Characterization of adapt33, a stress-inducible riboregulator

Divergent regulation of lncRNA expression by ischemia in adult and aging mice

Elderly patients have increased susceptibility to acute kidney injury (AKI). Long noncoding RNAs (lncRNA) are key regulators of cellular processes, and have been implicated in both aging and AKI. Our aim was to study the effects of aging and ischemia-reperfusion injury (IRI) on the renal expression of lncRNAs. Adult and old (10- and 26-30-month-old) C57BL/6 N mice were subjected to unilateral IRI followed by 7 days of reperfusion. Renal expression of 90 lncRNAs and mRNA expression of injury, regeneration, and fibrosis markers was measured by qPCR in the injured and contralateral control kidneys. Tubular injury, regeneration, and fibrosis were assessed by histology. Urinary lipocalin-2 excretion was increased in old mice prior to IRI, but plasma urea was similar. In the control kidneys of old mice tubular cell necrosis and apoptosis, mRNA expression of kidney injury molecule-1, fibronectin-1, p16, and p21 was elevated. IRI increased plasma urea concentration only in old mice, but injury, regeneration, and fibrosis scores and their mRNA markers were similar in both age groups. AK082072 and Y lncRNAs were upregulated, while H19 and RepA transcript were downregulated in the control kidneys of old mice. IRI upregulated Miat, Igf2as, SNHG5, SNHG6, RNCR3, Malat1, Air, Linc1633, and Neat1 v1, while downregulated Linc1242. LncRNAs H19, AK082072, RepA transcript, and Six3os were influenced by both aging and IRI. Our results indicate that both aging and IRI alter renal lncRNA expression suggesting that lncRNAs have a versatile and complex role in aging and kidney injury. An Ingenuity Pathway Analysis highlighted that the most downregulated H19 may be linked to aging/senescence through p53.

lncRNA 5430416N02Rik Promotes the Proliferation of Mouse Embryonic Stem Cells by Activating Mid1 Expression through 3D Chromatin Architecture

Both 3D chromatin architecture and long non-coding RNAs (lncRNAs) play essential roles in pluripotency maintenance. However, whether lncRNAs are involved in organizing 3D chromatin structure remains largely unexplored. We identified 39 lncRNAs bound by Klf4, among which we further revealed the 5430416N02Rik promoter is a chromatin interaction hub. Knockout of the 5430416N02Rik locus reduces the proliferation rate of embryonic stem cells (ESCs). Moreover, deleting both the promoter and the gene body of 5430416N02Rik causes a more severe proliferation defect and has a more profound impact on the transcriptome than deleting the gene body alone. The reduced proliferation of the 5430416N02Rik locus knockout ESCs is mainly due to the downregulation of Mid1, the expression of which requires the inter-chromosomal interaction between Mid1 and 5430416N02Rik loci. In summary, our data demonstrated that the lncRNA 5430416N02Rik gene locus maintains the fast proliferation of ESCs by activating the expression of Mid1 through chromatin interaction.

•

lncRNA 5430416N02Rik participates in organizing 3D chromatin architecture

•

lncRNA gene 5430416N02Rik promoter is a chromatin interaction hub

•

Knockout of 5430416N02Rik locus reduces the proliferation rate of ESCs

•

Interaction between 5430416N02Rik and Mid1 loci activates Mid1 transcription

Nonsense-mediated decay factor SMG7 sensitizes cells to TNFα-induced apoptosis via CYLD tumor suppressor and the noncoding oncogene Pvt1

Nonsense‐mediated decay (NMD) proteins are responsible for the surveillance and degradation of aberrant RNAs. Suppressor with morphogenetic effect on genitalia 7 (SMG7) is an NMD complex protein and a regulator of tumor necrosis factor (TNF)‐induced extrinsic apoptosis; however, this unique function has not been explored in detail. In this study, we show that loss of Smg7 leads to unrestricted expression of long noncoding RNAs (lncRNAs) in addition to NMD targets. Functional analysis of Smg7^−/− cells showed downregulation of the tumor suppressor cylindromatosis (CYLD) and diminished caspase activity, thereby switching cells to nuclear factor‐κB (NF‐κB)‐mediated protection. This positive relationship between SMG7 and CYLD was found to be widely conserved in human cancer cell lines and renal carcinoma samples from The Cancer Genome Atlas. In addition to CYLD suppression, upregulation of lncRNAs Pvt1 and Adapt33 rendered cells resistant to TNF, while pharmacologic inhibition of NF‐κB in Pvt1‐overexpressing TNF‐resistant cells and Smg7‐deficient spheroids re‐established TNF‐induced lethality. Thus, loss of SMG7 decouples regulation of two separate oncogenic factors with cumulative downstream effects on the NF‐κB pathway. The data highlight a novel and specific regulation of oncogenic factors by SMG7 and pinpoint a composite tumor suppressor role in response to TNF.

Genome-wide identification and characterization of long non-coding RNAs involved in the early somatic embryogenesis in Dimocarpus longan Lour

BACKGROUND

Long non-coding RNAs (lncRNAs) are involved in variable cleavage, transcriptional interference, regulation of DNA methylation and protein modification. However, the regulation of lncRNAs in plant somatic embryos remains unclear. The longan (Dimocarpus longan) somatic embryogenesis (SE) system is a good system for research on longan embryo development.

RESULTS

In this study, 7643 lncRNAs obtained during early SE in D. longan were identified by high-throughput sequencing, among which 6005 lncRNAs were expressed. Of the expressed lncRNAs, 4790 were found in all samples and 160 were specifically expressed in embryogenic callus (EC), 154 in incomplete embryogenic compact structures (ICpECs), and 376 in globular embryos (GEs). We annotated the 6005 expressed lncRNAs, and 1404 lncRNAs belonged to 506 noncoding RNA (ncRNA) families and 4682 lncRNAs were predicted to target protein-coding genes. The target genes included 5051 cis-regulated target genes (5712 pairs) and 1605 trans-regulated target genes (3618 pairs). KEGG analysis revealed that most of the differentially expressed target genes (mRNAs) of the lncRNAs were enriched in the "plant-pathogen interaction" and "plant hormone signaling" pathways during early longan SE. Real-time quantitative PCR confirmed that 20 selected lncRNAs showed significant differences in expression and that five lncRNAs were related to auxin response factors. Compared with the FPKM expression trends, 16 lncRNA expression trends were the same in qPCR. In lncRNA-miRNA-mRNA relationship prediction, 40 lncRNAs were predicted to function as eTMs for 15 miRNAs and 7 lncRNAs were identified as potential miRNA precursors. In addition, we verified the lncRNA-miRNA-mRNA regulatory relationships by transient expression of miRNAs (miR172a, miR159a.1 and miR398a).

CONCLUSION

Analyses of lncRNAs during early longan SE showed that differentially expressed lncRNAs were involved in expression regulation at each SE stage, and may form a regulatory network with miRNAs and mRNAs. These findings provide new insights into lncRNAs and lay a foundation for future functional analysis of lncRNAs during early longan SE.

Global insights into the Chinese hamster and CHO cell transcriptomes

Transcriptomics is increasingly being used on Chinese hamster ovary (CHO) cells to unveil physiological insights related to their performance during production processes. The rich transcriptome data can be exploited to provide impetus for systems investigation such as modeling the central carbon metabolism or glycosylation pathways, or even building genome-scale models. To harness the power of transcriptome assays, we assembled and annotated a set of RNA-Seq data from multiple CHO cell lines and Chinese hamster tissues, and constructed a DNA microarray. The identity of genes involved in major functional pathways and their transcript levels generated in this study will serve as a reference for future studies employing kinetic models. In particular, the data on glycolysis and glycosylation pathways indicate that the variability of gene expression level among different cell lines and tissues may contribute to their differences in metabolism and glycosylation patterns. Thereby, these insights can potentially lead to opportunities for cell engineering. This repertoire of transcriptome data also enables the identification of potential sequence variants in cell lines and allows tracing of cell lineages. Overall the study is an illustration of the potential benefit of RNA-Seq that is yet to be exploited.

Annotation of long non-coding RNAs expressed in collaborative cross founder mice in response to respiratory virus infection reveals a new class of interferon-stimulated transcripts

The outcome of respiratory virus infection is determined by a complex interplay of viral and host factors. Some potentially important host factors for the antiviral response, whose functions remain largely unexplored, are long non-coding RNAs (lncRNAs). Here we systematically inferred the regulatory functions of host lncRNAs in response to influenza A virus and severe acute respiratory syndrome coronavirus (SARS-CoV) based on their similarity in expression with genes of known function. We performed total RNA-Seq on viral-infected lungs from eight mouse strains, yielding a large data set of transcriptional responses. Overall 5,329 lncRNAs were differentially expressed after infection. Most of the lncRNAs were co-expressed with coding genes in modules enriched in genes associated with lung homeostasis pathways or immune response processes. Each lncRNA was further individually annotated using a rank-based method, enabling us to associate 5,295 lncRNAs to at least one gene set and to predict their potential cis effects. We validated the lncRNAs predicted to be interferon-stimulated by profiling mouse responses after interferon-α treatment. Altogether, these results provide a broad categorization of potential lncRNA functions and identify subsets of lncRNAs with likely key roles in respiratory virus pathogenesis. These data are fully accessible through the MOuse NOn-Code Lung interactive database (MONOCLdb).

Non-coding RNAs in homeostasis, disease and stress responses: an evolutionary perspective

Cells and organisms are subject to challenges and perturbations in their environment and physiology in all stages of life. The molecular response to such changes, including insulting conditions such as pathogen infections, involves coordinated modulation of gene expression programmes and has not only homeostatic but also ecological and evolutionary importance. Although attention has been primarily focused on signalling pathways and protein networks, non-coding RNAs (ncRNAs), which comprise a significant output of the genomes of prokaryotes and especially eukaryotes, are increasingly implicated in the molecular mechanisms of these responses. Long and short ncRNAs not only regulate development and cell physiology, they are also involved in disease states, including cancers, in host-pathogen interactions, and in a variety of stress responses. Indeed, regulatory RNAs are part of genetically encoded response networks and also underpin epigenetic processes, which are emerging as key mechanisms of adaptation and transgenerational inheritance. Here we present the growing evidence that ncRNAs are intrinsically involved in cellular and organismal adaptation processes, in both robustness and protection to stresses, as well as in mechanisms generating evolutionary change.

Identification of long stress-induced non-coding transcripts that have altered expression in cancer

It has recently become clear that the transcriptional output of the human genome is far more abundant than previously anticipated, with the vast majority of transcripts not coding for protein. Utilizing whole-genome tiling arrays, we analyzed the transcription across the entire genome in both normal human bronchial epithelial cells (NHBE) and NHBE cells exposed to the tobacco carcinogen NNK. Our efforts focused on the characterization of non-coding transcripts that were greater than 300 nucleotides in length and whose expression was increased in response to NNK. We identified 12 Long Stress-Induced Non-coding Transcripts that we term LSINCTs. Northern blot analysis revealed that these transcripts were larger than predicted from the tiling array data. Quantitative real-time RT-PCR performed across a panel of normal cell lines indicates that these transcripts are more abundantly expressed in rapidly growing tissues or in tissues that are more prone to cellular stress. These transcripts that have increased expression after exposure to NNK also had increased expression in a number of lung cancer cell lines and also in many breast cancer cell lines. Collectively, our results identified a new class of long stress responsive non-coding transcripts, LSINCTs, which have increased expression in response to DNA damage induced by NNK. LSINCTs interestingly also have increased expression in a number of cancer-derived cell lines, indicating that the expression is increased in both, correlating cellular stress and cancer.

A new paradigm for developmental biology

It is usually thought that the development of complex organisms is controlled by protein regulatory factors and morphogenetic signals exchanged between cells and differentiating tissues during ontogeny. However, it is now evident that the majority of all animal genomes is transcribed, apparently in a developmentally regulated manner, suggesting that these genomes largely encode RNA machines and that there may be a vast hidden layer of RNA regulatory transactions in the background. I propose that the epigenetic trajectories of differentiation and development are primarily programmed by feed-forward RNA regulatory networks and that most of the information required for multicellular development is embedded in these networks, with cell–cell signalling required to provide important positional information and to correct stochastic errors in the endogenous RNA-directed program.

Genetic regulation by non-coding RNAs

Large scale cDNA sequencing and genome tiling array studies have shown that around 50% of genomic DNA in humans is transcribed, of which 2% is translated into proteins and the remaining 98% is non-coding RNAs (ncRNAs). There is mounting evidence that these ncRNAs play critical roles in regulating DNA structure, RNA expression, protein translation and protein functions through multiple genetic mechanisms, and thus affect normal development of organisms at all levels. Today, we know very little about the regulatory mechanisms and functions of these ncRNAs, which is clearly essential knowledge for understanding the secret of life. To promote this emerging research subject of critical importance, in this paper we review (1) ncRNAs' past and present, (2) regulatory mechanisms and their functions, (3) experimental strategies for identifying novel ncRNAs, (4) experimental strategies for investigating their functions, and (5) methodologies and examples of the application of ncRNAs.

Non-coding RNAs: New players in eukaryotic biology

The completion of the human, mouse and other eukaryotic genomes were important scientific milestones, but they were just small steps towards the understanding of eukaryotic biology. Recent transcriptome analysis and different experimental approaches have identified a surprisingly large number of non-coding RNAs (ncRNAs) in eukaryotic cells. ncRNAs comprise microRNAs, anti-sense transcripts and other Transcriptional Units containing a high density of stop codons and lacking any extensive "Open Reading Frame". They have been shown to regulate gene expression by novel mechanisms such as RNA interference, gene co-suppression, gene silencing, imprinting and DNA demethylation. It is becoming clear that these novel RNAs perform critical functions during development and cell differentiation. There is also mounting evidence of their involvement in cancer and neurological diseases. Together, all this information indicates that ncRNAs are emerging as a new class of functional transcripts in eukaryotes. Therefore, great challenges lie in the years ahead: understanding the molecular biology of higher organisms will require revealing all proteins (Proteome), all ncRNAs (RNome) and their interactions (Interactome) in the complex molecular scenario within eukaryotic cells.