimental evidence and analysis of mRNA structure and interspecies conservation suggest that there is an evolutionary tradeoff between selective pressure acting at the RNA and protein levels. Here we provide a comprehensive overview of the studies that define the role of silent positions in regulating RNA structure and processing that exert downstream effects on proteins and their functions.

Characterization of synonymous codon usage bias in the pseudorabies virus US1 gene

In the present study, we examined the codon usage bias between pseudorabies virus (PRV) US1 gene and the US1-like genes of 20 reference alphaherpesviruses. Comparative analysis showed noticeable disparities of the synonymous codon usage bias in the 21 alphaherpesviruses, indicated by codon adaptation index, effective number of codons (ENc) and GC3s value. The codon usage pattern of PRV US1 gene was phylogenetically conserved and similar to that of the US1-like genes of the genus Varicellovirus of alphaherpesvirus, with a strong bias towards the codons with C and G at the third codon position. Cluster analysis of codon usage pattern of PRV US1 gene with its reference alphaherpesviruses demonstrated that the codon usage bias of US1-like genes of 21 alphaherpesviruses had a very close relation with their gene functions. ENc-plot revealed that the genetic heterogeneity in PRV US1 gene and the 20 reference alphaherpesviruses was constrained by G+C content, as well as the gene length. In addition, comparison of codon preferences in the US1 gene of PRV with those of E. coli, yeast and human revealed that there were 50 codons showing distinct usage differences between PRV and yeast, 49 between PRV and human, but 48 between PRV and E. coli. Although there were slightly fewer differences in codon usages between E.coli and PRV, the difference is unlikely to be statistically significant, and experimental studies are necessary to establish the most suitable expression system for PRV US1. In conclusion, these results may improve our understanding of the evolution, pathogenesis and functional studies of PRV, as well as contributing to the area of herpesvirus research or even studies with other viruses.

β-tubulin paralogue tubC is frequently misidentified as the benA gene in Aspergillus section Nigri taxonomy: primer specificity testing and taxonomic consequences

β-tubulin (benA, tub-2) and calmodulin (caM) are crucial genes in the taxonomy of Aspergillus section Nigri. Widely used β-tubulin primers are not specific for the benA gene for some taxa and preferentially amplify the tubC paralogue. Sequences of the tubC paralogue are widely combined with benA sequences in recent taxonomical works as well as other works, resulting in incongruent trees. In this study we newly provide benA sequences for several ex-type strains, which were characterised using the tubC gene only. We designed a highly specific forward primer to benA designated Ben2f for use in Aspergillus section Nigri, and tested specificity of numerous primer combinations to β-tubulin paralogs. The primer pairs with the highest specificity to the benA gene and functional across species in section Nigri includes Ben2f/Bt2b, Ben2f/T22 and T10/T22. We also provide tools based on codon usage bias analysis that reliably distinguish both paralogues. Exon/intron arrangement is the next distinctive characteristic, although this tool is not valid outside section Nigri. The species identity of taxa from the A. aculeatus clade used in previous molecular studies was revised using combined molecular data (ITS, benA, caM). These data together with two different PCR-fingerprinting methods indicated that A. japonicus should be treated as a synonym of A. violaceofuscus. Similarly, A. fijiensis is reduced to synonymy with A. brunneoviolaceus.

The grapevine expression atlas reveals a deep transcriptome shift driving the entire plant into a maturation program

We developed a genome-wide transcriptomic atlas of grapevine (Vitis vinifera) based on 54 samples representing green and woody tissues and organs at different developmental stages as well as specialized tissues such as pollen and senescent leaves. Together, these samples expressed ∼91% of the predicted grapevine genes. Pollen and senescent leaves had unique transcriptomes reflecting their specialized functions and physiological status. However, microarray and RNA-seq analysis grouped all the other samples into two major classes based on maturity rather than organ identity, namely, the vegetative/green and mature/woody categories. This division represents a fundamental transcriptomic reprogramming during the maturation process and was highlighted by three statistical approaches identifying the transcriptional relationships among samples (correlation analysis), putative biomarkers (O2PLS-DA approach), and sets of strongly and consistently expressed genes that define groups (topics) of similar samples (biclustering analysis). Gene coexpression analysis indicated that the mature/woody developmental program results from the reiterative coactivation of pathways that are largely inactive in vegetative/green tissues, often involving the coregulation of clusters of neighboring genes and global regulation based on codon preference. This global transcriptomic reprogramming during maturation has not been observed in herbaceous annual species and may be a defining characteristic of perennial woody plants.

The relation of codon bias to tissue-specific gene expression in Arabidopsis thaliana

The codon composition of coding sequences plays an important role in the regulation of gene expression. Herein, we report systematic differences in the usage of synonymous codons among Arabidopsis thaliana genes that are expressed specifically in distinct tissues. Although we observed that both regionally and transcriptionally associated mutational biases were associated significantly with codon bias, they could not explain the observed differences fully. Similarly, given that transcript abundances did not account for the differences in codon usage, it is unlikely that selection for translational efficiency can account exclusively for the observed codon bias. Thus, we considered the possible evolution of codon bias as an adaptive response to the different abundances of tRNAs in different tissues. Our analysis demonstrated that in some cases, codon usage in genes that were expressed in a broad range of tissues was influenced primarily by the tissue in which the gene was expressed maximally. On the basis of this finding we propose that genes that are expressed in certain tissues might show a tissue-specific compositional signature in relation to codon usage. These findings might have implications for the design of transgenes in relation to optimizing their expression.

Bioinformatic study of the relationship between protein regulation and sequence properties

Although protein expression and regulation have been intensively studied, a complete picture of its mechanisms is still to be drawn. Analysis of high-throughput quantitative proteomics data provides a way to better understand protein regulation. Here, we introduce a bioinformatic analysis method to correlate protein regulation with individual amino acid patterns. We compare the amino acid composition between groups of regulated and unregulated proteins and investigate the correlation between codon usage patterns and protein regulation levels in two Sulfolobus species in "biofilm vs planktonic" experiments. The identified amino acids can then be associated with the regulation of specific gene functions. Strikingly, our analysis shows that functional categories of regulated proteins with similar composition and codon usage pattern of specific amino acids behave similarly. This finding can contribute to a better understanding of protein and gene expression regulation and could find applications in gene optimisation.

Can simple codon pair usage predict protein-protein interaction?

Deciphering functional interactions between proteins is one of the great challenges in biology. Sequence-based homology-free encoding schemes have been increasingly applied to develop promising protein-protein interaction (PPI) predictors by means of statistical or machine learning methods. Here we analyze the relationship between codon pair usage and PPIs in yeast. We show that codon pair usage of interacting protein pairs differs significantly from randomly expected. This motivates the development of a novel approach for predicting PPIs, with codon pair frequency difference as input to a Support Vector Machine predictor, termed as CCPPI. 10-fold cross-validation tests based on yeast PPI datasets with balanced positive-to-negative ratios indicate that CCPPI performs better than other sequence-based encoding schemes. Moreover, it ranks the best when tested on an unbalanced large-scale dataset. Although CCPPI is subjected to high false positive rates like many PPI predictors, statistical analyses of the predicted true positives confirm that the success of CCPPI is partly ascribed to its capability to capture proteomic co-expression and functional similarities between interacting protein pairs. Our findings suggest that codon pairs of interacting protein pairs evolve in a coordinated manner and consequently they provide additional information beyond amino acids-based encoding schemes. CCPPI has been made freely available at: http://protein.cau.edu.cn/ccppi.

Codon usage variability determines the correlation between proteome and transcriptome fold changes

Background

The availability of high throughput experimental methods has made possible to observe the relationships between proteome and transcirptome. The protein abundances show a positive but weak correlation with the concentrations of their cognate mRNAs. This weak correlation implies that there are other crucial effects involved in the regulation of protein translation, different from the sole availability of mRNA. It is well known that ribosome and tRNA concentrations are sources of variation in protein levels. Thus, by using integrated analysis of omics data, genomic information, transcriptome and proteome, we aim to unravel important variables affecting translation.

Results

We identified how much of the variability in the correlation between protein and mRNA concentrations can be attributed to the gene codon frequencies. We propose the hypothesis that the influence of codon frequency is due to the competition of cognate and near-cognate tRNA binding; which in turn is a function of the tRNA concentrations. Transcriptome and proteome data were combined in two analytical steps; first, we used Self-Organizing Maps (SOM) to identify similarities among genes, based on their codon frequencies, grouping them into different clusters; and second, we calculated the variance in the protein mRNA correlation in the sampled genes from each cluster. This procedure is justified within a mathematical framework.

Conclusions

With the proposed method we observed that in all the six studied cases most of the variability in the relation protein-transcript could be explained by the variation in codon composition.

Silent mutations in sight: co-variations in tRNA abundance as a key to unravel consequences of silent mutations

Mutations that alter the amino acid sequence are known to potentially exert deleterious effects on protein function, whereas substitutions of nucleotides without amino acid change are assumed to be neutral for the protein's functionality. However, cumulative evidence suggests that synonymous substitutions might also induce phenotypic variability by affecting splicing accuracy, translation fidelity, and conformation and function of proteins. tRNA isoacceptors mediate the translation of codons to amino acids, and asymmetric tRNA abundance causes variations in the rate of translation of each single triplet. Consequently, the effect of a silent point mutation in the coding region could be significant due to differential abundances of the cognate tRNA(s), emphasizing the importance of precise assessment of tRNA composition. Here, we provide an overview of the methods used to quantitatively determine the concentrations of tRNA species and discuss synonymous mutations in the context of tRNA composition of the cell, thus providing a new twist on the detrimental impact of the silent mutations.

Synonymous codon usage influences the local protein structure observed

Translation of mRNA into protein is a unidirectional information flow process. Analysing the input (mRNA) and output (protein) of translation, we find that local protein structure information is encoded in the mRNA nucleotide sequence. The Coding Sequence and Structure (CSandS) database developed in this work provides a detailed mapping between over 4000 solved protein structures and their mRNA. CSandS facilitates a comprehensive analysis of codon usage over many organisms. In assigning translation speed, we find that relative codon usage is less informative than tRNA concentration. For all speed measures, no evidence was found that domain boundaries are enriched with slow codons. In fact, genes seemingly avoid slow codons around structurally defined domain boundaries. Translation speed, however, does decrease at the transition into secondary structure. Codons are identified that have structural preferences significantly different from the amino acid they encode. However, each organism has its own set of ‘significant codons’. Our results support the premise that codons encode more information than merely amino acids and give insight into the role of translation in protein folding.