Comprehensive analysis of coding-lncRNA gene co-expression network uncovers conserved functional lncRNAs in zebrafish

ETENLNC: An end to end lncRNA identification and analysis framework to facilitate construction of known and novel lncRNA regulatory networks

Long non-coding RNAs (lncRNAs) play crucial roles in the regulation of gene expression and maintenance of genomic integrity through various interactions with DNA, RNA, and proteins. The availability of large-scale sequence data from various high-throughput platforms has opened possibilities to identify, predict, and functionally annotate lncRNAs. As a result, there is a growing demand for an integrative computational framework capable of identifying known lncRNAs, predicting novel lncRNAs, and inferring the downstream regulatory interactions of lncRNAs at the genome-scale. We present ETENLNC (End-To-End-Novel-Long-NonCoding), a user-friendly, integrative, open-source, scalable, and modular computational framework for identifying and analyzing lncRNAs from raw RNA-Seq data. ETENLNC employs six stringent filtration steps to identify novel lncRNAs, performs differential expression analysis of mRNA and lncRNA transcripts, and predicts regulatory interactions between lncRNAs, mRNAs, miRNAs, and proteins. We benchmarked ETENLNC against six existing tools and optimized it for desktop workstations and high-performance computing environments using data from three different species. ETENLNC is freely available on GitHub: https://github.com/EvolOMICS-TU/ETENLNC.

Long non-coding RNA LTCONS8875 regulates innate immunity by up-regulating IRAK4 in Miichthys miiuy (miiuy croaker)

In recent years, many studies have shown that long non-coding RNAs (lncRNAs) can regulate many biochemical processes, such as cell growth, proliferation, and immune response, which have attracted great attention. There are relatively many studies on lncRNA in mammals, while the research on lncRNA in lower vertebrates has just begun. In this study, we found a lncRNA, lncRNA LTCONS8875, related to innate immune response in Miichthys miiuy (miiuy croaker). Our results showed that lncRNA LTCONS8875 can up-regulate the expression of IRAK4 at the mRNA and protein levels, and significantly increase the production of inflammatory factors under LPS stimulation. Our research also confirmed that lncRNA LTCONS8875 plays an active role in regulating inflammation, cell proliferation, and cell viability. In summary, this research results showed that lncRNA LTCONS8875 can as an active regulatory role of innate immunity in miiuy croaker by up-regulating the expression of IRAK4, providing some insights for understanding the network mechanism of non-coding regulation of fish immunity.

Changes in the Mucosa-Associated Microbiome and Transcriptome across Gut Segments Are Associated with Obesity in a Metabolic Syndrome Porcine Model

Obesity is a major risk factor for metabolic syndrome, which is the most common cause of death worldwide, especially in developed countries. The link between obesity and gut mucosa-associated microbiota is unclear due to challenges associated with the collection of intestinal samples from humans.

Systematic identification and characterization of long noncoding RNAs (lncRNAs) during Aedes albopictus development

Background

Aedes albopictus originated in the tropical forests of Southeast Asia and can currently be found on all continents. As one of the main arboviral vectors, the control of Ae. albopictus requires novel strategies, informed by a deep knowledge of its biology. Little is known regarding mosquito long noncoding RNAs (lncRNAs), which are transcripts longer than 200 nucleotides that lack protein-coding potential and have roles in developmental regulation.

Results

Based on RNA-seq data from five developmental time points, eggs, early larvae, late larvae, pupae, and adults (female and male) of Ae. albopictus, 21,414 lncRNAs were characterized in this study. Differential expression analysis revealed that lncRNAs exhibited developmental stage specificity. The expression of most lncRNAs was upregulated at the onset of metamorphosis developmental stages. More differentially expressed lncRNAs were observed between eggs and early larvae. Weighted gene co-expression network analysis (WGCNA) further confirmed that the expression patterns of lncRNAs were obviously correlated with specific developmental time points. Functional annotation using co-expression analysis revealed that lncRNAs may be involved in the regulation of metamorphic developmental transitions of Ae. albopictus. The hub lncRNAs and hub gene clusters were identified for each module that were highly associated with specific developmental time points.

Conclusions

The results of this study will facilitate future researches to elucidate the regulatory mechanisms of lncRNAs in the development of Ae. albopictus and utilize lncRNAs to assist with mosquito control.

GCEN: An Easy-to-Use Toolkit for Gene Co-Expression Network Analysis and lncRNAs Annotation

Gene co-expression network analysis has been widely used in gene function annotation, especially for long noncoding RNAs (lncRNAs). However, there is a lack of effective cross-platform analysis tools. For biologists to easily build a gene co-expression network and to predict gene function, we developed GCEN, a cross-platform command-line toolkit developed with C++. It is an efficient and easy-to-use solution that will allow everyone to perform gene co-expression network analysis without the requirement of sophisticated programming skills, especially in cases of RNA-Seq research and lncRNAs function annotation. Because of its modular design, GCEN can be easily integrated into other pipelines.

Data integration and evolutionary analysis of long non-coding RNAs in 25 flowering plants

Background

Long non-coding RNAs (lncRNAs) play vital roles in many important biological processes in plants. Currently, a large fraction of plant lncRNA studies center at lncRNA identification and functional analysis. Only a few plant lncRNA studies focus on understanding their evolutionary history, which is crucial for an in-depth understanding of lncRNAs. Therefore, the integration of large volumes of plant lncRNA data is required to deeply investigate the evolution of lncRNAs.

Results

We present a large-scale evolutionary analysis of lncRNAs in 25 flowering plants. In total, we identified 199,796 high-confidence lncRNAs through data integration analysis, and grouped them into 5497 lncRNA orthologous families. Then, we divided the lncRNAs into groups based on the degree of sequence conservation, and quantified the various characteristics of 756 conserved Arabidopsis thaliana lncRNAs. We found that compared with non-conserved lncRNAs, conserved lncRNAs might have more exons, longer sequence length, higher expression levels, and lower tissue specificities. Functional annotation based on the A. thaliana coding-lncRNA gene co-expression network suggested potential functions of conserved lncRNAs including autophagy, locomotion, and cell cycle. Enrichment analysis revealed that the functions of conserved lncRNAs were closely related to the growth and development of the tissues in which they were specifically expressed.

Conclusions

Comprehensive integration of large-scale lncRNA data and construction of a phylogenetic tree with orthologous lncRNA families from 25 flowering plants was used to provide an oversight of the evolutionary history of plant lncRNAs including origin, conservation, and orthologous relationships. Further analysis revealed a differential characteristic profile for conserved lncRNAs in A. thaliana when compared with non-conserved lncRNAs. We also examined tissue specific expression and the potential functional roles of conserved lncRNAs. The results presented here will further our understanding of plant lncRNA evolution, and provide the basis for further in-depth studies of their functions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08047-6.

Long noncoding RNA MIR2187HG suppresses TBK1-mediated antiviral signaling through deriving miR-2187-3p in teleost fish

Long non-coding RNAs (lncRNAs) function as microregulatory factors that influence gene expression after a variety of pathogenic infection, which have been extensively studied in the past few years. Although less attention has been paid to lncRNAs in lower vertebrates than in mammals, current studies reveals that lncRNAs plays a vital role in fish stimulated by pathogens. Here, we discovered a new lncRNA, termed as MIR2187HG, which can function as a precursor of a small RNA miR-2187-3p with regulatory functions in miiuy croaker (Miichthys miiuy). Upon Siniperca chuatsi rhabdovirus (SCRV) virus infection, the expression levels of MIR2187HG were remarkably enhanced. Elevated MIR2187HG expression can act as a pivotally negative regulator that participates in the innate immune response of teleost fish to inhibit the intracellular TANK-binding kinase 1 (TBK1)-mediated antiviral signaling pathways, which can effectively avoid excessive immunity. In addition, we found that the SCRV virus could also utilize MIR2187HG to enhance its own number. Our results not only provide evidence regarding the involvement of the lncRNAs in response to anti-viruses in fish, but also broaden our understanding of the function of lncRNAs as precursor miRNA in teleost fish for the first time. Importance: SCRV infection upregulates MIR2187HG levels, which in turn suppresses SCRV-triggered type I interferon production, thus promoting viral replication in miiuy croaker. Notably, MIR2187HG regulates the release of miR-2187-3p, and TBK1 is a target of miR-2187-3p. MIR2187HG could obtain the function from miR-2187-3p to inhibit TBK1 expression and subsequently modulate TBK1-mediated NF-κB and IRF3 signaling. The collective results suggest that the novel regulation mechanism of TBK1-mediated antiviral response during RNA viral infection was regulated by MIR2187HG. Therefore, a new regulation mechanism for lncRNAs to regulate antiviral immune responses in fish is proposed.

Extended mining of the oil biosynthesis pathway in biofuel plant Jatropha curcas by combined analysis of transcriptome and gene interactome data

BACKGROUND

Jatropha curcas L. is an important non-edible oilseed crop with a promising future in biodiesel production. However, little is known about the molecular biology of oil biosynthesis in this plant when compared with other established oilseed crops, resulting in the absence of agronomically improved varieties of Jatropha. To extensively discover the potentially novel genes and pathways associated with the oil biosynthesis in J. curcas, new strategy other than homology alignment is on the demand.

RESULTS

In this study, we proposed a multi-step computational framework that integrates transcriptome and gene interactome data to predict functional pathways in non-model organisms in an extended process, and applied it to study oil biosynthesis pathway in J. curcas. Using homologous mapping against Arabidopsis and transcriptome profile analysis, we first constructed protein-protein interaction (PPI) and co-expression networks in J. curcas. Then, using the homologs of Arabidopsis oil-biosynthesis-related genes as seeds, we respectively applied two algorithm models, random walk with restart (RWR) in PPI network and negative binomial distribution (NBD) in co-expression network, to further extend oil-biosynthesis-related pathways and genes in J. curcas. At last, using k-nearest neighbors (KNN) algorithm, the predicted genes were further classified into different sub-pathways according to their possible functional roles.

CONCLUSIONS

Our method exhibited a highly efficient way of mining the extended oil biosynthesis pathway of J. curcas. Overall, 27 novel oil-biosynthesis-related gene candidates were predicted and further assigned to 5 sub-pathways. These findings can help better understanding of the oil biosynthesis pathway of J. curcas, as well as paving the way for the following J. curcas breeding application.

FGGA-lnc: automatic gene ontology annotation of lncRNA sequences based on secondary structures

The study of long non-coding RNAs (lncRNAs), greater than 200 nucleotides, is central to understanding the development and progression of many complex diseases. Unlike proteins, the functionality of lncRNAs is only subtly encoded in their primary sequence. Current in-silico lncRNA annotation methods mostly rely on annotations inferred from interaction networks. But extensive experimental studies are required to build these networks. In this work, we present a graph-based machine learning method called FGGA-lnc for the automatic gene ontology (GO) annotation of lncRNAs across the three GO subdomains. We build upon FGGA (factor graph GO annotation), a computational method originally developed to annotate protein sequences from non-model organisms. In the FGGA-lnc version, a coding-based approach is introduced to fuse primary sequence and secondary structure information of lncRNA molecules. As a result, lncRNA sequences become sequences of a higher-order alphabet allowing supervised learning methods to assess individual GO-term annotations. Raw GO annotations obtained in this way are unaware of the GO structure and therefore likely to be inconsistent with it. The message-passing algorithm embodied by factor graph models overcomes this problem. Evaluations of the FGGA-lnc method on lncRNA data, from model and non-model organisms, showed promising results suggesting it as a candidate to satisfy the huge demand for functional annotations arising from high-throughput sequencing technologies.

The Use of Zebrafish Xenotransplant Assays to Analyze the Role of lncRNAs in Breast Cancer

Breast cancer represents a great challenge since it is the first cause of death by cancer in women worldwide. LncRNAs are a newly described class of non-coding RNAs that participate in cancer progression. Their use as cancer markers and possible therapeutic targets has recently gained strength. Animal xenotransplants allows for in vivo monitoring of disease development, molecular elucidation of pathogenesis and the design of new therapeutic strategies. Nevertheless, the cost and complexities of mice husbandry makes medium to high throughput assays difficult. Zebrafishes (Danio rerio) represent a novel model for these assays, given the ease with which xenotransplantation trials can be performed and the economic and experimental advantages it offers. In this review we propose the use of xenotransplants in zebrafish to study the role of breast cancer lncRNAs using low to medium high throughput assays.

Functional long non-coding and circular RNAs in zebrafish

The utility of model organisms to understand the function of a novel transcript/genes has allowed us to delineate their molecular mechanisms in maintaining cellular homeostasis. Organisms such as zebrafish have contributed a lot in the field of developmental and disease biology. Attributable to advancement and deep transcriptomics, many new transcript isoforms and non-coding RNAs such as long noncoding RNA (lncRNA) and circular RNAs (circRNAs) have been identified and cataloged in multiple databases and many more are yet to be identified. Various methods and tools have been utilized to identify lncRNAs/circRNAs in zebrafish using deep sequencing of transcriptomes as templates. Functional analysis of a few candidates such as tie1-AS, ECAL1 and CDR1as in zebrafish provides a prospective outline to approach other known or novel lncRNA/circRNA. New genetic alteration tools like TALENS and CRISPRs have helped in probing for the molecular function of lncRNA/circRNA in zebrafish. Further latest improvements in experimental and computational techniques offer the identification of lncRNA/circRNA counterparts in humans and zebrafish thereby allowing easy modeling and analysis of function at cellular level.

Altered non-coding RNA expression profile in F1 progeny 1 year after parental irradiation is linked to adverse effects in zebrafish

Gamma radiation produces DNA instability and impaired phenotype. Previously, we observed negative effects on phenotype, DNA methylation, and gene expression profiles, in offspring of zebrafish exposed to gamma radiation during gametogenesis. We hypothesize that previously observed effects are accompanied with changes in the expression profile of non-coding RNAs, inherited by next generations. Non-coding RNA expression profile was analysed in F₁ offspring (5.5 h post-fertilization) by high-throughput sequencing 1 year after parental irradiation (8.7 mGy/h, 5.2 Gy total dose). Using our previous F₁-γ genome-wide gene expression data (GSE98539), hundreds of mRNAs were predicted as targets of differentially expressed (DE) miRNAs, involved in pathways such as insulin receptor, NFkB and PTEN signalling, linking to apoptosis and cancer. snRNAs belonging to the five major spliceosomal snRNAs were down-regulated in the F₁-γ group, Indicating transcriptional and post-transcriptional alterations. In addition, DEpiRNA clusters were associated to 9 transposable elements (TEs) (LTR, LINE, and TIR) (p = 0.0024), probable as a response to the activation of these TEs. Moreover, the expression of the lincRNAs malat-1, and several others was altered in the offspring F₁, in concordance with previously observed phenotypical alterations. In conclusion, our results demonstrate diverse gamma radiation-induced alterations in the ncRNA profiles of F₁ offspring observable 1 year after parental irradiation.

LncRNA Mrhl orchestrates differentiation programs in mouse embryonic stem cells through chromatin mediated regulation

Long non-coding RNAs (lncRNAs) have been well-established to act as regulators and mediators of development and cell fate specification programs. LncRNA Mrhl (meiotic recombination hotspot locus) has been shown to act in a negative feedback loop with WNT signaling to regulate male germ cell meiotic commitment. In our current study, we have addressed the role of Mrhl in development and differentiation using mouse embryonic stem cells (mESCs) as our model system of study. Mrhl is a nuclear-localized, chromatin-bound lncRNA with moderately stable expression in mESCs. Transcriptome analyses and loss-of-function phenotype studies revealed dysregulation of developmental processes, lineage-specific transcription factors and key networks along with aberrance in specification of early lineages during differentiation of mESCs. Genome-wide chromatin occupancy studies suggest regulation of chromatin architecture at key target loci through triplex formation. Our studies thus reveal a role for lncRNA Mrhl in regulating differentiation programs in mESCs in the context of appropriate cues through chromatin-mediated responses.

The physiological function of long-noncoding RNAs

The physiological processes of cells and organisms are regulated by various biological macromolecules, including long-noncoding RNAs (lncRNAs), which cannot be translated into protein and are different from small-noncoding RNAs on their length. In animals, lncRNAs are involved in development, metabolism, reproduction, aging and other life events by cis or trans effects. For many functional lncRNAs, there is growing evidence that they play different roles on cellular level and organismal level. On the other hand, many annotated lncRNAs are not essential and could be transcription noises. In this minireview, we investigate the physiological function of lncRNAs in cells and focus on their functions and functional mechanisms on the organismal level. The studies on lncRNAs using different classic animal models such as worms and flies are summarized and discussed in this article.

Potential Involvement of lncRNAs in the Modulation of the Transcriptome Response to Nodavirus Challenge in European Sea Bass (Dicentrarchus labrax L.)

Long noncoding RNAs (lncRNAs) are being increasingly recognised as key modulators of various biological mechanisms, including the immune response. Although investigations in teleosts are still lagging behind those conducted in mammals, current research indicates that lncRNAs play a pivotal role in the response of fish to a variety of pathogens. During the last several years, interest in lncRNAs has increased considerably, and a small but notable number of publications have reported the modulation of the lncRNA profile in some fish species after pathogen challenge. This study was the first to identify lncRNAs in the commercial species European sea bass. A total of 12,158 potential lncRNAs were detected in the head kidney and brain. We found that some lncRNAs were not common for both tissues, and these lncRNAs were located near coding genes that are primarily involved in tissue-specific processes, reflecting a degree of cellular specialisation in the synthesis of lncRNAs. Moreover, lncRNA modulation was analysed in both tissues at 24 and 72 h after infection with nodavirus. Enrichment analysis of the neighbouring coding genes of the modulated lncRNAs revealed many terms related to the immune response and viral infectivity but also related to the stress response. An integrated analysis of the lncRNAs and coding genes showed a strong correlation between the expression of the lncRNAs and their flanking coding genes. Our study represents the first systematic identification of lncRNAs in European sea bass and provides evidence regarding the involvement of these lncRNAs in the response to nodavirus.

Zebrafish models of sarcopenia

Sarcopenia - the accelerated age-related loss of muscle mass and function - is an under-diagnosed condition, and is central to deteriorating mobility, disability and frailty in older age. There is a lack of treatment options for older adults at risk of sarcopenia. Although sarcopenia's pathogenesis is multifactorial, its major phenotypes - muscle mass and muscle strength - are highly heritable. Several genome-wide association studies of muscle-related traits were published recently, providing dozens of candidate genes, many with unknown function. Therefore, animal models are required not only to identify causal mechanisms, but also to clarify the underlying biology and translate this knowledge into new interventions. Over the past several decades, small teleost fishes had emerged as powerful systems for modeling the genetics of human diseases. Owing to their amenability to rapid genetic intervention and the large number of conserved genetic and physiological features, small teleosts - such as zebrafish, medaka and killifish - have become indispensable for skeletal muscle genomic studies. The goal of this Review is to summarize evidence supporting the utility of small fish models for accelerating our understanding of human skeletal muscle in health and disease. We do this by providing a basic foundation of the (zebra)fish skeletal muscle morphology and physiology, and evidence of muscle-related gene homology. We also outline challenges in interpreting zebrafish mutant phenotypes and in translating them to human disease. Finally, we conclude with recommendations on future directions to leverage the large body of tools developed in small fish for the needs of genomic exploration in sarcopenia.

Pod-shattering characteristics differences between two groups of soybeans are associated with specific changes in gene expression

Soybean is an economically important leguminous crop, and pod dehiscence of soybean could cause huge yield loss. In this study, we measured fruit-cracking forces and percentages of dehisced pods for ten soybean accessions, then separated them into two groups as shattering-sensitive (SS) and shattering-resistant (SR) soybeans. Pod transcriptomes from these two groups were analyzed, and 225 differentially expressed genes (DEGs) were identified between SS and SR soybeans. Some of these DEGs have been previously reported to be associated with pod dehiscence in soybean. The expression patterns of selected DEGs were validated by real-time quantitative reverse transcription PCR, which confirmed the expression changes found in RNA-seq analysis. We also de novo identified 246 soybean pod-long intergenic ncRNAs (lincRNAs), 401 intronic lncRNAs, and 23 antisense lncRNAs from these transcriptomes. Furthermore, genes and lincRNAs co-expression network analysis showed that there are distinct expression patterns between SS and SR soybeans in some co-expression modules. In conclusion, we systematically investigated potential genes and molecular pathways as candidates for differences in soybean pod dehiscence and will provide a useful resource for molecular breeding of soybeans.

A long noncoding RNA cluster-based genomic locus maintains proper development and visual function

Long noncoding RNAs (lncRNAs) represent a group of regulatory RNAs that play critical roles in numerous cellular events, but their functional importance in development remains largely unexplored. Here, we discovered a series of previously unidentified gene clusters harboring conserved lncRNAs at the nonimprinting regions in brain (CNIBs). Among the seven identified CNIBs, human CNIB1 locus is located at Chr 9q33.3 and conserved from Danio rerio to Homo sapiens. Chr 9q33.3-9q34.11 microdeletion has previously been linked to human nail-patella syndrome (NPS) which is frequently accompanied by developmental and visual deficiencies. By generating CNIB1 deletion alleles in zebrafish, we demonstrated the requirement of CNIB1 for proper growth and development, and visual activities. Furthermore, we found that the role of CNIB1 on visual activity is mediated through a regulator of ocular development-lmx1bb. Collectively, our study shows that CNIB1 lncRNAs are important for zebrafish development and provides an lncRNA cluster-mediated pathophysiological mechanism for human Chr 9q33.3-9q34.11 microdeletion syndrome.

Biological Network Approach for the Identification of Regulatory Long Non-Coding RNAs Associated With Metabolic Efficiency in Cattle

Background: Genomic regions associated with divergent livestock feed efficiency have been found predominantly outside protein coding sequences. Long non-coding RNAs (lncRNA) can modulate chromatin accessibility, gene expression and act as important metabolic regulators in mammals. By integrating phenotypic, transcriptomic, and metabolomic data with quantitative trait locus data in prioritizing co-expression network analyses, we aimed to identify and functionally characterize lncRNAs with a potential key regulatory role in metabolic efficiency in cattle. Materials and Methods: Crossbred animals (n = 48) of a Charolais x Holstein F₂-population were allocated to groups of high or low metabolic efficiency based on residual feed intake in bulls, energy corrected milk in cows and intramuscular fat content in both genders. Tissue samples from jejunum, liver, skeletal muscle and rumen were subjected to global transcriptomic analysis via stranded total RNA sequencing (RNAseq) and blood plasma samples were used for profiling of 640 metabolites. To identify lncRNAs within the indicated tissues, a project-specific transcriptome annotation was established. Subsequently, novel transcripts were categorized for potential lncRNA status, yielding a total of 7,646 predicted lncRNA transcripts belonging to 3,287 loci. A regulatory impact factor approach highlighted 92, 55, 35, and 73 lncRNAs in jejunum, liver, muscle, and rumen, respectively. Their ensuing high regulatory impact factor scores indicated a potential regulatory key function in a gene set comprising loci displaying differential expression, tissue specificity and loci overlapping with quantitative trait locus regions for residual feed intake or milk production. These were subjected to a partial correlation and information theory analysis with the prioritized gene set. Results and Conclusions: Independent, significant and group-specific correlations (|r| > 0.8) were used to build a network for the high and the low metabolic efficiency group resulting in 1,522 and 1,732 nodes, respectively. Eight lncRNAs displayed a particularly high connectivity (>100 nodes). Metabolites and genes from the partial correlation and information theory networks, which each correlated significantly with the respective lncRNA, were included in an enrichment analysis indicating distinct affected pathways for the eight lncRNAs. LncRNAs associated with metabolic efficiency were classified to be functionally involved in hepatic amino acid metabolism and protein synthesis and in calcium signaling and neuronal nitric oxide synthase signaling in skeletal muscle cells.

Comparative modulation of lncRNAs in wild-type and rag1-heterozygous mutant zebrafish exposed to immune challenge with spring viraemia of carp virus (SVCV)

Although the modulation of immune-related genes after viral infection has been widely described in vertebrates, the potential implications of non-coding RNAs (ncRNAs), especially long non-coding RNAs (lncRNAs), in immunity are still a nascent research field. The model species zebrafish could serve as a useful organism for studying the functionality of lncRNAs due to the numerous advantages of this teleost, including the existence of numerous mutant lines. In this work, we conducted a whole-transcriptome analysis of wild-type (WT) and heterozygous rag1 mutant (rag1^+/-) zebrafish after infection with the pathogen spring viraemia of carp virus (SVCV). WT and rag1^+/- zebrafish were infected with SVCV for 24 h. Kidney samples were sampled from infected and uninfected fish for transcriptome sequencing. From a total of 198,540 contigs, 12,165 putative lncRNAs were identified in zebrafish. Most of the putative lncRNAs were shared by the two zebrafish lines. However, by comparing the lncRNA profiles induced after SVCV infection in WT and rag1^+/- fish, most of the lncRNAs that were significantly induced after viral challenge were exclusive to each line, reflecting a highly differential response to the virus. Analysis of the neighboring genes of lncRNAs that were exclusively modulated in WT revealed high representation of metabolism-related terms, whereas those from rag1^+/- fish showed enrichment in terms related to the adaptive immune response, among others. On the other hand, genes involved in numerous antiviral processes surrounded commonly modulated lncRNAs, as expected. These results clearly indicate that after SVCV infection in zebrafish, the expression of an array of lncRNAs with functions in different aspects of immunity is induced.

Long non-coding RNA small nucleolar RNA host gene 7 is upregulated and promotes cell proliferation in thyroid cancer

Thyroid cancer (THCA) is one of the most common types of endocrine cancer worldwide. However, the mechanisms underlying THCA progression have not been fully elucidated. Recent studies have demonstrated that long non-coding RNAs (lncRNAs) are dysregulated in human diseases, and are involved in regulating various biological processes. Furthermore, several reports have indicated that lncRNAs serve important roles in THCA. In the present study, a dataset from The Cancer Genome Atlas was used to analyze the expression levels and the clinical information of small nucleolar RNA host gene 7 (SNHG7) in THCA. Starbase was used to construct the competing endogenous RNA network. The Molecule Annotation System was used to analyze the data from Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Furthermore, cell proliferation and cell cycle assays were used to detect the functions of SNHG7 in THCA. The present study revealed for the first time, to the best of our knowledge, that SNHG7 is markedly upregulated in THCA samples following analysis of The Cancer Genome Atlas datasets. SNHG7 expression was higher in advanced stage compared with early stage THCA samples. In addition, high expression levels of SNHG7 were associated with shorter survival times in THCA patients compared with low expression levels. Bioinformatics analysis revealed that SNHG7 was associated with the processes of ‘protein translation’, ‘viral life cycle’, ‘RNA processing’, ‘mRNA splicing’, ‘histone ubiquitination’, ‘endoplasmic reticulum-to-Golgi vesicle-mediated transport’, ‘sister chromatid cohesion’, ‘DNA damage checkpoint regulation’, ‘translation’ and ‘the spliceosome’. Additionally, knockdown of SNHG7 significantly inhibited thyroid cancer cell proliferation and cell cycle progression in vitro. Taken together, the results obtained in the present study suggested that SNHG7 may serve as a novel therapeutic and prognostic target for THCA.

Comprehensive analysis of differentially expressed long non-coding RNAs in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the primary subtype of lung cancer. Long non-coding RNAs (lncRNAs) have been reported to serve prominent roles in cancer progression. However, the expression patterns and potential roles of lncRNAs in NSCLC remain to be elucidated. In the present study, four public datasets were analyzed to identify differentially expressed lncRNAs (DElncs) in NSCLC. A further dataset, GSE19188, was analyzed to validate the findings. A total of 38 upregulated and 31 downregulated lncRNAs were identified in NSCLC, compared with samples from healthy controls. Among these, 12 lncRNAs were associated with the progression of NSCLC, and dysregulated between high grade (stage III and IV) and low grade (stage II) NSCLC samples. Moreover, dysregulation of lncRNA-SIGLEC17P, GGTA1P, A2M-AS1, LINC00938, GVINP1, LINC00667 and TMPO-AS1 was associated with overall survival time in patients with NSCLC. Co-expression analyses, combined with the construction of protein-protein interaction networks, were performed to reveal the potential roles of key lncRNAs in NSCLC. The present study revealed a series of lncRNAs involved in the progression of NSCLS, which may serve as novel biomarkers for the disease.

Transcriptional analysis of long non-coding RNAs in facet joint osteoarthritis

It is recognized that facet joint osteoarthritis (FJOA) is commonly induced by the degeneration of articular cartilage of the facet joint.

ZFLNC: a comprehensive and well-annotated database for zebrafish lncRNA

There is emerging evidence showing that lncRNAs can be involved in various critical biological processes. Zebrafish is a fully developed model system being used in a variety of basic research and biomedical studies. Hence, it is an ideal model organism to study the functions and mechanisms of lncRNAs. Here, we constructed ZFLNC—a comprehensive database of zebrafish lncRNA that is dedicated to providing a zebrafish-based platform for deep exploration of zebrafish lncRNAs and their mammalian counterparts to the relevant academic communities. The main data resources of lncRNAs in this database come from the NCBI, Ensembl, NONCODE, zflncRNApedia and literature. We also obtained lncRNAs as a supplement by analysing RNA-Seq datasets from SRA database. With these IncRNAs, we further carried out expression profiling, co-expression network prediction, Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG)/Online Mendelian Inheritance in Man (OMIM) annotation and conservation analysis. As far as we know, ZFLNC is the most comprehensive and well-annotated database for zebrafish lncRNA.