Ribosome Profiling of Plants.

Translation is a key step in control of gene expression, yet most analyses of global responses to a stimulus focus on transcription and the transcriptome. For RNA viruses in particular, which have no DNA-templated transcriptional control, control of viral and host translation is crucial. Here, we describe the method of ribosome profiling (ribo-seq) in plants, applied to virus infection. Ribo-seq is a deep sequencing technique that reveals the translatome by presenting a snapshot of the positions and relative amounts of translating ribosomes on all mRNAs in the cell. In contrast to RNA-seq, a crude cell extract is first digested with ribonuclease to degrade all mRNA not protected by a translating 80S ribosome. The resulting ribosome-protected fragments (RPFs) are deep sequenced. The number of reads mapping to a specific mRNA compared to the standard RNA-seq reads reveals the translational efficiency of that mRNA. Moreover, the precise positions of ribosome pause sites, previously unknown translatable open reading frames, and noncanonical translation events can be characterized quantitatively using ribo-seq. As this technique requires meticulous technique, here we present detailed step-by-step instructions for cell lysate preparation by flash freezing of samples, nuclease digestion of cell lysate, monosome collection by sucrose cushion ultracentrifugation, size-selective RNA extraction and rRNA depletion, library preparation for sequencing and finally quality control of sequenced data. These experimental methods apply to many plant systems, with minor nuclease digestion modifications depending on the plant tissue and species. This protocol should be valuable for studies of plant virus gene expression, and the global translational response to virus infection, or any other biotic or abiotic stress, by the host plant.

Variational inference for detecting differential translation in ribosome profiling studies.

Translational efficiency change is an important mechanism for regulating protein synthesis. Experiments with paired ribosome profiling (Ribo-seq) and mRNA-sequencing (RNA-seq) allow the study of translational efficiency by simultaneously quantifying the abundances of total transcripts and those that are being actively translated. Existing methods for Ribo-seq data analysis either ignore the pairing structure in the experimental design or treat the paired samples as fixed effects instead of random effects. To address these issues, we propose a hierarchical Bayesian generalized linear mixed effects model which incorporates a random effect for the paired samples according to the experimental design. We provide an analytical software tool, "riboVI," that uses a novel variational Bayesian algorithm to fit our model in an efficient way. Simulation studies demonstrate that "riboVI" outperforms existing methods in terms of both ranking differentially translated genes and controlling false discovery rate. We also analyzed data from a real ribosome profiling experiment, which provided new biological insight into virus-host interactions by revealing changes in hormone signaling and regulation of signal transduction not detected by other Ribo-seq data analysis tools.

Metagenomic identification of novel viruses of maize and teosinte in North America.

BACKGROUND: Maize-infecting viruses are known to inflict significant agronomic yield loss throughout the world annually. Identification of known or novel causal agents of disease prior to outbreak is imperative to preserve food security via future crop protection efforts. Toward this goal, a large-scale metagenomic approach utilizing high throughput sequencing (HTS) was employed to identify novel viruses with the potential to contribute to yield loss of graminaceous species, particularly maize, in North America. RESULTS: Here we present four novel viruses discovered by HTS and individually validated by Sanger sequencing. Three of these viruses are RNA viruses belonging to either the Betaflexiviridae or Tombusviridae families. Additionally, a novel DNA virus belonging to the Geminiviridae family was discovered, the first Mastrevirus identified in North American maize. CONCLUSIONS: Metagenomic studies of crop and crop-related species such as this may be useful for the identification and surveillance of known and novel viral pathogens of crops. Monitoring related species may prove useful in identifying viruses capable of infecting crops due to overlapping insect vectors and viral host-range to protect food security.

Yellow Dwarf Viruses of Cereals: Taxonomy and Molecular Mechanisms.

Yellow dwarf viruses are the most economically important and widespread viruses of cereal crops. Although they share common biological properties such as phloem limitation and obligate aphid transmission, the replication machinery and associated cis-acting signals of these viruses fall into two unrelated taxa represented by Barley yellow dwarf virus and Cereal yellow dwarf virus. Here, we explain the reclassification of these viruses based on their very different genomes. We also provide an overview of viral protein functions and their interactions with the host and vector, replication mechanisms of viral and satellite RNAs, and the complex gene expression strategies. Throughout, we point out key unanswered questions in virus evolution, structural biology, and genome function and replication that, when answered, may ultimately provide new tools for virus management.