Host Adaptation of Codon Usage in SARS-CoV-2 From Mammals Indicate Natural Selection

The outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, spread across hosts from humans to animals, transmitting particularly effectively in mink. How SARS-CoV-2 selects and evolves in the host, and the differences in the evolution of different animals are still unclear. To analysis the mutation and codon usage bias of SARS-CoV-2 in infected humans and animals. The SARS-CoV-2 sequence in mink (Mink-SARS2) and binding energy with receptor were calculated compared with human. The relative synonymous codon usage of viral encoded gene was analyzed to characterize the differences and the evolutionary characteristics. A synonymous codon usage analysis showed that SARS-CoV-2 is optimized to adapt in the animals in which it is currently reported, and all of the animals showed decreased adaptability relative to that of humans, except for mink. The neutrality plot showed that the effect of natural selection on different SARS-CoV-2 sequences is stronger than mutation pressure. A binding affinity analysis indicated that the spike protein of the SARS-CoV-2 variant in mink showed a greater preference for binding with the mink receptor ACE2 than with the human receptor, especially as the mutation Y453F and N501T in Mink-SARS2 lead to improvement of binding affinity for mink receptor. In summary, mutations Y453F and N501T in Mink-SARS2 lead to improvement of binding affinity with mink receptor, indicating possible natural selection and current host adaptation. Monitoring the variation and codon bias of SARS-CoV-2 provides a theoretical basis for tracing the epidemic, evolution and cross-species spread of SARS-CoV-2.

Intragenomic variation in mutation biases causes underestimation of selection on synonymous codon usage

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.

Comparative analysis of transcriptomic data shows the effects of multiple evolutionary selection processes on codon usage in Marsupenaeus japonicus and Marsupenaeus pulchricaudatus

Background Kuruma shrimp, a major commercial shrimp species in the world, has two cryptic or sibling species, Marsupenaeus japonicus and Marsupenaeus pulchricaudatus. Codon usage analysis would contribute to our understanding of the genetic and evolutionary characteristics of the two Marsupenaeus species. In this study, we analyzed codon usage and related indices using coding sequences (CDSs) from RNA-seq data. Results Using CodonW 1.4.2 software, we performed the codon bias analysis of transcriptomes obtained from hepatopancreas tissues, which indicated weak codon bias. Almost all parameters had similar correlations for both species. The gene expression level (FPKM) was negatively correlated with A/T3s. We determined 12 and 14 optimal codons for M. japonicus and M. pulchricaudatus, respectively, and all optimal codons have a C/G-ending. The two Marsupenaeus species had different usage frequencies of codon pairs, which contributed to further analysis of transcriptional differences between them. Orthologous genes that underwent positive selection (ω > 1) had a higher correlation coefficient than that of experienced purifying selection (ω < 1). Parity Rule 2 (PR2) and effective number of codons (ENc) plot analysis showed that the codon usage patterns of both species were influenced by both mutations and selection. Moreover, the average observed ENc value was lower than the expected value for both species, suggesting that factors other than GC may play roles in these phenomena. The results of multispecies clustering based on codon preference were consistent with traditional classification. Conclusions This study provides a relatively comprehensive understanding of the correlations among codon usage bias, gene expression, and selection pressures of CDSs for M. japonicus and M. pulchricaudatus. The genetic evolution was driven by mutations and selection pressure. Moreover, the results point out new insights into the specificities and evolutionary characteristics of the two Marsupenaeus species.

Analysis of Codon Usage Pattern and Predicted Gene Expression in Neurospora Crassa: A Novel in Silico Approach

The codon usage pattern of genes has a key role in the gene expression and adaptive evolution of an organism. It is very significant in understanding the role of complex genomic structure in defining cell fates and regulating diverse biological functions. In this paper, we discussed that the codon usage index (CAIg) based on all protein-coding genes is a promising alternative to the Codon Adaptation Index (CAI). CAIg which measures the extent that a gene uses a subset of preferred codons relies exclusively on sequence features and is used as a good indicator of the strength of codon bias. A critical analysis of predicted highly expressed (PHE) genes in Neurospora crassa has been performed using codon usage index (CAIg) as a numerical estimator of gene expression level. Analyzing compositional properties and codon usage pattern of genes in Neurospora crassa, our study indicates that codon composition plays an important role in the regulation of gene expression. We found a systematic strong correlation between CAIg and CBI (codon bias index) or other expression-measures. Here, we show that codon usage index CAIg correlates well with both protein and mRNA levels; suggesting that codon usage is an important determinant of gene expression. Our study highlights the relationship between gene expression and compositional signature in relation to codon usage bias in Neurospora crassa and sets the ground for future investigation in eukaryotic biology.

SkewDB: A comprehensive database of GC and a 10 other skews for over 28,000 chromosomes and plasmids

ABSTRACTGC skew denotes the relative excess of G nucleotides over C nucleotides on the leading versus the lagging replication strand of eubacteria. While the effect is small, typically around 2.5%, it is robust and pervasive. GC skew and the analogous TA skew are a localized deviation from Chargaff’s second parity rule, which states that G and C, and T and A occur with (mostly) equal frequency even within a strand.Most bacteria also show the analogous TA skew. Different phyla show different kinds of skew and differing relations between TA and GC skew.This article introduces an open access database (https://skewdb.org) of GC and 10 other skews for over 28,000 chromosomes and plasmids. Further details like codon bias, strand bias, strand lengths and taxonomic data are also included. The SkewDB database can be used to generate or verify hypotheses. Since the origins of both the second parity rule, as well as GC skew itself, are not yet satisfactorily explained, such a database may enhance our understanding of microbial DNA.

Glue genes are subjected to diverse selective forces during Drosophila development

Molecular evolutionary studies usually focus on genes with clear roles in adult fitness or on developmental genes expressed at multiple time points during the life of the organism. Here, we examine the evolutionary dynamics of Drosophila glue genes, a set of eight genes tasked with a singular primary function during a specific developmental stage: the production of glue that allows animal pupa to attach to a substrate for several days during metamorphosis. Using phenotypic assays and integrating data from transcriptomics, PacBio genomes, and genetic variation from global populations, we explore the selective forces acting on the glue genes within the cosmopolitan D. melanogaster species and its five closely related species, D. simulans, D. sechellia, D. mauritiana, D. yakuba, and D. teissieri. We observe a three-fold difference in glue adhesion between the least and the most adhesive D. melanogaster strain, indicating a strong genetic component to phenotypic variation. These eight glue genes are among the most highly expressed genes in salivary glands yet they display no notable codon bias. New copies of Sgs3 and Sgs7 are found in D. yakuba and D. teissieri with the Sgs3 coding sequence evolving rapidly after duplication in the D. yakuba branch. Multiple sites along the various glue genes appear to be constrained. Our population genetics analysis in D. melanogaster suggests signs of local adaptive evolution for Sgs5 and Sgs5bis and traces of selective sweeps for Sgs1, Sgs3, Sgs7 and Sgs8. Our work shows that stage-specific genes can be subjected to various dynamic evolutionary forces.

Insight of Codon usage bias and Evolutionary rate among the genes C, E, prM and NS5 of the Kyasanur Forest Disease virus

Kyasanur Forest Disease was first evolved in the Kyasanur forest, Karnataka. The transmission of the virus has occurred from the monkey to the human by the tick vector. On the early day of viral spread, the disease was restricted to the surrounded region of Kyasanur forest, Shimoga district. But in the present days, the disease has been spreading to neighboring districts and states as well. So, this study involves estimation of codon bias among the gene C, gene E, gene prM, and gene NS5 of the KFD virus and rate of evolution with phylogenetic analysis. The codon usage analysis has revealed the moderate codon bias among all the selected genes and the role of mutation pressure in genes- C and E and natural selection in genes- prM and NS5. Also, the tMRCA age was 1942, 1982, 1975, and 1931 of genes- C, E, prM, and NS5, respectively, of the KFD virus. The integrated analysis of codon usage bias and evolutionary rate analysis signifies that both mutational pressure and natural selection among the selected genes of the KFD virus.

Analysis of Codon Bias in Mitochondrial Genome of Epinephelus Fuscoguttatus

Background: Epinephelus fuscoguttatus is one of the rare marine economic fishes with high economic value. At present, the researches on grouper mainly focus on artificial propagation, physiology and biochemistry, diseases and so on. However, there are few reports on mitochondrial genome level. The research aimed to analyze composition characteristics and usage preference of codon of mitochondrial genome in E. fuscoguttatus, and explored main factors of affecting the formation of codon preference, thereby providing theoretical basis for studying species evolution, genetics and breeding, and improving expression efficiency of exogenous genes. Results: GC content of mitochondrial genome of E. fuscoguttatus changed between 44.00% and 46.30%, with 45.40% of mean. Change range of CAI value was between 0.125 and 0.202, and the mean was 0.155. Effective number of codons (ENC) changed between 36.08 and 49.55, with 44.98 of mean. There were 32 codons that relative synonymous codon usage (RSCU) was more than 1, mainly ended with A/C. ENC-plot analysis found that all the genes were in the lower middle of the standard curve, and there was larger difference between actual and theoretical ENC, illustrating that codon bias was mainly affected by the choice. Correspondence analysis showed that the first axis contributed 58.85% of the difference, while the second, third and fourth axes contributed 14.59%, 7.66% and 5.43% of the difference respectively. Cumulative contribution rate of the first four vectors was 85.53%. Finally, nine optimal codons were selected: CUU, AUC, GUU, CCU, GCA, UAU, CGC, AGC and GGC.Conclusions: Codon usage preference of mitochondrial genome of E. fuscoguttatus was weak, and it preferred to use A/C terminated codon, and preference was mainly influenced by choice.