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.