scholarly journals Recombination, meiotic expression and human codon usage

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Fanny Pouyet ◽  
Dominique Mouchiroud ◽  
Laurent Duret ◽  
Marie Sémon

Synonymous codon usage (SCU) varies widely among human genes. In particular, genes involved in different functional categories display a distinct codon usage, which was interpreted as evidence that SCU is adaptively constrained to optimize translation efficiency in distinct cellular states. We demonstrate here that SCU is not driven by constraints on tRNA abundance, but by large-scale variation in GC-content, caused by meiotic recombination, via the non-adaptive process of GC-biased gene conversion (gBGC). Expression in meiotic cells is associated with a strong decrease in recombination within genes. Differences in SCU among functional categories reflect differences in levels of meiotic transcription, which is linked to variation in recombination and therefore in gBGC. Overall, the gBGC model explains 70% of the variance in SCU among genes. We argue that the strong heterogeneity of SCU induced by gBGC in mammalian genomes precludes any optimization of the tRNA pool to the demand in codon usage.

2016 ◽  
Author(s):  
Fanny Pouyet ◽  
Dominique Mouchiroud ◽  
Laurent Duret ◽  
Marie Sémon

AbstractIn humans, as in other mammals, synonymous codon usage (SCU) varies widely among genes. In particular, genes involved in cell differentiation or in proliferation display a distinct codon usage, suggesting that SCU is adaptively constrained to optimize translation efficiency in distinct cellular states. However, in mammals, SCU is known to correlate with large-scale fluctuations of GC-content along chromosomes, caused by meiotic recombination, via the non-adaptive process of GC-biased gene conversion (gBGC). To disentangle and to quantify the different factors driving SCU in humans, we analyzed the relationships between functional categories, base composition, recombination, and gene expression. We first demonstrate that SCU is predominantly driven by large-scale variation in GC-content and is not linked to constraints on tRNA abundance, which excludes an effect of translational selection. In agreement with the gBGC model, we show that differences in SCU among functional categories are explained by variation in intragenic recombination rate, which, in turn, is strongly negatively correlated to gene expression levels during meiosis. Our results indicate that variation in SCU among functional categories (including variation associated to differentiation or proliferation) result from differences in levels of meiotic transcription, which interferes with the formation of crossovers and thereby affects gBGC intensity within genes. Overall, the gBGC model explains 70% of the variance in SCU among genes. We argue that the strong heterogeneity of SCU induced by gBGC in mammalian genomes precludes any optimization of the tRNA pool to the demand in codon usage.


Genetics ◽  
2001 ◽  
Vol 159 (3) ◽  
pp. 1191-1199
Author(s):  
Araxi O Urrutia ◽  
Laurence D Hurst

Abstract In numerous species, from bacteria to Drosophila, evidence suggests that selection acts even on synonymous codon usage: codon bias is greater in more abundantly expressed genes, the rate of synonymous evolution is lower in genes with greater codon bias, and there is consistency between genes in the same species in which codons are preferred. In contrast, in mammals, while nonequal use of alternative codons is observed, the bias is attributed to the background variance in nucleotide concentrations, reflected in the similar nucleotide composition of flanking noncoding and exonic third sites. However, a systematic examination of the covariants of codon usage controlling for background nucleotide content has yet to be performed. Here we present a new method to measure codon bias that corrects for background nucleotide content and apply this to 2396 human genes. Nearly all (99%) exhibit a higher amount of codon bias than expected by chance. The patterns associated with selectively driven codon bias are weakly recovered: Broadly expressed genes have a higher level of bias than do tissue-specific genes, the bias is higher for genes with lower rates of synonymous substitutions, and certain codons are repeatedly preferred. However, while these patterns are suggestive, the first two patterns appear to be methodological artifacts. The last pattern reflects in part biases in usage of nucleotide pairs. We conclude that we find no evidence for selection on codon usage in humans.


2021 ◽  
Author(s):  
Alexander L Cope ◽  
Premal Shah

Patterns of non-uniform usage of synonymous codons (codon bias) varies across genes in an organism and across species from all domains of life. The bias in codon usage is due to a combination of both non-adaptive (e.g. mutation biases) and adaptive (e.g. natural selection for translation efficiency/accuracy) evolutionary forces. Most population genetics models quantify the effects of mutation bias and selection on shaping codon usage patterns assuming a uniform mutation bias across the genome. However, mutation biases can vary both along and across chromosomes due to processes such as biased gene conversion, potentially obfuscating signals of translational selection. Moreover, estimates of variation in genomic mutation biases are often lacking for non-model organisms. Here, we combine an unsupervised learning method with a population genetics model of synonymous codon bias evolution to assess the impact of intragenomic variation in mutation bias on the strength and direction of natural selection on synonymous codon usage across 49 Saccharomycotina budding yeasts. We find that in the absence of a priori information, unsupervised learning approaches can be used to identify regions evolving under different mutation biases. We find that the impact of intragenomic variation in mutation bias varies widely, even among closely-related species. We show that the overall strength and direction of selection on codon usage can be underestimated by failing to account for intragenomic variation in mutation biases. Interestingly, genes falling into clusters identified by machine learning are also often physically clustered across chromosomes, consistent with processes such as biased gene conversion. Our results indicate the need for more nuanced models of sequence evolution that systematically incorporate the effects of variable mutation biases on codon frequencies.


2009 ◽  
Vol 2009 ◽  
pp. 1-11 ◽  
Author(s):  
Sameer Hassan ◽  
Vasantha Mahalingam ◽  
Vanaja Kumar

Synonymous codon usage of protein coding genes of thirty two completely sequenced mycobacteriophage genomes was studied using multivariate statistical analysis. One of the major factors influencing codon usage is identified to be compositional bias. Codons ending with either C or G are preferred in highly expressed genes among which C ending codons are highly preferred over G ending codons. A strong negative correlation between effective number of codons (Nc) and GC3s content was also observed, showing that the codon usage was effected by gene nucleotide composition. Translational selection is also identified to play a role in shaping the codon usage operative at the level of translational accuracy. High level of heterogeneity is seen among and between the genomes. Length of genes is also identified to influence the codon usage in 11 out of 32 phage genomes. Mycobacteriophage Cooper is identified to be the highly biased genome with better translation efficiency comparing well with the host specific tRNA genes.


2021 ◽  
Vol 12 ◽  
Author(s):  
Chenkang Yang ◽  
Qi Zhao ◽  
Ying Wang ◽  
Jiajia Zhao ◽  
Ling Qiao ◽  
...  

The synonymous codons usage shows a characteristic pattern of preference in each organism. This codon usage bias is thought to have evolved for efficient protein synthesis. Synonymous codon usage was studied in genes of the hexaploid wheat Triticum aestivum (AABBDD) and its progenitor species, Triticum urartu (AA), Aegilops tauschii (DD), and Triticum turgidum (AABB). Triticum aestivum exhibited stronger usage bias for G/C-ending codons than did the three progenitor species, and this bias was especially higher compared to T. turgidum and Ae. tauschii. High GC content is a primary factor influencing codon usage in T. aestivum. Neutrality analysis showed a significant positive correlation (p<0.001) between GC12 and GC3 in the four species with regression line slopes near zero (0.16–0.20), suggesting that the effect of mutation on codon usage was only 16–20%. The GC3s values of genes were associated with gene length and distribution density within chromosomes. tRNA abundance data indicated that codon preference corresponded to the relative abundance of isoaccepting tRNAs in the four species. Both mutation and selection have affected synonymous codon usage in hexaploid wheat and its progenitor species. GO enrichment showed that GC biased genes were commonly enriched in physiological processes such as photosynthesis and response to acid chemical. In some certain gene families with important functions, the codon usage of small parts of genes has changed during the evolution process of T. aestivum.


2020 ◽  
Vol 21 (11) ◽  
Author(s):  
Redi Aditama ◽  
Zulfikar Achmad Tanjung ◽  
Widyartini Made Sudania ◽  
Yogo Adhi Nugroho ◽  
Condro Utomo ◽  
...  

Abstract. Aditama R, Tanjung ZA, Sudania WM, Nugroho YA, Utomo C, Liwang T. 2020. Analysis of codon usage bias reveals optimal codons in Elaeis guineensis. Biodiversitas 21: 5331-5337. Codon usage bias of oil palm genome was reported employing several indices, including GC content, relative synonymous codon usage (RSCU), the effective number of codons (ENC), and codon adaptation index (CAI). Unimodal distribution of GC content was observed and matched with non-grass monocots characteristics. Correspondence analysis (COA) on synonymous codon usage bias showed that the main axis was strongly driven by GC content. The ENC and neutrality plot of oil palm genes indicating that natural selection played more vital role compared to mutational bias on shaping codon usage bias. A positive correlation between calculated CAI and experimental data of oil palm gene expression was detected indicating good ability of this index. Finally, eighteen codons were defined as “optimal codons” that may provide a useful reference for heterogeneous expression and genome editing studies.


2007 ◽  
Vol 53 (7) ◽  
pp. 830-839 ◽  
Author(s):  
Insung Ahn ◽  
Hyeon S. Son

To investigate the genomic patterns of influenza A virus subtypes, such as H3N2, H9N2, and H5N1, we collected 1842 sequences of the hemagglutinin and neuraminidase genes from the NCBI database and parsed them into 7 categories: accession number, host species, sampling year, country, subtype, gene name, and sequence. The sequences that were isolated from the human, avian, and swine populations were extracted and stored in a MySQL®database for intensive analysis. The GC content and relative synonymous codon usage (RSCU) values were calculated using JAVA codes. As a result, correspondence analysis of the RSCU values yielded the unique codon usage pattern (CUP) of each subtype and revealed no extreme differences among the human, avian, and swine isolates. H5N1 subtype viruses exhibited little variation in CUPs compared with other subtypes, suggesting that the H5N1 CUP has not yet undergone significant changes within each host species. Moreover, some observations may be relevant to CUP variation that has occurred over time among the H3N2 subtype viruses isolated from humans. All the sequences were divided into 3 groups over time, and each group seemed to have preferred synonymous codon patterns for each amino acid, especially for arginine, glycine, leucine, and valine. The bioinformatics technique we introduce in this study may be useful in predicting the evolutionary patterns of pandemic viruses.


2020 ◽  
Author(s):  
Mark G. Sterken ◽  
Ruud H.P. Wilbers ◽  
Pjotr Prins ◽  
Basten L. Snoek ◽  
George M. Giambasu ◽  
...  

ABSTRACTThe redundancy of the genetic code allows for a regulatory layer to optimize protein synthesis by modulating translation and degradation of mRNAs. Patterns in synonymous codon usage in highly expressed genes have been studied in many species, but scarcely in conjunction with mRNA secondary structure. Here, we analyzed over 2,000 expression profiles covering a range of strains, treatments, and developmental stages of five model species (Escherichia coli, Arabidopsis thaliana, Saccharomyces cerevisiae, Caenorhabditis elegans, and Mus musculus). By comparative analyses of genes constitutively expressed at high and low levels, we revealed a conserved shift in codon usage and predicted mRNA secondary structures. Highly abundant transcripts and proteins, as well as high protein per transcript ratios, were consistently associated with less variable and shorter stretches of weak mRNA secondary structures (loops). Genome-wide recoding showed that codons with the highest relative increase in highly expressed genes, often C-ending and not necessarily the most frequent, enhanced formation of uniform loop sizes. Our results point at a general selective force contributing to the optimal expression of abundant proteins as less variable secondary structures promote regular ribosome trafficking with less detrimental collisions, thereby leading to an increase in mRNA stability and a higher translation efficiency.


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Hoda Mirsafian ◽  
Adiratna Mat Ripen ◽  
Aarti Singh ◽  
Phaik Hwan Teo ◽  
Amir Feisal Merican ◽  
...  

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.


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