RNA Regulatory Networks as a Control of Stochasticity in Biological Systems

Non-Coding RNAs Are Brokers in Breast Cancer Interactome Networks and Add Discrimination Power between Subtypes

Despite the power of high-throughput genomics, most non-coding RNA (ncRNA) biotypes remain hard to identify, characterize, and validate. This is a clear indication that intensive next-generation sequencing research has led to great efficiency and accuracy in detecting ncRNAs, but not in their functionalization. Computational scientists continue to support the discovery process by spotting significant data features (expression or mutational profiles), elucidating phenotype uncertainty, and delineating complex regulation landscapes for biological pathways and pathophysiological processes. With reference to transcriptome regulation dynamics in cancer, this work introduces a novel network-driven inference approach designed to reveal the potential role of computationally identified ncRNAs in discriminating between breast cancer (BC) subtypes beyond the traditional gene expression signatures. As heterogeneity cast in the subtypes is a characteristic of most cancers, the proposed approach is generalizable beyond BC. Expression profiles of a wide transcriptome spectrum were obtained for a number of BC patients (and controls) listed in TCGA and processed with RNA-Seq. The well-known PAM50 subtype signature was available for the samples and used to move from differentially expressed transcript profiles to subtype-specific biclusters associating gene patterns with patients. Co-expressed gene networks were then generated and annotations were provided, focusing on the biclusters with basal and luminal signatures. These were used to build template maps, i.e., networks in which to embed the ncRNAs and contextually functionalize them based on their interactors. This inference approach is able to assess the influence of ncRNAs at the level of BC subtype. Network topology was considered through the brokerage measure to account for disruptiveness effects induced by the removal of nodes corresponding to ncRNAs. Equivalently, it is shown that ncRNAs can act as brokers of network interactome dynamics, and removing them allows the refinement of subtype-related characteristics previously obtained by gene signatures only. The results of the study elucidate the role of pseudogenes in two major BC subtypes, considering the contextual annotations. Put into a wider perspective, ncRNA brokers may help predictive functionalization studies targeted to new disease phenotypes, for instance those linked to the tumor microenvironment or metabolism, or those specifically involving metastasis. Overall, the approach may represent an in silico prioritization strategy toward the systems identification of new diagnostic and prognostic biomarkers.

Social Networking of Quasi-Species Consortia drive Virolution via Persistence

The emergence of cooperative quasi-species consortia (QS-C) thinking from the more accepted quasispecies equations of Manfred Eigen, provides a conceptual foundation from which concerted action of RNA agents can now be understood. As group membership becomes a basic criteria for the emergence of living systems, we also start to understand why the history and context of social RNA networks become crucial for survival and function. History and context of social RNA networks also lead to the emergence of a natural genetic code. Indeed, this QS-C thinking can also provide us with a transition point between the chemical world of RNA replicators and the living world of RNA agents that actively differentiate self from non-self and generate group identity with membership roles. Importantly the social force of a consortia to solve complex, multilevel problems also depend on using opposing and minority functions. The consortial action of social networks of RNA stem-loops subsequently lead to the evolution of cellular organisms representing a tree of life.

Characterization of natural antisense transcripts arisen from the locus encoding Toxoplasma gondii ubiquitin-like protease

Natural antisense transcripts (NATs) are non-protein coding RNAs that could play an important role in regulating the expression of their counterpart protein encoding sense transcript. Although NATs are widespread in most eukaryotic genomes, very little is known about their functions. This study focuses on gaining a better understanding of the function of NATs in Toxoplasma gondii, a pathogenic unicellular eukaryote. Previously, we characterized the gene encoding the first committed enzyme in sumoylation, named ubiquitin-like protease 1 (TgUlp1), and showed that the expression of TgUlp1 is vital to the life cycle of T. gondii. Interestingly, the locus of TgUlp1 also transcribes a NAT species. Using a dual luciferase assay, we identified the promoter of TgUlp1 NAT to be located within the 3'-region of its counterpart coding sequence. While TgUlp1 mRNA level was detected at a lower level throughout the life cycle of T. gondii, its NAT level was upregulated when the parasite converts from actively replicating tachyzoite form to slowly growing bradyzoite form. To investigate the effect of TgUlp1 NAT on the expression of its counterpart mRNA, we used a reporter system bearing TgUlp1 mRNA sequences and showed that the single-stranded TgUlp1 NAT and its in vitro RNase III processed products have the ability to lower the expression of the reporter system. Using a transgenic Dicer-knockout (TgDicer-KO) strain, we showed that TgDicer is required for the function of TgUlp1 NAT in vivo. The findings strongly suggest that the RNA interference pathway is necessary for the function of TgUlp1 NAT.

Revisiting the Role of Master Regulators in Tomato Ripening

The study of transcriptional regulation of tomato ripening has been led by spontaneous mutations in transcription factor (TF) genes that completely inhibit normal ripening, suggesting that they are 'master regulators'. Studies using CRISPR/Cas9 mutagenesis to produce knockouts of the underlying genes indicate a different picture, suggesting that the regulation is more robust than previously thought. This requires us to revisit our model of the regulation of ripening and replace it with one involving a network of partially redundant components. At the same time, the fast rise of CRISPR/Cas mutagenesis, resulting in unexpectedly weak phenotypes, compared with knockdown technology, suggests that compensatory mechanisms may obscure protein functions. This emphasises the need for assessment of these mechanisms in plants and for the careful design of mutagenesis experiments.

A Single Cell but Many Different Transcripts: A Journey into the World of Long Non-Coding RNAs

In late 2012 it was evidenced that most of the human genome is transcribed but only a small percentage of the transcripts are translated. This observation supported the importance of non-coding RNAs and it was confirmed in several organisms. The most abundant non-translated transcripts are long non-coding RNAs (lncRNAs). In contrast to protein-coding RNAs, they show a more cell-specific expression. To understand the function of lncRNAs, it is fundamental to investigate in which cells they are preferentially expressed and to detect their subcellular localization. Recent improvements of techniques that localize single RNA molecules in tissues like single-cell RNA sequencing and fluorescence amplification methods have given a considerable boost in the knowledge of the lncRNA functions. In recent years, single-cell transcription variability was associated with non-coding RNA expression, revealing this class of RNAs as important transcripts in the cell lineage specification. The purpose of this review is to collect updated information about lncRNA classification and new findings on their function derived from single-cell analysis. We also retained useful for all researchers to describe the methods available for single-cell analysis and the databases collecting single-cell and lncRNA data. Tables are included to schematize, describe, and compare exposed concepts.