Mixed viral infection constrains the genome formula of multipartite cucumber mosaic virus

Many plant viruses have a multipartite organization, with multiple genome segments packaged into separate virus particles. The genome formula describes the relative frequencies of all viral genome segments, and previous work suggests rapid changes in these frequencies facilitate virus adaptation. Many studies have reported mixed viral infections in plants, often resulting in strong virus–virus interactions. Here, we tested whether mixed infections with tripartite alfalfa mosaic virus (AMV) and monopartite potato virus Y (PVY) affected the genome formula of the tripartite cucumber mosaic virus (CMV), our experimental model. We found that the CMV titer was reduced in mixed infections with its tripartite Bromoviridae relative AMV and in triple infections with both AMV and PVY, indicating notable virus–virus interactions. The variability of the CMV genome formula was significantly lower in mixed infections (CMV and AMV, CMV and PVY, and CMV and AMV and PVY) than in single infections (CMV only). These observations led to the surprising conclusion that mixed infections with two distinct viruses constrain the CMV genome formula. It remains unclear how common these effects are for different combinations of virus species and strains and what the underlying mechanisms are. We, therefore, extended a simulation model to consider three putative scenarios in which a second virus affected the genome formula. The simulation results also suggested that shifts in the genome formula occur, but may not be widespread due to the required conditions. One scenario modeled—co-infection exclusion through niche differentiation—was congruent with the experimental data, as this scenario led to reductions in genome formula variability and titer of the multipartite virus. Whereas previous studies highlighted host–species effects, our results indicate that the genome formula is also affected by mixed infections, suggesting that there is a broader set of environmental cues that affect the genome formula

Metagenomic studies of viruses in weeds and wild plants: A powerful approach to characterise variable virus communities

High throughput sequencing (HTS) has revolutionised virus detection and discovery, al-lowing for the untargeted characterisation of whole viromes. Viral metagenomics studies have demonstrated the ubiquity of virus infection—often in the absence of disease symptoms—and tend to discover many novel viruses, highlighting the small fraction of virus biodiversity described to date. The majority of the studies using high-throughput sequencing to characterise plant viromes have focused on economically important crops, and only a small number of studies have considered weeds and wild plants. Characterising the viromes of wild plants is highly relevant, as these plants can affect disease dynamics in crops, often by acting as viral reservoirs. Moreover, the viruses in unmanaged systems may also have important effects on wild plant populations and communities. Here, we review metagenomic studies on weeds and wild plants to show the benefits and limita-tions of this approach and identify knowledge gaps. We consider key genomics developments that are likely to benefit the field in the near future. Although only a small number of HTS studies have been performed on weeds and wild plants, these studies have already discovered many novel vi-ruses, demonstrated unexpected trends in virus distributions, and highlighted the potential of met-agenomics as an approach

Metagenomic Studies of Viruses in Weeds and Wild Plants: A Powerful Approach to Characterise Variable Virus Communities

High throughput sequencing (HTS) has revolutionised virus detection and discovery, allowing for the untargeted characterisation of whole viromes. Viral metagenomics studies have demonstrated the ubiquity of virus infection – often in the absence of disease symptoms – and tend to discover many novel viruses, highlighting the small fraction of virus biodiversity described to date. The majority of the studies using high-throughput sequencing to characterise plant viromes have focused on economically important crops, and only a small number of studies have considered weeds and wild plants. Characterising the viromes of wild plants is highly relevant, as these plants can affect disease dynamics in crops, often by acting as viral reservoirs. Moreover, the viruses in unmanaged systems may also have important effects on wild plant populations and communities. Here, we review metagenomic studies on weeds and wild plants to show the benefits and limitations of this approach and identify knowledge gaps. We consider key genomics developments that are likely to benefit the field in the near future. Although only a small number of HTS studies have been performed on weeds and wild plants, these studies have already discovered many novel viruses, demonstrated unexpected trends in virus distributions, and highlighted the potential of metagenomics as an approach

Evaluation of sequencing and PCR-based methods for the quantification of the viral genome formula

Viruses show great diversity in their genome organization. Multipartite viruses package their genome segments into separate particles, most or all of which are required to initiate infection in the host cell. The benefits of such seemingly inefficient genome organization are not well understood. One hypothesised benefit of multipartition is that it allows for flexible changes in gene expression by altering the frequency of each genome segment in different environments, such as encountering different host species. The ratio of the frequency of segments is termed the genome formula (GF). Thus far, formal studies quantifying the GF have been performed for well-characterised virus-host systems in experimental settings using RT-qPCR. However, to understand GF variation in natural populations or novel virus-host systems, a comparison of several methods for GF estimation including high-throughput sequencing (HTS) based methods is needed. Currently, it is unclear how HTS-methods compare a golden standard, such as RT-qPCR. Here we show a comparison of multiple GF quantification methods (RT-qPCR, RT-digital PCR, Illumina RNAseq and Nanopore direct RNA sequencing) using three host plants (Nicotiana tabacum, Nicotiana benthamiana, and Chenopodium quinoa) infected with cucumber mosaic virus (CMV), a tripartite RNA virus. Our results show that all methods give roughly similar results, though there is a significant method effect on genome formula estimates. While the RT-qPCR and RT-dPCR GF estimates are congruent, the GF estimates from HTS methods deviate from those found with PCR. Our findings emphasize the need to tailor the GF quantification method to the experimental aim, and highlight that it may not be possible to compare HTS and PCR-based methods directly. The difference in results between PCR-based methods and HTS highlights that the choice of quantification technique is not trivial

Empirical estimates of the mutation rate for an alphabaculovirus

Mutation rates are of key importance for understanding evolutionary processes and predicting their outcomes. Empirical mutation rate estimates are available for a number of RNA viruses, but few are available for DNA viruses, which tend to have larger genomes. Whilst some viruses have very high mutation rates, lower mutation rates are expected for viruses with large genomes to ensure genome integrity. Alphabaculoviruses are insect viruses with large genomes and often have high levels of polymorphism, suggesting high mutation rates despite evidence of proofreading activity by the replication machinery. Here, we report an empirical estimate of the mutation rate per base per strand copying (s/n/r) of Autographa californica multiple nucleopolyhedrovirus (AcMNPV). To avoid biases due to selection, we analyzed mutations that occurred in a stable, non-functional genomic insert after five serial passages in Spodoptera exigua larvae. Our results highlight that viral demography and the stringency of mutation calling affect mutation rate estimates, and that using a population genetic simulation model to make inferences can mitigate the impact of these processes on estimates of mutation rate. We estimated a mutation rate of μ = 1×10−7 s/n/r when applying the most stringent criteria for mutation calling, and estimates of up to μ = 5×10−7 s/n/r when relaxing these criteria. The rates at which different classes of mutations accumulate provide good evidence for neutrality of mutations occurring within the inserted region. We therefore present a robust approach for mutation rate estimation for viruses with stable genomes, and strong evidence of a much lower alphabaculovirus mutation rate than supposed based on the high levels of polymorphism observed

Evaluation of sequencing and PCR-based methods for the quantification of the viral genome formula

Viruses show great diversity in their genome organization. Multipartite viruses package their genome segments into separate particles, most or all of which are required to initiate infection in the host cell. The benefits of such seemingly inefficient genome organization are not well understood. One hypothesised benefit of multipartition is that it allows for flexible changes in gene expression by altering the frequency of each genome segment in different environments, such as encountering different host species. The ratio of the frequency of segments is termed the genome formula (GF). Thus far, formal studies quantifying the GF have been performed for well-characterised virus-host systems in experimental settings using RT-qPCR. However, to understand GF variation in natural populations or novel virus-host systems, a comparison of several methods for GF estimation including high-throughput sequencing (HTS) based methods is needed. Currently, it is unclear how HTS-methods compare a golden standard, such as RT-qPCR. Here we show a comparison of multiple GF quantification methods (RT-qPCR, RT-digital PCR, Illumina RNAseq and Nanopore direct RNA sequencing) using three host plants (Nicotiana tabacum, Nicotiana benthamiana, and Chenopodium quinoa) infected with cucumber mosaic virus (CMV), a tripartite RNA virus. Our results show that all methods give roughly similar results, though there is a significant method effect on genome formula estimates. While the RT-qPCR and RT-dPCR GF estimates are congruent, the GF estimates from HTS methods deviate from those found with PCR. Our findings emphasize the need to tailor the GF quantification method to the experimental aim, and highlight that it may not be possible to compare HTS and PCR-based methods directly. The difference in results between PCR-based methods and HTS highlights that the choice of quantification technique is not trivial

Empirical estimates of the mutation rate for an alphabaculovirus

Mutation rates are of key importance for understanding evolutionary processes and predicting their outcomes. Empirical mutation rate estimates are available for a number of RNA viruses, but few are available for DNA viruses, which tend to have larger genomes. Whilst some viruses have very high mutation rates, lower mutation rates are expected for viruses with large genomes to ensure genome integrity. Alphabaculoviruses are insect viruses with large genomes and often have high levels of polymorphism, suggesting high mutation rates despite evidence of proofreading activity by the replication machinery. Here, we report an empirical estimate of the mutation rate per base per strand copying (s/n/r) of Autographa californica multiple nucleopolyhedrovirus (AcMNPV). To avoid biases due to selection, we analyzed mutations that occurred in a stable, non-functional genomic insert after five serial passages in Spodoptera exigua larvae. Our results highlight that viral demography and the stringency of mutation calling affect mutation rate estimates, and that using a population genetic simulation model to make inferences can mitigate the impact of these processes on estimates of mutation rate. We estimated a mutation rate of μ = 1×10−7 s/n/r when applying the most stringent criteria for mutation calling, and estimates of up to μ = 5×10−7 s/n/r when relaxing these criteria. The rates at which different classes of mutations accumulate provide good evidence for neutrality of mutations occurring within the inserted region. We therefore present a robust approach for mutation rate estimation for viruses with stable genomes, and strong evidence of a much lower alphabaculovirus mutation rate than supposed based on the high levels of polymorphism observed