Conceptual approaches for lncRNA drug discovery and future strategies

Whole genome discovery of regulatory genes responsible for the response of chicken to heat stress

Long noncoding RNAs (lncRNAs) are functional bridges connecting the genome with phenotypes by interacting with DNA, mRNA, and proteins. Using publically available acute heat stress (AHS)-related RNA-seq data, we discovered novel lncRNAs and tested their association with AHS along with ~ 8800 known lncRNAs and ~ 28,000 mRNA transcripts. Our pipeline discovered a total of 145 potentially novel-lncRNAs. One of them (Fishcomb_p-value = 0.06) along with another novel transcript (annotated as protein-coding; Fishcomb_p-value = 0.03) were identified as significantly associated with AHS. We found five known-lncRNAs and 134 mRNAs transcripts that were significantly associated with AHS. Four novel lncRNAs interact cis-regulated with 12 mRNA transcripts and are targeted by 11 miRNAs. Also six meta-lncRNAs associate with 134 meta-mRNAs through trans-acting co-expression, each targeted by 15 and 216 miRNAs, respectively. Three of the known-lncRNAs significantly co-expressed with almost 97 of the significant mRNAs (Pearson correlation p-value < 0.05). We report the mentioned three known-lncRNAs (ENSGALT00000099876, ENSGALT00000107573, and ENSGALT00000106323) as the most, significantly regulatory elements of AHS in chicken. It can be concluded that in order to alleviate the adverse effects of AHS on chicken, the manipulation of the three regulatory lncRNAs could lead to a more desirable result than the manipulation of the most significant mRNAs.

Genome-Wide Identification and Involvement in Response to Biotic and Abiotic Stresses of lncRNAs in Turbot (Scophthalmus maximus)

Long non-coding RNAs (lncRNAs) play crucial roles in a variety of biological processes, including stress response. However, the number, characteristics and stress-related expression of lncRNAs in turbot are still largely unknown. In this study, a total of 12,999 lncRNAs were identified at the genome-wide level of turbot for the first time using 24 RNA-seq datasets. Sequence characteristic analyses of transcripts showed that lncRNA transcripts were shorter in average length, lower in average GC content and in average expression level as compared to the coding genes. Expression pattern analyses of lncRNAs in 12 distinct tissues showed that lncRNAs, especially lincRNA, exhibited stronger tissue-specific expression than coding genes. Moreover, 612, 1351, 1060, 875, 420 and 1689 differentially expressed (DE) lncRNAs under Vibrio anguillarum, Enteromyxum scophthalmi, and Megalocytivirus infection and heat, oxygen, and salinity stress conditions were identified, respectively. Among them, 151 and 62 lncRNAs showed differential expression under various abiotic and biotic stresses, respectively, and 11 lncRNAs differentially expressed under both abiotic and biotic stresses were selected as comprehensive stress-responsive lncRNA candidates. Furthermore, expression pattern analysis and qPCR validation both verified the comprehensive stress-responsive functions of these 11 lncRNAs. In addition, 497 significantly co-expressed target genes (correlation coefficient (R) > 0.7 and q-value < 0.05) for these 11 comprehensive stress-responsive lncRNA candidates were identified. Finally, GO and KEGG enrichment analyses indicated that these target genes were enriched mainly in molecular function, such as cytokine activity and active transmembrane transporter activity, in biological processes, such as response to stimulus and immune response, and in pathways, such as protein families: signaling and cellular processes, transporters and metabolism. These findings not only provide valuable reference resources for further research on the molecular basis and function of lncRNAs in turbot but also help to accelerate the progress of molecularly selective breeding of stress-resistant turbot strains or varieties.

LncCat: An ORF attention model to identify LncRNA based on ensemble learning strategy and fused sequence information

Background

Long non-coding RNA (lncRNA) is one of the most essential forms of transcripts, playing crucial regulatory roles in the development of cancers and diseases without protein-coding ability. It was assumed that short ORFs (sORFs) in lncRNA were weak to translate proteins. However, recent research has shown that sORFs can encode peptides, which increases the difficulty to identify lncRNA. Therefore, identifying lncRNAs with sORFs facilitates finding novel regulatory factors.

Results

In this paper, we propose LncCat for identifying lncRNA based on category boosting (CatBoost) and ORF-attention features. LncCat combines five types of features to encode transcript sequences and employs CatBoost to build a prediction model. In addition, the visualization comparison reveals that the ORF-attention features between lncRNAs and protein-coding transcripts are significantly distinct. The comparison results show that LncCat outperforms competing methods on several benchmark datasets. For Matthew's Correlation Coefficient (MCC), LncCat achieves 0.9503, 0.9219, 0.8591, 0.8672, and 0.9047 on the human, mouse, zebrafish, wheat, and chicken datasets, with improvements ranging from 1.90% to 7.82%, 1.49-17.63%, 6.11-21.50%, 3.02-51.64% and 5.35-26.90%, respectively. Moreover, LncCat dramatically improves the MCC by at least 11.90%, 12.96% and 42.61% on sORF test datasets of human, mouse, and zebrafish, respectively.

Conclusions

Experiments indicate that LncCat performs better both on long ORF and sORF datasets, and ORF-attention features show positive effects on predicting lncRNA. In brief, LncCat is a reliable method for identifying lncRNA. Additionally, a user-friendly web server is developed for academics at http://cczubio.top/lnccat.

MiR-335-3p/miR-155-5p Involved in IGFBP7-AS1-Enhanced Odontogenic Differentiation

BACKGROUND

The differentiation of stem cells from exfoliated deciduous teeth (SHEDs) into odontoblasts determines the regeneration of dentin-pulp complex. Non-coding RNAs (ncRNAs), including microRNA (miRNA) and long non-coding RNA (lncRNA), participate in many multiple biological processes, but the specific miRNAs involved in odontogenesis are incompletely defined. It was confirmed that lncRNA IGFBP7-AS1 could positively regulate odontogenetic differentiation in SHEDs. To investigate the downstream mechanisms of this process, miR-335-3p and miR-155-5p were found to be closely related with SHED odontogenic differentiation through whole-genome sequencing. The aim of the current study was to determine the role of miR-335-3p/miR-155-5p in IGFBP7-AS1-enhanced SHED differentiation and explore the potential mechanism of IGFBP7-AS1-mediated odontogenesis.

METHODS

Putative miR-335-3p/miR-155-5p binding sites within IGFBP7-AS1 were identified by bioinformatics analysis, and the binding of miR-335-3p/miR-155-5p to these sites was confirmed by dual-luciferase reporter gene assays. The effects of miR-335-3p/miR-155-5p in odontogenesis were detected by tissue nonspecific alkaline phosphatase staining, Alizarin red staining, quantitative real-time polymerase chain reaction (qRT-PCR) analyses, and western blot testing. The molecular mechanisms of miR-335-3p/miR-155-5p involved in IGFBP7-AS1-mediated odontogenesis were analysed by qRT-PCR and western blot testing.

RESULTS

Dual-luciferase reporter gene assays showed that miR-335-3p/miR-155-5p could directly bind to IGFBP7-AS1. MiR-335-3p and miR-155-5p both could down-regulate dentin sialophosphoprotein expression, and both miRNAs could inhibit IGFBP7-AS1-mediated SHED odontogenetic differentiation via suppression of the extracellular signal-regulated kinase (ERK) pathway.

CONCLUSIONS

Both miR-335-3p and miR-155-5p were negative regulators to IGFBP7-AS1-enhanced odontogenic differentiation of SHED through suppression of the ERK pathway.

MALAT1 lncRNA and Parkinson's Disease: The role in the Pathophysiology and Significance for Diagnostic and Therapeutic Approaches

Parkinson's disease (PD) is the second most common age-related neurodegenerative disorder. PD is characterized by progressive loss of dopamine-producing neurons in the substantia nigra (SN) region of brain tissue followed by the α-synuclein-based Lewy bodies' formation. These conditions are manifested by various motor and non-motor symptoms such as resting tremor, limb rigidity, bradykinesia and posture instability, cognitive impairment, sleep disorders, and emotional and memory dysfunctions. Long non-coding RNAs (lncRNAs) are closely related to protein-coding genes and are involved in various biological processes. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) lncRNA is involved in different pathways, including alternative splicing, transcriptional regulation, and post-transcriptional regulation, and also interacts with RNAs as a miRNA sponge. MALAT1 is highly expressed in brain tissues and several lines of evidence suggested it is probably involved in synapse generation and other neurophysiological pathways. This narrative review discussed all aspects of MALAT1-associated mechanisms involved in the PD pathogenesis, i.e., perturbed α-synuclein homeostasis, apoptosis and autophagy, and neuro-inflammation. Lastly, the possible applications of MALAT1 as a diagnostic biomarker and its importance to developing therapeutic strategies were highlighted. The literature search was conducted using neurodegeneration, neurodegenerative disorders, Parkinson's disease, lncRNA, and MALAT1 as search items in Google Scholar, Web of Knowledge, PubMed, and Scopus up to December 2021.

Regulatory role of long non coding RNAs (lncRNAs) in neurological disorders: From novel biomarkers to promising therapeutic strategies

Long non coding RNAs (lncRNAs) are non-protein or low-protein coding transcripts that contain more than 200 nucleotides. They representing a large share of the cell's transcriptional output, demonstrate functional attributes viz. tissue-specific expression, determination of cell fate, controlled expression, RNA processing and editing, dosage compensation, genomic imprinting, conserved evolutionary traits etc. These long non coding variants are well associated with pathogenicity of various diseases including the neurological disorders like Alzheimer's disease, schizophrenia, Huntington's disease, Parkinson's disease etc. Neurological disorders are widespread and there knowing the underlying mechanisms become crucial. The lncRNAs take part in the pathogenesis by a plethora of mechanisms like decoy, scaffold, mi-RNA sequestrator, histone modifiers and in transcriptional interference. Detailed knowledge of the role of lncRNAs can help to use them further as novel biomarkers for therapeutic aspects. Here, in this review we discuss regulation and functional roles of lncRNAs in eight neurological diseases and psychiatric disorders, and the mechanisms by which they act. With these, we try to establish their roles as potential markers and viable diagnostic tools in these disorders.

LncFinder: an integrated platform for long non-coding RNA identification utilizing sequence intrinsic composition, structural information and physicochemical property

Discovering new long non-coding RNAs (lncRNAs) has been a fundamental step in lncRNA-related research. Nowadays, many machine learning-based tools have been developed for lncRNA identification. However, many methods predict lncRNAs using sequence-derived features alone, which tend to display unstable performances on different species. Moreover, the majority of tools cannot be re-trained or tailored by users and neither can the features be customized or integrated to meet researchers’ requirements. In this study, features extracted from sequence-intrinsic composition, secondary structure and physicochemical property are comprehensively reviewed and evaluated. An integrated platform named LncFinder is also developed to enhance the performance and promote the research of lncRNA identification. LncFinder includes a novel lncRNA predictor using the heterologous features we designed. Experimental results show that our method outperforms several state-of-the-art tools on multiple species with more robust and satisfactory results. Researchers can additionally employ LncFinder to extract various classic features, build classifier with numerous machine learning algorithms and evaluate classifier performance effectively and efficiently. LncFinder can reveal the properties of lncRNA and mRNA from various perspectives and further inspire lncRNA–protein interaction prediction and lncRNA evolution analysis. It is anticipated that LncFinder can significantly facilitate lncRNA-related research, especially for the poorly explored species. LncFinder is released as R package (https://CRAN.R-project.org/package=LncFinder). A web server (http://bmbl.sdstate.edu/lncfinder/) is also developed to maximize its availability.

Identification and characterization of long noncoding RNAs provide insight into the regulation of gene expression in response to heat stress in rainbow trout (Oncorhynchus mykiss)

Rainbow trout are typical cold-water fish species. However, with the intensification of global warming, high temperatures have severely restricted the development of aquaculture during the summer. Understanding the molecular regulatory mechanisms of rainbow trout responses to heat stress will be beneficial for alleviating heat stress-related damage. In this study, we performed RNA-seq of liver tissues from rainbow trout under heat stress (24 °C) and control conditions (18 °C) to identify lncRNAs and target genes by strand-specific library. Changes in nonspecific immune parameters revealed that a strong stress response occurred in rainbow trout at 24 °C. More than 658 million filtered reads and 5916 lncRNAs were identified from six libraries. A total of 927 novel lncRNAs were identified, and 428 differentially expressed lncRNAs were screened with stringent thresholds. The RNA-seq results were verified by RT-qPCR. In addition, a regulatory network of lncRNA-mRNA functional interactions was constructed, and the potential antisense, cis and trans targets of lncRNAs were predicted. GO and KEGG enrichment analyses showed that many target genes involved in maintenance of homeostasis or adaptation to stress and stimuli were highly induced under heat stress. Several regulatory pathways were also found to be involved in heat stress, including the thyroid hormone signaling pathway, the PI3K-Akt signaling pathway, and the estrogen signaling pathway, among others. These results broaden our understanding of lncRNAs associated with heat stress and provide new insights into the lncRNA mediated regulation of the rainbow trout heat stress response.

Role of Long Noncoding RNAs in Parkinson's Disease: Putative Biomarkers and Therapeutic Targets

Parkinson's disease (PD) is a neurodegenerative disease characterized by bradykinesia, rigidity, and tremor. Age is the main risk factor. Long noncoding RNAs (lncRNAs) are novel RNA molecules of more than 200 nucleotides in length. They may be involved in the regulation of many pathological processes of PD. PD has a variety of pathophysiological mechanisms, including alpha-synuclein aggregate, mitochondrial dysfunction, oxidative stress, calcium homeostasis, axonal transport, and neuroinflammation. Among these, the impacts of lncRNAs on the pathogenesis and progression of PD need to be highlighted. lncRNAs may serve as putative biomarkers and therapeutic targets for the early diagnosis of PD. This study aimed to investigate the role of lncRNAs in various pathological processes of PD and the specific lncRNAs that might be used as putative diagnostic biomarkers and therapeutic targets of PD.

Identification and Functional Inference for Tumor-Associated Long Non-Coding RNA

Gastric cancer is one of the top leading causes of cancer mortality worldwide especially in China. In recent years, some lncRNAs are discovered to be dysregulated in many cancers. The study on long non-coding RNAs (lncRNAs) relationship with cancers has attracted increasing attention. The molecular mechanism of gastric cancer remains largely unclear factors, especially for lncRNAs. Experiments are feasible to obtain related information, however, experimental identification of cancer-related lncRNAs usually possesses high time complexity and high cost. In this paper, a computational method is proposed to determine the relationship between lncRNA and gastric cancer by reusing the exon-based array of gastric cancer. One specific lncRNAs LINC00365 and its target differentially expressed genes whose products are predicted as blood, urine, or salvia-excretory are identified to be candidates for a combined biomarker for gastric cancer. Further biological function and molecular mechanism of the gastric cancer related lncRNAs and coding gene biomarkers are inferred in terms of multi-source biological knowledge.

LncRNA-Disease Association Prediction Using Two-Side Sparse Self-Representation

Evidences increasingly indicate the involvement of long non-coding RNAs (lncRNAs) in various biological processes. As the mutations and abnormalities of lncRNAs are closely related to the progression of complex diseases, the identification of lncRNA-disease associations has become an important step toward the understanding and treatment of diseases. Since only a limited number of lncRNA-disease associations have been validated, an increasing number of computational approaches have been developed for predicting potential lncRNA-disease associations. However, how to predict potential associations precisely through computational approaches remains challenging. In this study, we propose a novel two-side sparse self-representation (TSSR) algorithm for lncRNA-disease association prediction. By learning the self-representations of lncRNAs and diseases from known lncRNA-disease associations adaptively, and leveraging the information provided by known lncRNA-disease associations and the intra-associations among lncRNAs and diseases derived from other existing databases, our model could effectively utilize the estimated representations of lncRNAs and diseases to predict potential lncRNA-disease associations. The experiment results on three real data sets demonstrate that our TSSR outperforms other competing methods significantly. Moreover, to further evaluate the effectiveness of TSSR in predicting potential lncRNAs-disease associations, case studies of Melanoma, Glioblastoma, and Glioma are carried out in this paper. The results demonstrate that TSSR can effectively identify some candidate lncRNAs associated with these three diseases.

Prognostic Value of Long Noncoding RNA CRNDE as a Novel Biomarker in Solid Cancers: An Updated Systematic Review and Meta-Analysis

Background: Long noncoding RNA colorectal neoplasia differentially expressed (CRNDE) has been reported to exhibit a potential oncogenic role in the development of human cancers. However, the clinical value of CRNDE expression in various cancers still remains unclear. Herein, we conducted a meta-analysis to investigate the association between CRNDE and clinical outcomes in solid cancers.

Methods: A systematic search was performed though the PubMed, EMBASE, Web of Science, Ovid, Cochrane library, CNKI and WanFang databases for eligible studies on clinical values of CRNDE in solid cancers. The pooled hazard ratios (HRs) or odd ratios (ORs) with 95% confidence intervals (CIs) were used to evaluate the link between CRNDE and clinical outcomes.

Results: A total of 3690 patients from 20 studies (including 2 studies have 2 cohorts, respectively) were included. The results suggested that elevated CRNDE expression predicted a poor overall survival (OS) for in 13 types of solid cancers (HR=1.46, 95% CI: 1.33-1.58, P<0.001) with no heterogeneity (I²=21.8%, P=0.19). Subgroup analysis indicated a significant association between high CRNDE expression and shorter OS in the studies with digestive system cancers (HR=1.42, 95% CI: 1.28-1.55, P<0.001), qRT-PCR method (HR=1.45, 95% CI: 1.30-1.59, P<0.001), sample size >100 (HR=1.44, 95% CI: 1.32-1.57, P<0.001), and NOS>7 (HR= 1.50, 95% CI: 1.23-1.78, P<0.001). Furthermore, the pooled results showed that CRNDE was an independent prognostic factor for OS in cancer patients (HR=1.37, 95% CI: 1.22-1.52, P<0.001). In addition, we also revealed that CRNDE was positively related to tumor size (OR=2.10, 95%CI: 1.68-2.63, P<0.001), TNM stage (OR=2.86, 95%CI: 2.29-3.56, P<0.001), lymph node metastasis (LNM) (OR=3.21, 95%CI: 2.01-5.13, P<0.001), and distant metastasis (OR=4.36, 95%CI: 2.36-8.07, P<0.001). Although the probable evidences of publication bias were found in the studies with OS, tumor size, TNM stage or LNM, the trim and fill analysis confirmed the reliability of these results was not affected.

Conclusion: Elevated CRNDE expression was associated with larger tumor size, advanced TNM stage, worse LNM and distant metastasis, and shorter OS, suggesting that CRNDE may act as an independent prognostic biomarker in solid cancers.

A Probabilistic Matrix Factorization Method for Identifying lncRNA-disease Associations

Recently, an increasing number of studies have indicated that long-non-coding RNAs (lncRNAs) can participate in various crucial biological processes and can also be used as the most promising biomarkers for the treatment of certain diseases such as coronary artery disease and various cancers. Due to costs and time complexity, the number of possible disease-related lncRNAs that can be verified by traditional biological experiments is very limited. Therefore, in recent years, it has been very popular to use computational models to predict potential disease-lncRNA associations. In this study, we constructed three kinds of association networks, namely the lncRNA-miRNA association network, the miRNA-disease association network, and the lncRNA-disease correlation network firstly. Then, through integrating these three newly constructed association networks, we constructed an lncRNA-disease weighted association network, which would be further updated by adopting the KNN algorithm based on the semantic similarity of diseases and the similarity of lncRNA functions. Thereafter, according to the updated lncRNA-disease weighted association network, a novel computational model called PMFILDA was proposed to infer potential lncRNA-disease associations based on the probability matrix decomposition. Finally, to evaluate the superiority of the new prediction model PMFILDA, we performed Leave One Out Cross-Validation (LOOCV) based on strongly validated data filtered from MNDR and the simulation results indicated that the performance of PMFILDA was better than some state-of-the-art methods. Moreover, case studies of breast cancer, lung cancer, and colorectal cancer were implemented to further estimate the performance of PMFILDA, and simulation results illustrated that PMFILDA could achieve satisfying prediction performance as well.

LncRNAs regulating stemness in aging

One of the most outstanding observations from next-generation sequencing approaches was that only 1.5% of our genes code for proteins. The biggest part is transcribed but give rise to different families of RNAs without coding potential. The functional relevance of these abundant transcripts remains far from elucidated. Among them are the long non-coding RNAs (lncRNAs), a relatively large and heterogeneous group of RNAs shown to be highly tissue-specific, indicating a prominent role in processes controlling cellular identity. In particular, lncRNAs have been linked to both stemness properties and detrimental pathways regulating the aging process, being novel players in the intricate network guiding tissue homeostasis. Here, we summarize the up-to-date information on the role of lncRNAs that affect stemness and hence impact upon aging, highlighting the likelihood that lncRNAs may represent an unexploited reservoir of potential therapeutic targets for reprogramming applications and aging-related diseases.

Identifying Interactions Between Long Noncoding RNAs and Diseases Based on Computational Methods

With the development and improvement of next-generation sequencing technology, a great number of noncoding RNAs have been discovered. Long noncoding RNAs (lncRNAs) are the biggest kind of noncoding RNAs with more than 200 nt nucleotides in length. There are increasing evidences showing that lncRNAs play key roles in many biological processes. Therefore, the mutation and dysregulation of lncRNAs have close association with a number of complex human diseases. Identifying the most likely interaction between lncRNAs and diseases becomes a fundamental challenge in human health. A common view is that lncRNAs with similar function tend to be related to phenotypic similar diseases. In this chapter, we firstly introduce the concept of lncRNA, their biological features, and available data resources. Further, the recent computational approaches are explored to identify interactions between long noncoding RNAs and diseases, including their advantages and disadvantages. The key issues and potential future works of predicting interactions between long noncoding RNAs and diseases are also discussed.

Long non-coding RNA SNHG5 sponges miR-26a to promote the tumorigenesis of osteosarcoma by targeting ROCK1

BACKGROUND

Osteosarcoma (OS) is one of the most common invasive malignancies of the bone. The long non-coding RNA (lncRNA) SNHG5 (small nucleolar RNA host gene 5) has been consistently shown to be involved in many cancers, although its precise function in osteosarcoma remains poorly understood. In this study, we investigated the role of SNHG5 in OS progression and the underlying mechanism.

METHODS

SNHG5 expression in 32 OS tissues and 4 OS cell lines was measured by quantitative real-time PCR (qRT-PCR). Migration, invasion, proliferation and cell cycle profiles were analyzed by established assays to determine the biological functions of SNHG5 and miR-26a in OS cells. The binding sites of miR-26a in SNHG5 and ROCK1 were predicted by the RNAhybrid 2.2 program. Luciferase reporter assay was then used to validate the direct targeting of SNHG5 with miR-26a and of Rho-associated coiled coil-containing protein kinase 1 (ROCK1) with miR-26a. The effect of SNHG5 on the ROCK signaling pathway was assessed by western blotting.

RESULTS

Elevated expression of SNHG5 was correlated with poor clinical outcome and prognosis in OS patients. SNHG5 functioned as a sponge for miR-26a and promoted proliferation, invasion and migration, and accelerated G1 to S phase transition in OS cells. SNHG5 functioned as a competing endogenous RNA (ceRNA) for miR-26a and activated the ROCK signaling pathway through the miR-26a-ROCK1 axis.

CONCLUSION

SNHG5 acts as an oncogene in OS via the SNHG5-miR-26a-ROCK1 axis and is therefore a potential novel therapeutic target for OS treatment.

De novo reconstruction of human adipose transcriptome reveals conserved lncRNAs as regulators of brown adipogenesis

Obesity has emerged as an alarming health crisis due to its association with metabolic risk factors such as diabetes, dyslipidemia, and hypertension. Recent work has demonstrated the multifaceted roles of lncRNAs in regulating mouse adipose development, but their implication in human adipocytes remains largely unknown. Here we present a catalog of 3149 adipose active lncRNAs, of which 909 are specifically detected in brown adipose tissue (BAT) by performing deep RNA-seq on adult subcutaneous, omental white adipose tissue and fetal BATs. A total of 169 conserved human lncRNAs show positive correlation with their nearby mRNAs, and knockdown assay supports a role of lncRNAs in regulating their nearby mRNAs. The knockdown of one of those, lnc-dPrdm16, impairs brown adipocyte differentiation in vitro and a significant reduction of BAT-selective markers in in vivo. Together, our work provides a comprehensive human adipose catalog built from diverse fat depots and establishes a roadmap to facilitate the discovery of functional lncRNAs in adipocyte development.

Long non-coding RNAs are known to regulate mouse white adipose tissue development and brown adipose tissue program expression. Here, the authors construct a roadmap for human long non-coding RNAs expressed in fetal brown adipose tissue, adult omental and subcutaneous white adipose tissues.

Distinct and Modular Organization of Protein Interacting Sites in Long Non-coding RNAs

Background: Long non-coding RNAs (lncRNAs), are being reported to be extensively involved in diverse regulatory roles and have exhibited numerous disease associations. LncRNAs modulate their function through interaction with other biomolecules in the cell including DNA, RNA, and proteins. The availability of genome-scale experimental datasets of RNA binding proteins (RBP) motivated us to understand the role of lncRNAs in terms of its interactions with these proteins. In the current report, we demonstrate a comprehensive study of interactions between RBP and lncRNAs at a transcriptome scale through extensive analysis of the crosslinking and immunoprecipitation (CLIP) experimental datasets available for 70 RNA binding proteins.

Results: Our analysis suggests that density of interaction sites for these proteins was significantly higher for specific sub-classes of lncRNAs when compared to protein-coding transcripts. We also observe a positional preference of these RBPs across lncRNA and protein coding transcripts in addition to a significant co-occurrence of RBPs having similar functions, suggesting a modular organization of these elements across lncRNAs.

Conclusion: The significant enrichment of RBP sites across some lncRNA classes is suggestive that these interactions might be important in understanding the functional role of lncRNA. We observed a significant enrichment of RBPs which are involved in functional roles such as silencing, splicing, mRNA processing, and transport, indicating the potential participation of lncRNAs in such processes.

GATA1 activated lncRNA (Galont) promotes anoxia/reoxygenation-induced autophagy and cell death in cardiomyocytes by sponging miR-338

The hypernomic autophagy is associated with various cardiovascular diseases. Long noncoding RNAs (lncRNAs) are emerging as important regulators in gene expression, which have been involved in multiple physiological and pathological processes. However, the function of lncRNAs and how they functioned in the autophagy in cardiomyocytes were rarely reported. In this study, we report that a lncRNA, named GATA1 activated lncRNA (Galont), can directly interact with miR-338 and promote ATG5-mediated autophagic cell death in murine cardiomyocytes. First, we found that Galont was upregulated by anoxia/reoxygenation (A/R) stimulus, and it was able to promote autophagy and cell death in cardiomyocytes exposure to A/R. Then, miR-338 was identified as a novel suppressor in autophagy and autophagic cell death. Our results from bioinformatic analysis and luciferase reporter gene assay indicated that ATG5 is a target gene of miR-338. Furthermore, RNA pull-down assays demonstrated that Galont directly interacted with miR-338, and thus promoted ATG5 expression and autophagic cell death. Our findings reveal a novel regulatory circuit in the autophagy in cardiomyocytes, which consists of Galont, miR-338 and ATG5.

Long non-coding RNAs and complex diseases: from experimental results to computational models

LncRNAs have attracted lots of attentions from researchers worldwide in recent decades. With the rapid advances in both experimental technology and computational prediction algorithm, thousands of lncRNA have been identified in eukaryotic organisms ranging from nematodes to humans in the past few years. More and more research evidences have indicated that lncRNAs are involved in almost the whole life cycle of cells through different mechanisms and play important roles in many critical biological processes. Therefore, it is not surprising that the mutations and dysregulations of lncRNAs would contribute to the development of various human complex diseases. In this review, we first made a brief introduction about the functions of lncRNAs, five important lncRNA-related diseases, five critical disease-related lncRNAs and some important publicly available lncRNA-related databases about sequence, expression, function, etc. Nowadays, only a limited number of lncRNAs have been experimentally reported to be related to human diseases. Therefore, analyzing available lncRNA–disease associations and predicting potential human lncRNA–disease associations have become important tasks of bioinformatics, which would benefit human complex diseases mechanism understanding at lncRNA level, disease biomarker detection and disease diagnosis, treatment, prognosis and prevention. Furthermore, we introduced some state-of-the-art computational models, which could be effectively used to identify disease-related lncRNAs on a large scale and select the most promising disease-related lncRNAs for experimental validation. We also analyzed the limitations of these models and discussed the future directions of developing computational models for lncRNA research.

Long noncoding RNA SFTA1P promoted apoptosis and increased cisplatin chemosensitivity via regulating the hnRNP-U-GADD45A axis in lung squamous cell carcinoma

Chemotherapeutic insensitivity remains one of the major obstacles in clinical treatment of lung squamous cell carcinoma (LSCC). Recently, increasing evidence has suggested that long non-coding RNAs (lncRNAs) promote tumorigenesis in many cancer types. However, the potential biological roles and regulatory mechanisms of lncRNAs in response to cisplatin treatment are poorly understood. Here, we found that lncRNA SFTA1P (surfactant associated 1, pseudogene), highly expressed in lung, was down-regulated in LSCC tissues and could be induced upon cisplatin treatment in LSCC cells. Elevated SFTA1P induced apoptosis and enhanced the sensitivity to cisplatin of LSCC cells. We further identified that hnRNP-U (heterogeneous nuclear ribonucleoprotein U) was down-regulated in LSCCs and positively correlated with patients' poor prognosis as well as SFTA1P. Mechanistic studies revealed that SFTA1P could up-regulate hnRNP-U expression. In addition, we identified that hnRNP-U enhanced cisplatin-induced apoptosis through up-regulation of GADD45A, high expression of which was correlated with good prognosis in LSCC patients. Our findings demonstrated that SFTA1P might serve as a useful biomarker for LSCC diagnosis and a predictor for cisplatin chemotherapy response in patients with LSCC.

Genome-wide computational analysis of potential long noncoding RNA mediated DNA:DNA:RNA triplexes in the human genome

BACKGROUND

Only a handful of long noncoding RNAs have been functionally characterized. They are known to modulate regulation through interacting with other biomolecules in the cell: DNA, RNA and protein. Though there have been detailed investigations on lncRNA-miRNA and lncRNA-protein interactions, the interaction of lncRNAs with DNA have not been studied extensively. In the present study, we explore whether lncRNAs could modulate genomic regulation by interacting with DNA through the formation of highly stable DNA:DNA:RNA triplexes.

METHODS

We computationally screened 23,898 lncRNA transcripts as annotated by GENCODE, across the human genome for potential triplex forming sequence stretches (PTS). The PTS frequencies were compared across 5'UTR, CDS, 3'UTR, introns, promoter and 1000 bases downstream of the transcription termination sites. These regions were annotated by mapping to experimental regulatory regions, classes of repeat regions and transcription factors. We validated few putative triplex mediated interactions where lncRNA-gene pair interaction is via pyrimidine triplex motif using biophysical methods.

RESULTS

We identified 20,04,034 PTS sites to be enriched in promoter and intronic regions across human genome. Additional analysis of the association of PTS with core promoter elements revealed a systematic paucity of PTS in all regulatory regions, except TF binding sites. A total of 25 transcription factors were found to be associated with PTS. Using an interaction network, we showed that a subset of the triplex forming lncRNAs, have a positive association with gene promoters. We also demonstrated an in vitro interaction of one lncRNA candidate with its predicted gene target promoter regions.

CONCLUSIONS

Our analysis shows that PTS are enriched in gene promoter and largely associated with simple repeats. The current study suggests a major role of a subset of lncRNAs in mediating chromatin organization modulation through CTCF and NSRF proteins.

Primer in Genetics and Genomics, Article 2-Advancing Nursing Research With Genomic Approaches

PURPOSE

Nurses investigate reasons for variable patient symptoms and responses to treatments to inform how best to improve outcomes. Genomics has the potential to guide nursing research exploring contributions to individual variability. This article is meant to serve as an introduction to the novel methods available through genomics for addressing this critical issue and includes a review of methodological considerations for selected genomic approaches.

APPROACH

This review presents essential concepts in genetics and genomics that will allow readers to identify upcoming trends in genomics nursing research and improve research practice. It introduces general principles of genomic research and provides an overview of the research process. It also highlights selected nursing studies that serve as clinical examples of the use of genomic technologies. Finally, the authors provide suggestions about how to apply genomic technology in nursing research along with directions for future research.

CONCLUSIONS

Using genomic approaches in nursing research can advance the understanding of the complex pathophysiology of disease susceptibility and different patient responses to interventions. Nurses should be incorporating genomics into education, clinical practice, and research as the influence of genomics in health-care research and practice continues to grow. Nurses are also well placed to translate genomic discoveries into improved methods for patient assessment and intervention.

The link between long noncoding RNAs and depression

The major depressive disorder (MDD) is a relatively common mental disorder from which that hundreds of million people have suffered, leading to displeasing life quality, which is characterized by health damage and even suicidal thoughts. The complicated development and functioning of MDD is still under exploration. Long noncoding RNA (lncRNAs) are highly expressed in the brain, could affect neural stem cell maintenance, neurogenesis and gliogenesis, brain patterning, synaptic and stress responses, and neural plasticity. The dysregulation of certain lncRNAs induces in neurodevelopmental, neurodegenerative and neuroimmunological disorders, primary brain tumors, and psychiatric diseases. Although advances have been made, no fully satisfactory treatments for major depression are available, further investigation is requested. And recently data showed that the expression level of the majority of lncRNAs demonstrated a clear tendency of upregulation, and the certain dysregulated miRNAs and lncRNAs in the MDD have been proved to have a co-synergism mechanism, that is why we speculate lncRNA might get the capability to regulate MDD. Few identified lncRNAs have been deeply studied in detailed experiments up until now, little predictions of their function have been raised, and further researches is calling for discover their signal pathway and related regulatory networks.

Identification and Functional Prediction of Large Intergenic Noncoding RNAs (lincRNAs) in Rainbow Trout (Oncorhynchus mykiss)

Long noncoding RNAs (lncRNAs) have been recognized in recent years as key regulators of diverse cellular processes. Genome-wide large-scale projects have uncovered thousands of lncRNAs in many model organisms. Large intergenic noncoding RNAs (lincRNAs) are lncRNAs that are transcribed from intergenic regions of genomes. To date, no lincRNAs in non-model teleost fish have been reported. In this report, we present the first reference catalog of 9674 rainbow trout lincRNAs based on analysis of RNA-Seq data from 15 tissues. Systematic analysis revealed that lincRNAs in rainbow trout share many characteristics with those in other mammalian species. They are shorter and lower in exon number and expression level compared with protein-coding genes. They show tissue-specific expression pattern and are typically co-expressed with their neighboring genes. Co-expression network analysis suggested that many lincRNAs are associated with immune response, muscle differentiation, and neural development. The study provides an opportunity for future experimental and computational studies to uncover the functions of lincRNAs in rainbow trout.

Distinct patterns of epigenetic marks and transcription factor binding sites across promoters of sense-intronic long noncoding RNAs

Long noncoding RNAs (lncRNAs) are a new class of noncoding RNAs that have been extensively studied in the recent past as a regulator of gene expression, including modulation of epigenetic regulation. The lncRNAs class encompasses a number of subclasses, classified based on their genomic loci and relation to protein-coding genes. Functional differences between subclasses have been increasingly studied in the recent years, though the regulation of expression and biogenesis of lncRNAs have been poorly studied. The availability of genome-scale datasets of epigenetic marks has motivated us to understand the patterns and processes of epigenetic regulation of lncRNAs. Here we analysed the occurrence of expressive and repressive histone marks at the transcription start site (TSS) of lncRNAs and their subclasses, and compared these profiles with that of the protein-coding regions. We observe distinct differences in the density of histone marks across the TSS of a few lncRNA subclasses. The sense-intronic lncRNA subclass showed a paucity for mapped histone marks across the TSS which were significantly different than all the lncRNAs and protein-coding genes in most cases. Similar pattern was also observed for the density of transcription factor binding sites (TFBS). These observations were generally consistent across cell and tissue types. The differences in density across the promoter were significantly associated with the expression level of the genes, but the differences between the densities across long noncoding and protein-coding gene promoters were consistent irrespective of the expression levels. Apart from suggesting general differences in epigenetic regulatory marks across long noncoding RNA promoters, our analysis suggests a possible alternative mechanism of regulation and/or biogenesis of sense-intronic lncRNAs.

Long noncoding RNAs could be potential key players in the pathophysiology of Sjögren's syndrome

Long noncoding RNAs (lncRNAs) are a recently discovered class of noncoding functional RNAs encoded by metazoan genomes. Recent studies suggest a larger regulatory role for lncRNAs in critical biological and disease processes. Mounting evidence on the role of lncRNAs in regulating key processes of the immune system prompted us to hypothesize the role of lncRNAs as key regulators of the pathophysiology of Sjögren's syndrome (SS). We used two similar approaches based on reanalysis of microarray expression datasets and curation of lncRNA-protein coding gene interactions from literature to derive support for our hypothesis. We also discuss potential caveats to our approach and suggest approaches to validate the hypothesis. Our analysis suggests the potential larger and hitherto unknown role of lncRNA regulatory networks in modulating the expression of key genes involved in the pathogenesis of SS and thereby modulating the pathophysiology of SS.

The RNA world in the 21st century-a systems approach to finding non-coding keys to clinical questions

There was evidence that RNAs are a functionally rich class of molecules not only since the arrival of the next-generation sequencing technology. Non-coding RNAs (ncRNA) could be the key to accelerated diagnosis and enhanced prediction of disease and therapy outcomes as well as the design of advanced therapeutic strategies to overcome yet unsatisfactory approaches.In this review, we discuss the state of the art in RNA systems biology with focus on the application in the systems biomedicine field. We propose guidelines for analysing the role of microRNAs and long non-coding RNAs in human pathologies. We introduce RNA expression profiling and network approaches for the identification of stable and effective RNomics-based biomarkers, providing insights into the role of ncRNAs in disease regulation. Towards this, we discuss ways to model the dynamics of gene regulatory networks and signalling pathways that involve ncRNAs. We also describe data resources and computational methods for finding putative mechanisms of action of ncRNAs. Finally, we discuss avenues for the computer-aided design of novel RNA-based therapeutics.

Short stories on zebrafish long noncoding RNAs

The recent re-annotation of the transcriptome of human and other model organisms, using next-generation sequencing approaches, has unravelled a hitherto unknown repertoire of transcripts that do not have a potential to code for proteins. These transcripts have been largely classified into an amorphous class popularly known as long noncoding RNAs (lncRNA). This discovery of lncRNAs in human and other model systems have added a new layer to the understanding of gene regulation at the transcriptional and post-transcriptional levels. In recent years, three independent studies have discovered a number of lncRNAs expressed in different stages of zebrafish development and adult tissues using a high-throughput RNA sequencing approach, significantly adding to the repertoire of genes known in zebrafish. A subset of these transcripts also shows distinct and specific spatiotemporal patterns of gene expression, pointing to a tight regulatory control and potential functional roles in development, organogenesis, and/ or homeostasis. This review provides an overview of the lncRNAs in zebrafish and discusses how their discovery could provide new insights into understanding biology, explaining mutant phenotypes, and helping in potentially modeling disease processes.

zflncRNApedia: A Comprehensive Online Resource for Zebrafish Long Non-Coding RNAs

Recent transcriptome annotation using deep sequencing approaches have annotated a large number of long non-coding RNAs in zebrafish, a popular model organism for human diseases. These studies characterized lncRNAs in critical developmental stages as well as adult tissues. Each of the studies has uncovered a distinct set of lncRNAs, with minor overlaps. The availability of the raw RNA-Seq datasets in public domain encompassing critical developmental time-points and adult tissues provides us with a unique opportunity to understand the spatiotemporal expression patterns of lncRNAs. In the present report, we created a catalog of lncRNAs in zebrafish, derived largely from the three annotation sets, as well as manual curation of literature to compile a total of 2,267 lncRNA transcripts in zebrafish. The lncRNAs were further classified based on the genomic context and relationship with protein coding gene neighbors into 4 categories. Analysis revealed a total of 86 intronic, 309 promoter associated, 485 overlapping and 1,386 lincRNAs. We created a comprehensive resource which houses the annotation of lncRNAs as well as associated information including expression levels, promoter epigenetic marks, genomic variants and retroviral insertion mutants. The resource also hosts a genome browser where the datasets could be browsed in the genome context. To the best of our knowledge, this is the first comprehensive resource providing a unified catalog of lncRNAs in zebrafish. The resource is freely available at URL: http://genome.igib.res.in/zflncRNApedia

Human 45,X fibroblast transcriptome reveals distinct differentially expressed genes including long noncoding RNAs potentially associated with the pathophysiology of Turner syndrome

Turner syndrome is a chromosomal abnormality characterized by the absence of whole or part of the X chromosome in females. This X aneuploidy condition is associated with a diverse set of clinical phenotypes such as gonadal dysfunction, short stature, osteoporosis and Type II diabetes mellitus, among others. These phenotypes differ in their severity and penetrance among the affected individuals. Haploinsufficiency for a few X linked genes has been associated with some of these disease phenotypes. RNA sequencing can provide valuable insights to understand molecular mechanism of disease process. In the current study, we have analysed the transcriptome profiles of human untransformed 45,X and 46,XX fibroblast cells and identified differential expression of genes in these two karyotypes. Functional analysis revealed that these differentially expressing genes are associated with bone differentiation, glucose metabolism and gonadal development pathways. We also report differential expression of lincRNAs in X monosomic cells. Our observations provide a basis for evaluation of cellular and molecular mechanism(s) in the establishment of Turner syndrome phenotypes.

High-resolution profiling of novel transcribed regions during rat spermatogenesis

Mammalian spermatogenesis is a complex and highly orchestrated combination of processes in which male germline proliferation and differentiation result in the production of mature spermatozoa. If recent genome-wide studies have contributed to the in-depth analysis of the male germline protein-encoding transcriptome, little effort has yet been devoted to the systematic identification of novel unannotated transcribed regions expressed during mammalian spermatogenesis. We report high-resolution expression profiling of male germ cells in rat, using next-generation sequencing technology and highly enriched testicular cell populations. Among 20 424 high-confidence transcripts reconstructed, we defined a stringent set of 1419 long multi-exonic unannotated transcripts expressed in the testis (testis-expressed unannotated transcripts [TUTs]). TUTs were divided into 7 groups with different expression patterns. Most TUTs share many of the characteristics of vertebrate long noncoding RNAs (lncRNAs). We also markedly reinforced the finding that TUTs and known lncRNAs accumulate during the meiotic and postmeiotic stages of spermatogenesis in mammals and that X-linked meiotic TUTs do not escape the silencing effects of meiotic sex chromosome inactivation. Importantly, we discovered that TUTs and known lncRNAs with a peak expression during meiosis define a distinct class of noncoding transcripts that exhibit exons twice as long as those of other transcripts. Our study provides new insights in transcriptional profiling of the male germline and represents a high-quality resource for novel loci expressed during spermatogenesis that significantly contributes to rat genome annotation.

Microarray profiling and co-expression network analysis of circulating lncRNAs and mRNAs associated with major depressive disorder

LncRNAs, which represent one of the most highly expressed classes of ncRNAs in the brain, are becoming increasingly interesting with regard to brain functions and disorders. However, changes in the expression of regulatory lncRNAs in Major Depressive Disorder (MDD) have not yet been reported. Using microarrays, we profiled the expression of 34834 lncRNAs and 39224 mRNAs in peripheral blood sampled from MDD patients as well as demographically-matched controls. Among these, we found that 2007 lncRNAs and 1667 mRNAs were differentially expressed, 17 of which were documented as depression-related gene in previous studies. Gene Ontology (GO) and pathway analyses indicated that the biological functions of differentially expressed mRNAs were related to fundamental metabolic processes and neurodevelopment diseases. To investigate the potential regulatory roles of the differentially expressed lncRNAs on the mRNAs, we also constructed co-expression networks composed of the lncRNAs and mRNAs, which shows significant correlated patterns of expression. In the MDD-derived network, there were a greater number of nodes and connections than that in the control-derived network. The lncRNAs located at chr10:874695-874794, chr10:75873456-75873642, and chr3:47048304-47048512 may be important factors regulating the expression of mRNAs as they have previously been reported associations with MDD. This study is the first to explore genome-wide lncRNA expression and co-expression with mRNA patterns in MDD using microarray technology. We identified circulating lncRNAs that are aberrantly expressed in MDD and the results suggest that lncRNAs may contribute to the molecular pathogenesis of MDD.

Dynamic expression of long non-coding RNAs (lncRNAs) in adult zebrafish

Long non-coding RNAs (lncRNA) represent an assorted class of transcripts having little or no protein coding capacity and have recently gained importance for their function as regulators of gene expression. Molecular studies on lncRNA have uncovered multifaceted interactions with protein coding genes. It has been suggested that lncRNAs are an additional layer of regulatory switches involved in gene regulation during development and disease. LncRNAs expressing in specific tissues or cell types during adult stages can have potential roles in form, function, maintenance and repair of tissues and organs. We used RNA sequencing followed by computational analysis to identify tissue restricted lncRNA transcript signatures from five different tissues of adult zebrafish. The present study reports 442 predicted lncRNA transcripts from adult zebrafish tissues out of which 419 were novel lncRNA transcripts. Of these, 77 lncRNAs show predominant tissue restricted expression across the five major tissues investigated. Adult zebrafish brain expressed the largest number of tissue restricted lncRNA transcripts followed by cardiovascular tissue. We also validated the tissue restricted expression of a subset of lncRNAs using independent methods. Our data constitute a useful genomic resource towards understanding the expression of lncRNAs in various tissues in adult zebrafish. Our study is thus a starting point and opens a way towards discovering new molecular interactions of gene expression within the specific adult tissues in the context of maintenance of organ form and function.

Long non-coding RNAs: novel targets for nervous system disease diagnosis and therapy

The human genome encodes tens of thousands of long non-coding RNAs (lncRNAs), a novel and important class of genes. Our knowledge of lncRNAs has grown exponentially since their discovery within the last decade. lncRNAs are expressed in a highly cell- and tissue-specific manner, and are particularly abundant within the nervous system. lncRNAs are subject to post-transcriptional processing and inter- and intra-cellular transport. lncRNAs act via a spectrum of molecular mechanisms leveraging their ability to engage in both sequence-specific and conformational interactions with diverse partners (DNA, RNA, and proteins). Because of their size, lncRNAs act in a modular fashion, bringing different macromolecules together within the three-dimensional context of the cell. lncRNAs thus coordinate the execution of transcriptional, post-transcriptional, and epigenetic processes and critical biological programs (growth and development, establishment of cell identity, and deployment of stress responses). Emerging data reveal that lncRNAs play vital roles in mediating the developmental complexity, cellular diversity, and activity-dependent plasticity that are hallmarks of brain. Corresponding studies implicate these factors in brain aging and the pathophysiology of brain disorders, through evolving paradigms including the following: (i) genetic variation in lncRNA genes causes disease and influences susceptibility; (ii) epigenetic deregulation of lncRNAs genes is associated with disease; (iii) genomic context links lncRNA genes to disease genes and pathways; and (iv) lncRNAs are otherwise interconnected with known pathogenic mechanisms. Hence, lncRNAs represent prime targets that can be exploited for diagnosing and treating nervous system diseases. Such clinical applications are in the early stages of development but are rapidly advancing because of existing expertise and technology platforms that are readily adaptable for these purposes.

lncRNome: a comprehensive knowledgebase of human long noncoding RNAs

The advent of high-throughput genome scale technologies has enabled us to unravel a large amount of the previously unknown transcriptionally active regions of the genome. Recent genome-wide studies have provided annotations of a large repertoire of various classes of noncoding transcripts. Long noncoding RNAs (lncRNAs) form a major proportion of these novel annotated noncoding transcripts, and presently known to be involved in a number of functionally distinct biological processes. Over 18 000 transcripts are presently annotated as lncRNA, and encompass previously annotated classes of noncoding transcripts including large intergenic noncoding RNA, antisense RNA and processed pseudogenes. There is a significant gap in the resources providing a stable annotation, cross-referencing and biologically relevant information. lncRNome has been envisioned with the aim of filling this gap by integrating annotations on a wide variety of biologically significant information into a comprehensive knowledgebase. To the best of our knowledge, lncRNome is one of the largest and most comprehensive resources for lncRNAs.

Database URL:http://genome.igib.res.in/lncRNome

Roles of long noncoding RNAs in brain development, functional diversification and neurodegenerative diseases

Long noncoding RNAs (lncRNAs) have been attracting immense research interest, while only a handful of lncRNAs have been characterized thoroughly. Their involvement in the fundamental cellular processes including regulate gene expression at epigenetics, transcription, and post-transcription highlighted a central role in cell homeostasis. However, lncRNAs studies are still at a relatively early stage, their definition, conservation, functions, and action mechanisms remain fairly complicated. Here, we give a systematic and comprehensive summary of the existing knowledge of lncRNAs in order to provide a better understanding of this new studying field. lncRNAs play important roles in brain development, neuron function and maintenance, and neurodegenerative diseases are becoming increasingly evident. In this review, we also highlighted recent studies related lncRNAs in central nervous system (CNS) development and neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD) and amyotrophic lateral sclerosis (ALS), and elucidated some specific lncRNAs which may be important for understanding the pathophysiology of neurodegenerative diseases, also have the potential as therapeutic targets.

Systematic transcriptome wide analysis of lncRNA-miRNA interactions

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.

Genome-wide analysis reveals distinct patterns of epigenetic features in long non-coding RNA loci

A major fraction of the transcriptome of higher organisms comprised an extensive repertoire of long non-coding RNA (lncRNA) which express in a cell type and development stage-specific manner. While lncRNAs are a proven component of epigenetic gene expression modulation, epigenetic regulation of lncRNA itself remains poorly understood. Here we have analysed pan-genomic DNA methylation and histone modification marks (H3K4me3, H3K9me3, H3K27me3 and H3K36me3) associated with transcription start site (TSS) of lncRNA in four different cell types and three different tissue types representing various cellular stages. We observe that histone marks associated with active transcription H3K4me3 and H3K36me3 along with the repressive histone mark H3K27me3 have similar distribution pattern around TSS irrespective of cell types. Also, the density of these marks correlates well with expression of protein-coding and lncRNA genes. In contrast, the lncRNA genes harbour higher methylation density around TSS than protein-coding genes regardless of their expression status. Furthermore, we found that DNA methylation along with the other repressive histone mark H3K9me3 does not seem to play a role in lncRNA expression. Thus, our observation suggests that epigenetic regulation of lncRNA shares common features with mRNA except the role of DNA methylation which is markedly dissimilar.

Integrative transcriptome analysis suggest processing of a subset of long non-coding RNAs to small RNAs

Background

The availability of sequencing technology has enabled understanding of transcriptomes through genome-wide approaches including RNA-sequencing. Contrary to the previous assumption that large tracts of the eukaryotic genomes are not transcriptionally active, recent evidence from transcriptome sequencing approaches have revealed pervasive transcription in many genomes of higher eukaryotes. Many of these loci encode transcripts that have no obvious protein-coding potential and are designated as non-coding RNA (ncRNA). Non-coding RNAs are classified empirically as small and long non-coding RNAs based on the size of the functional RNAs. Each of these classes is further classified into functional subclasses. Although microRNAs (miRNA), one of the major subclass of ncRNAs, have been extensively studied for their roles in regulation of gene expression and involvement in a large number of patho-physiological processes, the functions of a large proportion of long non-coding RNAs (lncRNA) still remains elusive. We hypothesized that some lncRNAs could potentially be processed to small RNA and thus could have a dual regulatory output.

Results

Integration of large-scale independent experimental datasets in public domain revealed that certain well studied lncRNAs harbor small RNA clusters. Expression analysis of the small RNA clusters in different tissue and cell types reveal that they are differentially regulated suggesting a regulated biogenesis mechanism.

Conclusions

Our analysis suggests existence of a potentially novel pathway for lncRNA processing into small RNAs. Expression analysis, further suggests that this pathway is regulated. We argue that this evidence supports our hypothesis, though limitations of the datasets and analysis cannot completely rule out alternate possibilities. Further in-depth experimental verification of the observation could potentially reveal a novel pathway for biogenesis.

Reviewers

This article was reviewed by Dr Rory Johnson (nominated by Fyodor Kondrashov), Dr Raya Khanin (nominated by Dr Yuriy Gusev) and Prof Neil Smalheiser. For full reviews, please go to the Reviewer’s comment section.