Differentiating Protein-Coding and Noncoding RNA: Challenges and Ambiguities

The assumption that RNA can be readily classified into either protein-coding or non-protein–coding categories has pervaded biology for close to 50 years. Until recently, discrimination between these two categories was relatively straightforward: most transcripts were clearly identifiable as protein-coding messenger RNAs (mRNAs), and readily distinguished from the small number of well-characterized non-protein–coding RNAs (ncRNAs), such as transfer, ribosomal, and spliceosomal RNAs. Recent genome-wide studies have revealed the existence of thousands of noncoding transcripts, whose function and significance are unclear. The discovery of this hidden transcriptome and the implicit challenge it presents to our understanding of the expression and regulation of genetic information has made the need to distinguish between mRNAs and ncRNAs both more pressing and more complicated. In this Review, we consider the diverse strategies employed to discriminate between protein-coding and noncoding transcripts and the fundamental difficulties that are inherent in what may superficially appear to be a simple problem. Misannotations can also run in both directions: some ncRNAs may actually encode peptides, and some of those currently thought to do so may not. Moreover, recent studies have shown that some RNAs can function both as mRNAs and intrinsically as functional ncRNAs, which may be a relatively widespread phenomenon. We conclude that it is difficult to annotate an RNA unequivocally as protein-coding or noncoding, with overlapping protein-coding and noncoding transcripts further confounding this distinction. In addition, the finding that some transcripts can function both intrinsically at the RNA level and to encode proteins suggests a false dichotomy between mRNAs and ncRNAs. Therefore, the functionality of any transcript at the RNA level should not be discounted

Deducing the Temporal Order of Cofactor Function in Ligand-Regulated Gene Transcription: Theory and Experimental Verification

Cofactors are intimately involved in steroid-regulated gene expression. Two critical questions are (1) the steps at which cofactors exert their biological activities and (2) the nature of that activity. Here we show that a new mathematical theory of steroid hormone action can be used to deduce the kinetic properties and reaction sequence position for the functioning of any two cofactors relative to a concentration limiting step (CLS) and to each other. The predictions of the theory, which can be applied using graphical methods similar to those of enzyme kinetics, are validated by obtaining internally consistent data for pair-wise analyses of three cofactors (TIF2, sSMRT, and NCoR) in U2OS cells. The analysis of TIF2 and sSMRT actions on GR-induction of an endogenous gene gave results identical to those with an exogenous reporter. Thus new tools to determine previously unobtainable information about the nature and position of cofactor action in any process displaying first-order Hill plot kinetics are now available

lncRNAdb: a reference database for long noncoding RNAs

Large numbers of long RNAs with little or no protein-coding potential [long noncoding RNAs (lncRNAs)] are being identified in eukaryotes. In parallel, increasing data describing the expression profiles, molecular features and functions of individual lncRNAs in a variety of systems are accumulating. To enable the systematic compilation and updating of this information, we have developed a database (lncRNAdb) containing a comprehensive list of lncRNAs that have been shown to have, or to be associated with, biological functions in eukaryotes, as well as messenger RNAs that have regulatory roles. Each entry contains referenced information about the RNA, including sequences, structural information, genomic context, expression, subcellular localization, conservation, functional evidence and other relevant information. lncRNAdb can be searched by querying published RNA names and aliases, sequences, species and associated protein-coding genes, as well as terms contained in the annotations, such as the tissues in which the transcripts are expressed and associated diseases. In addition, lncRNAdb is linked to the UCSC Genome Browser for visualization and Noncoding RNA Expression Database (NRED) for expression information from a variety of sources. lncRNAdb provides a platform for the ongoing collation of the literature pertaining to lncRNAs and their association with other genomic elements. lncRNAdb can be accessed at: http://www.lncrnadb.org/

Multiple Roles for the Non-Coding RNA SRA in Regulation of Adipogenesis and Insulin Sensitivity

Peroxisome proliferator-activated receptor-γ (PPARγ) is a master transcriptional regulator of adipogenesis. Hence, the identification of PPARγ coactivators should help reveal mechanisms controlling gene expression in adipose tissue development and physiology. We show that the non-coding RNA, Steroid receptor RNA Activator (SRA), associates with PPARγ and coactivates PPARγ-dependent reporter gene expression. Overexpression of SRA in ST2 mesenchymal precursor cells promotes their differentiation into adipocytes. Conversely, knockdown of endogenous SRA inhibits 3T3-L1 preadipocyte differentiation. Microarray analysis reveals hundreds of SRA-responsive genes in adipocytes, including genes involved in the cell cycle, and insulin and TNFα signaling pathways. Some functions of SRA may involve mechanisms other than coactivation of PPARγ. SRA in adipocytes increases both glucose uptake and phosphorylation of Akt and FOXO1 in response to insulin. SRA promotes S-phase entry during mitotic clonal expansion, decreases expression of the cyclin-dependent kinase inhibitors p21Cip1 and p27Kip1, and increases phosphorylation of Cdk1/Cdc2. SRA also inhibits the expression of adipocyte-related inflammatory genes and TNFα-induced phosphorylation of c-Jun NH2-terminal kinase. In conclusion, SRA enhances adipogenesis and adipocyte function through multiple pathways

A Critical Analysis of Atoh7 (Math5) mRNA Splicing in the Developing Mouse Retina

The Math5 (Atoh7) gene is transiently expressed during retinogenesis by progenitors exiting mitosis, and is essential for ganglion cell (RGC) development. Math5 contains a single exon, and its 1.7 kb mRNA encodes a 149-aa polypeptide. Mouse Math5 mutants have essentially no RGCs or optic nerves. Given the importance of this gene in retinal development, we thoroughly investigated the possibility of Math5 mRNA splicing by Northern blot, 3′RACE, RNase protection assays, and RT-PCR, using RNAs extracted from embryonic eyes and adult cerebellum, or transcribed in vitro from cDNA clones. Because Math5 mRNA contains an elevated G+C content, we used graded concentrations of betaine, an isostabilizing agent that disrupts secondary structure. Although ∼10% of cerebellar Math5 RNAs are spliced, truncating the polypeptide, our results show few, if any, spliced Math5 transcripts exist in the developing retina (<1%). Rare deleted cDNAs do arise via RT-mediated RNA template switching in vitro, and are selectively amplified during PCR. These data differ starkly from a recent study (Kanadia and Cepko 2010), which concluded that the vast majority of Math5 and other bHLH transcripts are spliced to generate noncoding RNAs. Our findings clarify the architecture of the Math5 gene and its mechanism of action. These results have implications for all members of the bHLH gene family, for any gene that is alternatively spliced, and for the interpretation of all RT-PCR experiments

SRA Regulates Adipogenesis by Modulating p38/JNK Phosphorylation and Stimulating Insulin Receptor Gene Expression and Downstream Signaling

The Steroid Receptor RNA Activator (SRA) enhances adipogenesis and increases both glucose uptake and phosphorylation of Akt and FOXO1 in response to insulin. To assess the mechanism, we differentiated ST2 mesenchymal precursor cells that did or did not overexpress SRA into adipocytes using combinations of methylisobutylxanthine, dexamethasone and insulin. These studies showed that SRA overexpression promotes full adipogenesis in part by stimulation of insulin/insulin-like growth factor-1 (IGF-1) signaling. SRA overexpression inhibited phosphorylation of p38 mitogen activated protein kinase (MAPK) and c-Jun NH2-terminal kinase (JNK) in the early differentiation of ST2 cells. Conversely, knockdown of endogenous SRA in 3T3-L1 cells increased phosphorylation of JNK. Knockdown of SRA in mature 3T3-L1 adipocytes reduced insulin receptor (IR) mRNA and protein levels, which led to decreased autophosphorylation of IRβ and decreased phosphorylation of insulin receptor substrate-1 (IRS-1) and Akt. This likely reflects a stimulatory role of SRA on IR transcription, as transfection studies showed that SRA increased expression of an IR promoter-luciferase reporter construct

Alternative Splicing of the First Intron of the Steroid Receptor RNA Activator (SRA) Participates in the Generation of Coding and Noncoding RNA Isoforms in Breast Cancer Cell Lines

Reproduced by generous permission of the publisher.http://www.liebertpub.com/The Steroid Receptor RNA Activator 1 (SRA1) has originally been described as a noncoding RNA specifically activating steroid receptor transcriptional activity. We have, however, identified, in human breast tissue, exon- 1 extended SRA1 isoforms containing two initiating AUG codons and encoding a protein we called SRAP. We recently reported a decreased estrogen receptor activity in breast cancer cells overexpressing SRAP, suggesting antagonist roles played by SRA1 RNA and SRAP. SRA1 appears to be the first example of a molecule active both at the RNA and at the protein level. No data are currently available regarding the mechanisms possibly involved in the generation of coding and noncoding functional SRA1 RNAs. Using 5 -Rapid Amplification of cDNA Extremities (5 -RACE), we have herein identified several putative transcription initiation sites surrounding the second methionine codon and used to generate coding SRA1 transcripts. In the process, we also identified an alternatively spliced noncoding SRA1 transcript still containing an intron-1 sequence. Using targeted RT-PCR approaches, we confirmed the presence in breast cancer cell lines of SRA1 RNAs containing a full as well as a partial intron-1 sequence and established that the relative proportion of these RNAs varied within breast cancer cell lines. Using a “minigene” strategy, we also showed that artificial RNAs containing the SRA1 intron-1 sequence are alternatively spliced in breast cancer cell lines. Interestingly, the splicing pattern of the minigene products parallels the one of the endogenous SRA1 transcripts. Altogether, our data suggest that the primary genomic sequence in and around intron-1 is sufficient to lead to a differential splicing of this intron. We propose that alternative splicing of intron-1 is one mechanism used by breast cancer cells to regulate the balance between coding and functional noncoding SRA1 RNAs