Computational prediction of lncRNA-mRNA interactionsby integrating tissue specificity in human transcriptome

ERβ-activated LINC01018 promotes endometriosis development by regulating the CDC25C/CDK1/CyclinB1 pathway

Endometriosis refers to as an estrogen-dependent disease. Estrogen receptor β (ERβ), the main estrogen receptor subtype which is encoded by the estrogen receptor 2 (ESR2) gene, can mediate the action of estrogen in endometriosis. Although selective estrogen receptor modulators can target the ERβ, they are not specific due to the wide distribution of ERβ. Recently, long noncoding RNAs have been implicated in endometriosis. Therefore, we aim to explore and validate the downstream regulatory mechanism of ERβ, and to investigate the potential role of long intergenic noncoding RNA 1018 (LINC01018) as a nonhormonal treatment for endometriosis. Our study demonstrates that the expression levels of ESR2 and LINC01018 are increased in ectopic endometrial tissues and reveals a significant positive correlation between the ESR2 and LINC01018 expression. Mechanistically, ERβ directly binds to an estrogen response element located in the LINC01018 promoter region and activates LINC01018 transcription. Functionally, ERβ can regulate the CDC25C/CDK1/CyclinB1 pathway and promote ectopic endometrial stromal cell proliferation via LINC01018 in vitro. Consistent with these findings, the knockdown of LINC01018 inhibits endometriotic lesion proliferation in vivo. In summary, our study demonstrates that the ERβ/LINC01018/CDC25C/CDK1/CyclinB1 signaling axis regulates endometriosis progression.

Role of long noncoding RNAs in pathological cardiac remodeling after myocardial infarction: An emerging insight into molecular mechanisms and therapeutic potential

Myocardial infarction (MI) is the leading cause of heart failure (HF), accounting for high mortality and morbidity worldwide. As a consequence of ischemia/reperfusion injury during MI, multiple cellular processes such as oxidative stress-induced damage, cardiomyocyte death, and inflammatory responses occur. In the next stage, the proliferation and activation of cardiac fibroblasts results in myocardial fibrosis and HF progression. Therefore, developing a novel therapeutic strategy is urgently warranted to restrict the progression of pathological cardiac remodeling. Recently, targeting long non-coding RNAs (lncRNAs) provided a novel insight into treating several disorders. In this regard, numerous investigations have indicated that several lncRNAs could participate in the pathogenesis of MI-induced cardiac remodeling, suggesting their potential therapeutic applications. In this review, we summarized lncRNAs displayed in the pathophysiology of cardiac remodeling after MI, emphasizing molecular mechanisms. Also, we highlighted the possible translational role of lncRNAs as therapeutic targets for this condition and discussed the potential role of exosomes in delivering the lncRNAs involved in post-MI cardiac remodeling.

Plasma Circulating Terminal Differentiation-Induced Non-Coding RNA Serves as a Biomarker in Breast Cancer

Background: Breast cancer is identified as the most common malignancy and cause of cancer-related death worldwide. Compared with healthy controls, this study evaluated the expression level and diagnostic power of lncRNA plasma TINCR in breast cancer patients. Materials and Methods: Fifty-eight women diagnosed with invasive ductal carcinoma and fifty healthy age- matched controls were included in the study. TRIzol® LS regent was used to isolate the total RNA from the whole plasma. Total RNA was converted to cDNA using Prime ScriptTM RT reagent kit and the expression levels of TINCR were quantified by qRT-PCR. Results: Low levels of TINCR lncRNA were observed in the plasma of breast cancer patients compared with control subjects. Plasma TINCR level was also positively correlated with the diagnostic age of breast cancer patients. Conclusion: A low level of plasma TINCR could discriminate breast cancer patients from healthy control subjects.

Targeting non-coding RNAs: Perspectives and challenges of in-silico approaches

The growing information currently available on the central role of non-coding RNAs (ncRNAs) including microRNAs (miRNAS) and long non-coding RNAs (lncRNAs) for chronic and degenerative human diseases makes them attractive therapeutic targets. RNAs carry out different functional roles in human biology and are deeply deregulated in several diseases. So far, different attempts to therapeutically target the 3D RNA structures with small molecules have been reported. In this scenario, the development of computational tools suitable for describing RNA structures and their potential interactions with small molecules is gaining more and more interest. Here, we describe the most suitable strategies to study ncRNAs through computational tools. We focus on methods capable of predicting 2D and 3D ncRNA structures. Furthermore, we describe computational tools to identify, design and optimize small molecule ncRNA binders. This review aims to outline the state of the art and perspectives of computational methods for ncRNAs over the past decade.

Fast RNA-RNA Interaction Prediction Methods for Interaction Analysis of Transcriptome-Scale Large Datasets

The computational prediction of RNA-RNA interactions has long been studied in RNA informatics. Most of the existing approaches focused on the interaction prediction of short RNAs in small datasets. However, in recent years, two fast prediction methods, RIsearch2 and RIblast, have been developed to predict transcriptome-scale interactions or long RNA interactions. The key idea of the software acceleration of these tools was the integration of a seed-and-extend method, which is used in fast sequence alignment tools, into RNA-RNA interaction prediction. As a result, the two software programs were ten to a thousand times faster than the existing tools; because of this acceleration, detection of genome-wide microRNA target sites or interaction partners of function-unknown long noncoding RNAs has become possible. In this review, we describe the basic concept of the algorithm, its applications, and the future perspectives of the fast RNA-RNA interaction prediction tools.

Web Services for RNA-RNA Interaction Prediction

Non-coding RNAs have various biological functions such as translational regulation, and RNA-RNA interactions play essential roles in the mechanisms of action of these RNAs. Therefore, RNA-RNA interaction prediction is an important problem in bioinformatics, and many tools have been developed for the computational prediction of RNA-RNA interactions. In addition to the development of novel algorithms with high accuracy, the development and maintenance of web services is essential for enhancing usability by experimental biologists. In this review, we survey web services for RNA-RNA interaction predictions and introduce how to use primary web services. We present various prediction tools, including general interaction prediction tools, prediction tools for specific RNA classes, and RNA-RNA interaction-based RNA design tools. Additionally, we discuss the future perspectives of the development of RNA-RNA interaction prediction tools and the sustainability of web services.

New Insights into lncRNAs in Aβ Cascade Hypothesis of Alzheimer's Disease

Alzheimer's disease (AD) is the most common type of dementia, but its pathogenesis is not fully understood, and effective drugs to treat or reverse the progression of the disease are lacking. Long noncoding RNAs (lncRNAs) are abnormally expressed and deregulated in AD and are closely related to the occurrence and development of AD. In addition, the high tissue specificity and spatiotemporal specificity make lncRNAs particularly attractive as diagnostic biomarkers and specific therapeutic targets. Therefore, an in-depth understanding of the regulatory mechanisms of lncRNAs in AD is essential for developing new treatment strategies. In this review, we discuss the unique regulatory functions of lncRNAs in AD, ranging from Aβ production to clearance, with a focus on their interaction with critical molecules. Additionally, we highlight the advantages and challenges of using lncRNAs as biomarkers for diagnosis or therapeutic targets in AD and present future perspectives in clinical practice.

LncRNA-Mediated Adipogenesis in Different Adipocytes

Long-chain noncoding RNAs (lncRNAs) are RNAs that do not code for proteins, widely present in eukaryotes. They regulate gene expression at multiple levels through different mechanisms at epigenetic, transcription, translation, and the maturation of mRNA transcripts or regulation of the chromatin structure, and compete with microRNAs for binding to endogenous RNA. Adipose tissue is a large and endocrine-rich functional tissue in mammals. Excessive accumulation of white adipose tissue in mammals can cause metabolic diseases. However, unlike white fat, brown and beige fats release energy as heat. In recent years, many lncRNAs associated with adipogenesis have been reported. The molecular mechanisms of how lncRNAs regulate adipogenesis are continually investigated. In this review, we discuss the classification of lncRNAs according to their transcriptional location. lncRNAs that participate in the adipogenesis of white or brown fats are also discussed. The function of lncRNAs as decoy molecules and RNA double-stranded complexes, among other functions, is also discussed.

Liver-specific LINC01146, a promising prognostic indicator, inhibits the malignant phenotype of hepatocellular carcinoma cells both in vitro and in vivo

Background

Long non-coding RNAs (lncRNAs) are involved in the development of hepatocellular carcinoma (HCC). We aimed to investigate the function of LINC01146 in HCC.

Methods

The expression of LINC01146 in HCC tissues was explored via The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and was verified using quantitative real-time polymerase chain reaction (qRT–PCR) in our HCC cohort. Kaplan–Meier analysis was used to assess the relationship between LINC01146 and the prognosis of HCC patients. Cell Counting Kit 8, colony formation assays, Transwell assays, flow cytometric assays, and tumour formation models in nude mice were conducted to reveal the effects of LINC01146 on HCC cells both in vitro and in vivo. Bioinformatic methods were used to explore the possible potential pathways of LINC01146 in HCC.

Results

LINC01146 was significantly decreased in HCC tissues compared with adjacent normal tissues and was found to be related to the clinical presentations of malignancy and the poor prognosis of HCC patients. Overexpression of LINC01146 inhibited the proliferation, migration, and invasion of HCC cells in vitro, while promoting their apoptosis. In contrast, downregulation of LINC01146 exerted the opposite effects on HCC cells in vitro. In addition, overexpression of LINC01146 significantly inhibited tumour growth, while downregulation of LINC01146 promoted tumour growth in vivo. Furthermore, the coexpressed genes of LINC01146 were mainly involved in the “metabolic pathway” and “complement and coagulation cascade pathway”.

Conclusion

LINC01146 expression was found to be decreased in HCC tissues and associated with the prognosis of HCC patients. It may serve as a cancer suppressor and prognostic biomarker in HCC.

Bioinformatics Approaches for Determining the Functional Impact of Repetitive Elements on Non-coding RNAs

With a large number of annotated non-coding RNAs (ncRNAs), repetitive sequences are found to constitute functional components (termed as repetitive elements) in ncRNAs that perform specific biological functions. Bioinformatics analysis is a powerful tool for improving our understanding of the role of repetitive elements in ncRNAs. This chapter summarizes recent findings that reveal the role of repetitive elements in ncRNAs. Furthermore, relevant bioinformatics approaches are systematically reviewed, which promises to provide valuable resources for studying the functional impact of repetitive elements on ncRNAs.

Transcriptome profiling of lncRNA and co-expression network in the vaginal epithelial tissue of women with lubrication disorders

Background

Vaginal lubrication is a crucial physiological response that occurs at the beginning of sexual arousal. However, research on lubrication disorders (LD) is still in its infancy, and the role of long non-coding RNAs (lncRNAs) in LD remains unclear. This study aimed to explore the function of lncRNAs in the pathogenesis of vaginal LD.

Methods

The expression profiles of LD and normal control (NC) lncRNAs were examined using next-generation sequencing (NGS), and eight selected differentially expressed lncRNAs were verified by quantitative real-time PCR. We conducted GO annotation and KEGG pathway enrichment analyses to determine the principal functions of significantly deregulated genes. LncRNA-mRNA co-expression and protein-protein interaction (PPI) networks were constructed and the lncRNA transcription factors (TFs) were predicted.

Results

From the results, we identified 181,631 lncRNAs and 145,224 mRNAs in vaginal epithelial tissue. Subsequently, our preliminary judgment revealed a total of 499 up-regulated and 337 down-regulated lncRNAs in LD. The top three enriched GO items of the dysregulated lncRNAs included the following significant terms: “contractile fiber part,” “actin filament-based process,” and “contractile fiber”. The most enriched pathways were “cell-extracellular matrix interactions,” “muscle contraction,” “cell-cell communication,” and “cGMP-PKG signaling pathway”. Our results also showed that the lncRNA-mRNA co-expression network was a powerful platform for predicting lncRNA functions. We determined the three hub genes, ADCY5, CXCL12, and NMU, using PPI network construction and analysis. A total of 231 TFs were predicted with RHOXF1, SNAI2, ZNF354C and TBX15 were suspected to be involved in the mechanism of LD.

Conclusion

In this study, we constructed the lncRNA-mRNA co-expression network, predicted the lncRNA TFs, and comprehensively analyzed lncRNA expression profiles in LD, providing a basis for future studies on LD clinical biomarkers and therapeutic targets. Further research is also needed to fully determine lncRNA’s role in LD development.

Regulatory Non-coding RNAs for Death Associated Protein Kinase Family

The death associated protein kinases (DAPKs) are a family of calcium dependent serine/threonine kinases initially identified in the regulation of apoptosis. Previous studies showed that DAPK family members, including DAPK1, DAPK2 and DAPK3 play a crucial regulatory role in malignant tumor development, in terms of cell apoptosis, proliferation, invasion and metastasis. Accumulating evidence has demonstrated that non-coding RNAs, including microRNA (miRNA), long non-coding RNA (lncRNA) and circRNA, are involved in the regulation of gene expression and tumorigenesis. Recent studies indicated that non-coding RNAs participate in the regulation of DAPKs. In this review, we summarized the current knowledge of non-coding RNAs, as well as the potential miRNAs, lncRNAs and circRNAs, that are involved in the regulation of DAPKs.

Overexpression of DDIT4 and TPTEP1 are associated with metastasis and advanced stages in colorectal cancer patients: a study utilizing bioinformatics prediction and experimental validation

BACKGROUND

Various diagnostic and prognostic tools exist in colorectal cancer (CRC) due to multiple genetic and epigenetic alterations causing the disease. Today, the expression of RNAs is being used as prognostic markers for cancer.

METHODS

In the current study, various dysregulated RNAs in CRC were identified via bioinformatics prediction. Expression of several of these RNAs were measured by RT-qPCR in 48 tissues from CRC patients as well as in colorectal cancer stem cell-enriched spheroids derived from the HT-29 cell line. The relationships between the expression levels of these RNAs and clinicopathological features were analyzed.

RESULTS

Our bioinformatics analysis determined 11 key mRNAs, 9 hub miRNAs, and 18 lncRNAs which among them 2 coding RNA genes including DDIT4 and SULF1 as well as 3 non-coding RNA genes including TPTEP1, miR-181d-5p, and miR-148b-3p were selected for the further investigations. Expression of DDIT4, TPTEP1, and miR-181d-5p showed significantly increased levels while SULF1 and miR-148b-3p showed decreased levels in CRC tissues compared to the adjacent normal tissues. Positive relationships between DDIT4, SULF1, and TPTEP1 expression and metastasis and advanced stages of CRC were observed. Additionally, our results showed significant correlations between expression of TPTEP1 with DDIT4 and SULF1.

CONCLUSIONS

Our findings demonstrated increased expression levels of DDIT4 and TPTEP1 in CRC were associated with more aggressive tumor behavior and more advanced stages of the disease. The positive correlations between TPTEP1 as non-coding RNA and both DDIT4 and SULF1 suggest a regulatory effect of TPTEP1 on these genes.

Approaches to Identify and Characterise the Post-Transcriptional Roles of lncRNAs in Cancer

It is becoming increasingly evident that the non-coding genome and transcriptome exert great influence over their coding counterparts through complex molecular interactions. Among non-coding RNAs (ncRNA), long non-coding RNAs (lncRNAs) in particular present increased potential to participate in dysregulation of post-transcriptional processes through both RNA and protein interactions. Since such processes can play key roles in contributing to cancer progression, it is desirable to continue expanding the search for lncRNAs impacting cancer through post-transcriptional mechanisms. The sheer diversity of mechanisms requires diverse resources and methods that have been developed and refined over the past decade. We provide an overview of computational resources as well as proven low-to-high throughput techniques to enable identification and characterisation of lncRNAs in their complex interactive contexts. As more cancer research strategies evolve to explore the non-coding genome and transcriptome, we anticipate this will provide a valuable primer and perspective of how these technologies have matured and will continue to evolve to assist researchers in elucidating post-transcriptional roles of lncRNAs in cancer.

Integrative Analysis of lncRNA-mRNA Coexpression in Human Lung Epithelial Cells Exposed to Dimethyl Selenide-Derived Secondary Organic Aerosols

Dimethyl selenide (DMSe) is one of the major volatile organoselenium compounds released into the atmosphere through plant metabolism and microbial methylation. DMSe has been recently revealed as a precursor of secondary organic aerosol (SOA), and its resultant SOA possesses strong oxidizing capability toward thiol groups that can perturb several major biological pathways in human airway epithelial cells and is linked to genotoxicity, DNA damage, and p53-mediated stress responses. Mounting evidence has suggested that long noncoding RNAs (lncRNAs) are involved in stress responses to internal and environmental stimuli. However, the underlying molecular interactions remain to be elucidated. In this study, we performed integrative analyses of lncRNA-mRNA coexpression in the transformed human bronchial epithelial BEAS-2B cell line exposed to DMSe-derived SOA. We identified a total of 971 differentially expressed lncRNAs in BEAS-2B cells exposed to SOA derived from O₃ and OH oxidation of DMSe. Gene ontology (GO) network analysis of cis-targeted genes showed significant enrichment of DNA damage, apoptosis, and p53-mediated stress response pathways. trans-Acting lncRNAs, including PINCR, PICART1, DLGAP1-AS2, and LINC01629, known to be associated with human carcinogenesis, also showed altered expression in cell treated with DMSe-SOA. Overall, this study highlights the regulatory role of lncRNAs in altered gene expression induced by DMSe-SOA exposure.

The lncRNA Toolkit: Databases and In Silico Tools for lncRNA Analysis

Long non-coding RNAs (lncRNAs) are a rapidly expanding field of research, with many new transcripts identified each year. However, only a small subset of lncRNAs has been characterized functionally thus far. To aid investigating the mechanisms of action by which new lncRNAs act, bioinformatic tools and databases are invaluable. Here, we review a selection of computational tools and databases for the in silico analysis of lncRNAs, including tissue-specific expression, protein coding potential, subcellular localization, structural conformation, and interaction partners. The assembled lncRNA toolkit is aimed primarily at experimental researchers as a useful starting point to guide wet-lab experiments, mainly containing multi-functional, user-friendly interfaces. With more and more new lncRNA analysis tools available, it will be essential to provide continuous updates and maintain the availability of key software in the future.

Long non-coding RNA Gm15441 attenuates hepatic inflammasome activation in response to PPARA agonism and fasting

Exploring the molecular mechanisms that prevent inflammation during caloric restriction may yield promising therapeutic targets. During fasting, activation of the nuclear receptor peroxisome proliferator-activated receptor α (PPARα) promotes the utilization of lipids as an energy source. Herein, we show that ligand activation of PPARα directly upregulates the long non-coding RNA gene Gm15441 through PPARα binding sites within its promoter. Gm15441 expression suppresses its antisense transcript, encoding thioredoxin interacting protein (TXNIP). This, in turn, decreases TXNIP-stimulated NLR family pyrin domain containing 3 (NLRP3) inflammasome activation, caspase-1 (CASP1) cleavage, and proinflammatory interleukin 1β (IL1B) maturation. Gm15441-null mice were developed and shown to be more susceptible to NLRP3 inflammasome activation and to exhibit elevated CASP1 and IL1B cleavage in response to PPARα agonism and fasting. These findings provide evidence for a mechanism by which PPARα attenuates hepatic inflammasome activation in response to metabolic stress through induction of lncRNA Gm15441.

Towards a comprehensive pipeline to identify and functionally annotate long noncoding RNA (lncRNA)

Long noncoding RNAs (lncRNAs) are implicated in various genetic diseases and cancer, attributed to their critical role in gene regulation. They are a divergent group of RNAs and are easily differentiated from other types with unique characteristics, functions, and mechanisms of action. In this review, we provide a list of some of the prominent data repositories containing lncRNAs, their interactome, and predicted and validated disease associations. Next, we discuss various wet-lab experiments formulated to obtain the data for these repositories. We also provide a critical review of in silico methods available for the identification purpose and suggest techniques to further improve their performance. The bulk of the methods currently focus on distinguishing lncRNA transcripts from the coding ones. Functional annotation of these transcripts still remains a grey area and more efforts are needed in that space. Finally, we provide details of current progress, discuss impediments, and illustrate a roadmap for developing a generalized computational pipeline for comprehensive annotation of lncRNAs, which is essential to accelerate research in this area.

The expression of long non-coding RNAs is associated with H3Ac and H3K4me2 changes regulated by the HDA6-LDL1/2 histone modification complex in Arabidopsis

In recent years, eukaryotic long non-coding RNAs (lncRNAs) have been identified as important factors involved in a wide variety of biological processes, including histone modification, alternative splicing and transcription enhancement. The expression of lncRNAs is highly tissue-specific and is regulated by environmental stresses. Recently, a large number of plant lncRNAs have been identified, but very few of them have been studied in detail. Furthermore, the mechanism of lncRNA expression regulation remains largely unknown. Arabidopsis HISTONE DEACETYLASE 6 (HDA6) and LSD1-LIKE 1/2 (LDL1/2) can repress gene expression synergistically by regulating H3Ac/H3K4me. In this research, we performed RNA-seq and ChIP-seq analyses to further clarify the function of HDA6-LDL1/2. Our results indicated that the global expression of lncRNAs is increased in hda6/ldl1/2 and that this increased lncRNA expression is particularly associated with H3Ac/H3K4me2 changes. In addition, we found that HDA6-LDL1/2 is important for repressing lncRNAs that are non-expressed or show low-expression, which may be strongly associated with plant development. GO-enrichment analysis also revealed that the neighboring genes of the lncRNAs that are upregulated in hda6/ldl1/2 are associated with various developmental processes. Collectively, our results revealed that the expression of lncRNAs is associated with H3Ac/H3K4me2 changes regulated by the HDA6-LDL1/2 histone modification complex.

TINCR: An lncRNA with dual functions in the carcinogenesis process

Long non-coding RNAs (lncRNAs) have prominent roles in the pathogenesis of human cancers. Several studies have shown oncogenic or tumor suppressor roles of lncRNAs in different human tissues. Thus, these transcripts have been regarded as putative targets in treatment of cancer. The lncRNA terminal differentiation-induced non-coding RNA (TINCR) has an especial position in this regard, as it exerts different opposite roles in the pathogenesis of different human cancers. While it is up-regulated in gastric, esophageal, bladder and breast cancer; it is down-regulated in glioma, retinoblastoma and prostate cancer. Notably, data regarding expression profile of this lncRNA in a number of human cancers such as colon cancer, squamous cell carcinoma, non-small cell lung cancer (NSCLC) and hepatocellular carcinoma (HCC) are controversial. Expression level of this lncRNA has been associated with clinical outcome in patients with gastric cancer, colorectal cancer, NSCLC and head and neck squamous cell carcinoma. Moreover, Kaplan-Meier analyses have shown correlation between expression levels of TINCR and patients survival in patients with lung cancer and HCC. A number of cellular pathways such as Wnt/β-catenin, ERK1/2‐SP3 and MAPK signaling pathways have been identified as targets of this lncRNA in different cancers. Moreover, the rs8113645, rs2288947 and rs8105637 within this lncRNA have been associated with risk of gastric and colorectal cancer. In conclusion, although the role of TINCR in the carcinogenesis is essential, based on the conflicting data regarding the direction of effect of this lncRNA, therapeutic targeting of this lncRNA is a complicated issue which should be considered in a tissue-specific or even individualized manner.

Inferring and analyzing module-specific lncRNA-mRNA causal regulatory networks in human cancer

It is known that noncoding RNAs (ncRNAs) cover ∼98% of the transcriptome, but do not encode proteins. Among ncRNAs, long noncoding RNAs (lncRNAs) are a large and diverse class of RNA molecules, and are thought to be a gold mine of potential oncogenes, anti-oncogenes and new biomarkers. Although only a minority of lncRNAs is functionally characterized, it is clear that they are important regulators to modulate gene expression and involve in many biological functions. To reveal the functions and regulatory mechanisms of lncRNAs, it is vital to understand how lncRNAs regulate their target genes for implementing specific biological functions. In this article, we review the computational methods for inferring lncRNA-mRNA interactions and the third-party databases of storing lncRNA-mRNA regulatory relationships. We have found that the existing methods are based on statistical correlations between the gene expression levels of lncRNAs and mRNAs, and may not reveal gene regulatory relationships which are causal relationships. Moreover, these methods do not consider the modularity of lncRNA-mRNA regulatory networks, and thus, the networks identified are not module-specific. To address the above two issues, we propose a novel method, MSLCRN, to infer and analyze module-specific lncRNA-mRNA causal regulatory networks. We have applied it into glioblastoma multiforme, lung squamous cell carcinoma, ovarian cancer and prostate cancer, respectively. The experimental results show that MSLCRN, as an expression-based method, could be a useful complementary method to study lncRNA regulations.

Knockdown of long non-coding RNA TINCR decreases radioresistance in colorectal cancer cells

An increasing number of studies have revealed the role of long non-coding RNAs in cancer. However, the mechanisms of action and functional utility in colorectal cancer (CRC) have not been fully elucidated. Here we describe the functional role and potential mechanism of TINCR (terminal differentiation-induced non-coding RNA) in CRC. Firstly, TINCR was selected using sequencing analyses and the starBase database. Cell Counting Kit-8, scratch wound healing, and transwell assays revealed that TINCR inhibited proliferation and migration in SW620 and HTC116 cells. Intriguingly, TINCR expression was up-regulated in a radioresistant CRC cell line (SW620R). Although TINCR had no significant effects on SW620R cell proliferation or migration, knockdown of TINCR reduced the radioresistance, and its overexpression had opposite effects. We then focused on transcription factor 4 (TCF4) as it is downregulated in CRC and associated with increased stemness in tumors. We found that TINCR and TCF4 levels were positively related in SW620R cells. TINCR knockdown reduced sphere formation ability in SW620R cells. TINCR also suppressed the OCT4 and SOX2 stemness genes, despite having no effect on NANOG. The expression levels of these genes were substantially higher in SW620R than in SW620 cells. To further explore the mechanism of TINCR and radioresistance, miR-137 was analyzed as it targets TCF4. We firstly confirmed that TCF4 is a target of miR-137. We then identified that TINCR knockdown enhanced miR-137 expression in SW620R cells. Collectively, these findings suggest that TINCR knockdown inhibits TCF4 by regulating miR-137 expression.

Comprehensive Profiles of mRNAs and miRNAs Reveal Molecular Characteristics of Multiple Organ Physiologies and Development in Pigs

The pig (Sus scrofa) is not only an important livestock animal but also widely used as a biomedical model. However, the understanding of the molecular characteristics of organs and of the developmental skeletal muscle of the pig is severely limited. Here, we performed a comprehensive transcriptome profiling of mRNAs and miRNAs across nine tissues and three skeletal muscle developmental stages in the Guizhou miniature pig. The reproductive organs (ovary and testis) had greater transcriptome complexity and activity than other tissues, and the highest transcriptome similarity was between skeletal muscle and heart (R = 0.79). We identified 1,819 mRNAs and 96 miRNAs to be tissue-specific in nine organs. Testis had the largest number of tissue-specific mRNAs (992) and miRNAs (40). Only 15 genes and two miRNAs were specifically expressed in skeletal muscle and fat, respectively. During postnatal skeletal muscle development, the mRNAs associated with focal adhesion, Notch signaling, protein digestion, and absorption pathways were up-regulated from D0 to D30 and then down-regulated from D30 and D240, while genes with opposing expression patterns were significantly enriched in the oxidative phosphorylation and proteasome pathways. The miRNAs mainly regulated genes associated with insulin, Wnt, fatty acid biosynthesis, Notch, MAPK, TGF-beta, insulin secretion, ECM-receptor interaction, focal adhesion, and calcium signaling pathways. We also identified 37 new miRNA-mRNA interaction pairs involved in skeletal muscle development. Overall, our data not only provide a rich resource for understanding pig organ physiology and development but also aid the study of the molecular functions of mRNA and miRNA in mammals.

LncRRIsearch: A Web Server for lncRNA-RNA Interaction Prediction Integrated With Tissue-Specific Expression and Subcellular Localization Data

Long non-coding RNAs (lncRNAs) play critical roles in various biological processes, but the function of the majority of lncRNAs is still unclear. One approach for estimating a function of a lncRNA is the identification of its interaction target because functions of lncRNAs are expressed through interaction with other biomolecules in quite a few cases. In this paper, we developed “LncRRIsearch,” which is a web server for comprehensive prediction of human and mouse lncRNA-lncRNA and lncRNA-mRNA interaction. The prediction was conducted using RIblast, which is a fast and accurate RNA-RNA interaction prediction tool. Users can investigate interaction target RNAs of a particular lncRNA through a web interface. In addition, we integrated tissue-specific expression and subcellular localization data for the lncRNAs with the web server. These data enable users to examine tissue-specific or subcellular localized lncRNA interactions. LncRRIsearch is publicly accessible at http://rtools.cbrc.jp/LncRRIsearch/.

Spatio-Temporal Transcriptional Dynamics of Maize Long Non-Coding RNAs Responsive to Drought Stress

Long non-coding RNAs (lncRNAs) have emerged as important regulators in plant stress response. Here, we report a genome-wide lncRNA transcriptional analysis in response to drought stress using an expanded series of maize samples collected from three distinct tissues spanning four developmental stages. In total, 3488 high-confidence lncRNAs were identified, among which 1535 were characterized as drought responsive. By characterizing the genomic structure and expression pattern, we found that lncRNA structures were less complex than protein-coding genes, showing shorter transcripts and fewer exons. Moreover, drought-responsive lncRNAs exhibited higher tissue- and development-specificity than protein-coding genes. By exploring the temporal expression patterns of drought-responsive lncRNAs at different developmental stages, we discovered that the reproductive stage R1 was the most sensitive growth stage with more lncRNAs showing altered expression upon drought stress. Furthermore, lncRNA target prediction revealed 653 potential lncRNA-messenger RNA (mRNA) pairs, among which 124 pairs function in cis-acting mode and 529 in trans. Functional enrichment analysis showed that the targets were significantly enriched in molecular functions related to oxidoreductase activity, water binding, and electron carrier activity. Multiple promising targets of drought-responsive lncRNAs were discovered, including the V-ATPase encoding gene, vpp4. These findings extend our knowledge of lncRNAs as important regulators in maize drought response.

Multi-tissue observation of the long non-coding RNA effects on sexually biased gene expression in cattle

OBJECTIVE

Recent studies have implied that gene expression has high tissue-specificity, and therefore it is essential to investigate gene expression in a variety of tissues when performing the transcriptomic analysis. In addition, the gradual increase of long non-coding RNA (lncRNA) annotation database has increased the importance and proportion of mapped reads accordingly.

METHODS

We employed simple statistical models to detect the sexually biased/dimorphic genes and their conjugate lncRNAs in 40 RNA-seq samples across two factors: sex and tissue. We employed two quantification pipeline: mRNA annotation only and mRNA+lncRNA annotation.

RESULTS

As a result, the tissue-specific sexually dimorphic genes are affected by the addition of lncRNA annotation at a non-negligible level. In addition, many lncRNAs are expressed in a more tissue-specific fashion and with greater variation between tissues compared to protein-coding genes. Due to the genic region lncRNAs, the differentially expressed gene list changes, which results in certain sexually biased genes to become ambiguous across the tissues.

CONCLUSION

In a past study, it has been reported that tissue-specific patterns can be seen throughout the differentially expressed genes between sexes in cattle. Using the same dataset, this study used a more recent reference, and the addition of conjugate lncRNA information, which revealed alterations of differentially expressed gene lists that result in an apparent distinction in the downstream analysis and interpretation. We firmly believe such misquantification of genic lncRNAs can be vital in both future and past studies.

Coordinate regulation of long non-coding RNAs and protein-coding genes in germ-free mice

BACKGROUND

Long non-coding RNAs (lncRNAs) are increasingly recognized as regulators of tissue-specific cellular functions and have been shown to regulate transcriptional and translational processes, acting as signals, decoys, guides, and scaffolds. It has been suggested that some lncRNAs act in cis to regulate the expression of neighboring protein-coding genes (PCGs) in a mechanism that fine-tunes gene expression. Gut microbiome is increasingly recognized as a regulator of development, inflammation, host metabolic processes, and xenobiotic metabolism. However, there is little known regarding whether the gut microbiome modulates lncRNA gene expression in various host metabolic organs. The goals of this study were to 1) characterize the tissue-specific expression of lncRNAs and 2) identify and annotate lncRNAs differentially regulated in the absence of gut microbiome.

RESULTS

Total RNA was isolated from various tissues (liver, duodenum, jejunum, ileum, colon, brown adipose tissue, white adipose tissue, and skeletal muscle) from adult male conventional and germ-free mice (n = 3 per group). RNA-Seq was conducted and reads were mapped to the mouse reference genome (mm10) using HISAT. Transcript abundance and differential expression was determined with Cufflinks using the reference databases NONCODE 2016 for lncRNAs and UCSC mm10 for PCGs. Although the constitutive expression of lncRNAs was ubiquitous within the enterohepatic (liver and intestine) and the peripheral metabolic tissues (fat and muscle) in conventional mice, differential expression of lncRNAs by lack of gut microbiota was highly tissue specific. Interestingly, the majority of gut microbiota-regulated lncRNAs were in jejunum. Most lncRNAs were co-regulated with neighboring PCGs. STRING analysis showed that differentially expressed PCGs in proximity to lncRNAs form tissue-specific networks, suggesting that lncRNAs may interact with gut microbiota/microbial metabolites to regulate tissue-specific functions.

CONCLUSIONS

This study is among the first to demonstrate that gut microbiota critically regulates the expression of lncRNAs not only locally in intestine but also remotely in other metabolic organs, suggesting that common transcriptional machinery may be shared to transcribe lncRNA-PCG pairs, and lncRNAs may interact with PCGs to regulate tissue-specific pathways.

LncRNA TINCR is associated with clinical progression and serves as tumor suppressive role in prostate cancer

Introduction

Terminal differentiation-induced non-coding RNA (TINCR) has been suggested to have aberrant expression in multiple human cancers, and functions as tumor suppressor or promoter in various types of human tumors depending on the specific cancer types. The expression status and biological function of TINCR in prostate cancer is still unknown.

Materials and methods

In our study, we detected TINCR expression in prostate cancer tissue samples and cell lines, and analyzed the association between TINCR expression and clinical parameters in 160 prostate cancer patients. Moreover, we conducted gain-of-function and loss-of-function studies in prostate cancer cell to explore the biological function and molecular mechanism of TINCR.

Results

In our results, low-expression TINCR was observed in prostate cancer, and correlated with advanced clinical T stage, lymph node involvement, distant metastasis, high Gleason score and poor prognosis in prostate cancer patients. Moreover, levels of TINCR expression were negatively associated with TRIP13 mRNA and protein expressions in prostate cancer tissues, and negatively regulated the TRIP13 mRNA and protein expressions in prostate cancer cell lines. TINCR inhibits prostate cancer cell proliferation, migration and invasion via suppressing TRIP13 expression.

Conclusion

TINCR plays a tumor suppressive role in regulating prostate cancer cell proliferation, migration and invasion through modulating TRIP13 expression.

A Novel Method for Assessing the Statistical Significance of RNA-RNA Interactions Between Two Long RNAs

RNA-RNA interactions are key mechanisms through which noncoding RNA (ncRNA) regions exert biological functions. Computational prediction of RNA-RNA interactions is an essential method for detecting novel RNA-RNA interactions because their comprehensive detection by biological experimentation is still quite difficult. Many RNA-RNA interaction prediction tools have been developed, but they tend to produce many false positives. Accordingly, assessment of the statistical significance of computationally predicted interactions is an important task. However, there is no method to evaluate the statistical significance of RNA-RNA interactions that is applicable to interactions between two long RNA sequences. We developed a method to calculate the p-value for the minimal interaction energy between two long RNA sequences. The developed method depends on the fact that minimum interaction energies of RNA-RNA interactions between long RNAs follow a Gumbel distribution when repeat sequences in RNAs are masked. To show the usefulness of the developed method, we applied it to whole human 5'-untranslated region (UTR) and 3'-UTR sequences to detect novel 5'-UTR-3'-UTR interactions. We thus identified two significant 5'-UTR-3'-UTR interactions. Specifically, the human small proline-rich repeat protein 3 shows conserved 5'-UTR-3'-UTR interactions with some nucleotide variations preserving base pairings among primates. Our developed method enables us to detect statistically significant RNA-RNA interactions between long RNAs such as long ncRNAs. Statistical significance estimates help in identification of interactions for experimental validation and provide novel insights into the function of ncRNA regions.

The Role of Transposable Elements in Emergence of Metazoa

Systems initially emerged for protecting genomes against insertions of transposable elements and represented by mechanisms of splicing regulation, RNA-interference, and epigenetic factors have played a key role in the evolution of animals. Many studies have shown inherited transpositions of mobile elements in embryogenesis and preservation of their activities in certain tissues of adult organisms. It was supposed that on the emergence of Metazoa the self-regulation mechanisms of transposons related with the gene networks controlling their activity could be involved in intercellular cell coordination in the cascade of successive divisions with differentiated gene expression for generation of tissues and organs. It was supposed that during evolution species-specific features of transposons in the genomes of eukaryotes could form the basis for creation of dynamically related complexes of systems for epigenetic regulation of gene expression. These complexes could be produced due to the influence of noncoding transposon-derived RNAs on DNA methylation, histone modifications, and processing of alternative splicing variants, whereas the mobile elements themselves could be directly involved in the regulation of gene expression in cis and in trans. Transposons are widely distributed in the genomes of eukaryotes; therefore, their activation can change the expression of specific genes. In turn, this can play an important role in cell differentiation during ontogenesis. It is supposed that transposons can form a species-specific pattern for control of gene expression, and that some variants of this pattern can be favorable for adaptation. The presented data indicate the possible influence of transposons in karyotype formation. It is supposed that transposon localization relative to one another and to protein-coding genes can influence the species-specific epigenetic regulation of ontogenesis.

Identification of Transposable Elements Contributing to Tissue-Specific Expression of Long Non-Coding RNAs

It has been recently suggested that transposable elements (TEs) are re-used as functional elements of long non-coding RNAs (lncRNAs). This is supported by some examples such as the human endogenous retrovirus subfamily H (HERVH) elements contained within lncRNAs and expressed specifically in human embryonic stem cells (hESCs), as required to maintain hESC identity. There are at least two unanswered questions about all lncRNAs. How many TEs are re-used within lncRNAs? Are there any other TEs that affect tissue specificity of lncRNA expression? To answer these questions, we comprehensively identify TEs that are significantly related to tissue-specific expression levels of lncRNAs. We downloaded lncRNA expression data corresponding to normal human tissue from the Expression Atlas and transformed the data into tissue specificity estimates. Then, Fisher's exact tests were performed to verify whether the presence or absence of TE-derived sequences influences the tissue specificity of lncRNA expression. Many TE-tissue pairs associated with tissue-specific expression of lncRNAs were detected, indicating that multiple TE families can be re-used as functional domains or regulatory sequences of lncRNAs. In particular, we found that the antisense promoter region of L1PA2, a LINE-1 subfamily, appears to act as a promoter for lncRNAs with placenta-specific expression.

Long non-coding RNA PAX8-AS1 polymorphisms increase the risk of childhood acute lymphoblastic leukemia

The present case-control study was conducted on 110 children with acute lymphoblastic leukemia (ALL) and 120 healthy children to determine the impact of polymorphisms in paired-box gene 8 (PAX8) antisense RNA 1 (PAX8-AS1), namely rs4848320 C>T, rs6726151 T>G and rs1110839 G>T, on ALL risk. Genotyping was performed through the polymerase chain reaction-restriction fragment length polymorphism method. The findings indicated that the rs4848320 variant increased the risk of ALL in codominant [CT vs. CC: odds ratio (OR)=2.13, 95% confidence interval (CI)=1.16-3.90, P=0.014; and TT vs. CC: OR=2.21, 95% CI=1.03-4.74, P=0.041], dominant (CT+TT vs. CC: OR=2.15, 95% CI=1.22-3.81, P=0.009,) and allele (T vs. C: OR=1.55, 95% CI=1.07-2.25, P=0.024) inheritance models. The rs6726151 variant significantly increased the risk of ALL in codominant (GT vs. GG: OR=1.88, 95% CI=1.08-3.27, P=0.036) and overdominant (GT vs. GG+TT: OR=2.08, 95% CI=1.23-3.53, P=0.008) inheritance models. No significant relationship was identified between the rs1110839 G>T variant and disease risk/protection in childhood ALL. In conclusion, the findings of the present study indicated that rs4848320 and rs6726151 polymorphisms of PAX8-AS1 may be a risk factor for the development of childhood ALL. Further studies with larger sample sizes and different ethnicities are now required to confirm these findings.