The role of long noncoding RNAs in the epigenetic control of gene expression

Epigenetic modulation of fungal pathogens: a focus on Magnaporthe oryzae

Epigenetics has emerged as a potent field of study for understanding the factors influencing the effectiveness of human disease treatments and for identifying alternations induced by pathogens in host plants. However, there has been a paucity of research on the epigenetic control of the proliferation and pathogenicity of fungal plant pathogens. Fungal plant pathogens such as Magnaporthe oryzae, a significant threat to global rice production, provide an important model for exploring how epigenetic mechanisms govern fungal proliferation and virulence. In M. oryzae, epigenetic alterations, such as DNA methylation, histone modification, and non-coding RNAs, regulate gene expression patterns that influence the pathogen's ability to infect its host. These modifications can enhance fungal adaptability, allowing the pathogen to survive in diverse environments and evade host immune responses. Our primary objective is to provide a comprehensive review of the existing epigenetic research on M. oryzae and shed light on how these changes influence the pathogen's lifecycle, its ability to invade host tissues, and the overall severity of the disease. We begin by examining the epigenetic alterations occurring in M. oryzae and their contributions to the virulence and proliferation of the fungus. To advance our understanding of epigenetic mechanisms in M. oryzae and similar plant diseases, we emphasize the need to address unanswered questions and explore future research directions. This information is crucial for developing new antifungal treatments that target epigenetic pathways, which could lead to improved disease management.

Lnc-ing RNA to intestinal homeostasis and inflammation

Long noncoding RNAs (lncRNAs) play important roles in numerous biological processes, including the immune system. Initial research in this area focused on cell-based studies, but recent advances underscore the profound significance of lncRNAs at the organismal level, providing invaluable insights into their roles in inflammatory diseases. In this rapidly evolving field, lncRNAs have been described with pivotal roles in the intestinal tract where they regulate intestinal homeostasis and inflammation by influencing processes such as immune cell development, inflammatory signaling pathways, epithelial barrier function, and cellular metabolism. Understanding the regulation and function of lncRNAs in this tissue may position lncRNAs not only as potential disease biomarkers but also as promising targets for therapeutic intervention in inflammatory bowel disease and related diseases.

Identification of Dezhou donkey muscle development-related genes and long non-coding RNA based on differential expression analysis

Long non-coding RNAs (lncRNAs) play a critical role in the development of muscles. However, the role of lncRNAs in regulating skeletal muscle development has not been studied systematically in the donkey. In this study, we performed the RNA sequencing for different stages of muscles in donkeys, and investigate their expression profile, which showed that 3215 mRNAs (p-adjust <0.05) and 471 lncRNAs (p-value <0.05) were significantly differently expressed (DE) verified by RT-qPCR. GO and KEGG enrichment analysis indicated that DE genes and target genes of DE lncRNAs were associated with muscle development in the donkey. We also found these four target genes (DCN, ITM2A, MUSTN1, ARRDC2) involved in skeletal muscle growth and development. Combined with transcriptome data, network, and RT-qPCR results showed that four co-expression networks of DCN and lnc-008278, ITM2A and lnc_017247, MUSTN1 and lnc_030153, and ARRDC2 and lnc_033914, which may play an important role in the formation and development of muscle in the donkey.

Proteomic analysis of murine kidney proximal tubule sub-segment derived cell lines reveals preferences in mitochondrial pathway activity

The proximal tubule (PT) is a nephron segment that is responsible for the majority of solute and water reabsorption in the kidney. Each of its sub-segments have specialized functions; however, little is known about the genes and proteins that determine the oxidative phosphorylation capacity of the PT sub-segments. This information is critical to understanding kidney function and will provide a comprehensive landscape of renal cell adaptations to injury, physiologic stressors, and development. This study analyzed three immortalized murine renal cell lines (PT S1, S2, and S3 segments) for protein content and compared them to a murine fibroblast cell line. All three proximal tubule cell lines generate ATP predominantly by oxidative phosphorylation while the fibroblast cell line is glycolytic. The proteomic data demonstrates that the most significant difference in proteomic signatures between the cell lines are proteins known to be localized in the nucleus followed by mitochondrial proteins. Mitochondrial metabolic substrate utilization assays were performed using the proximal tubule cell lines to determine substrate utilization kinetics thereby providing a physiologic context to the proteomic dataset. This data will allow researchers to study differences in nephron-specific cell lines, between epithelial and fibroblast cells, and between actively respiring cells and glycolytic cells. SIGNIFICANCE: Proteomic analysis of proteins expressed in immortalized murine renal proximal tubule cells was compared to a murine fibroblast cell line proteome. The proximal tubule segment specific cell lines: S1, S2 and S3 are all grown under conditions whereby the cells generate ATP by oxidative phosphorylation while the fibroblast cell line utilizes anaerobic glycolysis for ATP generation. The proteomic studies allow for the following queries: 1) comparisons between the proximal tubule segment specific cell lines, 2) comparisons between polarized epithelia and fibroblasts, 3) comparison between cells employing oxidative phosphorylation versus anaerobic glycolysis and 4) comparisons between cells grown on clear versus opaque membrane supports. The data finds major differences in nuclear protein expression and mitochondrial proteins. This proteomic data set will be an important baseline dataset for investigators who need immortalized renal proximal tubule epithelial cells for their research.

Deregulation of NF-κB associated long non-coding RNAs in bipolar disorder

Long non-coding RNAs (lncRNAs) are major genetic factors whose disruption lead to many diseases, including nervous system diseases. Bipolar disorder (BD) is a neuro-psychiatric disease with no definitive diagnosis and incomplete treatment. Regarding the role of NF-κB-associated lncRNAs in the neuro-psychiatric disorders, we examined the expression of three lncRNAs, DICER1-AS1, DILC, and CHAST, in BD patients. To assess lncRNA expression in peripheral blood mononuclear cells (PBMCs) of 50 BD patients and 50 healthy individuals, Real-time PCR was used. Additionally, some clinical characteristics of BD patients were investigated via an analysis of ROC curves and correlations. Based on our results, the expression level of CHAST increased significantly in BD patients in comparison with healthy people, in BD men compared with healthy men, as well as in BD women in comparison with control females (p < 0.05). A similar increase in expression was observed for DILC and DICER1-AS1 lncRNAs in female patients compared with healthy women. Whereas compared to healthy men, DILC was decreased in diseased men. Based on the results of the ROC curve, the area under the curve (AUC) for CHAST lncRNA was 0.83 with a P value of 0.0001. So, the expression level of CHAST lncRNA could play a role in the pathobiology of the BD and be considered a good putative biomarker for individuals with bipolar disorder.

Identification and Characterization of lncRNAs Expression Profile Related to Goat Skeletal Muscle at Different Development Stages

LncRNAs are essential for regulating skeletal muscle. However, the expression profile and function of lncRNAs in goat muscle remains unclear. Here, an average of ~14.58 Gb high-quality reads were obtained from longissimus dorsi tissues of 1-month-old (n = 3) and 9-month-old (n = 3) Wu'an black goats using RNA sequencing. Of a total of 3441 lncRNAs, 1281 were lincRNAs, 805 were antisense lncRNAs, and 1355 were sense_overlapping lncRNAs. These lncRNAs shared some properties with goats, such as fewer exons, shorter transcript, and open reading frames (ORFs) length. Among them, 36 differentially expressed lncRNAs (DE lncRNA) were identified, and then 10 random lncRNAs were validated by RT-qPCR. Furthermore, 30 DE lncRNAs were neighboring 71 mRNAs and several genes were functionally enriched in muscle development-related pathways, such as APC, IFRD1, NKX2-5, and others. Additionally, 36 DE lncRNAs and 2684 mRNAs were included in co-expression interactions. A lncRNA-miRNA-mRNA network containing 4 lncRNAs, 3 miRNAs, and 8 mRNAs was finally constructed, of which XR_001296113.2 might regulate PDLIM7 expression by interaction with chi-miR-1296 to affect skeletal muscle development. This study revealed the expression profile of goat lncRNAs for further investigative studies and provides a fuller understanding of skeletal muscle development.

NPI-RGCNAE: Fast predicting ncRNA-protein interactions using the Relational Graph Convolutional Network Auto-Encoder

- ncRNAs play important roles in a variety of biological processes by interacting with RNA-binding proteins. Therefore, identifying ncRNA-protein interactions is important to understanding the biological functions of ncRNAs. Since experimental methods to determine ncRNA-protein interactions are always costly and time-consuming, computational methods have been proposed as alternative approaches. We developed a novel method NPI-RGCNAE (predicting ncRNA-Protein Interactions by the Relational Graph Convolutional Network Auto-Encoder). With a reliable negative sample selection strategy, we applied the Relational Graph Convolutional Network encoder and the DistMult decoder to predict ncRNA-protein interactions in an accurate and efficient way. By using the 5-fold cross-validation, we found that our method achieved a comparable performance to all state-of-the-art methods. Our method requires less than 10% training time of all state-of-the-art methods. It is a more efficient choice with large datasets in practice. All datasets and source codes of NPI-RGCNAE have been deposited in a public Github repository (https://github.com/Angelia0hh/NPI-RGCNAE).

PRPI-SC: an ensemble deep learning model for predicting plant lncRNA-protein interactions

BACKGROUND

Plant long non-coding RNAs (lncRNAs) play vital roles in many biological processes mainly through interactions with RNA-binding protein (RBP). To understand the function of lncRNAs, a fundamental method is to identify which types of proteins interact with the lncRNAs. However, the models or rules of interactions are a major challenge when calculating and estimating the types of RBP.

RESULTS

In this study, we propose an ensemble deep learning model to predict plant lncRNA-protein interactions using stacked denoising autoencoder and convolutional neural network based on sequence and structural information, named PRPI-SC. PRPI-SC predicts interactions between lncRNAs and proteins based on the k-mer features of RNAs and proteins. Experiments proved good results on Arabidopsis thaliana and Zea mays datasets (ATH948 and ZEA22133). The accuracy rates of ATH948 and ZEA22133 datasets were 88.9% and 82.6%, respectively. PRPI-SC also performed well on some public RNA protein interaction datasets.

CONCLUSIONS

PRPI-SC accurately predicts the interaction between plant lncRNA and protein, which plays a guiding role in studying the function and expression of plant lncRNA. At the same time, PRPI-SC has a strong generalization ability and good prediction effect for non-plant data.

HOTAIR lncRNA promotes epithelial-mesenchymal transition by redistributing LSD1 at regulatory chromatin regions

Epithelial‐to‐mesenchymal transition (EMT) describes the loss of epithelial traits and gain of mesenchymal traits by normal cells during development and by neoplastic cells during cancer metastasis. The long noncoding RNA HOTAIR triggers EMT, in part by serving as a scaffold for PRC2 and thus promoting repressive histone H3K27 methylation. In addition to PRC2, HOTAIR interacts with the LSD1 lysine demethylase, an epigenetic regulator of cell fate during development and differentiation, but little is known about the role of LSD1 in HOTAIR function during EMT. Here, we show that HOTAIR requires its LSD1‐interacting domain, but not its PRC2‐interacting domain, to promote the migration of epithelial cells. This activity is suppressed by LSD1 overexpression. LSD1‐HOTAIR interactions induce partial reprogramming of the epithelial transcriptome altering LSD1 distribution at promoter and enhancer regions. Thus, we uncover an unexpected role of HOTAIR in EMT as an LSD1 decommissioning factor, counteracting its activity in the control of epithelial identity.

Identification and Characterization of lncRNAs Related to the Muscle Growth and Development of Japanese Flounder (Paralichthys olivaceus)

Long noncoding RNAs (lncRNAs) play an important role in many life activities, but the expression pattern and function of lncRNAs in Japanese flounder skeletal muscle are unclear. In this study, 751 lncRNAs were selected from skeletal muscle in different development stages of the Japanese flounder [stage A: larval 7 days post hatching (dph); stage B: juvenile about 90 dph; stage C (female) and stage D (male): adult about 24 months] using coding potential analysis methods. In total, 232, 211, 194, 28, 29, and 14 differentially expressed lncRNAs and 9549, 8673, 9181, 1821, 1080, and 557 differentially expressed mRNAs were identified in comparisons of A versus B, A versus C, A versus D, B versus C, B versus D, and C versus D, respectively. We identified the cis- and trans-regulatory target genes of differentially expressed lncRNAs, and lncRNA-gene interaction networks were constructed using the Cytoscape program. In total, there were 200, 200, 200, 93, 47, and 11 cis-regulation relationships, and 29, 19, 24, 38, 8, and 47 trans-regulation relationships in the comparisons between A versus B, A versus C, A versus D, B versus C, B versus D, and C versus D, respectively. These results indicate that lncRNA may participate in the development of Japanese flounder skeletal muscle through cis- or trans-acting mechanisms, thus providing a scientific basis for further study of the biological function of lncRNA in Japanese flounder skeletal muscle. Based on these relationships, functional annotation of the related lncRNAs was performed by gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Differentially expressed genes associated with muscle development were enriched in multiple pairs of comparisons (e.g., differentially expressed genes LOC109640370, LOC109634180, LOC109643555, rusc1, and LOC109626999 were enriched in the actin-binding term, and differentially expressed genes LOC109640370, was, LOC109644970, LOC109643555, and itga9 were enriched in the regulation of the actin cytoskeleton pathway in the KEGG pathway analysis in the comparison of stages C and D). We predicted lncRNA-mRNA, miRNA-mRNA, and lncRNA-miRNA regulatory relationships and constructed interactive networks using Cytoscape software. Co-expression networks show that most lncRNAs interact with one or two predicted miRNAs involved in muscle growth and development. These results provide a basis for further study of the function of lncRNAs on skeletal muscle in different developmental stages of Japanese flounder.

Comprehensive analysis of dysregulated exosomal long non-coding RNA networks associated with arteriovenous malformations

Arteriovenous malformations (AVMs) are congenital vascular lesions with a high tendency for aggravation and recurrence after treatment, and their genesis remains enigmatic. In this study, we investigated exosomal long non-coding RNA (lncRNA) and mRNA expression and constructed a competitive endogenous RNA regulatory network in AVMs. Ethics approval was provided, and informed written consent was given prior to the inclusion of all participants. Blood samples were obtained from patients with AVMs and healthy controls at Shanghai Ninth People's Hospital, China, from May to November 2018, and total exosomes were isolated and validated. Differentially expressed exosomal lncRNAs and mRNAs were detected by RNA-seq, analysed by bioinformatic methods and validated by qRT-PCR. A competitive endogenous RNA regulatory network was constructed. The characteristics of the captured extracellular vesicles conformed to the features of exosomes. A total of 117 dysregulated exosomal lncRNAs and 1159 dysregulated exosomal mRNAs were identified in AVMs. qRT-PCR demonstrated that the exosomal lncRNAs MIR4435-1HG, LINC00657, LOC101927854 and SEPT5-GP1BB were upregulated in AVM exosomes. The Gene Ontology (GO) terms haemopoiesis and negative regulation of neuron projection development were significantly enriched in relation to dysregulated exosomal cis lncRNAs. A total of 199 GO terms and 80 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched for the dysregulated exosomal mRNAs. In the exosomal lncRNA-miRNA-mRNA-related ceRNA regulatory network, the top 3 significant modules involved 31 dysregulated exosomal lncRNAs and 114 dysregulated exosomal mRNAs, which were enriched in the Rap 1, Ras, MAPK signalling pathways and platelet activation KEGG pathway. This study comprehensively identified dysregulated exosomal lncRNAs and mRNAs in AVMs, demonstrated the involvement of dysregulated lncRNA and mRNA patterns in AVMs and constructed an exosomal competitive endogenous RNA regulatory network.

Osblr8 orchestrates intrachromosomal loop structure required for maintaining stem cell pluripotency

Induced pluripotent stem cells (iPSCs), derived from reprogramming of somatic cells by a cocktail of transcription factors, have the capacity for unlimited self-renewal and the ability to differentiate into all of cell types present in the body. iPSCs may have therapeutic potential in regenerative medicine, replacing injured tissues or even whole organs. In this study, we examine epigenetic factors embedded in the specific 3-dimensional intrachromosomal architecture required for the activation of endogenous pluripotency genes. Using chromatin RNA in situ reverse transcription sequencing (CRIST-seq), we identified an Oct4-Sox2 binding long noncoding RNA, referred as to Osblr8, that is present in association with pluripotency status. Osblr8 was highly expressed in iPSCs and E14 embryonic stem cells, but it was silenced in fibroblasts. By using shRNA to knock down Osblr8, we found that this lncRNA was required for the maintenance of pluripotency. Overexpression of Osblr8 activated endogenous stem cell core factor genes. Mechanistically, Osblr8 participated in the formation of an intrachromosomal looping structure that is required to activate stem cell core factors during reprogramming. In summary, we have demonstrated that lncRNA Osblr8 is a chromatin architecture modulator of pluripotency-associated master gene promoters, highlighting its critical epigenetic role in reprogramming.

Genome-wide interaction target profiling reveals a novel Peblr20-eRNA activation pathway to control stem cell pluripotency

Background: Long non-coding RNAs (lncRNAs) constitute an important component of the regulatory apparatus that controls stem cell pluripotency. However, the specific mechanisms utilized by these lncRNAs in the control of pluripotency are not fully characterized.

Methods: We utilized a RNA reverse transcription-associated trap sequencing (RAT-seq) approach to profile the mouse genome-wide interaction targets for lncRNAs that are screened by RNA-seq.

Results: We identified Peblr20 (Pou5F1 enhancer binding lncRNA 20) as a novel lncRNA that is associated with stem cell reprogramming. Peblr20 was differentially transcribed in fibroblasts compared to induced pluripotent stem cells (iPSCs). Notably, we found that Peblr20 utilized a trans mechanism to interact with the regulatory elements of multiple stemness genes. Using gain- and loss-of-function experiments, we showed that knockdown of Peblr20 caused iPSCs to exit from pluripotency, while overexpression of Peblr20 activated endogenous Pou5F1 expression. We further showed that Peblr20 promoted pluripotent reprogramming. Mechanistically, we demonstrated that Peblr20 activated endogenous Pou5F1 by binding to the Pou5F1 enhancer in trans, recruiting TET2 demethylase and activating the enhancer-transcribed RNAs.

Conclusions: Our data reveal a novel epigenetic mechanism by which a lncRNA controls the fate of stem cells by trans-regulating the Pou5F1 enhancer RNA pathway. We demonstrate the potential for leveraging lncRNA biology to enhance the generation of stem cells for regenerative medicine.

MRPS30-DT Knockdown Inhibits Breast Cancer Progression by Targeting Jab1/Cops5

Longnoncoding RNAs (lncRNAs) are significantly correlated with cancer pathogenesis, development, and metastasis. Microarray analysis showed that lncRNA MRPS30-DT is overexpressed in breast carcinoma; however, the function of MRPS30-DT in breast cancer tumorigenesis remains unclear. In situ hybridization and immunohistochemical analysis were used to evaluate the expression levels of MRPS30-DT and Jab1 in clinical samples of breast carcinoma and their relation to survival outcome. qRT-PCR was used to measure MRPS30-DT and Jab1 mRNA expressions. Protein levels were detected using Western blot. Cell proliferation and invasion ability were evaluated via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), colony formation, and transwell assays. MRPS30-DT was knocked down in breast cancer cells to investigate its potential functional roles in cell growth and metastasis in vitro and in vivo. We found that MRPS30-DT was upregulated in breast cancer specimens and was accompanied by high Jab1 expression compared with that of paired para-carcinoma tissues. Knocking down MRPS30-DT significantly inhibited cancer cell proliferation and invasion and induced apoptosis in breast cancer cells. Similarly, knocking down MRPS30-DT in MDA-MB-231 cells significantly suppressed tumor growth. Furthermore, knocking down MRPS30-DT markedly reduced Jab1 expression in breast cancer cells and murine carcinoma. Statistical analyses suggested that high MRPS30-DT or Jab1 levels in breast cancer patients were positively correlated with poor prognoses. These data indicate the possible mechanisms of MRPS30-DT and Jab1 in breast cancer; thus, MRPS30-DT and Jab1 may be novel prognostic biomarkers and potential therapeutic targets for breast cancer treatment.

Long non-coding RNAs in non-small cell lung cancer: functions and distinctions from other malignancies

Lung cancer leads to the most cancer-related death in the world. It was shown from the increasing evidences that long non-coding RNAs (lncRNAs) are emerging as molecules for diagnosis, prognosis and even therapy of lung cancer and other malignancies. The biological functions or involved signaling pathways of lncRNAs are always found to be inconsistent among different types of malignancies. However, no available literature has systemically summarized differences in the functions and underlying molecular mechanisms of lncRNAs between lung cancer and other cancers. In this review, the biological functions and molecular mechanisms of lncRNAs in lung cancer were introduced. Furthermore, their functional differences between lung cancer and other malignancies were discussed. Finally, their potential clinical applications in future lung cancer therapy were focused on.

Long non-coding RNA in stem cell pluripotency and lineage commitment: functions and evolutionary conservation

LncRNAs have recently emerged as new and fundamental transcriptional and post-transcriptional regulators acting at multiple levels of gene expression. Indeed, lncRNAs participate in a wide variety of stem cell and developmental processes, acting in cis and/or in trans in the nuclear and/or in the cytoplasmic compartments, and generating an intricate network of interactions with RNAs, enhancers, and chromatin-modifier complexes. Given the versatility of these molecules to operate in different subcellular compartments, via different modes of action and with different target specificity, the interest in this research field is rapidly growing. Here, we review recent progress in defining the functional role of lncRNAs in stem cell biology with a specific focus on the underlying mechanisms. We also discuss recent findings on a new family of evolutionary conserved lncRNAs transcribed from ultraconserved elements, which show perfect conservation between human, mouse, and rat genomes, and that are emerging as new player in this complex scenario.

TADKB: Family classification and a knowledge base of topologically associating domains

Background

Topologically associating domains (TADs) are considered the structural and functional units of the genome. However, there is a lack of an integrated resource for TADs in the literature where researchers can obtain family classifications and detailed information about TADs.

Results

We built an online knowledge base TADKB integrating knowledge for TADs in eleven cell types of human and mouse. For each TAD, TADKB provides the predicted three-dimensional (3D) structures of chromosomes and TADs, and detailed annotations about the protein-coding genes and long non-coding RNAs (lncRNAs) existent in each TAD. Besides the 3D chromosomal structures inferred by population Hi-C, the single-cell haplotype-resolved chromosomal 3D structures of 17 GM12878 cells are also integrated in TADKB. A user can submit query gene/lncRNA ID/sequence to search for the TAD(s) that contain(s) the query gene or lncRNA. We also classified TADs into families. To achieve that, we used the TM-scores between reconstructed 3D structures of TADs as structural similarities and the Pearson’s correlation coefficients between the fold enrichment of chromatin states as functional similarities. All of the TADs in one cell type were clustered based on structural and functional similarities respectively using the spectral clustering algorithm with various predefined numbers of clusters. We have compared the overlapping TADs from structural and functional clusters and found that most of the TADs in the functional clusters with depleted chromatin states are clustered into one or two structural clusters. This novel finding indicates a connection between the 3D structures of TADs and their DNA functions in terms of chromatin states.

Conclusion

TADKB is available at http://dna.cs.miami.edu/TADKB/.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5551-2) contains supplementary material, which is available to authorized users.

Prediction of RNA-protein interactions using conjoint triad feature and chaos game representation

RNA-protein interactions (RPIs) play a very important role in a wide range of post-transcriptional regulations, and identifying whether a given RNA-protein pair can form interactions or not is a vital prerequisite for dissecting the regulatory mechanisms of functional RNAs. Currently, expensive and time-consuming biological assays can only determine a very small portion of all RPIs, which calls for computational approaches to help biologists efficiently and correctly find candidate RPIs. Here, we integrated a successful computing algorithm, conjoint triad feature (CTF), and another method, chaos game representation (CGR), for representing RNA-protein pairs and by doing so developed a prediction model based on these representations and random forest (RF) classifiers. When testing two benchmark datasets, RPI369 and RPI2241, the combined method (CTF+CGR) showed some superiority compared with four existing tools. Especially on RPI2241, the CTF+CGR method improved prediction accuracy (ACC) from 0.91 (the best record of all published works) to 0.95. When independently testing a newly constructed dataset, RPI1449, which only contained experimentally validated RPIs released between 2014 and 2016, our method still showed some generalization capability with an ACC of 0.75. Accordingly, we believe that our hybrid CTF+CGR method will be an important tool for predicting RPIs in the future.

RPITER: A Hierarchical Deep Learning Framework for ncRNA⁻Protein Interaction Prediction

Non-coding RNAs (ncRNAs) play crucial roles in multiple fundamental biological processes, such as post-transcriptional gene regulation, and are implicated in many complex human diseases. Mostly ncRNAs function by interacting with corresponding RNA-binding proteins. The research on ncRNA⁻protein interaction is the key to understanding the function of ncRNA. However, the biological experiment techniques for identifying RNA⁻protein interactions (RPIs) are currently still expensive and time-consuming. Due to the complex molecular mechanism of ncRNA⁻protein interaction and the lack of conservation for ncRNA, especially for long ncRNA (lncRNA), the prediction of ncRNA⁻protein interaction is still a challenge. Deep learning-based models have become the state-of-the-art in a range of biological sequence analysis problems due to their strong power of feature learning. In this study, we proposed a hierarchical deep learning framework RPITER to predict RNA⁻protein interaction. For sequence coding, we improved the conjoint triad feature (CTF) coding method by complementing more primary sequence information and adding sequence structure information. For model design, RPITER employed two basic neural network architectures of convolution neural network (CNN) and stacked auto-encoder (SAE). Comprehensive experiments were performed on five benchmark datasets from PDB and NPInter databases to analyze and compare the performances of different sequence coding methods and prediction models. We found that CNN and SAE deep learning architectures have powerful fitting abilities for the k-mer features of RNA and protein sequence. The improved CTF coding method showed performance gain compared with the original CTF method. Moreover, our designed RPITER performed well in predicting RNA⁻protein interaction (RPI) and could outperform most of the previous methods. On five widely used RPI datasets, RPI369, RPI488, RPI1807, RPI2241 and NPInter, RPITER obtained A U C of 0.821, 0.911, 0.990, 0.957 and 0.985, respectively. The proposed RPITER could be a complementary method for predicting RPI and constructing RPI network, which would help push forward the related biological research on ncRNAs and lncRNAs.

LEADeR role of miR-205 host gene as long noncoding RNA in prostate basal cell differentiation

Though miR-205 function has been largely characterized, the nature of its host gene, MIR205HG, is still completely unknown. Here, we show that only lowly expressed alternatively spliced MIR205HG transcripts act as de facto pri-miRNAs, through a process that involves Drosha to prevent unfavorable splicing and directly mediate miR-205 excision. Notably, MIR205HG-specific processed transcripts revealed to be functional per se as nuclear long noncoding RNA capable of regulating differentiation of human prostate basal cells through control of the interferon pathway. At molecular level, MIR205HG directly binds the promoters of its target genes, which have an Alu element in proximity of the Interferon-Regulatory Factor (IRF) binding site, and represses their transcription likely buffering IRF1 activity, with the ultimate effect of preventing luminal differentiation. As MIR205HG functions autonomously from (albeit complementing) miR-205 in preserving the basal identity of prostate epithelial cells, it warrants reannotation as LEADeR (Long Epithelial Alu-interacting Differentiation-related RNA).

miR-205 is known to have context-dependent tumor suppressive or oncogenic roles. Here, the authors report the host gene of miR-205, MIR205HG as a nuclear lincRNA that maintains the basal identity of prostate cell and prevents luminal cell differentiation via the repression of interferon responsive genes.

Genome-wide identification and characterization of long non-coding RNAs during postnatal development of rabbit adipose tissue

Background

The rabbit is widely used as an important experimental model for biomedical research, and shows low adipose tissue deposition during growth. Long non-coding RNAs (lncRNAs) are associated with adipose growth, but little is known about the function of lncRNAs in the rabbit adipose tissue.

Methods

Deep RNA-sequencing and comprehensive bioinformatics analyses were used to characterize the lncRNAs of rabbit visceral adipose tissue (VAT) at 35, 85 and 120 days after birth. Differentially expressed (DE) lncRNAs were identified at the three growth stages by DESeq. The cis and trans prediction ways predicted the target genes of the DE lncRNAs. To explore the function of lncRNAs, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on the candidate genes.

Results

A total of 991,157,544 clean reads were generated after RNA-Seq of the three growth stages, of which, 30,353 and 107 differentially expressed (DE) lncRNAs were identified. Compared to the protein-coding transcripts, the rabbit lncRNAs shared some characteristics such as shorter length and fewer exons. Cis and trans target gene prediction revealed, 43 and 64 DE lncRNAs respectively, corresponding to 72 and 20 protein-coding genes. GO enrichment and KEGG pathway analyses revealed that the candidate DE lncRNA target genes were involved in oxidative phosphorylation, glyoxylate and dicarboxylate metabolism, and other adipose growth-related pathways. Six DE lncRNAs were randomly selected and validated by q-PCR.

Conclusions

This study is the first to profile the potentially functional lncRNAs in the adipose tissue growth in rabbits, and contributes to our understanding of mammalian adipogenesis.

Electronic supplementary material

The online version of this article (10.1186/s12944-018-0915-1) contains supplementary material, which is available to authorized users.

Deficiency in the nuclear long noncoding RNA Charme causes myogenic defects and heart remodeling in mice

Myogenesis is a highly regulated process that involves the conversion of progenitor cells into multinucleated myofibers. Besides proteins and miRNAs, long noncoding RNAs (lncRNAs) have been shown to participate in myogenic regulatory circuitries. Here, we characterize a murine chromatin‐associated muscle‐specific lncRNA, Charme, which contributes to the robustness of the myogenic program in vitro and in vivo. In myocytes, Charme depletion triggers the disassembly of a specific chromosomal domain and the downregulation of myogenic genes contained therein. Notably, several Charme‐sensitive genes are associated with human cardiomyopathies and Charme depletion in mice results in a peculiar cardiac remodeling phenotype with changes in size, structure, and shape of the heart. Moreover, the existence of an orthologous transcript in human, regulating the same subset of target genes, suggests an important and evolutionarily conserved function for Charme. Altogether, these data describe a new example of a chromatin‐associated lncRNA regulating the robustness of skeletal and cardiac myogenesis.

LncRNA-uc.40 silence promotes P19 embryonic cells differentiation to cardiomyocyte via the PBX1 gene

Uc.40 is a long noncoding RNA that is highly conserved among different species, although its function is unknown. It is highly expressed in abnormal human embryonic heart. We previously reported that overexpression of uc.40 promoted apoptosis and inhibited proliferation of P19 cells, and downregulated PBX1, which was identified as a potential target gene of uc.40. The current study evaluated the effects of uc40-siRNA-44 (siRNA against uc.40) on the differentiation, proliferation, apoptosis, and mitochondrial function in P19 cells, and investigated the relationship between uc.40 and PBX1 in cardiomyocytes. The uc.40 silencing expression was confirmed by quantitative real-time polymerase chain reaction (RT-PCR). Observation of morphological changes in transfected P19 cells during different stages of differentiation revealed that uc40-siRNA-44 increased the number of cardiomyocyes. There was no significant difference in the morphology or time of differentiation between the uc40-siRNA-44 group and the control group. uc40-siRNA-44 significantly promoted proliferation of P19 cells and inhibited serum starvation-induced apoptosis. There was no significant difference in mitochondrial DNA copy number or cellular ATP level between the two groups, and ROS levels were significantly decreased in uc40-siRNA-44-transfected cells. The levels of PBX1 and myocardial markers of differentiation were examined in transfected P19 cells; uc40-siRNA-44 downregulated myocardial markers and upregulated PBX1 expression. These results suggest that uc.40 may play an important role during the differentiation of P19 cells by regulation of PBX1 to promote proliferation and inhibit apoptosis. These studies provide a foundation for further study of uc.40/PBX1 in cardiac development.

IRWNRLPI: Integrating Random Walk and Neighborhood Regularized Logistic Matrix Factorization for lncRNA-Protein Interaction Prediction

Long non-coding RNA (lncRNA) plays an important role in many important biological processes and has attracted widespread attention. Although the precise functions and mechanisms for most lncRNAs are still unknown, we are certain that lncRNAs usually perform their functions by interacting with the corresponding RNA- binding proteins. For example, lncRNA-protein interactions play an important role in post transcriptional gene regulation, such as splicing, translation, signaling, and advances in complex diseases. However, experimental verification of lncRNA-protein interactions prediction is time-consuming and laborious. In this work, we propose a computational method, named IRWNRLPI, to find the potential associations between lncRNAs and proteins. IRWNRLPI integrates two algorithms, random walk and neighborhood regularized logistic matrix factorization, which can optimize a lot more than using an algorithm alone. Moreover, the method is semi-supervised and does not require negative samples. Based on the leave-one-out cross validation, we obtain the AUC of 0.9150 and the AUPR of 0.7138, demonstrating its reliable performance. In addition, by means of case study in the “Mus musculus,” many lncRNA-protein interactions which are predicted by our method can be successfully confirmed by experiments. This suggests that IRWNRLPI will be a useful bioinformatics resource in biomedical research.

Long non-coding RNAs: implications in targeted diagnoses, prognosis, and improved therapeutic strategies in human non- and triple-negative breast cancer

Triple-negative breast cancer (TNBC) has been clinically difficult to manage because of tumor aggressiveness, cellular and histological heterogeneity, and molecular mechanisms’ complexity. All this in turn leads us to evaluate that tumor biological behavior is not yet fully understood. Additionally, the heterogeneity of tumor cells represents a great biomedicine challenge in terms of the complex molecular—genetical-transcriptional and epigenetical—mechanisms, which have not been fully elucidated on human solid tumors.

Recently, human breast cancer, but specifically TNBC is under basic and clinical-oncology research in the discovery of new molecular biomarkers and/or therapeutic targets to improve treatment responses, as well as for seeking algorithms for patient stratification, seeking a positive impact in clinical-oncology outcomes and life quality on breast cancer patients.

In this sense, important knowledge is emerging regarding several cancer molecular aberrations, including higher genetic mutational rates, LOH, CNV, chromosomal, and epigenetic alterations, as well as transcriptome aberrations in terms of the total gene-coding ribonucleic acids (RNAs), known as mRNAs, as well as non-coding RNA (ncRNA) sequences. In this regard, novel investigation fields have included microRNAs (miRNAs), as well as long ncRNAs (lncRNAs), which have been importantly related and are likely involved in the induction, promotion, progression, and/or clinical therapeutic response trackers of TNBC. Based on this, in general terms according with the five functional archetype classification, the lncRNAs may be involved in the regulation of several molecular mechanisms which include genetic expression, epigenetic, transcriptional, and/or post-transcriptional mechanisms, which are nowadays not totally understood.

Here, we have reviewed the main dis-regulated and functionally non- and well-characterized lncRNAs and their likely involvement, from a molecular enrichment and mechanistic point of view, as tumor biomarkers for breast cancer and its specific histological subtype, TNBC. In reference to the abovementioned, it has been described that some lncRNA expression profiles correspond or are associated with the TNBC histological subtype, potentially granting their use for TNBC malignant progression, diagnosis, tumor clinical stage, and likely therapy. Based on this, lncRNAs have been proposed as potential biomarkers which might represent potential predictive tools in the differentiated breast carcinomas versus TNBC malignant disease. Finally, elucidation of the specific or multi-functional archetypal of lncRNAs in breast cancer and TNBC could be fundamental, as these molecular intermediary-regulator “lncRNAs” are widely involved in the genome expression, epigenome regulation, and transcriptional and post-transcriptional tumor biology, which in turn will probably represent a new prospect in clinical and/or therapeutic molecular targets for the oncological management of breast carcinomas in general and also for TNBC patients.

The Ever-Evolving Concept of the Gene: The Use of RNA/Protein Experimental Techniques to Understand Genome Functions

The completion of the human genome sequence together with advances in sequencing technologies have shifted the paradigm of the genome, as composed of discrete and hereditable coding entities, and have shown the abundance of functional noncoding DNA. This part of the genome, previously dismissed as “junk” DNA, increases proportionally with organismal complexity and contributes to gene regulation beyond the boundaries of known protein-coding genes. Different classes of functionally relevant nonprotein-coding RNAs are transcribed from noncoding DNA sequences. Among them are the long noncoding RNAs (lncRNAs), which are thought to participate in the basal regulation of protein-coding genes at both transcriptional and post-transcriptional levels. Although knowledge of this field is still limited, the ability of lncRNAs to localize in different cellular compartments, to fold into specific secondary structures and to interact with different molecules (RNA or proteins) endows them with multiple regulatory mechanisms. It is becoming evident that lncRNAs may play a crucial role in most biological processes such as the control of development, differentiation and cell growth. This review places the evolution of the concept of the gene in its historical context, from Darwin's hypothetical mechanism of heredity to the post-genomic era. We discuss how the original idea of protein-coding genes as unique determinants of phenotypic traits has been reconsidered in light of the existence of noncoding RNAs. We summarize the technological developments which have been made in the genome-wide identification and study of lncRNAs and emphasize the methodologies that have aided our understanding of the complexity of lncRNA-protein interactions in recent years.

Helicobacter pylori infection related long noncoding RNA (lncRNA) AF147447 inhibits gastric cancer proliferation and invasion by targeting MUC2 and up-regulating miR-34c

Long non-coding RNAs (lncRNAs) were shown to play critical roles in cancer biology. We investigated whether H. pylori infection could promote gastric cancer by regulating lncRNAs expression. Differentially expressed lncRNAs between H. pylori positive and negative tissues were identified by microarray and validated by qRT-PCR. Our results indicated that H. pylori positive tissues have a specific profile of lncRNAs. Cell biological assays with siRNA-mediated knockdown or lentivirus vector-mediated over-expression were performed to probe the functional relevance of the lncRNAs. We identified an lncRNA-AF147447 decreased expressed by H. pylori infection, which can inhibit GC proliferation and invasion in vitro and in vivo, act as a tumor suppressor in the development of H. pylori induced GC. LncRNA AF147447 could repress MUC2 expression by direct binding or increasing miR-34c expression. We also found that transcription factor E2F1 could be recruited to lncRNA AF147447 promoter by RNA immunoprecipatation and RNA pull down assays. These findings support a role of lncRNA AF147447 in tumor suppression. This discovery contributes to a better understanding of the importance of the deregulated lncRNAs by H. pylori infection and provides a rationale for the potential development of lncRNA-based targeted approaches for the treatment of H. pylori-related gastric cancer.

Helicobacter pylori infection related long noncoding RNA (lncRNA) AF147447 inhibits gastric cancer proliferation and invasion by targeting MUC2 and up-regulating miR-34c

Long non-coding RNAs (lncRNAs) were shown to play critical roles in cancer biology. We investigated whether H. pylori infection could promote gastric cancer by regulating lncRNAs expression. Differentially expressed lncRNAs between H. pylori positive and negative tissues were identified by microarray and validated by qRT-PCR. Our results indicated that H. pylori positive tissues have a specific profile of lncRNAs. Cell biological assays with siRNA-mediated knockdown or lentivirus vector-mediated over-expression were performed to probe the functional relevance of the lncRNAs. We identified an lncRNA-AF147447 decreased expressed by H. pylori infection, which can inhibit GC proliferation and invasion in vitro and in vivo, act as a tumor suppressor in the development of H. pylori induced GC. LncRNA AF147447 could repress MUC2 expression by direct binding or increasing miR-34c expression. We also found that transcription factor E2F1 could be recruited to lncRNA AF147447 promoter by RNA immunoprecipatation and RNA pull down assays. These findings support a role of lncRNA AF147447 in tumor suppression. This discovery contributes to a better understanding of the importance of the deregulated lncRNAs by H. pylori infection and provides a rationale for the potential development of lncRNA-based targeted approaches for the treatment of H. pylori-related gastric cancer.

Assessment and comparison of thermal stability of phosphorothioate-DNA, DNA, RNA, 2'-F RNA, and LNA in the context of Phi29 pRNA 3WJ

The question of whether RNA is more stable or unstable compared to DNA or other nucleic acids has long been a subject of extensive scrutiny and public attention. Recently, thermodynamically stable and degradation-resistant RNA motifs have been utilized in RNA nanotechnology to build desired architectures and integrate multiple functional groups. Here we report the effects of phosphorothioate deoxyribonucleotides (PS-DNA), deoxyribonucleotides (DNA), ribonucleotides (RNA), 2'-F nucleotides (2'-F), and locked nucleic acids (LNA) on the thermal and in vivo stability of the three-way junction (3WJ) of bacteriophage phi29 motor packaging RNA. It was found that the thermal stability gradually increased following the order of PS-DNA/PS-DNA < DNA/DNA < DNA/RNA < RNA/RNA < RNA/2'-F RNA < 2'-F RNA/2'-F RNA < 2'-F RNA/LNA < LNA/LNA. This proposition is supported by studies on strand displacement and the melting of homogeneous and heterogeneous 3WJs. By simply mixing different chemically modified oligonucleotides, the thermal stability of phi29 pRNA 3WJ can be tuned to cover a wide range of melting temperatures from 21.2°C to over 95°C. The 3WJ_LNA was resistant to boiling temperature denaturation, urea denaturation, and 50% serum degradation. Intravenous injection of fluorescent LNA/2'-F hybrid 3WJs into mice revealed its exceptional in vivo stability and presence in urine. It is thus concluded that incorporation of LNA nucleotides, alone or in combination with 2'-F, into RNA nanoparticles derived from phi29 pRNA 3WJ can extend the half-life of the RNA nanoparticles in vivo and improve their pharmacokinetics profile.

Polymorphisms of long non-coding RNA HOTAIR with breast cancer susceptibility and clinical outcomes for a southeast Chinese Han population

Hox transcript antisense intergenic RNA (HOTAIR) is a well-known long non-coding RNA (lncRNA) which participates in tumorigenesis and progress of multiple cancers. However, the associations among polymorphisms on HOTAIR, breast cancer (BC) susceptibility and clinical outcomes have remained obscure. In this case-control study, we assessed the interaction between three lncRNA HOTAIR single nucleotide polymorphisms (SNPs) (rs1899663, rs4759314 and rs7958904) on the risk and clinical outcome of breast cancer in a Chinese Han population. In total, 969 breast cancer cases and 970 healthy controls were enrolled in this study. Associations among genotypes, BC risk and survival were evaluated by univariate and multivariate logistic regression to estimate the odds ratio (OR), hazard ratio (HR) and its 95% confidence interval (CI). The disease-free survival (DFS) and overall survival (OS) was calculated by the Kaplan–Meier method. We found that the T allele of rs1899663 and C allele of rs7958904 both achieved significant differences between cases and controls in the single locus analyses (P = 0.017 and 0.010, respectively). Multivariate analyses also revealed the rs1899663 TT genotype and rs7958904 CC genotype were both at higher risk of breast cancer compared with the GG homozygotes (OR = 2.08, 95% CI = 1.20–3.60 and OR = 1.45, 95% CI = 1.01–2.08, respectively). In survival analysis, we observed that the T allele of rs1899663 presented significant differences for both DFS (HR = 1.64, 95% CI = 1.12–2.40) and OS (HR = 2.10, 95% CI = 1.29–3.42) in younger subjects (age ≤ 40). Our findings may provide new insights into the associations among the genetic susceptibility, the fine classifications and the prognosis of breast cancer. Further studies with larger sample size and functional research should also be conducted to validate our findings and better elucidate the underlying biological mechanisms.

mRNA, microRNA and lncRNA as novel bladder tumor markers

Early detection of bladder cancer (BC) is essential for improvement of the patient's prognosis and general survival rates. Current diagnostic methods are still limited, so new specific and cost-effective biomarkers are emerging as the noninvasive tools in treatment decisions in recurrent BC. Gene expression and epigenetic profile can be analysed using quantitative real-time-PCR (qRT-PCR) method in urine, blood and tissue. This review provides an update of recent findings on BC molecular profile as novel markers in diagnosis and prognosis of bladder tumors. We describe mRNA-, microRNA- and lncRNA-based biomarkers involved in the BC detection, diagnosis, prediction of recurrence and monitoring after treatment.

The multidimensional mechanisms of long noncoding RNA function

A major shift in our understanding of genome regulation has emerged recently. It is now apparent that the majority of cellular transcripts do not code for proteins, and many of them are long noncoding RNAs (lncRNAs). Increasingly, studies suggest that lncRNAs regulate gene expression through diverse mechanisms. We review emerging mechanistic views of lncRNAs in gene regulation in the cell nucleus. We discuss the functional interactions that lncRNAs establish with other molecules as well as the relationship between lncRNA transcription and function. While some of these mechanisms are specific to lncRNAs, others might be shared with other types of genes.

LPI-NRLMF: lncRNA-protein interaction prediction by neighborhood regularized logistic matrix factorization

LncRNA-protein interactions play important roles in many important cellular processes including signaling, transcriptional regulation, and even the generation and progression of complex diseases. However, experimental methods for determining proteins bound by a specific lncRNA remain expensive, difficult and time-consuming, and only a few theoretical approaches are available for predicting potential lncRNA-protein associations. In this study, we developed a novel matrix factorization computational approach to uncover lncRNA-protein relationships, namely lncRNA-protein interactions prediction by neighborhood regularized logistic matrix factorization (LPI-NRLMF). Moreover, it is a semi-supervised and does not need negative samples. As a result, new model obtained reliable performance in the leave-one-out cross validation (the AUC of 0.9025 and AUPR of 0.6924), which significantly improved the prediction performance of previous models. Furthermore, the case study demonstrated that many lncRNA-protein interactions predicted by our method can be successfully confirmed by experiments. It is anticipated that LPI-NRLMF could serve as a useful resource for potential lncRNA-protein association identification.

Tissue- and Cell Type-Specific Expression of the Long Noncoding RNA Klhl14-AS in Mouse

lncRNAs are acquiring increasing relevance as regulators in a wide spectrum of biological processes. The extreme heterogeneity in the mechanisms of action of these molecules, however, makes them very difficult to study, especially regarding their molecular function. A novel lncRNA has been recently identified as the most enriched transcript in mouse developing thyroid. Due to its genomic localization antisense to the protein-encoding Klhl14 gene, we named it Klhl14-AS. In this paper, we highlight that mouse Klhl14-AS produces at least five splicing variants, some of which have not been previously described. Klhl14-AS is expressed with a peculiar pattern, characterized by diverse relative abundance of its isoforms in different mouse tissues. We examine the whole expression level of Klhl14-AS in a panel of adult mouse tissues, showing that it is expressed in the thyroid, lung, kidney, testis, ovary, brain, and spleen, although at different levels. In situ hybridization analysis reveals that, in the context of each organ, Klhl14-AS shows a cell type-specific expression. Interestingly, databases report a similar expression profile for human Klhl14-AS. Our observations suggest that this lncRNA could play cell type-specific roles in several organs and pave the way for functional characterization of this gene in appropriate biological contexts.

Role of the long non-coding RNA PVT1 in the dysregulation of the ceRNA-ceRNA network in human breast cancer

Recent findings have identified competing endogenous RNAs (ceRNAs) as the drivers in many disease conditions, including cancers. The ceRNAs indirectly regulate each other by reducing the amount of microRNAs (miRNAs) available to target messenger RNAs (mRNAs). The ceRNA interactions mediated by miRNAs are modulated by a titration mechanism, i.e. large changes in the ceRNA expression levels either overcome, or relieve, the miRNA repression on competing RNAs; similarly, a very large miRNA overexpression may abolish competition. The ceRNAs are also called miRNA "decoys" or miRNA "sponges" and encompass different RNAs competing with each other to attract miRNAs for interactions: mRNA, long non-coding RNAs (lncRNAs), pseudogenes, or circular RNAs. Recently, we developed a computational method for identifying ceRNA-ceRNA interactions in breast invasive carcinoma. We were interested in unveiling which lncRNAs could exert the ceRNA activity. We found a drastic rewiring in the cross-talks between ceRNAs from the physiological to the pathological condition. The main actor of this dysregulated lncRNA-associated ceRNA network was the lncRNA PVT1, which revealed a net biding preference towards the miR-200 family members in normal breast tissues. Despite its up-regulation in breast cancer tissues, mimicked by the miR-200 family members, PVT1 stops working as ceRNA in the cancerous state. The specific conditions required for a ceRNA landscape to occur are still far from being determined. Here, we emphasized the importance of the relative concentration of the ceRNAs, and their related miRNAs. In particular, we focused on the withdrawal in breast cancer tissues of the PVT1 ceRNA activity and performed a gene expression and sequence analysis of its multiple isoforms. We found that the PVT1 isoform harbouring the binding site for a representative miRNA of the miR-200 family shows a drastic decrease in its relative concentration with respect to the miRNA abundance in breast cancer tissues, providing a plausibility argument to the breakdown of the sponge program orchestrated by the oncogene PVT1.

The regulatory role of long noncoding RNAs in cancer

With the advances in genomic analysis technologies, especially next-generation RNA sequencing, a large number of new transcripts have been discovered, leading to better understanding of long noncoding RNAs (lncRNAs). Recent investigations have provided firm evidence for the critical roles of lncRNAs in chromatin modification, gene transcription, RNA splicing, RNA transport and translation. In vitro and in vivo studies have also proven that aberrant lncRNA expression is essential for the initiation and progression of cancers. Due to their unique tissue- and cancer-specific expression profiles, aberrant expression of lncRNAs can be used as reliable prognostic markers for cancer diagnoses and treatment stratification, and lncRNAs are novel therapeutic targets with high therapeutic windows.

Genome-wide identification and characterization of long non-coding RNAs in developmental skeletal muscle of fetal goat

Background

Long non-coding RNAs (lncRNAs) have been studied extensively over the past few years. Large numbers of lncRNAs have been identified in mouse, rat, and human, and some of them have been shown to play important roles in muscle development and myogenesis. However, there are few reports on the characterization of lncRNAs covering all the development stages of skeletal muscle in livestock.

Results

RNA libraries constructed from developing longissimus dorsi muscle of fetal (45, 60, and 105 days of gestation) and postnatal (3 days after birth) goat (Capra hircus) were sequenced. A total of 1,034,049,894 clean reads were generated. Among them, 3981 lncRNA transcripts corresponding to 2739 lncRNA genes were identified, including 3515 intergenic lncRNAs and 466 anti-sense lncRNAs. Notably, in pairwise comparisons between the libraries of skeletal muscle at the different development stages, a total of 577 transcripts were differentially expressed (P < 0.05) which were validated by qPCR using randomly selected six lncRNA genes. The identified goat lncRNAs shared some characteristics, such as fewer exons and shorter length, with the lncRNAs in other mammals. We also found 1153 lncRNAs genes were neighbored 1455 protein-coding genes (<10 kb upstream and downstream) and functionally enriched in transcriptional regulation and development-related processes, indicating they may be in cis-regulatory relationships. Additionally, Pearson’s correlation coefficients of co-expression levels suggested 1737 lncRNAs and 19,422 mRNAs were possibly in trans-regulatory relationships (r > 0.95 or r < −0.95). These co-expressed mRNAs were enriched in development-related biological processes such as muscle system processes, regulation of cell growth, muscle cell development, regulation of transcription, and embryonic morphogenesis.

Conclusions

This study provides a catalog of goat muscle-related lncRNAs, and will contribute to a fuller understanding of the molecular mechanism underpinning muscle development in mammals.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3009-3) contains supplementary material, which is available to authorized users.

Identification of novel long non-coding RNAs deregulated in hepatocellular carcinoma using RNA-sequencing

Functional characterization of long non-coding RNAs (lncRNAs) and their pathological relevance is still a challenging task. Abnormal expression of a few long non-coding RNAs have been found associated with hepatocellular carcinoma, with potential implications to both improve our understanding of molecular mechanism of liver carcinogenesis and to discover biomarkers for early diagnosis or therapy. However, the understanding of the global role of lncRNAs during HCC development is still in its infancy. In this study, we produced RNA-Seq data from 23 liver tissues (controls, cirrhotic and HCCs) and applied statistical and gene network analysis approaches to identify and characterize expressed lncRNAs. We detected 5,525 lncRNAs across different tissue types and identified 57 differentially expressed lncRNAs in HCC compared with adjacent non-tumour tissues using stringent criteria (FDR<0.05, Fold Change>2). Using weighted gene co-expression network analysis (WGCNA), we found that differentially expressed lncRNAs are co-expressed with genes involved in cell cycle regulation, TGF-β signalling and liver metabolism. Furthermore, we found that more than 20% of differentially expressed lncRNAs are associated to actively transcribed enhancers and that the co-expression patterns with their closest genes change dramatically during HCC development. Our study provides the most comprehensive compendium of lncRNAs expressed in HCC, as well as in control or cirrhotic livers. Our results identified both known oncogenic lncRNAs (such as H19 and CRNDE) and novel lncRNAs involved in cell cycle deregulation and liver metabolism deficits occurring during HCC development.

Noncoding RNA as regulators of cardiac fibrosis: current insight and the road ahead

Cardiac fibrosis is an important pathological feature of cardiac remodeling in heart diseases. The molecular mechanisms of cardiac fibrosis are unknown. Genomic analyses estimated that many noncoding DNA regions generate noncoding RNAs (ncRNAs). ncRNAs have emerged as key molecular players in the regulation of gene expression in different biological processes. Recent studies have started to reveal the importance of ncRNAs in heart development and suggest also an involvement in cardiac fibrosis. These molecules are emerging as important regulators of cellular process. Here, we review particularly focuses on the involvement of two large families of ncRNAs, namely microRNAs (miRNAs) and long noncoding RNAs (LncRNAs) in the regulation of cardiac fibrosis. Furthermore, we review the functions and role of ncRNAs in cardiac biology and discuss these reports and the therapeutic potential of ncRNAs for cardiac fibrosis associated with fibroblast activation and proliferation.

The LINK-A lncRNA activates normoxic HIF1α signalling in triple-negative breast cancer

Although long noncoding RNAs (lncRNAs) predominately reside in nuclear and exert their functions in many biological processes, their potential involvement in cytoplasmic signal transduction remains unexplored. Here, we identified a cytoplasmic lncRNA, Long-Intergenic Noncoding RNA for Kinase Activation (LINK-A), which mediates HB-EGF triggered, EGFR:GPNMB heterodimer-dependent HIF1α phosphorylation at Tyr565 and Ser797 by BRK and LRRK2 respectively. These events cause HIF1α stabilization, HIF1α-p300 interaction, and activation of HIF1α transcriptional programs under normoxic conditions. Mechanistically, LINK-A facilitates the recruitment of BRK to EGFR:GPNMB complex and BRK kinase activation. The BRK-dependent HIF1α Tyr565 phosphorylation interferes with Pro564 hydroxylation, leading to normoxic HIF1α stabilization. Both LINK-A and LINK-A-dependent signaling pathway activation correlate with TNBC, promoting breast cancer glycolysis reprogramming and tumorigenesis. Our findings illustrate the magnitude and diversity of cytoplasmic lncRNAs in signal transduction and highlight the important roles of lncRNAs in cancer.

Predicting Long Noncoding RNA and Protein Interactions Using Heterogeneous Network Model

Recent study shows that long noncoding RNAs (lncRNAs) are participating in diverse biological processes and complex diseases. However, at present the functions of lncRNAs are still rarely known. In this study, we propose a network-based computational method, which is called lncRNA-protein interaction prediction based on Heterogeneous Network Model (LPIHN), to predict the potential lncRNA-protein interactions. First, we construct a heterogeneous network by integrating the lncRNA-lncRNA similarity network, lncRNA-protein interaction network, and protein-protein interaction (PPI) network. Then, a random walk with restart is implemented on the heterogeneous network to infer novel lncRNA-protein interactions. The leave-one-out cross validation test shows that our approach can achieve an AUC value of 96.0%. Some lncRNA-protein interactions predicted by our method have been confirmed in recent research or database, indicating the efficiency of LPIHN to predict novel lncRNA-protein interactions.

LncRNAs: key players and novel insights into cervical cancer

Cervical cancer contributed the second highest number of deaths in female cancers, exceeded only by breast cancer, carrying high risks of morbidity and mortality. There was a great need and urgency in searching novel treatment targets and prognosis biomarkers to improve the survival rate of cervical cancer patients. Many long non-coding RNAs (lncRNAs) were emerging as pivotal regulators in various biological processes and took vitally an effect on the oncogenesis and progression of cervical cancer. In this review, we summarized the origin and overview function of lncRNAs; highlighted the roles of lncRNAs in cervical cancer in terms of prognosis and tumor progression, invasion and metastasis, apoptosis, and radio-resistance; and outlined the molecular mechanisms of lncRNAs in cervical cancer from the aspects of the interaction of lncRNAs with proteins/mRNAs (especially in HPV protein) and miRNAs, as well as RNA N-methyladenosine (m6A) methylation of lncRNAs. Meanwhile, the application of lncRNAs as biomarkers in cervical cancer prognosis and predictors for metastasis was also discussed. An overview of these researches will be valuable for broadening horizons into mechanisms, selection of meritorious biomarkers for diagnosis as well as prognosis, and future targeted therapy of cervical cancer.

Long Noncoding RNA Regulation of Pluripotency

Pluripotent stem cells (PSCs) represent a unique kind of stem cell, as they are able to indefinitely self-renew and hold the potential to differentiate into any derivative of the three germ layers. As such, human Embryonic Stem Cells (hESCs) and human induced Pluripotent Stem Cells (hiPSCs) provide a unique opportunity for studying the earliest steps of human embryogenesis and, at the same time, are of great therapeutic interest. The molecular mechanisms underlying pluripotency represent a major field of research. Recent evidence suggests that a complex network of transcription factors, chromatin regulators, and noncoding RNAs exist in pluripotent cells to regulate the balance between self-renewal and multilineage differentiation. Regulatory noncoding RNAs come in two flavors: short and long. The first class includes microRNAs (miRNAs), which are involved in the posttranscriptional regulation of cell cycle and differentiation in PSCs. Instead, long noncoding RNAs (lncRNAs) represent a heterogeneous group of long transcripts that regulate gene expression at transcriptional and posttranscriptional levels. In this review, we focus on the role played by lncRNAs in the maintenance of pluripotency, emphasizing the interplay between lncRNAs and other pivotal regulators in PSCs.

Emerging role of long noncoding RNAs in lung cancer: Current status and future prospects

Lung cancer is the leading cause of cancer-related death worldwide with a 5-year survival rate of less than 15%, despite significant advances in both diagnostic and therapeutic approaches. Combined genomic and transcriptomic sequencing studies have identified numerous genetic driver mutations that are responsible for the development of lung cancer. Importantly, these approaches have also uncovered the widespread expression of "noncoding RNAs" including long noncoding RNAs (LncRNAs), which impact biologic responses through the regulation of mRNA transcription or translation. To date, most studies of the role of noncoding RNAs have focused on LncRNAs, which regulate mRNA translation via the RNA interference pathway. Although many of their attributes, such as patterns of expression, remain largely unknown, LncRNAs have key functions in transcriptional, post-transcriptional, and epigenetic gene regulation. Recent research showed that LncRNAs regulate flowering time in the lung cancer. In this review, we discuss these investigations into long noncoding RNAs were performed almost exclusively in lung cancer. Future work will need to extend these into lung cancer and to analyze how LncRNAs interact to regulate mRNA expression. From a clinical perspective, the targeting of LncRNAs as a novel therapeutic approach will require a deeper understanding of their function and mechanism of action.

Long Non-Coding RNAs: New Players in Hematopoiesis and Leukemia

Long non-coding RNAs (lncRNAs) are important regulators of gene expression that influence almost every step in the life cycle of genes, from transcription to mRNA splicing, RNA decay, and translation. Besides their participation to normal physiology, lncRNA expression and function have been already associated to cancer development and progression. Here, we review the functional role and mechanisms of action of lncRNAs in normal hematopoiesis and how their misregulation may be implicated in the development of blood cell cancer, such as leukemia.