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 long-read RNA sequencing developed by Oxford Nanopore Technologies provides a direct quantification of transcript isoforms, thereby making it possible to present alternative splicing (AS) profiles as arrays of single splice variants with different abundances. Additionally, AS profiles can be presented as arrays of genes characterized by the degree of alternative splicing (the DAS—the number of detected splice variants per gene). Here, we successfully utilized the DAS to reveal biological pathways influenced by the alterations in AS in human liver tissue and the hepatocyte-derived malignant cell lines HepG2 and Huh7, thus employing the mathematical algorithm of gene set enrichment analysis. Furthermore, analysis of the AS profiles as abundances of single splice variants by using the graded tissue specificity index τ provided the selection of the groups of genes expressing particular splice variants specifically in liver tissue, HepG2 cells, and Huh7 cells. The majority of these splice variants were translated into proteins products and appeal to be in focus regarding further insights into the mechanisms underlying cell malignization. The used metrics are intrinsically suitable for transcriptome-wide AS profiling using long-read sequencing.

Glucose and lipid metabolism are crucial functional systems in eukaryotes. A large number of experimental studies both in animal models and humans have shown that long non-coding RNAs (lncRNAs) play an important role in glucose and lipid metabolism. Previously, human lncRNA DEANR1/linc00261 was described as a tumor suppressor that regulates a variety of biological processes such as cell proliferation, apoptosis, glucose metabolism and tumorigenesis. Here we report that murine lncRNA Falcor/LL35, a proposed functional analog of human DEANR1/linc00261, is predominantly expressed in murine normal hepatocytes and downregulated in HCC and after partial hepatectomy. The application of high-throughput approaches such as RNA-seq, LC-MS proteomics, lipidomics and metabolomics analysis allowed changes to be found in the transcriptome, proteome, lipidome and metabolome of hepatocytes after LL35 depletion. We revealed that LL35 is involved in the regulation of glycolysis and lipid biosynthesis in vitro and in vivo. Moreover, LL35 affects Notch and NF-κB signaling pathways in normal hepatocytes. All observed changes result in the decrease in the proliferation and migration of hepatocytes. We demonstrated similar phenotype changes between murine LL35 and human linc00261 depletion in vitro and in vivo that opens the opportunity to translate results for LL35 from a liver murine model to possible functions of human lncRNA linc00261.