Codon Bias In Genes Research Articles

Comprehensive Identification and Analyses of the GRF Gene Family in the Whole-Genome of Four Juglandaceae Species.

The GRF gene family plays an important role in plant growth and development as regulators involved in plant hormone signaling and metabolism. However, the Juglandaceae GRF gene family remains to be studied. Here, we identified 15, 15, 19, and 20 GRF genes in J. regia, C. illinoinensis, J. sigillata, and J. mandshurica, respectively. The phylogeny shows that the Juglandaceae family GRF is divided into two subfamilies, the ε-group and the non-ε-group, and that selection pressure analysis did not detect amino acid loci subject to positive selection pressure. In addition, we found that the duplications of the Juglandaceae family GRF genes were all segmental duplication events, and a total of 79 orthologous gene pairs and one paralogous homologous gene pair were identified in four Juglandaceae families. The Ka/KS ratios between these homologous gene pairs were further analyzed, and the Ka/KS values were all less than 1, indicating that purifying selection plays an important role in the evolution of the Juglandaceae family GRF genes. The codon bias of genes in the GRF family of Juglandaceae species is weak, and is affected by both natural selection pressure and base mutation, and translation selection plays a dominant role in the mutation pressure in codon usage. Finally, expression analysis showed that GRF genes play important roles in pecan embryo development and walnut male and female flower bud development, but with different expression patterns. In conclusion, this study will serve as a rich genetic resource for exploring the molecular mechanisms of flower bud differentiation and embryo development in Juglandaceae. In addition, this is the first study to report the GRF gene family in the Juglandaceae family; therefore, our study will provide guidance for future comparative and functional genomic studies of the GRF gene family in the Juglandaceae specie.

Leucine encoding codon TTG shows an inverse relationship with GC content in genes involved in neurodegeneration with iron accumulation.

We determined various forces involved in shaping codon usage of the genes linked to brain iron accumulation and infantile neuroaxonal dystrophy. The analysis paved the way for determining the forces responsible for composition, expression level, physical properties and codon bias of a gene. An interesting observation related to composition was that, on all the three codon positions, any two of the four nucleotides had similar compositions. CpG, TpA, and GpT dinucleotides were underrepresented with the overrepresentation of TpG dinucleotide. CpG and TpA containing codons ATA, CTA, TCG, and GCG were underrepresented, while TpG dinucleotide containing codon CTG was overrepresented, indicative of compositional constraints importance. GC ending codons were favored when the genome is GC rich, except leucine encoding codon TTG, which exhibits an inverse relationship with GC content. Nucleotide disproportions are found associated with the physical properties of proteins. The values of CAI and ENc are suggestive of low codon bias in genes. Considering the results of neutrality analysis, parity analysis, underrepresentation of TpA and CpG codons, and over-representation of TpG codons, the correlation between the compositional constraints and skew relationships with protein properties suggested the role of all the three selectional, mutational and compositional forces in shaping codon usage with the dominance of selectional pressure.

Codon bias analyses on thyroid carcinoma genes.

Thyroid carcinoma is one of the most common cancers in the world. Although the genetics of thyroid carcinoma was intensively studied, new mechanisms could be involved in its development as the codon bias. In this paper, we studied the codon bias of thyroid-cancer genes, considering not only the sequences but also the synonymous mutations. Different measures and statistical analyses were employed to characterize the thyroid-cancer genes. We considered classical measures as RSCU and ENC, the compositional and protein characteristics, but also the codon bias landscape via the %MinMax algorithm. The compositional analyses highlighted two groups of thyroid cancer genes according to the GC% and GC3% content. The ENC did not show a clear codon bias in the genes. Differently, the RSCU analyses showed interesting codons that could play an important role in the development of thyroid cancer as the codon Ser-tcG. Furthermore, interesting synonymous mutations were detected that could affect the codon bias. The codon bias landscape detected genes enriched in rare codons as AKAP9 and KTN1. A cluster analysis based on %MinMax classified the thyroid cancer genes in four different groups according to the distribution of rare/frequent codons in the sequence. This is the first study that analyzed the codon bias in thyroid cancer genes based also on synonymous mutations. This study provided different hints that should be further investigated by wet-lab validation and that it could open new scenarios in the understanding the molecular mechanisms involved in thyroid cancer development based on codon bias.

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.

Eukaryotic Evolutionary Transitions Are Associated with Extreme Codon Bias in Functionally-Related Proteins

Codon bias in the genome of an organism influences its phenome by changing the speed and efficiency of mRNA translation and hence protein abundance. We hypothesized that differences in codon bias, either between-species differences in orthologous genes, or within-species differences between genes, may play an evolutionary role. To explore this hypothesis, we compared the genome-wide codon bias in six species that occupy vital positions in the Eukaryotic Tree of Life. We acquired the entire protein coding sequences for these organisms, computed the codon bias for all genes in each organism and explored the output for relationships between codon bias and protein function, both within- and between-lineages. We discovered five notable coordinated patterns, with extreme codon bias most pronounced in traits considered highly characteristic of a given lineage. Firstly, the Homo sapiens genome had stronger codon bias for DNA-binding transcription factors than the Saccharomyces cerevisiae genome, whereas the opposite was true for ribosomal proteins – perhaps underscoring transcriptional regulation in the origin of complexity. Secondly, both mammalian species examined possessed extreme codon bias in genes relating to hair – a tissue unique to mammals. Thirdly, Arabidopsis thaliana showed extreme codon bias in genes implicated in cell wall formation and chloroplast function – which are unique to plants. Fourthly, Gallus gallus possessed strong codon bias in a subset of genes encoding mitochondrial proteins – perhaps reflecting the enhanced bioenergetic efficiency in birds that co-evolved with flight. And lastly, the G. gallus genome had extreme codon bias for the Ciliary Neurotrophic Factor – which may help to explain their spontaneous recovery from deafness. We propose that extreme codon bias in groups of genes that encode functionally related proteins has a pathway-level energetic explanation.

Molecular evolution under increasing transposable element burden in Drosophila: a speed limit on the evolutionary arms race.

BackgroundGenome architecture is profoundly influenced by transposable elements (TEs), and natural selection against their harmful effects is a critical factor limiting their spread. Genome defense by the piRNA silencing pathway also plays a crucial role in limiting TE proliferation. How these two forces jointly determine TE abundance is not well understood. To shed light on the nature of factors that predict TE success, we test three distinct hypotheses in the Drosophila genus. First, we determine whether TE abundance and relaxed genome-wide purifying selection on protein sequences are positively correlated. This serves to test the hypothesis that variation in TE abundance in the Drosophila genus can be explained by the strength of natural selection, relative to drift, acting in parallel against mildly deleterious non-synonymous mutations. Second, we test whether increasing TE abundance is correlated with an increased rate of amino-acid evolution in genes encoding the piRNA machinery, as might be predicted by an evolutionary arms race model. Third, we test whether increasing TE abundance is correlated with greater codon bias in genes of the piRNA machinery. This is predicted if increasing TE abundance selects for increased efficiency in the machinery of genome defense.ResultsSurprisingly, we find neither of the first two hypotheses to be true. Specifically, we found that genome-wide levels of purifying selection, measured by the ratio of non-synonymous to synonymous substitution rates (ω), were greater in species with greater TE abundance. In addition, species with greater TE abundance have greater levels of purifying selection in the piRNA machinery. In contrast, it appears that increasing TE abundance has primarily driven adaptation in the piRNA machinery by increasing codon bias.ConclusionsThese results indicate that within the Drosophila genus, a historically reduced strength of selection relative to drift is unlikely to explain patterns of increased TE success across species. Other factors, such as ecological exposure, are likely to contribute to variation in TE abundances within species. Furthermore, constraints on the piRNA machinery may temper the evolutionary arms race that would drive increasing rates of evolution at the amino acid level. In the face of these constraints, selection may act primarily by improving the translational efficiency of the machinery of genome defense through efficient codon usage.

Determinants of translation efficiency and accuracy

Proper functioning of biological cells requires that the process of protein expression be carried out with high efficiency and fidelity. Given an amino-acid sequence of a protein, multiple degrees of freedom still remain that may allow evolution to tune efficiency and fidelity for each gene under various conditions and cell types. Particularly, the redundancy of the genetic code allows the choice between alternative codons for the same amino acid, which, although 'synonymous,' may exert dramatic effects on the process of translation. Here we review modern developments in genomics and systems biology that have revolutionized our understanding of the multiple means by which translation is regulated. We suggest new means to model the process of translation in a richer framework that will incorporate information about gene sequences, the tRNA pool of the organism and the thermodynamic stability of the mRNA transcripts. A practical demonstration of a better understanding of the process would be a more accurate prediction of the proteome, given the transcriptome at a diversity of biological conditions.

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.

Mathematical relations between codon bias indexes and their applications

Codon Adaptation Index (CAI), Effective Number of Codons \((\hat{N_{c}})\) as well as its modifications \(\hat{N_{c}}^*\) , \(\hat{N_{c}}^{**}\) can be used to measure gene codon bias. In this article, we prove \(\hat{N_{c}}^{**}\) is more efficient and unbiased than \(\hat{N_{c}}^*\) and \(\hat{N_{c}}\) by revisiting correlations of them with CAI in the level of individual amino acid’s codon bias. Correlations are studied by mathematical expressions rather than statistic methods, because the latter unavoidably depend on the data set used. Additionally, the immediate cause of correlations of \(\hat{N_{i}}\) with CAI (as well as those of RSCU with CAI) are also described in mathematical language. Perhaps, mathematics provides us a new way to study correlations between biological indexes.

Absence of Classical Heat Shock Response in the Citrus Pathogen Xylella fastidiosa

The fastidious bacterium Xylella fastidiosa is associated with important crop diseases worldwide. We have recently shown that X. fastidiosa is a peculiar organism having unusually low values of gene codon bias throughout its genome and, unexpectedly, in the group of the most abundant proteins. Here, we hypothesized that the lack of codon usage optimization in X. fastidiosa would incapacitate this organism to undergo quick and massive changes in protein expression as occurs in a classical stress response. Proteomic analysis of the response to heat stress in X. fastidiosa revealed that no changes in protein expression can be detected. Moreover, stress-inducible proteins identified in the closely related citrus pathogen Xanthomonas axonopodis pv citri were found to be constitutively expressed in X. fastidiosa. These proteins have extremely high codon bias values in the X. citri and other well-studied organisms, but low values in X. fastidiosa. Because biased codon usage is well known to correlate to the rate of protein synthesis, we speculate that the peculiar codon bias distribution in X. fastidiosa is related to the absence of a classical stress response, and, probably, alternative strategies for survival of X. fastidiosa under stressfull conditions.

Intragenic codon bias in a set of mouse and human genes

To better conceptualize the mechanism underlying the evolution of synonymous codons, we have analysed intragenic codon usage in chosen “regions” of some mouse and human genes. We divided a given gene into two regions: one consisting of a trinucleotide repeat (TNR) and the other consisting of the “rest of the coding region” (RCR). Usually, a TNR is composed of a repetitive single codon, which may reflect its frequency in a gene. In contrast, a non-random frequency of a codon in the RCR versus TNR (or vice versa) of a gene should indicate a bias for that codon within the TNR. We examined this scenario by comparing codon frequency between the RCR and the cognate TNR(s) for a set of human and mouse genes. A TNR length of six amino acids or more was used to identify genes from the Genbank database. Twenty nine human and twenty one mouse genes containing TNRs coding for nine different amino acid runs were identified. The ratio of codon frequency in a TNR versus the corresponding RCR was expressed as “fold change” which was also regarded as a measure of codon bias (defined as preferential use either in TNR or in RCR). Chi-square values were then determined from the distribution of codon frequency in a TNR vs. the cognate RCR. At p<0.001, 22% and 27%, respectively, of human and mouse TNRs showed codon bias. Greater than 40% of the TNRs (29 out of 69 in human, and 18 of 42 in mouse) showed codon bias at p<0.05. In addition, we identify eight single-codon TNRs in mouse and ten in human genes. Thus, our results show intragenic codon bias in both mouse and human genes expressed in diverse tissue types. Since our results are independent of the Codon Adaptation Index (CAI) and starvation CAI, and since the tRNA repertoire in a cell or in a tissue is constant, our data suggest that other constraints besides tRNA abundance played a role in creating intragenic codon bias in these genes.

Population, evolutionary and genomic consequences of interference selection.

Weakly selected mutations are most likely to be physically clustered across genomes and, when sufficiently linked, they alter each others' fixation probability, a process we call interference selection (IS). Here we study population genetics and evolutionary consequences of IS on the selected mutations themselves and on adjacent selectively neutral variation. We show that IS reduces levels of polymorphism and increases low-frequency variants and linkage disequilibrium, in both selected and adjacent neutral mutations. IS can account for several well-documented patterns of variation and composition in genomic regions with low rates of crossing over in Drosophila. IS cannot be described simply as a reduction in the efficacy of selection and effective population size in standard models of selection and drift. Rather, IS can be better understood with models that incorporate a constant "traffic" of competing alleles. Our simulations also allow us to make genome-wide predictions that are specific to IS. We show that IS will be more severe at sites in the center of a region containing weakly selected mutations than at sites located close to the edge of the region. Drosophila melanogaster genomic data strongly support this prediction, with genes without introns showing significantly reduced codon bias in the center of coding regions. As expected, if introns relieve IS, genes with centrally located introns do not show reduced codon bias in the center of the coding region. We also show that reasonably small differences in the length of intermediate "neutral" sequences embedded in a region under selection increase the effectiveness of selection on the adjacent selected sequences. Hence, the presence and length of sequences such as introns or intergenic regions can be a trait subject to selection in recombining genomes. In support of this prediction, intron presence is positively correlated with a gene's codon bias in D. melanogaster. Finally, the study of temporal dynamics of IS after a change of recombination rate shows that nonequilibrium codon usage may be the norm rather than the exception.

Interactions between natural selection, recombination and gene density in the genes of Drosophila.

In Drosophila, as in many organisms, natural selection leads to high levels of codon bias in genes that are highly expressed. Thus codon bias is an indicator of the intensity of one kind of selection that is experienced by genes and can be used to assess the impact of other genomic factors on natural selection. Among 13,000 genes in the Drosophila genome, codon bias has a slight positive, and strongly significant, association with recombination--as expected if recombination allows natural selection to act more efficiently when multiple linked sites segregate functional variation. The same reasoning leads to the expectation that the efficiency of selection, and thus average codon bias, should decline with gene density. However, this prediction is not confirmed. Levels of codon bias and gene expression are highest for those genes in an intermediate range of gene density, a pattern that may be the result of a tradeoff between the advantages for gene expression of close gene spacing and disadvantages arising from regulatory conflicts among tightly packed genes. These factors appear to overlay the more subtle effect of linkage among selected sites that gives rise to the association between recombination rate and codon bias.

The mutational-response index and codon bias in genes from a Frankia nif operon

The mutational response index (MRI) and measurements of codon bias were determined in three characterised genes, and two open reading frames of unknown function, from the Frankia nif operon, which encodes genes for nitrogen fixation. The merits of the different systems of measuring codon usage are discussed in the light of the results, as are the applicability of these techniques to the assessment of the translational function of putative open reading frames.

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.

A part of codon bias in genes protects protein spatial structures from destabilization by random single point mutations

Relationships are examined, using a primitive approximation, between the known general codon bias in genes and resistance of protein tertiary structure to destabilization by random single point mutations. A correlation of these two properties is found in the case of the first codon position while the second and third codon positions are evidently used for other purposes. This study suggests a separation of roles of the particular codon positions in the translation of the genetic message.