Does every transcript originate from a gene?

Change in energy-consuming strategy, nucleolar metabolism and physical defense in Macrobrachium rosenbergii after acute and chronic polystyrene nanoparticles exposure

The COVID-19 pandemic has further intensified plastic pollution due to the escalated use of single-use gloves and masks, consequently leading to the widespread presence of microplastics (MPs) and nanoplastics (NPs) in major rivers and lakes worldwide. Macrobrachium rosenbergii has become an important experimental subject due to its ecological role and environmental sensitivity. In this study, we sought to comprehend the ramifications of NPs on the widely-distributed freshwater prawn, M rosenbergii, by conducting a detailed analysis of its responses to NPs after both 96 h and 30 days of exposure. The transcriptome analysis revealed 918 differentially expressed unigenes (DEGs) after 30 days of NPs exposure (356 upregulated, 562 downregulated) and 2376 DEGs after 96 h of NPs exposure (1541 upregulated, 835 downregulated). The results of DEGs expression indicated that acute NPs exposure enhanced carbohydrate transport and metabolism, fostering chitin and extracellular matrix processes. In contrast, chronic NPs exposure induced nucleolar stress in M. rosenbergii, impeding ribosome development and mRNA maturation while showing no significant changes in glucose metabolism. Our findings underscore the M. rosenbergii distinct coping mechanisms during acute and chronic NPs exposure, elucidating its vital adaptive strategies. These results contribute to our understanding of the ecological implications of NPs pollution and its impact on aquatic animals.

Complexities of mammalian transcriptome revealed by targeted RNA enrichment techniques

Studies using highly sensitive targeted RNA enrichment methods have shown that a large portion of the human transcriptome remains to be discovered and that most of the genome is transcribed in a complex, interleaved fashion characterized by a complex web of transcripts emanating from protein coding and noncoding loci. These results resonate with those from single-cell transcriptome profiling endeavors that reveal the existence of multiple novel, cell type-specific transcripts and clearly demonstrate that our understanding of the complexities of the human transcriptome is far from being complete. Here, we review the current status of the targeted RNA enrichment techniques, their application to the discovery of novel cell type-specific transcripts, and their impact on our understanding of the human genome and transcriptome.

Methods to Analyze the Non-Coding RNA Interactome—Recent Advances and Challenges

Most of the human genome is transcribed to generate a multitude of non-coding RNAs. However, while these transcripts have generated an immense amount of scientific interest, their biological function remains a subject of an intense debate. Understanding mechanisms of action of non-coding RNAs is a key to addressing the issue of biological relevance of these transcripts. Based on some well-understood non-coding RNAs that function inside the cell by interacting with other molecules, it is generally believed many other non-coding transcripts could also function in a similar fashion. Therefore, development of methods that can map RNA interactome is the key to understanding functionality of the extensive cellular non-coding transcriptome. Here, we review the vast progress that has been made in the past decade in technologies that can map RNA interactions with different sites in DNA, proteins or other RNA molecules; the general approaches used to validate the existence of novel interactions; and the challenges posed by interpreting the data obtained using the interactome mapping methods.

Reverse-genetics studies of lncRNAs-what we have learnt and paths forward

Long non-coding RNAs (lncRNAs) represent a major fraction of the transcriptome in multicellular organisms. Although a handful of well-studied lncRNAs are broadly recognized as biologically meaningful, the fraction of such transcripts out of the entire collection of lncRNAs remains a subject of vigorous debate. Here we review the evidence for and against biological functionalities of lncRNAs and attempt to arrive at potential modes of lncRNA functionality that would reconcile the contradictory conclusions. Finally, we discuss different strategies of phenotypic analyses that could be used to investigate such modes of lncRNA functionality.

A CRISPR/Cas13-based approach demonstrates biological relevance of vlinc class of long non-coding RNAs in anticancer drug response

Long non-coding (lnc) RNAs represent a fascinating class of transcripts that remains highly controversial mainly due to ambiguity surrounding overall biological relevance of these RNAs. Multitude of reverse genetics studies showing functionality of lncRNAs are unfortunately based on assays that are either plagued by non-specific effects and/or cannot unambiguously assign observed phenotypes to the transcript per se. Here, we show application of the novel CRISPR/Cas13 RNA knockdown system that has superior specificity compared to other transcript-targeting knockdown methods like RNAi. We applied this method to a novel widespread subclass of nuclear lncRNAs - very long intergenic non-coding (vlinc) RNAs - in a high-throughput phenotypic assay based on survival challenge in response to anticancer drug treatments. We used multiple layers of controls including mismatch control for each targeting gRNA to ensure uncovering true phenotype-transcript relationships. We found evidence supporting importance for cellular survival for up to 60% of the tested protein-coding mRNAs and, importantly, 64% of vlincRNAs. Overall, this study demonstrates utility of CRISPR/Cas13 as a highly sensitive and specific tool for reverse genetics study of both protein-coding genes and lncRNAs. Furthermore, importantly, this approach provides evidence supporting biological significance of the latter transcripts in anticancer drug response.

Long non-coding RNAs display higher natural expression variation than protein-coding genes in healthy humans

Background

Long non-coding RNAs (lncRNAs) are increasingly implicated as gene regulators and may ultimately be more numerous than protein-coding genes in the human genome. Despite large numbers of reported lncRNAs, reference annotations are likely incomplete due to their lower and tighter tissue-specific expression compared to mRNAs. An unexplored factor potentially confounding lncRNA identification is inter-individual expression variability. Here, we characterize lncRNA natural expression variability in human primary granulocytes.

Results

We annotate granulocyte lncRNAs and mRNAs in RNA-seq data from 10 healthy individuals, identifying multiple lncRNAs absent from reference annotations, and use this to investigate three known features (higher tissue-specificity, lower expression, and reduced splicing efficiency) of lncRNAs relative to mRNAs. Expression variability was examined in seven individuals sampled three times at 1- or more than 1-month intervals. We show that lncRNAs display significantly more inter-individual expression variability compared to mRNAs. We confirm this finding in two independent human datasets by analyzing multiple tissues from the GTEx project and lymphoblastoid cell lines from the GEUVADIS project. Using the latter dataset we also show that including more human donors into the transcriptome annotation pipeline allows identification of an increasing number of lncRNAs, but minimally affects mRNA gene number.

Conclusions

A comprehensive annotation of lncRNAs is known to require an approach that is sensitive to low and tight tissue-specific expression. Here we show that increased inter-individual expression variability is an additional general lncRNA feature to consider when creating a comprehensive annotation of human lncRNAs or proposing their use as prognostic or disease markers.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-0873-8) contains supplementary material, which is available to authorized users.