Mapping the RNA structural landscape of viral genomes.

Functional RNA structures are prevalent in viral genomes, and have been shown to play roles in almost every aspect of their biology. However, the majority of viral RNA remains structurally uncharacterized. This is likely to remain true as the cost of sequencing decreases much faster than the cost of structural characterizations. Because of this, there is a need for rapid, inexpensive methods to highlight regions of viral RNA which are ideal candidates for structure-function analyses. The ScanFold method was developed as a single sequence alternative to traditional RNA structural motif discovery pipelines, which rely heavily on well curated sequence alignments to identify conserved RNA structures. ScanFold focuses on identifying (based on their more stable than expected folding energies) the most likely functional structures encoded within a single large RNA sequence, while allowing predicted motifs to be tested for evidence of structural conservation later. Decoupling these processes can be a benefit to researchers studying viruses lacking the ideal phylogenetic depth to yield evidence of structural conservation. Here, we demonstrate how the most significant ScanFold predicted structures correspond to higher base pairing probabilities, SHAPE reactivities, and predict known functional structures within the ZIKV and HIV-1 genomes with accuracy. Best practices and examples are also shown to aid users in utilizing ScanFold for their own systems of interest. ScanFold is available as a Webserver (https://mosslabtools.bb.iastate.edu/scanfold) or can be downloaded (https://github.com/moss-lab/ScanFold) and run locally.

SCNBase: a genomics portal for the soybean cyst nematode (Heterodera glycines).

Soybean is an important worldwide crop, and farmers continue to experience significant yield loss due to the soybean cyst nematode (SCN), Heterodera glycines. This soil-borne roundworm parasite is rated the most important pathogen problem in soybean production. The infective nematodes enter into complex interactions with their host plant by inducing the development of specialized plant feeding cells that provide the parasites with nourishment. Addressing the SCN problem will require the development of genomic resources and a global collaboration of scientists to analyze and use these resources. SCNBase.org was designed as a collaborative hub for the SCN genome. All data and analyses are downloadable and can be analyzed with three integrated genomic tools: JBrowse, Feature Search and BLAST. At the time of this writing, a number of genomic and transcriptomic data sets are already available, with 43 JBrowse tracks and 21 category pages describing SCN genomic analyses on gene predictions, transcriptome and read alignments, effector-like genes, expansion and contraction of genomic repeats, orthology and synteny with related nematode species, Single Nucleotide Polymorphism (SNPs) from 15 SCN populations and novel splice sites. Standard functional gene annotations were supplemented with orthologous gene annotations using a comparison to nine related plant-parasitic nematodes, thereby enabling functional annotations for 85% of genes. These annotations led to a greater grasp on the SCN effectorome, which include over 3324 putative effector genes. By designing SCNBase as a hub, future research findings and genomic resources can easily be uploaded and made available for use by others with minimal needs for further curation. By providing these resources to nematode research community, scientists will be empowered to develop novel, more effective SCN management tools.

RNAStructuromeDB: A genome-wide database for RNA structural inference.

RNA plays important roles in almost every aspect of biology, and every aspect of RNA biology is influenced by its folding. This is a particularly important consideration in the era of high-throughput sequencing, when the discovery of novel transcripts far outpaces our knowledge of their functions. To gain a comprehensive picture of biology requires a structural framework for making functional inferences on RNA. To this end we have developed the RNA Structurome Database ( https://structurome.bb.iastate.edu ), a comprehensive repository of RNA secondary structural information that spans the entire human genome. Here, we compile folding information for every base pair of the genome that may be transcribed: coding, noncoding, and intergenic regions, as well as repetitive elements, telomeres, etc. This was done by fragmenting the GRCh38 reference genome into 154,414,320 overlapping sequence fragments and, for each fragment, calculating a set of metrics based on the sequence's folding properties. These data will facilitate a wide array of investigations: e.g. discovery of structured regulatory elements in differential gene expression data or noncoding RNA discovery, as well as allow genome-scale analyses of RNA folding.