A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer

The signature of SARS-CoV-2 evolution reflects selective pressures within human guts

In somatic cells, microRNAs (miRNAs) bind to the genomes of RNA viruses and influence their translation and replication. In London and Berlin samples represented in GISAID database, we traced severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineages and divided these sequenced in two groups, "Ancestral variants" and "Omicrons," and analyzed them through the prism of the tissue-specific binding between host miRNAs and viral messenger RNAs. We demonstrate a significant number of miRNA-binding sites in the NSP4 region of the SARS-CoV-2 genome, with evidence of evolutionary pressure within this region exerted by human intestinal miRNAs. Notably, in infected cells, NSP4 promotes the formation of double-membrane vesicles, which serve as the scaffolds for replication-transcriptional complexes and protect viral RNA from intracellular destruction. In 3 years of selection, the loss of many miRNA-binding sites in general and those within the NSP4 in particular has shaped the SARS-CoV-2 genomes. With that, the descendants of the BA.2 variants were promoted as dominant strains, which define current momentum of the pandemics.

One locus, several functional RNAs-emerging roles of the mechanisms responsible for the sequence variability of microRNAs

With the development of modern molecular genetics, the original "one gene-one enzyme" hypothesis has been outdated. For protein coding genes, the discovery of alternative splicing and RNA editing provided the biochemical background for the RNA repertoire of a single locus, which also serves as an important pillar for the enormous protein variability of the genomes. Non-protein coding RNA genes were also revealed to produce several RNA species with distinct functions. The loci of microRNAs (miRNAs), encoding for small endogenous regulatory RNAs, were also found to produce a population of small RNAs, rather than a single defined product. This review aims to present the mechanisms contributing to the astonishing variability of miRNAs revealed by the new sequencing technologies. One important source is the careful balance of arm selection, producing sequentially different 5p- or 3p-miRNAs from the same pre-miRNA, thereby broadening the number of regulated target RNAs and the phenotypic response. In addition, the formation of 5', 3' and polymorphic isomiRs, with variable end and internal sequences also leads to a higher number of targeted sequences, and increases the regulatory output. These miRNA maturation processes, together with other known mechanisms such as RNA editing, further increase the potential outcome of this small RNA pathway. By discussing the subtle mechanisms behind the sequence diversity of miRNAs, this review intends to reveal this engaging aspect of the inherited "RNA world", how it contributes to the almost infinite molecular variability among living organisms, and how this variability can be exploited to treat human diseases.

Differential co-expression network analysis with DCoNA reveals isomiR targeting aberrations in prostate cancer

MOTIVATION

One of the standard methods of high-throughput RNA sequencing analysis is differential expression. However, it does not detect changes in molecular regulation. In contrast to the standard differential expression analysis, differential co-expression one aims to detect pairs or clusters whose mutual expression changes between two conditions.

RESULTS

We developed Differential Co-expression Network Analysis (DCoNA)-an open-source statistical tool that allows one to identify pair interactions, which correlation significantly changes between two conditions. Comparing DCoNA with the state-of-the-art analog, we showed that DCoNA is a faster, more accurate and less memory-consuming tool. We applied DCoNA to prostate mRNA/miRNA-seq data collected from The Cancer Genome Atlas (TCGA) and compared predicted regulatory interactions of miRNA isoforms (isomiRs) and their target mRNAs between normal and cancer samples. As a result, almost all highly expressed isomiRs lost negative correlation with their targets in prostate cancer samples compared to ones without the pathology. One exception to this trend was the canonical isomiR of hsa-miR-93-5p acquiring cancer-specific targets. Further analysis showed that cancer aggressiveness simultaneously increased with the expression level of this isomiR in both TCGA primary tumor samples and 153 blood plasma samples of P. Hertsen Moscow Oncology Research Institute patients' cohort analyzed by miRNA microarrays.

AVAILABILITY AND IMPLEMENTATION

Source code and documentation of DCoNA are available at https://github.com/zhiyanov/DCoNA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.