Pseudo–Messenger RNA: Phantoms of the Transcriptome

The mammalian transcriptome harbours shadowy entities that resist classification and analysis. In analogy with pseudogenes, we define pseudo–messenger RNA to be RNA molecules that resemble protein-coding mRNA, but cannot encode full-length proteins owing to disruptions of the reading frame. Using a rigorous computational pipeline, which rules out sequencing errors, we identify 10,679 pseudo–messenger RNAs (approximately half of which are transposon-associated) among the 102,801 FANTOM3 mouse cDNAs: just over 10% of the FANTOM3 transcriptome. These comprise not only transcribed pseudogenes, but also disrupted splice variants of otherwise protein-coding genes. Some may encode truncated proteins, only a minority of which appear subject to nonsense-mediated decay. The presence of an excess of transcripts whose only disruptions are opal stop codons suggests that there are more selenoproteins than currently estimated. We also describe compensatory frameshifts, where a segment of the gene has changed frame but remains translatable. In summary, we survey a large class of non-standard but potentially functional transcripts that are likely to encode genetic information and effect biological processes in novel ways. Many of these transcripts do not correspond cleanly to any identifiable object in the genome, implying fundamental limits to the goal of annotating all functional elements at the genome sequence level

A Novel RNA Transcript with Antiapoptotic Function Is Silenced in Fragile X Syndrome

Several genome-wide transcriptomics efforts have shown that a large percentage of the mammalian genome is transcribed into RNAs, however, only a small percentage (1–2%) of these RNAs is translated into proteins. Currently there is an intense interest in characterizing the function of the different classes of noncoding RNAs and their relevance to human disease. Using genomic approaches we discovered FMR4, a primate-specific noncoding RNA transcript (2.4 kb) that resides upstream and likely shares a bidirectional promoter with FMR1. FMR4 is a product of RNA polymerase II and has a similar half-life to FMR1. The CGG expansion in the 5′ UTR of FMR1 appears to affect transcription in both directions as we found FMR4, similar to FMR1, to be silenced in fragile X patients and up-regulated in premutation carriers. Knockdown of FMR4 by several siRNAs did not affect FMR1 expression, nor vice versa, suggesting that FMR4 is not a direct regulatory transcript for FMR1. However, FMR4 markedly affected human cell proliferation in vitro; siRNAs knockdown of FMR4 resulted in alterations in the cell cycle and increased apoptosis, while the overexpression of FMR4 caused an increase in cell proliferation. Collectively, our results demonstrate an antiapoptotic function of FMR4 and provide evidence that a well-studied genomic locus can show unexpected functional complexity. It cannot be excluded that altered FMR4 expression might contribute to aspects of the clinical presentation of fragile X syndrome and/or related disorders

MicroScope: ChIP-seq and RNA-seq software analysis suite for gene expression heatmaps

BACKGROUND: Heatmaps are an indispensible visualization tool for examining large-scale snapshots of genomic activity across various types of next-generation sequencing datasets. However, traditional heatmap software do not typically offer multi-scale insight across multiple layers of genomic analysis (e.g., differential expression analysis, principal component analysis, gene ontology analysis, and network analysis) or multiple types of next-generation sequencing datasets (e.g., ChIP-seq and RNA-seq). As such, it is natural to want to interact with a heatmap’s contents using an extensive set of integrated analysis tools applicable to a broad array of genomic data types. RESULTS: We propose a user-friendly ChIP-seq and RNA-seq software suite for the interactive visualization and analysis of genomic data, including integrated features to support differential expression analysis, interactive heatmap production, principal component analysis, gene ontology analysis, and dynamic network analysis. CONCLUSIONS: MicroScope is hosted online as an R Shiny web application based on the D3 JavaScript library: http://microscopebioinformatics.org/. The methods are implemented in R, and are available as part of the MicroScope project at: https://github.com/Bohdan-Khomtchouk/Microscope

Evidence for natural antisense transcript-mediated inhibition of microRNA function

MicroRNAs (miRNAs) have the potential to regulate diverse sets of mRNA targets. In addition, mammalian genomes contain numerous natural antisense transcripts, most of which appear to be non-protein-coding RNAs (ncRNAs). We have recently identified and characterized a highly conserved non-coding antisense transcript for beta-secretase-1 (BACE1), a critical enzyme in Alzheimer's disease pathophysiology. The BACE1-antisense transcript is markedly up-regulated in brain samples from Alzheimer's disease patients and promotes the stability of the (sense) BACE1 transcript. We report here that BACE1-antisense prevents miRNA-induced repression of BACE1 mRNA by masking the binding site for miR-485-5p. Indeed, miR-485-5p and BACE1-antisense compete for binding within the same region in the open reading frame of the BACE1 mRNA. We observed opposing effects of BACE1-antisense and miR-485-5p on BACE1 protein in vitro and showed that Locked Nucleic Acid-antimiR mediated knockdown of miR-485-5p as well as BACE1-antisense over-expression can prevent the miRNA-induced BACE1 suppression. We found that the expression of BACE1-antisense as well as miR-485-5p are dysregulated in RNA samples from Alzheimer's disease subjects compared to control individuals. Our data demonstrate an interface between two distinct groups of regulatory RNAs in the computation of BACE1 gene expression. Moreover, bioinformatics analyses revealed a theoretical basis for many other potential interactions between natural antisense transcripts and miRNAs at the binding sites of the latter

Defective HNF4alpha-dependent gene expression as a driver of hepatocellular failure in alcoholic hepatitis

Alcoholic hepatitis (AH) is a life-threatening condition characterized by profound hepatocellular dysfunction for which targeted treatments are urgently needed. Identification of molecular drivers is hampered by the lack of suitable animal models. By performing RNA sequencing in livers from patients with different phenotypes of alcohol-related liver disease (ALD), we show that development of AH is characterized by defective activity of liver-enriched transcription factors (LETFs). TGFβ1 is a key upstream transcriptome regulator in AH and induces the use of HNF4α P2 promoter in hepatocytes, which results in defective metabolic and synthetic functions. Gene polymorphisms in LETFs including HNF4α are not associated with the development of AH. In contrast, epigenetic studies show that AH livers have profound changes in DNA methylation state and chromatin remodeling, affecting HNF4α-dependent gene expression. We conclude that targeting TGFβ1 and epigenetic drivers that modulate HNF4α-dependent gene expression could be beneficial to improve hepatocellular function in patients with AH

The Reality of Pervasive Transcription

Despite recent controversies, the evidence that the majority of the human genome is transcribed into RNA remains strong