Long-read direct RNA sequencing developed by Oxford Nanopore Technologies (ONT) is quickly gaining popularity for transcriptome studies, while fast turnaround time and low cost make it an attractive instrument for clinical applications. There is a growing interest to utilize transcriptome data to unravel activated biological processes responsible for disease progression and response to therapies. This trend is of particular interest for precision medicine which aims at single-patient analysis. Here we evaluated whether gene abundances measured by MinION direct RNA sequencing are suited to produce robust estimates of pathway activation for single sample scoring methods. We performed multiple RNA-seq analyses for a single sample that originated from the HepG2 cell line, namely five ONT replicates, and three replicates using Illumina NovaSeq. Two pathway scoring methods were employed—ssGSEA and singscore. We estimated the ONT performance in terms of detected protein-coding genes and average pairwise correlation between pathway activation scores using an exhaustive computational scheme for all combinations of replicates. In brief, we found that at least two ONT replicates are required to obtain reproducible pathway scores for both algorithms. We hope that our findings may be of interest to researchers planning their ONT direct RNA-seq experiments.

The ring rot of potato caused by the bacterial pathogen Clavibacter sepedonicus is a quarantine disease posing a threat to the potato industry worldwide. The sensitive and selective detection of C. sepedonicus is of a high importance for its effective control. Here, the detection system is reported to determine viable bacteria of C. sepedonicus in potato tubers, based on the coupling of CRISPR/Cas13a nuclease with NASBA (Nucleic Acid Sequence Based Amplification)—the method of isothermal amplification of RNA. Detection can be conducted using both instrumental and non-instrumental (visual inspection of test tubes under blue light) modes. When NASBA and Cas13a analyses were carried out in separate test tubes, the limit of detection (LOD) for the system was 1000 copies of purified target 16S rRNA per NASBA reaction or about 24 colony-forming units (CFUs) of C. sepedonicus per 1 g of tuber tissue. The testing can also be conducted in the “one-pot” format (a single test tube), though with lower sensitivity: LOD was 10,000 copies of target RNA or about 100 CFU per 1 g of tuber tissue for both instrumental and visual detection modes. The overall time of NASBA/Cas13a analysis did not exceed 2 h. The developed NASBA/Cas13a detection system has the potential to be employed as a routine test of C. sepedonicus, especially for on-site testing.

The long-read RNA sequencing developed by Oxford Nanopore Technology provides a direct quantification of transcript isoforms. That makes the number of transcript isoforms per gene an intrinsically suitable metric for alternative splicing (AS) profiling in the application to this particular type of RNA sequencing. By using this simple metric and recruiting principal component analysis (PCA) as a tool to visualize the high-dimensional transcriptomic data, we were able to group biospecimens of normal human liver tissue and hepatocyte-derived malignant HepG2 and Huh7 cells into clear clusters in a 2D space. For the transcriptome-wide analysis, the clustering was observed regardless whether all genes were included in analysis or only those expressed in all biospecimens tested. However, in the application to a particular set of genes known as pharmacogenes, which are involved in drug metabolism, the clustering worsened dramatically in the latter case. Based on PCA data, the subsets of genes most contributing to biospecimens’ grouping into clusters were selected and subjected to gene ontology analysis that allowed us to determine the top 20 biological processes among which translation and processes related to its regulation dominate. The suggested metrics can be a useful addition to the existing metrics for describing AS profiles, especially in application to transcriptome studies with long-read sequencing.

The genetic diversity and phylogeny of rhizobia from eight genera belonging to four tribes (Loteae, Genisteae, Galegeae, and Hedysareae) that nodulate 18 species of South Urals wild-growing bean plants are studied. It is demonstrated that symbiotic interaction with various strains of nodule bacteria that are closely related to bacteria of Mesorhizobium sp. was typical for the wild growing plants of the Galegeae and Hedysareae tribes and interaction with bacteria of Bradyrhizobium sp. for the plants of the Genisteae tribe. A rhizobium that is closely related to the bacteria of Mesorhizobium sp. is found in the nodules of Lotus ucrainicus from the Loteae tribe, and Coronilla varia rhizobia strains obtained are found to be closely related to Rhizobium sp., based on the sequence of a 16S rRNA gene. Some minor species of rhizobia, the structure of which is greatly influenced by the conditions of the host plant growth, were also found in the nodules of some kinds of investigated plants.

RNA modifications, particularly N6-methyladenosine (m6A), are pivotal regulators of RNA functionality and cellular processes. We analyzed m6A modifications by employing Oxford Nanopore technology and the m6Anet algorithm, focusing on the HepG2 cell line. We identified 3968 potential m6A modification sites in 2851 transcripts, corresponding to 1396 genes. A gene functional analysis revealed the active involvement of m6A-modified genes in ubiquitination, transcription regulation, and protein folding processes, aligning with the known role of m6A modifications in histone ubiquitination in cancer. To ensure data robustness, we assessed reproducibility across technical replicates. This study underscores the importance of evaluating algorithmic reproducibility, especially in supervised learning. Furthermore, we examined correlations between transcriptomic, translatomic, and proteomic levels. A strong transcriptomic–translatomic correlation was observed. In conclusion, our study deepens our understanding of m6A modifications’ multifaceted impacts on cellular processes and underscores the importance of addressing reproducibility concerns in analytical approaches.