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Rotavirus A Genome Segments Show Distinct Segregation and Codon Usage Patterns.

ABSTRACT: Reassortment of the Rotavirus A (RVA) 11-segment dsRNA genome may generate new genome constellations that allow RVA to expand its host range or evade immune responses. Reassortment may also produce phylogenetic incongruities and weakly linked evolutionary histories across the 11 segments, obscuring reassortment-specific epistasis and changes in substitution rates. To determine the co-segregation patterns of RVA segments, we generated time-scaled phylogenetic trees for each of the 11 segments of 789 complete RVA genomes isolated from mammalian hosts and compared the segments' geodesic distances. We found that segments 4 (VP4) and 9 (VP7) occupied significantly different tree spaces from each other and from the rest of the genome. By contrast, segments 10 and 11 (NSP4 and NSP5/6) occupied nearly indistinguishable tree spaces, suggesting strong co-segregation. Host-species barriers appeared to vary by segment, with segment 9 (VP7) presenting the weakest association with host species. Bayesian Skyride plots were generated for each segment to compare relative genetic diversity among segments over time. All segments showed a dramatic decrease in diversity around 2007 coinciding with the introduction of RVA vaccines. To assess selection pressures, codon adaptation indices and relative codon deoptimization indices were calculated with respect to different host genomes. Codon usage varied by segment with segment 11 (NSP5) exhibiting significantly higher adaptation to host genomes. Furthermore, RVA codon usage patterns appeared optimized for expression in humans and birds relative to the other hosts examined, suggesting that translational efficiency is not a barrier in RVA zoonosis.

SUBMITTER: Hoxie I

PROVIDER: S-EPMC8402926 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background and Aims:Studies on codon usage in monocots have focused on grasses, and observed patterns of this taxon were generalized to all monocot species. Here, non-grass monocot species were analysed to investigate the differences between grass and non-grass monocots. Methods:First, studies of codon usage in monocots were reviewed. The current information was then extended regarding codon usage, as well as codon-pair context bias, using four completely sequenced non-grass monocot genomes (Musa acuminata, Musa balbisiana, Phoenix dactylifera and Spirodela polyrhiza) for which comparable transcriptome datasets are available. Measurements were taken regarding relative synonymous codon usage, effective number of codons, derived optimal codon and GC content and then the relationships investigated to infer the underlying evolutionary forces. Key Results:The research identified optimal codons, rare codons and preferred codon-pair context in the non-grass monocot species studied. In contrast to the bimodal distribution of GC3 (GC content in third codon position) in grasses, non-grass monocots showed a unimodal distribution. Disproportionate use of G and C (and of A and T) in two- and four-codon amino acids detected in the analysis rules out the mutational bias hypothesis as an explanation of genomic variation in GC content. There was found to be a positive relationship between CAI (codon adaptation index; predicts the level of expression of a gene) and GC3. In addition, a strong correlation was observed between coding and genomic GC content and negative correlation of GC3 with gene length, indicating a strong impact of GC-biased gene conversion (gBGC) in shaping codon usage and nucleotide composition in non-grass monocots. Conclusion:Optimal codons in these non-grass monocots show a preference for G/C in the third codon position. These results support the concept that codon usage and nucleotide composition in non-grass monocots are mainly driven by gBGC.

Project description:BackgroundGroup A rotavirus (RVA) is a common causative agent of acute gastroenteritis in infants and young children worldwide. RVA P genotypes, determined by VP4 sequences, have been confirmed to infect humans and animals. However, their codon usage patterns that are essential to obtain insights into the viral evolution, host adaptability, and genetic characterization remained unclear, especially across animal hosts.ResultsWe performed a comprehensive codon usage analysis of eight host-specific RVA P genotypes, including human RVA (P[4] and P[8]), porcine RVA (P[13] and P[23]), and zoonotic RVA (P[1], P[6], P[7] and P[19]), based on 233 VP4 complete coding sequences. Nucleotide composition, relative synonymous codon usage (RSCU), and effective number of codons (ENC) were calculated. Principal component analysis (PCA) based on RSCU values was used to explore the codon usage patterns of different RVA P genotypes. In addition, mutation pressure and natural selection were identified by using ENC-plot, parity rule 2 plot, and neutrality plot analyses. All VP4 sequences preferred using A/U nucleotides (A: 0.354-0.377, U: 0.267-0.314) than G/C nucleotides across genotypes. Similarly, majority of commonly used synonymous codons were likely to end with A/U nucleotides (A: 9/18-12/18, U: 6/18-9/18). In PCA, human, porcine, and zoonotic genotypes clustered separately in terms of RSCU values, indicating the host-specific codon usage patterns; however, porcine and zoonotic genotypes were partly overlapped. Human genotypes, P[4] and P[8], had stronger codon usage bias, as indicated by more over-represented codons and lower ENC, compared to porcine and zoonotic genotypes. Moreover, natural selection was determined to be a predominant driver in shaping the codon usage bias across the eight P genotypes. In addition, mutation pressure contributed to the codon usage bias of human genotypes.ConclusionsOur study identified a strong codon usage bias of human RVA P genotypes attributable to both natural selection and mutation pressure, whereas similar codon usage bias between porcine and zoonotic genotypes predominantly attributable to natural selection. It further suggests possible cross-species transmission. Therefore, it warrants further surveillance of RVA P genotypes for early identification of zoonotic infection.

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Rotavirus A Genome Segments Show Distinct Segregation and Codon Usage Patterns.

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