Codon Frequencies Research Articles

Scrapie-associated polymorphisms of the prion protein gene (PRNP) in Nigerian native goats

Scrapie is a fatal prion protein disease stiffly associated with single nucleotide polymorphism (SNPs) of the prion protein gene (PRNP). The prevalence of this deadly disease has been reported in small ruminants, including goats. The Nigerian goats are hardy, trypano-tolerant, and contribute to the protein intake of the increasing population. Although scrapie has been reported in Nigerian goats, there is no study on the polymorphism of the PRNP gene. Herein, we evaluated the genetic and allele distributions of PRNP polymorphism in 132 Nigerian goats and compared them with publicly available studies on scrapie-affected goats. We utilized Polyphen-2, PROVEAN and AMYCO programs to examine structural variations produced by the non-synonymous SNPs. Our study revealed 29 SNPs in Nigerian goats, of which 14 were non-synonymous, and 23 were novel. There were significant differences (P < 0.001) in the allele frequencies of PRNP codons 139, 146, 154 and 193 in Nigerian goats compared with scrapie-affected goats, except for Northern Italian goats at codon 154. Based on the prediction by Polyphen-2, R139S and N146S were ‘benign’, R154H was ‘probably damaging’, and T193I was ‘possibly damaging’. In contrast, PROVEAN predicted ‘neutral’ for all non-synonymous SNPs, while AMYCO showed a similar amyloid propensity of PRNP for resistant haplotype and two haplotypes of Nigerian goats. Our study is the first to investigate the polymorphism of scrapie-related genes in Nigerian goats.

Comparative Analysis on the Codon Usage Pattern of the Chloroplast Genomes in Malus Species.

Codon usage bias of coding sequences has been usually used for exploring the evolutionary factors that affect the variation of genes. We took 20 chloroplast genomes of Malus species into account to explore the codon usage patterns, including the composition, relationship between GC3s and effective number of codons, the parity rule two analyses, the relative synonymous codon usage, the codon adaptation index, the frequency of optimal codons, the codon bias index, etc., of their coding genes. The relationship between GC3 and the ENC values showed that when the separate genes are concerned, the distribution of their GC3 contents is relatively concentrated and the distribution of the ENC values are from 35 to 61 or so. The neutrality plot showed that the correlation coefficient between GC12 and GC3 is 0.095, revealing the mutation factor played a weak role in codon pattern formation. Correspondence analysis results revealed that the codon usage patterns in the chloroplast genomes of Malus species are similar. All these results showed that all Malus chloroplast genomes are AT rich ones, the third bases of the codons are affected by the natural selection pressure, the first two nucleotide base of the codon are affected by mutation pressure. Some genes, such as the rsp7, psbA and ycf2 are of lower codon usage divergences, while the rps12, rps16 and ndhD are of higher codon usage divergences. Codon usage bias exists in the Malus genomes could be used for exploring the evolutionary characteristics in chloroplast genomes and for further study on evolutionary phenomenon in other species.

Evolution and codon usage bias of mitochondrial and nuclear genomes in Aspergillus section Flavi.

The fungal genus Aspergillus contains a diversity of species divided into taxonomic sections of closely related species. Section Flavi contains 33 species, many of industrial, agricultural, or medical relevance. Here, we analyze the mitochondrial genomes (mitogenomes) of 20 Flavi species-including 18 newly assembled mitogenomes-and compare their evolutionary history and codon usage bias patterns to their nuclear counterparts. Codon usage bias refers to variable frequencies of synonymous codons in coding DNA and is shaped by a balance of neutral processes and natural selection. All mitogenomes were circular DNA molecules with highly conserved gene content and order. As expected, genomic content, including GC content, and genome size differed greatly between mitochondrial and nuclear genomes. Phylogenetic analysis based on 14 concatenated mitochondrial genes predicted evolutionary relationships largely consistent with those predicted by a phylogeny constructed from 2,422 nuclear genes. Comparing similarities in interspecies patterns of codon usage bias between mitochondrial and nuclear genomes showed that species grouped differently by patterns of codon usage bias depending on whether analyses were performed using mitochondrial or nuclear relative synonymous usage values. We found that patterns of codon usage bias at gene level are more similar between mitogenomes of different species than the mitogenome and nuclear genome of the same species. Finally, we inferred that, although most genes-both nuclear and mitochondrial-deviated from the neutral expectation for codon usage, mitogenomes were not under translational selection while nuclear genomes were under moderate translational selection. These results contribute to the study of mitochondrial genome evolution in filamentous fungi.

METTL1 promotes neuroblastoma development through m7G tRNA modification and selective oncogenic gene translation

BackgroundNeuroblastoma (NBL) is the most common extra-cranial solid tumour in childhood, with prognosis ranging from spontaneous remission to high risk for rapid and fatal progression. Despite existing therapy approaches, the 5-year event-free survival (EFS) for patients with advanced NBL remains below 30%, emphasizing urgent necessary for novel therapeutic strategies. Studies have shown that epigenetic disorders play an essential role in the pathogenesis of NBL. However, the function and mechanism of N7-methylguanosine (m7G) methyltransferase in NBL remains unknown.MethodsThe expression levels of m7G tRNA methyltransferase Methyltransferase-like 1 (METTL1) were analyzed by querying the Gene Expression Omnibus (GEO) database and further confirmed by immunohistochemistry (IHC) assay. Kaplan-Meier, univariate and multivariate cox hazard analysis were performed to reveal the prognostic role of METTL1. Cell function assays were performed to evaluate how METTL1 works in proliferation, apoptosis and migration in cell lines and xenograft mouse models. The role of METTL1 on mRNA translation activity of NBL cells was measured using puromycin intake assay and polysome profiling assay. The m7G modified tRNAs were identified by tRNA reduction and cleavage sequencing (TRAC-seq). Ribosome nascent-chain complex-bound mRNA sequencing (RNC-seq) was utilized to identify the variation of gene translation efficiency (TE). Analyzed the codon frequency decoded by m7G tRNA to clarify the translation regulation and mechanism of m7G modification in NBL.ResultsThis study found that METTL1 were significantly up-regulated in advanced NBL, which acted as an independent risk factor and predicted poor prognosis. Further in NBL cell lines and BALB/c-nu female mice, we found METTL1 played a crucial role in promoting NBL progression. Furthermore, m7G profiling and translation analysis revealed downregulation of METTL1 would inhibit puromycin intake efficiency of NBL cells, indicating that METTL1 did count crucially in regulation of NBL cell translation. With all tRNAs with m7G modification identified in NBL cells, knockdown of METTL1 would significantly reduce the levels of both m7G modification and m7G tRNAs expressions. Result of RNC-seq shew there were 339 overlapped genes with impaired translation in NBL cells upon METTL1 knockdown. Further analysis revealed these genes contained higher frequency of codons decoded by m7G-modified tRNAs and were enriched in oncogenic pathways.ConclusionThis study revealed the critical role and mechanism of METTL1-mediated tRNA m7G modification in regulating NBL progression, providing new insights for developing therapeutic approaches for NBL patients.

Codon Usage Bias for Fatty Acid Genes FAE1 and FAD2 in Oilseed Brassica Species

Codon usage bias (CUB) phenomenon varies with the species and even within the genes of the same species, where few codons are preferred more frequently than their other synonymous codons. It also categorizes the differences between species. Nucleotide compositional analysis reveals the molecular mechanisms of genes and the evolutionary relationship of a gene in dissimilar plant species. In the present study, three orthologous sequences of each FAE1 (FAE1.1, FAE1.2, and FAE1.3) and FAD2 (FAD2.1, FAD2.2, and FAD2.3) genes, from six Brassica species were accessed using the GenBank database. Further, CUB-related parameters such as nucleotide composition (AT and GC content), relative synonymous codon usage (RSCU), the effective number of codons (ENC), frequency of optimal codons (Fop), relative codon usage bias (RCBS), neutrality plot (GC12 vs. GC3), parity rule-2 [(A3/(A3 + T3) vs. (G3/(G3 + C3)], and correspondence analysis (COA) were analyzed to compare codon bias in U’s triangle Brassica species. The FAE1 genes were AT-biased and FAD2 genes were GC-biased across the studied Brassica species. RSCU values indicated that both the genes had moderate codon usage frequency for selected amino acids. The evolutionary study confirmed that codon usage preference is similar within the species grouped into the same cluster for FAE1; however, B. nigra performed differently for FAD2.2 orthologue. The high ENC value, low Fop, and RSCU value highlighted that FAE1 and FAD2 genes had a low level of gene expression and moderate preference for codon usage across the Brassicas. In addition, neutrality plot, parity rule, and correspondence analysis revealed that natural selection pressure had significantly contributed to CUB for FAE1 genes, whereas mutation and selection pressure occurred for FAD2 genes. This study would help to decode codon optimization, improve the level of expression of exogenous genes, and transgenic engineering to increase fatty acid profiling for the betterment of seed oil in Brassica species.

Analysis of codon usage patterns in Haloxylon ammodendron based on genomic and transcriptomic data

Haloxylon ammodendron, a xero-halophytic shrub of Chenopodiaceae, is a dominant species in deserts, which has a strong drought and salt tolerance and plays an important role in sand fixation. However, the codon usage bias (CUB) in H. ammodendron is still unclear at present. In this study, the codon usage patterns of 38,657 coding sequences (CDSs) in the newly released whole-genome sequence data of H. ammodendron and 3,948 CDSs in the previously obtained transcriptome sequencing data were compared and analyzed. The results showed that the CDSs with the total guanineandcytosine(GC)content in the range of 40–45 % was the most in the genome and transcriptome. Among which, the GC1, GC2, and GC3 contents of genomic CDSs were 50.83 %, 40.56 %, and 40.23 %, respectively, and those of CDSs in the transcriptome were 47.16 %, 39.02 %, and 39.59 %, respectively. Therefore, the bases in H. ammodendron were rich in adenine and thymine, and the overallcodonusage was biasedtoward A- and U-ending codons. The analysis of neutrality plot, effective number of codon (ENC) plot, and parity rule 2 (PR2) bias plot showed that both natural selection and mutation pressure had great influences on the CUB of H. ammodendron, but natural selection was the most important determinant. Besides, gene expression level and the function and protein length of some specific genes also had influences on the codon usage pattern. Finally, a total of 25 common optimal codons were found in the genomic and transcriptomic data, and AU/GC-ending codons ratio was 24:1. It should be noted that the salt-tolerant unigenes had similar codon usage, and the highly expressed genes had higher usage frequency of optimal codons and lower GC content than the lowly expressed genes. In addition, there was no difference in the ENC values of salt-tolerant unigenes in H. ammodendron, and the expression level of the genes had no correlation with CAI. This study will help to elucidate the formation mechanism of H. ammodendron codon usage bias, and make contributions to the identification of new genes and the genetic engineering study on H. ammodendron.

The Codon Statistics Database: A Database of Codon Usage Bias.

We present the Codon Statistics Database, an online database that contains codon usage statistics for all the species with reference or representative genomes in RefSeq (over 15,000). The user can search for any species and access two sets of tables. One set lists, for each codon, the frequency, the Relative Synonymous Codon Usage, and whether the codon is preferred. Another set of tables lists, for each gene, its GC content, Effective Number of Codons, Codon Adaptation Index, and frequency of optimal codons. Equivalent tables can be accessed for (1) all nuclear genes, (2) nuclear genes encoding ribosomal proteins, (3) mitochondrial genes, and (4) chloroplast genes (if available in the relevant assembly). The user can also search for any taxonomic group (e.g., “primates”) and obtain a table comparing all the species in the group. The database is free to access without registration at http://codonstatsdb.unr.edu.

Genome-wide identification and comparative evolutionary analysis of sorbitol metabolism pathway genes in four Rosaceae species and three model plants

In contrast to most land plant species, sorbitol, instead of sucrose, is the major photosynthetic product in many Rosaceae species. It has been well illustrated that three key functional genes encoding sorbitol-6-phosphate dehydrogenase (S6PDH), sorbitol dehydrogenase (SDH), and sorbitol transporter (SOT), are mainly responsible for the synthesis, degradation and transportation of sorbitol. In this study, the genome-wide identification of S6PDH, SDH and SOT genes was conducted in four Rosaceae species, peach, mei, apple and pear, and showed the sorbitol bio-pathway to be dominant (named sorbitol present group, SPG); another three related species, including tomato, poplar and Arabidopsis, showed a non-sorbitol bio-pathway (named sorbitol absent group, SAG). To understand the evolutionary differences of the three important gene families between SAG and SPG, their corresponding gene duplication, evolutionary rate, codon bias and positive selection patterns have been analyzed and compared. The sorbitol pathway genes in SPG were found to be expanded through dispersed and tandem gene duplications. Branch-specific model analyses revealed SDH and S6PDH clade A were under stronger purifying selection in SPG. A higher frequency of optimal codons was found in S6PDH and SDH than that of SOT in SPG, confirming the purifying selection effect on them. In addition, branch-site model analyses revealed SOT genes were under positive selection in SPG. Expression analyses showed diverse expression patterns of sorbitol-related genes. Overall, these findings provide new insights in the evolutionary characteristics for the three key sorbitol metabolism-related gene families in Rosaceae and other non-sorbitol dominant pathway species.

Mitotic checkpoint gene expression is tuned by codon usage bias

The mitotic checkpoint (also called spindle assembly checkpoint, SAC) is a signaling pathway that safeguards proper chromosome segregation. Correct functioning of the SAC depends on adequate protein concentrations and appropriate stoichiometries between SAC proteins. Yet very little is known about the regulation of SAC gene expression. Here, we show in the fission yeast Schizosaccharomyces pombe that a combination of short mRNA half‐lives and long protein half‐lives supports stable SAC protein levels. For the SAC genes mad2+ and mad3+, their short mRNA half‐lives are caused, in part, by a high frequency of nonoptimal codons. In contrast, mad1+ mRNA has a short half‐life despite a higher frequency of optimal codons, and despite the lack of known RNA‐destabilizing motifs. Hence, different SAC genes employ different strategies of expression. We further show that Mad1 homodimers form co‐translationally, which may necessitate a certain codon usage pattern. Taken together, we propose that the codon usage of SAC genes is fine‐tuned to ensure proper SAC function. Our work shines light on gene expression features that promote spindle assembly checkpoint function and suggests that synonymous mutations may weaken the checkpoint.

Intragenomic variation in non-adaptive nucleotide biases causes underestimation of selection on synonymous codon usage.

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

Decoding the codon usage patterns in Y-domain region of hepatitis E viruses

BackgroundHepatitis E virus (HEV) is a positive-sense RNA virus belonging to the family Hepeviridae. The genome of HEV is organized into three open-reading frames (ORFs): ORF1, ORF2, and ORF3. The ORF1 non-structural Y-domain region (YDR) has been demonstrated to play an important role in the HEV pathogenesis. The nucleotide composition, synonymous codon usage bias in conjunction with other factors influencing the viral YDR genes of HEV have not been studied. Codon usage represents a significant mechanism in establishing the host-pathogen relationship. The present study for the first time elucidates the detailed codon usage patterns of YDR among HEV and HEV-hosts (Human, Rabbit, Mongoose, Pig, Wild boar, Camel, Monkey). ResultsThe overall nucleotide composition revealed the abundance of C and U nucleotides in YDR genomes. The relative synonymous codon usage (RSCU) analysis indicated biasness towards C and U over A and G ended codons in HEV across all hosts. Codon frequency comparative analyses among HEV-hosts showed both similarities and discrepancies in usage of preferred codons encoding amino acids, which revealed that HEV codon preference neither completely differed nor completely showed similarity with its hosts. Thus, our results clearly indicated that the synonymous codon usage of HEV is a mixture of the two types of codon usage: coincidence and antagonism. Mutation pressure from virus and natural selection from host seems to be accountable for shaping the codon usage patterns in YDR. The study emphasised that the influence of compositional constraints, codon usage biasness, mutational alongside the selective forces were reflected in the occurrence of YDR codon usage patterns. ConclusionsOur study is the first in its kind to have reported the analysis of codon usage patterns on a total of seven different natural HEV hosts. Therefore, knowledge of preferred codons obtained from our study will not only augment our understanding towards molecular evolution but is also envisaged to provide insight into the efficient viral expression, viral adaptation, and host effects on the HEV YDR codon usage.

Tempo of Degeneration Across Independently Evolved Nonrecombining Regions.

Recombination is beneficial over the long term, allowing more effective selection. Despite long-term advantages of recombination, local recombination suppression can evolve and lead to genomic degeneration, in particular on sex chromosomes. Here, we investigated the tempo of degeneration in nonrecombining regions, that is, the function curve for the accumulation of deleterious mutations over time, leveraging on 22 independent events of recombination suppression identified on mating-type chromosomes of anther-smut fungi, including newly identified ones. Using previously available and newly generated high-quality genome assemblies of alternative mating types of 13 Microbotryum species, we estimated degeneration levels in terms of accumulation of nonoptimal codons and nonsynonymous substitutions in nonrecombining regions. We found a reduced frequency of optimal codons in the nonrecombining regions compared with autosomes, that was not due to less frequent GC-biased gene conversion or lower ancestral expression levels compared with recombining regions. The frequency of optimal codons rapidly decreased following recombination suppression and reached an asymptote after ca. 3 Ma. The strength of purifying selection remained virtually constant at dN/dS = 0.55, that is, at an intermediate level between purifying selection and neutral evolution. Accordingly, nonsynonymous differences between mating-type chromosomes increased linearly with stratum age, at a rate of 0.015 per My. We thus develop a method for disentangling effects of reduced selection efficacy from GC-biased gene conversion in the evolution of codon usage and we quantify the tempo of degeneration in nonrecombining regions, which is important for our knowledge on genomic evolution and on the maintenance of regions without recombination.

SARS-CoV-2 host prediction based on virus-host genetic features

The genetic diversity of the Coronaviruses gives them different biological abilities, such as infect different cells and/or organisms, a wide spectrum of clinical manifestations, their different routes of dispersion, and viral transmission in a specific host. In recent decades, different Coronaviruses have emerged that are highly adapted for humans and causing serious diseases, leaving their host of unknown origin. The viral genome information is particularly important to enable the recognition of patterns linked to their biological characteristics, such as the specificity in the host-parasite relationship. Here, based on a previously computational tool, the Seq2Hosts, we developed a novel approach which uses new variables obtained from the frequency of spike-Coronaviruses codons, the Relative Synonymous Codon Usage (RSCU) to shed new light on the molecular mechanisms involved in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) host specificity. By using the RSCU obtained from nucleotide sequences before the SARS-CoV-2 pandemic, we assessed the possibility of know the hosts capable to be infected by these new emerging species, which was first identified infecting humans during 2019 in Wuhan, China. According to the model trained and validated using sequences available before the pandemic, bats are the most likely the natural host to the SARS-CoV-2 infection, as previously suggested in other studies that searched for the host viral origin.

Why Is the UAG (Amber) Stop Codon Almost Absent in Highly Expressed Bacterial Genes?

The genome hypothesis postulates that genes in a genome tend to conform to their species’ usage of the codon catalog and the GC content of the DNA. Thus, codon frequencies differ across organisms, including the three termination codons in the standard genetic code. Here, we analyze the frequencies of stop codons in a group of highly expressed genes from 196 prokaryotes under strong translational selection. The occurrence of the three translation termination codons is highly biased, with UAA (ochre) being the most prevalent in almost all bacteria. In contrast, UAG (amber) is the least frequent termination codon, e.g., only 321 occurrences (7.4%) in E. coli K-12 substr. W3110. Of the 253 highly expressed genes, only two end with an UAG codon. The strength of the selective bias against UAG in highly expressed genes varies among bacterial genomes, but it is not affected by the GC content of these genomes. In contrast, increased GC content results in a decrease in UAA abundance with a concomitant increase in UGA abundance. We propose that readthrough efficiency and context effects could explain the prevalence of UAA over UAG, particularly in highly expressed genes. Findings from this communication can be utilized for the optimization of gene expression.

Coronavirus Genus Recognition Based on Prototype Virus Variants

Method named as variant approach to recognizing genus of coronavirus that is based on frequency of codon distribution in viral ORF1ab and genes of structural proteins (S, M and N) was proposed in the work. This method uses modified statistics whose efficiency was demonstrated earlier for flavivirus species recognition. To recognize genus of coronavirus the variant approach considers both various combinations of several structural coronavirus genes and individual structural genes. Finally, coronavirus genus is determined in the result of analysis of all variants considered. The method proposed was developed with the help of learning sample from prototype viral variants of Alphacoronavirus, Betacoronavirus, Deltacoronavirus and Gammacoronavirus genus. Application of the variant approach to recognizing genus of coronavirus has demonstrated the approach high assurance at level of 95 %. Among all variants of joint analysis, the most reliability (98 %) in recognizing genus has been achieved if codon frequency of the ORF1ab was used. Variant approach has revealed a phenomenon of mosaic structure in coronavirus genomes, i.e., when the results of genus recognition for a few genes differ from final conclusion about coronavirus genus. It seems that such phenomenon reflects homologous recombinations of the genes between various species of the coronaviruses and plasticity of their genomes in evolutionary processes.

Codon Usage Bias in Phytoplankton

Non-random usage of synonymous codons, known as “codon bias”, has been described in many organisms, from bacteria to Drosophila, but little is known about it in phytoplankton. This phenomenon is thought to be driven by selection for translational efficiency. As the efficacy of selection is proportional to the effective population size, species with large population sizes, such as phytoplankton, are expected to have strong codon bias. To test this, we measured codon bias in 215 strains from Haptophyta, Chlorophyta, Ochrophyta (except diatoms that were studied previously), Dinophyta, Cryptophyta, Ciliophora, unicellular Rhodophyta and Chlorarachniophyta. Codon bias is modest in most groups, despite the astronomically large population sizes of marine phytoplankton. The strength of the codon bias, measured with the effective number of codons, is the strongest in Haptophyta and the weakest in Chlorarachniophyta. The optimal codons are GC-ending in most cases, but several shifts to AT-ending codons were observed (mainly in Ochrophyta and Ciliophora). As it takes a long time to reach a new equilibrium after such shifts, species having AT-ending codons show a lower frequency of optimal codons compared to other species. Genetic diversity, calculated for species with more than three strains sequenced, is modest, indicating that the effective population sizes are many orders of magnitude lower than the astronomically large census population sizes, which helps to explain the modest codon bias in marine phytoplankton. This study represents the first comparative analysis of codon bias across multiple major phytoplankton groups.

Kingdom-Wide Analysis of FungalProtein-Coding and tRNA Genes Reveals Conserved Patterns of Adaptive Evolution.

Protein-coding genes evolved codon usage bias due to the combined but uneven effects of adaptive and nonadaptive influences. Studies in model fungi agree on codon usage bias as an adaptation for fine-tuning gene expression levels; however, such knowledge is lacking for most other fungi. Our comparative genomics analysis of over 450 species supports codon usage and transfer RNAs (tRNAs) as coadapted for translation speed and this is most likely a realization of convergent evolution. Rather than drift, phylogenetic reconstruction inferred adaptive radiation as the best explanation for the variation of interspecific codon usage bias. Although the phylogenetic signals for individual codon and tRNAs frequencies are lower than expected by genetic drift, we found remarkable conservation of highly expressed genes being codon optimized for translation by the most abundant tRNAs, especially by inosine-modified tRNAs. As an application, we present a sequence-to-expression neural network that uses codons to reliably predict highly expressed transcripts. The kingdom Fungi, with over a million species, includes many key players in various ecosystems and good targets for biotechnology. Collectively, our results have implications for better understanding the evolutionary success of fungi, as well as informing the biosynthetic manipulation of fungal genes.

Codon Usage for Genetic Diversity, and Evolutionary Dynamics of Novel Porcine Parvoviruses 2 through 7 (PPV2-PPV7).

Porcine parvovirus (PPV) is the main pathogen of reproductive disorders. In recent years, a new type of porcine parvovirus has been discovered and named porcine parvovirus 2 to 7 (PPV2–PPV7), and it is associated with porcine circovirus type 2 in pigs. Codon usage patterns and their effects on the evolution and host adaptation of different PPV sub-types are still largely unknown. Here, we define six main sub-types based on the Bayesian method of structural proteins of each sub-type of PPV, including PPV2, PPV3, PPV4, PPV5, PPV6, and PPV7, which show different degrees of codon usage preferences. The effective number of codons (ENC) indicates that all PPV sub-types have low codon bias. According to the codon adaptation index (CAI), PPV3 and PPV7 have the highest similarity with the host, which is related to the main popular tendency of the host in the field; according to the frequency of optimal codons (FOP), PPV7 has the highest frequency of optimal codons, indicating the most frequently used codons in its genes; and according to the relative codon deoptimization index (RCDI), PPV3 has a higher degree. Therefore, it is determined that mutational stress has a certain impact on the codon usage preference of PPV genes, and natural selection plays a very decisive and dominant role in the codon usage pattern. Our research provides a new perspective on the evolution of porcine parvovirus (PPV) and may help provide a new method for future research on the origin, evolutionary model, and host adaptation of PPV.

CoCoView - A codon conservation viewer via sequence logos

Sequence logos are a simple way to display a set of aligned sequences, and they are useful to identify conserved patterns. Since their introduction, several tools have been developed for generating these representations at the single residue level (amino acids or nucleotides). We have developed a tool to build sequence logos of protein-coding sequences at the codon level, allowing more accurate analysis of coding-sequences as they represent synonymous and non-synonymous changes instead of showing only changes that imply on amino acid substitutions. We built CoCoView on top of the Logomaker Python API. It creates codon sequence logos from a multiple sequence alignment of protein-coding sequences. Some properties of the data and the generated logos can be controlled by the end-users, such as data redundancy, plot type and alphabet color.• Split aligned sequences into codon positions;• For each position compute codon frequency and information content;• Use the computed information to plot the graphic.

Codon usage bias and purifying selection identified in Cirrhinus reba mitogenome

In our previous study, we described sequence assembly and organization of the complete mitochondrial genome of a threatened labeonine fish, Cirrhinus reba (GenBank accession no.: MN862482). In this study, our attempts were to find out any mutation or selection pressures and codon usage patterns existing in the mitogenome of the same fish. We applied bioinformatics tools to measure important gene parameters including AT/GC skewness, codon adaptation index (CAI), the effective number of codons (ENc) and GC percentages of each protein coding gene. We found an overrepresentation of A and C resulting a lower number of T and G bases, respectively, where AT-skew was slightly positive and GC-skew was slightly negative. Except for ND6, all protein coding genes (PCGs) had negative GC-skew, which indicated the higher occurrence of Cs. With reference to other two mitogenomes, the dN/dS or Ka/Ks ratios ranged from the lowest value (0.016) for ND4L to the highest value (0.694) for ND1 gene which indicated that PCGs of this fish evolved under strong purifying selection. We further analyzed the codon frequency and relative synonymous codon usage (RSCU) and observed a total of 3802 codons which were used for coding 20 amino acids by a standard set of 64 codons. The amino acids Leucine and Serine were encoded each by six different codons, whereas rest of the amino acids was encoded by either two or four codons. We identified a total of 25 RSCU values (&gt; 1) and revealed 12 codons as “overpresented” that implied for codon usage bias to engage in highly expressed genes for efficient protein synthesis via translational selection. The existence of codon usage biasness rolling in translational selection and the signs of purifying selection identified in PCGs suggest obvious conservation of this threatened fish species.