sRNA Profiler: A User-Focused Interface for Small RNA Mapping and Profiling

Viroids are circular, highly structured, single-stranded, non-coding RNA pathogens known to infect and cause disease in several plant species. They are known to trigger the host plant’s RNA silencing machinery. The detection of viroid-derived small RNAs (vd-sRNA) in viroid-infected host plants opened a new avenue of study in host–viroid pathogenicity. Since then, several viroid research groups have studied the vd-sRNA retrieved from different host–viroid combinations. Such studies require the segregation of 21- to 24-nucleotide long small RNAs (sRNA) from a deep-sequencing databank, followed by separating the vd-sRNA from any sRNA within this group that showed sequence similarity with either the genomic or the antigenomic strands of the viroid. Such mapped vdsRNAs are then profiled on both the viroid’s genomic and antigenomic strands for visualization. Although several commercial interfaces are currently available for this purpose, they are all programmed for linear RNA molecules. Hence, viroid researchers must develop a computer program that accommodates the sRNAs derived from the circular viroid genome. This is a laborious process, and consequently, it often creates a bottleneck for biologists. In order to overcome this constraint, and to help the research community in general, in this study, a python-based pattern matching interface was developed so as to be able to both profile and map sRNAs on a circular genome. A “matching tolerance” feature has been included in the program, thus permitting the mapping of the sRNAs derived from the quasi-species. Additionally, the “topology” feature allows the researcher to profile sRNA derived from both linear and circular RNA molecules. The efficiency of the program was tested using previously reported deep-sequencing data obtained from two independent studies. Clearly, this novel software should be a key tool with which to both evaluate the production of sRNA and to profile them on their target RNA species, irrespective of the topology of the target RNA molecule.

Subcellular Localization of miRNAs and Implications in Cellular Homeostasis

MicroRNAs (miRNAs) are thought to act as post-transcriptional regulators in the cytoplasm by either dampening translation or stimulating degradation of target mRNAs. With the increasing resolution and scope of RNA mapping, recent studies have revealed novel insights into the subcellular localization of miRNAs. Based on miRNA subcellular localization, unconventional functions and mechanisms at the transcriptional and post-transcriptional levels have been identified. This minireview provides an overview of the subcellular localization of miRNAs and the mechanisms by which they regulate transcription and cellular homeostasis in mammals, with a particular focus on the roles of phase-separated biomolecular condensates.

RNA Transcriptome Mapping with GraphMap

Next generation sequencing technologies have made RNA sequencing widely accessible and applicable in many areas of research. In recent years, 3rd generation sequencing technologies have matured and are slowly replacing NGS for DNA sequencing. This paper presents a novel tool for RNA mapping guided by gene annotations. The tool is an adapted version of a previously developed DNA mapper – GraphMap, tailored for third generation sequencing data, such as those produced by Pacific Biosciences or Oxford Nanopore Technologies devices. It uses gene annotations to generate a transcriptome, uses a DNA mapping algorithm to map reads to the transcriptome, and finally transforms the mappings back to genome coordinates. Modified version of GraphMap is compared on several synthetic datasets to the state-of-the-art RNAseq mappers enabled to work with third generation sequencing data. The results show that our tool outperforms other tools in general mapping quality.

Mapping Hfq-RNA interaction surfaces using tryptophan fluorescence quenching

Hfq is a posttranscriptional riboregulator and RNA chaperone that binds small RNAs and target mRNAs to effect their annealing and message-specific regulation in response to environmental stressors. Structures of Hfq-RNA complexes indicate that U-rich sequences prefer the proximal face and A-rich sequences the distal face; however, the Hfq-binding sites of most RNAs are unknown. Here, we present an Hfq-RNA mapping approach that uses single tryptophan-substituted Hfq proteins, all of which retain the wild-type Hfq structure, and tryptophan fluorescence quenching (TFQ) by proximal RNA binding. TFQ properly identified the respective distal and proximal binding of A15 and U6 RNA to Gram-negative Escherichia coli (Ec) Hfq and the distal face binding of (AA)3A, (AU)3A and (AC)3A to Gram-positive Staphylococcus aureus (Sa) Hfq. The inability of (GU)3G to bind the distal face of Sa Hfq reveals the (R-L)n binding motif is a more restrictive (A-L)n binding motif. Remarkably Hfq from Gram-positive Listeria monocytogenes (Lm) binds (GU)3G on its proximal face. TFQ experiments also revealed the Ec Hfq (A-R-N)n distal face-binding motif should be redefined as an (A-A-N)n binding motif. TFQ data also demonstrated that the 5′-untranslated region of hfq mRNA binds both the proximal and distal faces of Ec Hfq and the unstructured C-terminus.