ABSTRACT: Recent genome-wide interrogations of transcribed RNA have yielded compelling evidence for pervasive and complex transcription throughout a large majority of the human genome. Tens of thousands of noncoding RNA transcripts have been identified, most of which have yet to be functionally characterized. Along with the revelation that noncoding RNAs in the human genome are surprisingly abundant, there has been a surge in molecular and genetic data showing important and diverse regulatory roles for noncoding RNA. In this report, we summarize the potential roles that noncoding RNAs may play in the molecular pathogenesis of different mental retardation disorders. We suspect that these findings are just the tip of the iceberg, with noncoding RNAs possibly being involved in disease pathogenesis at different levels and through multiple distinct mechanisms.
Project description:BACKGROUND: Within the last decade a large number of noncoding RNA genes have been identified, but this may only be the tip of the iceberg. Using comparative genomics a large number of sequences that have signals concordant with conserved RNA secondary structures have been discovered in the human genome. Moreover, genome wide transcription profiling with tiling arrays indicate that the majority of the genome is transcribed. RESULTS: We have combined tiling array data with genome wide structural RNA predictions to search for novel noncoding and structural RNA genes that are expressed in the human neuroblastoma cell line SK-N-AS. Using this strategy, we identify thousands of human candidate RNA genes. To further verify the expression of these genes, we focused on candidate genes that had a stable hairpin structures or a high level of covariance. Using northern blotting, we verify the expression of 2 out of 3 of the hairpin structures and 3 out of 9 high covariance structures in SK-N-AS cells. CONCLUSION: Our results demonstrate that many human noncoding, structured and conserved RNA genes remain to be discovered and that tissue specific tiling array data can be used in combination with computational predictions of sequences encoding structural RNAs to improve the search for such genes.
Project description:Long noncoding RNAs have been shown to play crucial roles in cancer biology, while the long noncoding RNA landscapes of pancreatic ductal adenocarcinoma have not been completely characterized. We aimed to determine whether long noncoding RNA could serve as early diagnostic biomarkers for pancreatic ductal adenocarcinoma.We conducted a genome-wide microarray analysis on pancreatic ductal adenocarcinoma and their adjacent noncancerous tissues from 8 Chinese patients.A total of 3352 significantly differentially expressed long noncoding RNAs were detected. Of total, 1249 long noncoding RNAs were upregulated and 2103 were downregulated (fold change ?2, P < 0.05, FDR <0.05). These differentially expressed long noncoding RNAs were not evenly distributed among chromosomes in human genome. Hierarchical clustering of these differentially expressed long noncoding RNAs revealed large variabilities in long noncoding RNA expression among individual patient, indicating that certain long noncoding RNAs could play a unique role or be used as a biomarker for specific subtype of pancreatic ductal adenocarcinoma. Gene Ontology enrichment and pathway analysis identified several remarkably dysregulated pathways in pancreatic ductal adenocarcinoma tissue, such as interferon-?-mediated signaling pathway, mitotic cell cycle and proliferation, extracellular matrix receptor interaction, focal adhesion, and regulation of actin cytoskeleton. The co-expression network analysis detected 393 potential interactions between 80 differentially expressed long noncoding RNAs and 105 messenger RNAs. We experimentally verified 7 most markedly dysregulated long noncoding RNAs from the network.Our study provided a genome-wide survey of dysregulated long noncoding RNAs and long noncoding RNA/messenger RNA co-regulation networks in pancreatic ductal adenocarcinoma tissue. These dysregulated long noncoding RNA/messenger RNA networks could be used as biomarkers to provide early diagnosis of pancreatic ductal adenocarcinoma or its subtype, predict prognosis, and evaluate treatment efficacy.
Project description:The correlation between diabetes and systematic well-being on human life has long established. As a common complication of diabetes, the prevalence of diabetic nephropathy (DN) has been increasing globally. DN is known to be a major cause of end-stage kidney disease (ESKD). Till now, the molecular mechanisms for DN have not been fully explored and the effective therapies are still lacking. Noncoding RNAs are a class of RNAs produced by genome transcription that cannot be translated into proteins. It has been documented that ncRNAs participate in the pathogenesis of DN by regulating inflammation, apoptosis, autophagy, cell proliferation, and other pathological processes. In this review, the pathological roles and diagnostic and therapeutic potential of three types of ncRNAs (microRNA, long noncoding RNA, and circular RNA) in the progression of DN are summarized and illustrated.
Project description:Gastric cancer is one of the most commonly occurring cancers worldwide. Investigation of long noncoding RNAs is of increasing interest, particularly in relation to their contribution to progression and prognosis of gastric cancers; however, insufficient studies been performed investigating the part of long noncoding RNAs play in gastric cancer carcinogenesis. Patterns of dysregulated long noncoding RNA and messenger RNA between mucosa gastric cancer and adjacent normal tissues were identified using long noncoding RNAs microarray analysis. Quantitative real-time polymerase chain reaction was conducted as a means to verify the obtained data. Both Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were subsequently used to investigate the function of dysregulated long noncoding RNAs and messenger RNAs. Cis and trans action was used to predict the possible targets of long noncoding RNAs, and a coexpression network was created to simulate the complex intergenic interactions. Ninety-five dysregulated long noncoding RNAs and 123 messenger RNAs were identified, and quantitative real-time polymerase chain reaction was used to validate 6 filtered long noncoding RNAs. Gene Ontology and KEGG pathway analyses identified several remarkably biological processes and signaling pathways, including spliceosome, RNA transport, and ubiquitin-mediated proteolysis. The transcriptional factors MYC, GABPA, and E2F1 were found to play a central function in the long noncoding RNAs process, as indicated by the coexpression network. This study revealed the dysregulated long noncoding RNA profiles of mucosal gastric cancer. The results shed light on the biological function of long noncoding RNAs in gastric cancer pathogenesis. This provides useful information for exploring potential early screening biomarkers in gastric cancer.
Project description:Rrp6-mediated nuclear RNA surveillance tunes eukaryotic transcriptomes through noncoding RNA degradation and mRNA quality control, including exosomal RNA decay and transcript retention triggered by defective RNA processing. It is unclear whether Rrp6 can positively regulate noncoding RNAs and whether RNA retention occurs in normal cells. Here we report that AtRRP6L1, an Arabidopsis Rrp6-like protein, controls RNA-directed DNA methylation through positive regulation of noncoding RNAs. Discovered in a forward genetic screen, AtRRP6L1 mutations decrease DNA methylation independently of exosomal RNA degradation. Accumulation of Pol V-transcribed scaffold RNAs requires AtRRP6L1 that binds to RNAs in vitro and in vivo. AtRRP6L1 helps retain Pol V-transcribed RNAs in chromatin to enable their scaffold function. In addition, AtRRP6L1 is required for genome-wide Pol IV-dependent siRNA production that may involve retention of Pol IV transcripts. Our results suggest that AtRRP6L1 functions in epigenetic regulation by helping with the retention of noncoding RNAs in normal cells.
Project description:Head and neck squamous cell carcinoma persists as one of the most common and deadly malignancies, with early detection and effective treatment still posing formidable challenges. To expand our currently sparse knowledge of the noncoding alterations involved in the disease and identify potential biomarkers and therapeutic targets, we globally profiled the dysregulation of small nucleolar and long noncoding RNAs in head and neck tumors. Using next-generation RNA-sequencing data from 40 pairs of tumor and matched normal tissues, we found 2808 long noncoding RNA (lncRNA) transcripts significantly differentially expressed by a fold change magnitude ?2. Meanwhile, RNA-sequencing analysis of 31 tumor-normal pairs yielded 33 significantly dysregulated small nucleolar RNAs (snoRNA). In particular, we identified two dramatically down-regulated lncRNAs and one down-regulated snoRNA whose expression levels correlated significantly with overall patient survival, suggesting their functional significance and clinical relevance in head and neck cancer pathogenesis. We confirmed the dysregulation of these noncoding RNAs in head and neck cancer cell lines derived from different anatomic sites, and determined that ectopic expression of the two lncRNAs inhibited key EMT and stem cell genes and reduced cellular proliferation and migration. As a whole, noncoding RNAs are pervasively dysregulated in head and squamous cell carcinoma. The precise molecular roles of the three transcripts identified warrants further characterization, but our data suggest that they are likely to play substantial roles in head and neck cancer pathogenesis and are significantly associated with patient survival.
Project description:Noncoding RNA species play a diverse set of roles in the eukaryotic cell. While much recent attention has focused on smaller RNA species, larger noncoding transcripts are also thought to be highly abundant in mammalian cells. To search for large noncoding RNAs that might control gene expression or mRNA metabolism, we used Affymetrix expression arrays to identify polyadenylated RNA transcripts displaying nuclear enrichment.This screen identified no more than three transcripts; XIST, and two unique noncoding nuclear enriched abundant transcripts (NEAT) RNAs strikingly located less than 70 kb apart on human chromosome 11: NEAT1, a noncoding RNA from the locus encoding for TncRNA, and NEAT2 (also known as MALAT-1). While the two NEAT transcripts share no significant homology with each other, each is conserved within the mammalian lineage, suggesting significant function for these noncoding RNAs. NEAT2 is extraordinarily well conserved for a noncoding RNA, more so than even XIST. Bioinformatic analyses of publicly available mouse transcriptome data support our findings from human cells as they confirm that the murine homologs of these noncoding RNAs are also nuclear enriched. RNA FISH analyses suggest that these noncoding RNAs function in mRNA metabolism as they demonstrate an intimate association of these RNA species with SC35 nuclear speckles in both human and mouse cells. These studies show that one of these transcripts, NEAT1 localizes to the periphery of such domains, whereas the neighboring transcript, NEAT2, is part of the long-sought polyadenylated component of nuclear speckles.Our genome-wide screens in two mammalian species reveal no more than three abundant large non-coding polyadenylated RNAs in the nucleus; the canonical large noncoding RNA XIST and NEAT1 and NEAT2. The function of these noncoding RNAs in mRNA metabolism is suggested by their high levels of conservation and their intimate association with SC35 splicing domains in multiple mammalian species.
Project description:Autism spectrum disorders are neurodevelopmental disorders characterized by significant deficits in reciprocal social interactions, impaired communication and restricted, repetitive behaviors. As autism spectrum disorders are among the most heritable of neuropsychiatric disorders, much of autism research has focused on the search for genetic variants in protein-coding genes (i.e., the 'trees'). However, no single gene can account for more than 1% of the cases of autism spectrum disorders. Yet, genome-wide association studies have often identified statistically significant associations of genetic variations in regions of DNA that do not code for proteins (i.e., intergenic regions). There is increasing evidence that such noncoding regions are actively transcribed and may participate in the regulation of genes, including genes on different chromosomes. This article summarizes evidence that suggests that the research spotlight needs to be expanded to encompass far-reaching gene-regulatory mechanisms that include a variety of epigenetic modifications, as well as noncoding RNA (i.e., the 'forest'). Given that noncoding RNA represents over 90% of the transcripts in most cells, we may be observing just the 'tip of the iceberg' or the 'edge of the forest' in the genomic landscape of autism.
Project description:BACKGROUND: Long noncoding RNAs (lncRNAs) are a recently discovered class of non-protein coding RNAs, which have now increasingly been shown to be involved in a wide variety of biological processes as regulatory molecules. The functional role of many of the members of this class has been an enigma, except a few of them like Malat and HOTAIR. Little is known regarding the regulatory interactions between noncoding RNA classes. Recent reports have suggested that lncRNAs could potentially interact with other classes of non-coding RNAs including microRNAs (miRNAs) and modulate their regulatory role through interactions. We hypothesized that lncRNAs could participate as a layer of regulatory interactions with miRNAs. The availability of genome-scale datasets for Argonaute targets across human transcriptome has prompted us to reconstruct a genome-scale network of interactions between miRNAs and lncRNAs. RESULTS: We used well characterized experimental Photoactivatable-Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP) datasets and the recent genome-wide annotations for lncRNAs in public domain to construct a comprehensive transcriptome-wide map of miRNA regulatory elements. Comparative analysis revealed that in addition to targeting protein-coding transcripts, miRNAs could also potentially target lncRNAs, thus participating in a novel layer of regulatory interactions between noncoding RNA classes. Furthermore, we have modeled one example of miRNA-lncRNA interaction using a zebrafish model. We have also found that the miRNA regulatory elements have a positional preference, clustering towards the mid regions and 3' ends of the long noncoding transcripts. We also further reconstruct a genome-wide map of miRNA interactions with lncRNAs as well as messenger RNAs. CONCLUSIONS: This analysis suggests widespread regulatory interactions between noncoding RNAs classes and suggests a novel functional role for lncRNAs. We also present the first transcriptome scale study on miRNA-lncRNA interactions and the first report of a genome-scale reconstruction of a noncoding RNA regulatory interactome involving lncRNAs.
Project description:BACKGROUND:COVID-19 is currently a global pandemic, but the response of human immune system to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains unclear. Noncoding RNAs serve as immune regulators and thus may play a critical role in disease progression. METHODS:We performed multi-transcriptome sequencing of both noncoding RNAs and mRNAs isolated from the red blood cell depleted whole blood of moderate and severe COVID-19 patients. The functions of noncoding RNAs were validated by analyses of the expression of downstream mRNAs. We further utilized the single-cell RNA-seq data of COVID-19 patients from Wilk et al. and Chua et al. to characterize noncoding RNA functions in different cell types. RESULTS:We defined four types of microRNAs with different expression tendencies that could serve as biomarkers for COVID-19 progress. We also identified miR-146a-5p, miR-21-5p, miR-142-3p, and miR-15b-5p as potential contributors to the disease pathogenesis, possibly serving as biomarkers of severe COVID-19 and as candidate therapeutic targets. In addition, the transcriptome profiles consistently suggested hyperactivation of the immune response, loss of T-cell function, and immune dysregulation in severe patients. CONCLUSIONS:Collectively, these findings provide a comprehensive view of the noncoding and coding transcriptional landscape of peripheral immune cells during COVID-19, furthering our understanding and offering novel insights into COVID-19 pathogenesis.